Orcun Goksel

Assistant Professor, ETH Zurich

Department of Information Technology and Electrical Engineering (D-ITET)

Head of Computer-assisted Applications in Medicine (CAiM) Group

ETH Zurich -- Computer Vision Lab   (ETF C107)
Sternwartstrasse 7
8092 Zurich, Switzerland         +41 44 632 2529

Dr. Goksel received two BSc degrees in electrical engineering (2001) and in computer science (2002) from Middle East Technical University, Ankara, Turkey. He received his MASc (2004) and PhD (2009) degrees in Electrical and Computer Engineering at the University of British Columbia, Vancouver, Canada. Following postdoc and senior scientist positions, since 2014 he is an assistant professor at ETH Zurich, Switzerland; leading the Computer-assisted Applications in Medicine (CAiM) group within the Computer Vision Lab. Dr. Goksel has received the 2016 ETH Spark Award (for most promising invention of the year), the 2014 CTI Swiss MedTech Award, and the 2011 WAGS Innovation in Technology Award (for best dissertation in western North America). His research interests include ultrasound imaging, medical image analysis, tissue biomechanical characterization, patient-specific modelling, image-guided therapy, and medical simulation in virtual-reality.

2017
2015

Master/Semester Theses: Various projects are available for supervision. Please inquire regarding the research topics currently on offer.
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Journal Articles:

[*] Christine Tanner, Barbara Flach, Céline Eggenberger, Oliver Mattausch, Michael Bajka, and Orcun Goksel: "Consistent Reconstruction of 4D Fetal Heart Ultrasound Images to Cope with Fetal Motion", Int J Computer Assisted Radiology and Surgery, 2017.  accepted
BibTeX:
@article{Tanner_consistent_17,
  author = {Christine Tanner and Barbara Flach and C\'{e}line Eggenberger and Oliver Mattausch and Michael Bajka and Orcun Goksel},
  title = {Consistent Reconstruction of 4D Fetal Heart Ultrasound Images to Cope with Fetal Motion},
  journal = {Int J Computer Assisted Radiology and Surgery},
  year = {2017}
}
[*] Oliver Mattausch and Orcun Goksel: "Realistic Ultrasound Simulation of Complex Surface Models Using Interactive Monte-Carlo Path Tracing", Computer Graphics Forum, 2017.  accepted
BibTeX:
@article{Mattausch_monte-carlo_17,
  author = {Oliver Mattausch and Orcun Goksel},
  title = {Realistic Ultrasound Simulation of Complex Surface Models Using Interactive Monte-Carlo Path Tracing},
  journal = {Computer Graphics Forum},
  year = {2017}
}
[*] Firat Ozdemir, Neerav Karani, Philipp Fuernstahl, and Orcun Goksel: "Interactive Segmentation in MRI for Orthopedic Surgery Planning: Bone Tissue", Int J Computer Assisted Radiology and Surgery 12(6):1031-9, Jun 2017.  
BibTeX:
@article{Ozdemir_interactive_17,
  author = {Firat Ozdemir and Neerav Karani and Philipp Fuernstahl and Orcun Goksel},
  title = {Interactive Segmentation in MRI for Orthopedic Surgery Planning: Bone Tissue},
  journal = {Int J Computer Assisted Radiology and Surgery},
  year = {2017},
  volume = {12},
  number = {6},
  pages = {1031-9},
  doi = {10.1007/s11548-017-1570-0}
}
[*] Ece Ozkan, Christine Tanner, Matej Kastelic, Oliver Mattausch, Maxim Makhinya, and Orcun Goksel: "Robust Motion Tracking in Liver from 2D Ultrasound Images Using Supporters", Int J Computer Assisted Radiology and Surgery 12(6):941–950, Jun 2017.  
BibTeX:
@article{Ozkan_robust_17,
  author = {Ece Ozkan and Christine Tanner and Matej Kastelic and Oliver Mattausch and Maxim Makhinya and Orcun Goksel},
  title = {Robust Motion Tracking in Liver from 2D Ultrasound Images Using Supporters},
  journal = {Int J Computer Assisted Radiology and Surgery},
  year = {2017},
  volume = {12},
  number = {6},
  pages = {941–950},
  doi = {10.1007/s11548-017-1559-8}
}
[*] Valeriy Vishnevskiy, Tobias Gass, Gabor Szekely, Christine Tanner, and Orcun Goksel: "Isotropic Total Variation Regularization of Displacements in Parametric Image Registration", IEEE Trans Medical Imaging 36(2):385-395, Feb 2017.  
Abstract: Spatial regularization is essential in image registration, which is an ill-posed problem.
Regularization can help to avoid both physically implausible displacement fields and local minima during optimization.
Tikhonov regularization (squared L2-norm) is unable to correctly redrepresent non-smooth displacement fields, that can, for example, occur at sliding interfaces in the thorax and abdomen in image time-series during respiration.
In this paper, isotropic Total Variation (TV) regularization is used to enable accurate registration near such interfaces.
We further develop the TV-regularization for parametric displacement fields and provide an efficient numerical solution scheme using the Alternating Directions Method of Multipliers (ADMM).
The proposed method was successfully applied to four clinical databases which capture breathing motion, including CT lung and MR liver images.
It provided accurate registration results for the whole volume.
A key strength of our proposed method is that it does not depend on organ masks that are conventionally required by many algorithms to avoid errors at sliding interfaces.
Furthermore, our method is robust to parameter selection, allowing the use of the same parameters for all tested databases.
The average target registration error (TRE) of our method is superior (10% to 40%) to other techniques in the literature.
It provides precise motion quantification and sliding detection with sub-pixel accuracy on the publicly available breathing motion databases (mean TREs of 0.95mm for DIR 4DCT, 0.96mm for DIR COPDgene, 0.91mm for POPI databases.
BibTeX:
@article{Vishnevskiy_isotropic_17,
  author = {Valeriy Vishnevskiy and Tobias Gass and Gabor Szekely and Christine Tanner and Orcun Goksel},
  title = {Isotropic Total Variation Regularization of Displacements in Parametric Image Registration},
  journal = {IEEE Trans Medical Imaging},
  year = {2017},
  volume = {36},
  number = {2},
  pages = {385-395},
  doi = {10.1109/tmi.2016.2610583}
}
[*] Antje-Christin Knopf, Kristin Stützer, Christian Richter, Antoni Rucinsk, Joakim da Silva, Justin Phillips, Martijn Engelsman, Shinichi Shimizu, Rene Werner, Annika Jakobi, Orcun Goksel, Ye Zhang, Tuathan Oshea, Martin Fast, Rosalind Perrin, Christoph Bert, EriK Korevaar, and Jamie McClelland: "Required transition from research to clinical application: report on the 4D treatment planning workshops 2014 and 2015", Physica Medica: European J Medical Physics 32(7):874-82, Jul 2016.  
Abstract: Since 2009, a 4D treatment planning workshop has taken place annually, gathering researchers working on the treatment of moving targets, mainly with scanned ion beams. Topics discussed during the workshops range from problems of time resolved imaging, the challenges of motion modelling, the implementation of 4D capabilities for treatment planning, different aspects related to 4D dosimetry and treatment verification, up to discussions of an �ideal� design for ion beam therapy centres aiming to treat moving targets.
This report gives an overview on topics discussed at the 4D workshops in 2014 and 2015. It summarizes recent findings, developments and challenges in the field and discusses the relevant literature of recent years. The report is structured in three parts pointing out developments in the context of understanding moving geometries, of treating moving targets, and of 4D quality assurance (QA) and 4D dosimetry.
The community represented at the 4D workshops agrees that research in the context of treating moving targets with scanned ion beams faces a crucial phase of clinical translation. In the coming years it will be important to define standards for motion monitoring, to establish 4D treatment planning guidelines, and to develop 4D QA tools. These basic requirements for the clinical application of scanned ion beams to moving targets could, e.g., be determined by a dedicated ESTRO task group.
Besides reviewing recent research results and pointing out urgent needs when treating moving targets with scanned ion beams, the report also gives an outlook on the upcoming 4D workshop organized at the University Medical Center Groningen (UMCG) in the Netherlands at the end of 2016.
BibTeX:
@article{Knopf_required_16,
  author = {Antje-Christin Knopf and Kristin St\"utzer and Christian Richter and Antoni Rucinsk and Joakim da Silva and Justin Phillips and Martijn Engelsman and Shinichi Shimizu and Rene Werner and Annika Jakobi and Orcun Goksel and Ye Zhang and Tuathan Oshea and Martin Fast and Rosalind Perrin and Christoph Bert and EriK Korevaar and Jamie McClelland},
  title = {Required transition from research to clinical application: report on the 4D treatment planning workshops 2014 and 2015},
  journal = {Physica Medica: European J Medical Physics},
  year = {2016},
  volume = {32},
  number = {7},
  pages = {874-82},
  doi = {10.1016/j.ejmp.2016.05.064}
}
[*] Oscar Alfonso Jiménez-del-Toro, Henning Müller, Markus Krenn, Katharina Gruenberg, Abdel Aziz Taha, Marianne Winterstein, Ivan Eggel, Antonio Foncubierta-Rodríguez, Orcun Goksel, András Jakab, Georgios Kontokotsios, Georg Langs, Bjoern Menze, Tomàs Salas Fernandez, Roger Schaer, Anna Walley, Marc-Andr/e Weber, Yashin Dicente Cid, Tobias Gass, Mattias Heinrich, Fucang Jia, Fredrik Kahl, Razmig Kechichian, Dominic Mai, Assaf B. Spanier, Graham Vincent, Chunliang Wang, Daniel Wyeth, and Allan Hanbury: "Cloud-based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms: VISCERAL Anatomy Benchmarks", IEEE Trans Medical Imaging 35(11):2459-75, Nov 2016.  
BibTeX:
@article{Jimenez_cloud-based_16,
  author = {Oscar Alfonso {Jim\'enez-del-Toro} and Henning M\"uller and Markus Krenn and Katharina Gruenberg and Abdel Aziz Taha and Marianne Winterstein and Ivan Eggel and Antonio Foncubierta-Rodr\'iguez and Orcun Goksel and Andr\'as Jakab and Georgios Kontokotsios and Georg Langs and Bjoern Menze and Tom\`as Salas Fernandez and Roger Schaer and Anna Walley and Marc-Andr/e Weber and Yashin Dicente Cid and Tobias Gass and Mattias Heinrich and Fucang Jia and Fredrik Kahl and Razmig Kechichian and Dominic Mai and Assaf B. Spanier and Graham Vincent and Chunliang Wang and Daniel Wyeth and Allan Hanbury},
  title = {Cloud-based Evaluation of Anatomical Structure Segmentation and Landmark Detection Algorithms:  VISCERAL Anatomy Benchmarks},
  journal = {IEEE Trans Medical Imaging},
  year = {2016},
  volume = {35},
  number = {11},
  pages = {2459-75},
  doi = {10.1109/tmi.2016.2578680}
}
[*] Lazaros Vlachopoulos, Celestine Dünner, Tobias Gass, Matthias Graf, Orcun Goksel, Christian Gerber, Gábor Székely, and Philipp Fürnstahl: "Computer algorithms for three-dimensional measurement of humeral anatomy: analysis of 140 paired humeri", J Shoulder and Elbow Surgery 25(2):e38-e48, Feb 2016.  
Abstract: BACKGROUND: In the presence of severe osteoarthritis, osteonecrosis, or proximal humeral fracture, the contralateral humerus may serve as a template for the 3-dimensional (3D) preoperative planning of reconstructive surgery. The purpose of this study was to develop algorithms for performing 3D measurements of the humeral anatomy and further to assess side-to-side (bilateral) differences in humeral head retrotorsion, humeral head inclination, humeral length, and humeral head radius and height.
METHODS: The 3D models of 140 paired humeri (70 cadavers) were extracted from computed tomographic data. Geometric characteristics quantifying the humeral anatomy in 3D were determined in a semiautomatic fashion using the developed computer algorithms. The results between the sides were compared for evaluating bilateral differences.
RESULTS: The mean bilateral difference of the humeral retrotorsion angle was 6.7� (standard deviation [SD], 5.7$^rc$; range, -15.1$^rc$ to 24.0$^rc$; P = .063); the mean side difference of the humeral head inclination angle was 2.3� (SD, 1.8�; range, -5.1� to 8.4�; P = .12). The side difference in humeral length (mean, 2.9 mm; SD, 2.5 mm; range, -8.7 mm to 10.1 mm; P = .04) was significant. The mean side difference in the head sphere radius was 0.5 mm (SD, 0.6 mm; range, -3.2 mm to 2.2 mm; P = .76), and the mean side difference in humeral head height was 0.8 mm (SD, 0.6 mm; range, -2.4 mm to 2.4 mm; P = .44).
CONCLUSIONS: The contralateral anatomy may serve as a reliable reconstruction template for humeral length, humeral head radius, and humeral head height if it is analyzed with 3D algorithms. In contrast, determining humeral head retrotorsion and humeral head inclination from the contralateral anatomy may be more prone to error.
BibTeX:
@article{Vlachopoulos_computer_16,
  author = {Lazaros Vlachopoulos and Celestine D\"unner and Tobias Gass and Matthias Graf and Orcun Goksel and Christian Gerber and G\'abor Sz\'ekely and Philipp F\"urnstahl},
  title = {Computer algorithms for three-dimensional measurement of humeral anatomy: analysis of 140 paired humeri},
  journal = {J Shoulder and Elbow Surgery},
  year = {2016},
  volume = {25},
  number = {2},
  pages = {e38-e48},
  doi = {10.1016/j.jse.2015.07.027}
}
[*] Alessandro Crimi, Maxim Makhinya, Ulrich Baumann, Christoph Thalhammer, Gabor Szekely, and Orcun Goksel: "Automatic Measurement of Venous Pressure Using B-Mode Ultrasound", IEEE Trans Biomedical Engineering 63(2):288-299, Feb 2016.  

* Having been selected as the best project of the year, this work received 2014 CTI MedTech Award at the funding agency's annual event.

Abstract: Central venous pressure (CVP) information is crucial in clinical situations such as cardiac failure, intravascular volume overload, and sepsis. The measurement of CVP, however, requires catheterization of vena cava through the subclavian or internal jugular veins, which is an impractical and costly procedure with related risk of complications. Peripheral venous pressure (PVP), which correlates with CVP under certain patient positioning, can be measured noninvasively using ultrasound via controlled compressions of a superficial vein. This paper presents an automatic system for acquiring such noninvasive measurements. Robust signal and image processing techniques developed for this purpose are introduced in this work. The proposed stand-alone, mobile platform collects images in real-time from the display output of any ultrasound machine, meanwhile measuring the pressure on the skin underneath the ultrasound transducer via a liquid-filled pouch. The image and pressure data are synchronized through an automated temporal calibration procedure. During forearm compressions, blood vessels are detected and tracked in the images using robust geometric (ellipse) models, the parameters of which are used further in model-based estimation of PVP. The proposed system was tested in 56 image sequences on 14 healthy volunteers, and was shown to achieve measurements with errors comparable to or lower than the interoperator variability between expert manual assessments.
BibTeX:
@article{Crimi_automatic_16,
  author = {Alessandro Crimi and Maxim Makhinya and Ulrich Baumann and Christoph Thalhammer and Gabor Szekely and Orcun Goksel},
  title = {Automatic Measurement of Venous Pressure Using B-Mode Ultrasound},
  journal = {IEEE Trans Biomedical Engineering},
  year = {2016},
  volume = {63},
  number = {2},
  pages = {288-299},
  doi = {10.1109/TBME.2015.2455953}
}
[*] Siavash Khallaghi, C. Antonio Sánchez, Joy Sun, Farhad Imani, Amir Khojaste Galesh Khale, Orcun Goksel, Abtin Rasoulian, Cesare Romagnoli, Hamidreza Abdi, Silvia Chang, Parvin Mousavi, Aaron Fenster, Aaron Ward, Sidney Fels, and Purang Abolmaesumi: "Biomechanically Constrained Surface Registration: Application to MR-TRUS Fusion for Prostate Interventions", IEEE Trans Med Imag 34(11):2404-14, Nov 2015.  
Abstract: In surface-based registration for image-guided interventions, the presence of missing data can be a significant issue. This often arises with real-time imaging modalities such as ultrasound, where poor contrast can make tissue boundaries difficult to distinguish from surrounding tissue. Missing data poses two challenges: ambiguity in establishing correspondences; and extrapolation of the deformation field to those missing regions. To address these, we present a novel non-rigid registration method. For establishing correspondences, we use a probabilistic framework based on a Gaussian mixture model (GMM) that treats one surface as a potentially partial observation. To extrapolate and constrain the deformation field, we incorporate biomechanical prior knowledge in the form of a finite element model (FEM). We validate the algorithm, referred to as GMM-FEM, in the context of prostate interventions. Our method leads to a significant reduction in target registration error (TRE) compared to similar state-of-the-art registration algorithms in the case of missing data up to 30%, with a mean TRE of 2:6 mm. The method also performs well when full segmentations are available, leading to TREs that are comparable to or better than other surface-based techniques. We also analyze robustness of our approach, showing that GMM-FEM is a practical and reliable solution for surfacebased registration.
BibTeX:
@article{Khallaghi_biomechanically_15,
  author = {Siavash Khallaghi and C. Antonio S\'{a}nchez and Joy Sun and Farhad Imani and Amir Khojaste Galesh Khale and Orcun Goksel and Abtin Rasoulian and Cesare Romagnoli and Hamidreza Abdi and Silvia Chang and Parvin Mousavi and Aaron Fenster and Aaron Ward and Sidney Fels and Purang Abolmaesumi},
  title = {Biomechanically Constrained Surface Registration: Application to MR-TRUS Fusion for Prostate Interventions},
  journal = {IEEE Trans Med Imag},
  year = {2015},
  volume = {34},
  number = {11},
  pages = {2404-14},
  doi = {10.1109/TMI.2015.2440253}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Consistency-Based Rectification of Non-Rigid Registrations", SPIE J Medical Imaging 2(1):014005, May 2015.  
Abstract: We present a technique to rectify nonrigid registrations by improving their group-wise consistency, which is a widely used unsupervised measure to assess pair-wise registration quality. While pair-wise registration methods cannot guarantee any group-wise consistency, group-wise approaches typically enforce perfect consistency by registering all images to a common reference. However, errors in individual registrations to the reference then propagate, distorting the mean and accumulating in the pair-wise registrations inferred via the reference. Furthermore, the assumption that perfect correspondences exist is not always true, e.g., for interpatient registration. The proposed consistency-based registration rectification (CBRR) method addresses these issues by minimizing the group-wise inconsistency of all pair-wise registrations using a regularized least-squares algorithm. The regularization controls the adherence to the original registration, which is additionally weighted by the local postregistration similarity. This allows CBRR to adaptively improve consistency while locally preserving accurate pair-wise registrations. We show that the resulting registrations are not only more consistent, but also have lower average transformation error when compared to known transformations in simulated data. On clinical data, we show improvements of up to 50% target registration error in breathing motion estimation from four-dimensional MRI and improvements in atlas-based segmentation quality of up to 65% in terms of mean surface distance in three-dimensional (3-D) CT. Such improvement was observed consistently using different registration algorithms, dimensionality (two-dimensional/3-D), and modalities (MRI/CT).
BibTeX:
@article{Gass_consistency-based_15,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Consistency-Based Rectification of Non-Rigid Registrations},
  journal = {SPIE J Medical Imaging},
  year = {2015},
  volume = {2},
  number = {1},
  pages = {014005},
  doi = {10.1117/1.JMI.2.1.014005}
}
[*] Peter Baki, Sergio J Sanabria, Gabor Kosa, Gabor Szekely, and Orcun Goksel: "Thermal Expansion Imaging for Monitoring Lesion Depth using M-Mode Ultrasound during Cardiac RF Ablation: In-vitro Study", Int J Computer Assisted Radiology and Surgery 10(6):681-693, Jun 2015.  

* Received 3rd place (of 100 papers) in IPCAI/PHILIPS Best Paper Award at Information Processing in Computer-Assisted Interventions Conference, Barcelona, Spain, June 2015

Abstract: Purpose We demonstrate a novel method for automatic direct lesion depth (LD) tracking during coagulation from time series of a single A-mode ultrasound (US) transducer custom fit at the tip of a RFA catheter. This method is named thermal expansion imaging (TEI). Methods A total of 35 porcine myocardium samples were ablated (LD 0.5--5 mm) while acquiring US, electrical impedance (EI) and contact force (CF) data. US images are generated in real time in terms of echo intensity (M-mode) and phase (TEI). For TEI, displacements between US time series are estimated with time-domain cross-correlation. A modified least squares strain estimation with temporal and depth smoothing reveals a thermal expansion boundary (TEB), negative zero-crossing of temporal strain, which is associated to the coagulated tissue front. Results M-mode does not reliably delineate RFA lesions. TEI images reveal a traceable TEB with RMSE = 0.50 mm and R2=0.85 with respect to visual observations. The conventional technique, EI, shows lower R2=0.7 and >200 % variations with CF. The discontinuous time progression of the TEB is qualitatively associated to tissue heterogeneity and CF variations, which are directly traceable with TEI. The speed of sound, measured in function of tissue temperature, increases up to a plateau at 55 C, which does not explain the observed strain bands in the TEB. Conclusions TEI successfully tracks LD in in vitro experiments based on a single US transducer and is robust to catheter/tissue contact, ablation time and even tissue heterogeneity. The presence of a TEB suggests thermal expansion as the main strain mechanism during coagulation, accompanied by compression of the adjacent non-ablated tissue. The isolation of thermally induced displacements from in vivo motion is a matter of future research. TEI is potentially applicable to other treatments such as percutaneous RFA of liver and high-intensity focused ultrasound.
BibTeX:
@article{Baki_thermal_15,
  author = {Peter Baki and Sergio J Sanabria and Gabor Kosa and Gabor Szekely and Orcun Goksel},
  title = {Thermal Expansion Imaging for Monitoring Lesion Depth using M-Mode Ultrasound during Cardiac RF Ablation: In-vitro Study},
  journal = {Int J Computer Assisted Radiology and Surgery},
  year = {2015},
  volume = {10},
  number = {6},
  pages = {681-693},
  doi = {10.1007/s11548-015-1203-4}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Simultaneous Segmentation and Multi-Resolution Nonrigid Atlas Registration", IEEE Trans Image Processing 23(7):2931-43, July 2014.  
Abstract: In this paper, a novel Markov random field (MRF)-based approach is presented for segmenting medical images while simultaneously registering an atlas nonrigidly. In the literature, both segmentation and registration have been studied extensively. For applications that involve both, such as segmentation via atlas-based registration, earlier studies proposed addressing these problems iteratively by feeding the output of each to initialize the other. This scheme, however, cannot guarantee an optimal solution for the combined task at hand, since these two individual problems are then treated separately. In this paper, we formulate simultaneous registration and segmentation (SRS) as a maximum a-posteriori (MAP) problem. We decompose the resulting probabilities such that the MAP inference can be done using MRFs. An efficient hierarchical implementation is employed, allowing coarse-to-fine registration while estimating segmentation at pixel level. The method is evaluated on two clinical data sets: 1) mandibular bone segmentation in 3D CT and 2) corpus callosum segmentation in 2D midsaggital slices of brain MRI. A video tracking example is also given. Our implementation allows us to directly compare the proposed method with the individual segmentation/registration and the iterative approach using the exact same potential functions. In a leave-one-out evaluation, SRS demonstrated more accurate results in terms of dice overlap and surface distance metrics for both data sets. We also show quantitatively that the SRS method is less sensitive to the errors in the registration as opposed to the iterative approach.
BibTeX:
@article{Gass_simultaneous_14,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Simultaneous Segmentation and Multi-Resolution Nonrigid Atlas Registration},
  journal = {IEEE Trans Image Processing},
  year = {2014},
  volume = {23},
  number = {7},
  pages = {2931-43},
  doi = {10.1109/TIP.2014.2322447}
}
[*]Orcun Goksel, Kirill Sapchuk, William James Morris, and Septimiu E. Salcudean: "Prostate Brachytherapy Training with Simulated Ultrasound and Fluoroscopy Images", IEEE Trans Biomedical Engineering 60(4):1002-12, Apr 2013.  
Abstract: In this paper, a novel computer-based virtual training system for prostate brachytherapy is presented. This system incorporates, in a novel way, prior methodologies of ultrasound image synthesis and haptic transrectal ultrasound (TRUS) transducer interaction in a complete simulator that allows a trainee to maneuver the needle and the TRUS, to see the resulting patientspecific images and feel the interaction forces. The simulated TRUS images reflect the volumetric tissue deformation and comprise validated appearance models for the needle and implanted seeds. Rendered haptic forces use validated models for needle shaft flexure and friction, tip cutting, and deflection due to bevel. This paper also presents additional new features that make the simulator complete, in the sense that all aspects of the brachytherapy procedure as practiced at many cancer centers are simulated, including simulations of seed unloading, fluoroscopy imaging, and transversal/sagittal TRUS plane switching. For realtime rendering, methods for fast TRUS-needle-seed image formation are presented. In addition, the simulator computes realtime dosimetry, allowing a trainee to immediately see the consequence of planning changes. The simulation is also patientspecific, as it allows the user to import the treatment plan for a patient together with the imaging data in order for a physician to practice an upcoming procedure or for a medical resident to train using typical implant scenarios or rarely encountered cases.
BibTeX:
@article{Goksel_prostate_13,
  author = {Orcun Goksel and Kirill Sapchuk and William James Morris and Septimiu E. Salcudean},
  title = {Prostate Brachytherapy Training with Simulated Ultrasound and Fluoroscopy Images},
  journal = {IEEE Trans Biomedical Engineering},
  year = {2013},
  volume = {60},
  number = {4},
  pages = {1002-12},
  doi = {10.1109/TBME.2012.2222642}
}
[*]Orcun Goksel, Hani Eskandari, and Septimiu E. Salcudean: "Mesh Adaptation for Improving Elasticity Reconstruction using the FEM Inverse Problem", IEEE Trans Medical Imaging 32(2):408-418, Feb 2013.  
Abstract: The finite element method is commonly used to model tissue deformation in order to solve for unknown parameters in the inverse problem of viscoelasticity. Typically, a (regular-grid) structured mesh is used since the internal geometry of the domain to be identified is not known a priori. In this work, the generation of problem-specific meshes is studied and such meshes are shown to significantly improve inverse-problem elastic parameter reconstruction. Improved meshes are generated from axial strain images, which provide an approximation to the underlying structure, using an optimization-based mesh adaptation approach. Such strain-based adapted meshes fit the underlying geometry even at coarse mesh resolutions, therefore improving the effective resolution of the reconstruction at a given mesh size/complexity. Elasticity reconstructions are then performed iteratively using the reflective trust-region method for optimizing the fit between estimated and observed displacements. This approach is studied for Young�s modulus reconstruction at various mesh resolutions through simulations, yielding 40% to 72% decrease in root-mean-square reconstruction error and 4 to 52 times improvement in contrast-to-noise ratio in simulations of a numerical phantom with a circular inclusion. A noise study indicates that conventional structured meshes with no noise perform considerably worse than the proposed adapted meshes with noise levels up to 20% of the compression amplitude. A phantom study and preliminary in-vivo results from a breast tumor case confirm the benefit of the proposed technique. Not only conventional axial strain images but also other elasticity approximations can be used to adapt meshes. This is demonstrated on images generated by combining axial strain and axial-shear strain, which enhances lateral image contrast in particular settings, consequently further improving meshadapted reconstructions.
BibTeX:
@article{Goksel_mesh_13,
  author = {Orcun Goksel and Hani Eskandari and Septimiu E. Salcudean},
  title = {Mesh Adaptation for Improving Elasticity Reconstruction using the FEM Inverse Problem},
  journal = {IEEE Trans Medical Imaging},
  year = {2013},
  volume = {32},
  number = {2},
  pages = {408-418},
  doi = {10.1109/TMI.2012.2228664}
}
[*] Hani Eskandari, Orcun Goksel, Septimiu E. Salcudean, and Robert Rohling: "Dilatation parameterization for two dimensional modeling of nearly incompressible isotropic materials", Physics in Medicine and Biology 57(12):4055-73, Jun 2012.  
Abstract: A new method to model the stress�strain relationship in two dimensions is proposed, which is particularly suited for analyzing nearly incompressible materials, such as soft tissue. In most cases of soft tissue modeling, plane strain is reported to approximate the deformation when an external compression is applied. However, it is subject to limitations when dealing with incompressible materials, e.g., when solving the inverse problem of elasticity. We propose a novel 2D model for the linear stress�strain relationship by describing the out-of-plane strain as a linear combination of the two in-plane strains. As such, the model can be represented in 2D while being able to explain the three-dimensional deformation. We show that in simple cases where the applied force is dominantly in one direction, one can approximate the sum of the three principal strain components in a plane by a scalar multiplied by the out-of-plane strain. 3D finite-element simulations have been performed. The proposed model has been tested under different boundary conditions and material properties. The results show that the model parametrization is affected mostly by the boundary conditions, while being relatively independent of the underlying distribution of Young's modulus. An application to the inverse problem of elasticity is presented where a more accurate estimate is obtained using the proposed dilatation model compared to the plane-stress and plane-strain models.
BibTeX:
@article{Eskandari_dilatation_12,
  author = {Hani Eskandari and Orcun Goksel and Septimiu E. Salcudean and Robert Rohling},
  title = {Dilatation parameterization for two dimensional modeling of nearly incompressible isotropic materials},
  journal = {Physics in Medicine and Biology},
  year = {2012},
  volume = {57},
  number = {12},
  pages = {4055-73},
  doi = {10.1088/0031-9155/57/12/4055}
}
[*] Jeffrey M. Abeysekera, Reza Zahiri-Azar, Orcun Goksel, Robert Rohling, and Septimiu E. Salcudean: "Analysis of 2-D Motion Tracking in Ultrasound with Dual Transducers", Ultrasonics 52(1):156-168, Jan 2012.  
Abstract: We study displacement and strain measurement error of dual transducers (two linear arrays, aligned orthogonally and coplanar). Displacements along the beam of each transducer are used to obtain measurements in two-dimensions. Simulations (5 MHz) and experiments (10 MHz) are compared to measurements with a single linear array, with and without angular compounding. Translation simulations demonstrate factors of 1.07 larger and 8 smaller biases in the axial and lateral directions respectively, for dual transducers compared to angular compounding. As the angle between dual transducers decreases from 90 to 40 degrees, for 1% compression simulations, the lateral RMS error ranges from 2.1-3.9 microns compared to 9 microns with angular compounding. Simulation of dual transducer misalignment of 1 mm and 2 degrees result in errors of less than 9 microns. Experiments demonstrate factors of 3.0 and 5.2 lower biases for dual transducers in the axial and lateral directions respectively compared to angular compounding.
BibTeX:
@article{Abeysekera_analysis_12,
  author = {Jeffrey M. Abeysekera and Reza Zahiri-Azar and Orcun Goksel and Robert Rohling and Septimiu E. Salcudean},
  title = {Analysis of 2-D Motion Tracking in Ultrasound with Dual Transducers},
  journal = {Ultrasonics},
  year = {2012},
  volume = {52},
  number = {1},
  pages = {156-168},
  doi = {10.1016/j.ultras.2011.07.011}
}
[*] Reza Zahiri Azar, Orcun Goksel, and Septimiu E. Salcudean: "Comparison Between 2-D Cross Correlation With 2-D Sub-Sampling and 2-D Tracking Using Beam Steering", IEEE Trans Ultrasonics, Ferroelectrics, and Frequency Control 58(8):1534-7, Aug 2011.  
Abstract: We have previously presented multi-dimensional sub-sample motion estimation techniques that use multi-dimensional polynomial fitting to the discrete cross-correlation function to jointly estimate the sub-sample motion in all three spatial directions. Previous simulation and experimental results showed that these estimators significantly improve the performance of the motion estimation in 2-D and 3-D. In this short communication, we present additional simulation results and compare these techniques to 2-D tracking using beam steering. The results show that beam steering technique performs better in estimating the motion vector especially the lateral component.
BibTeX:
@article{Azar_comparison_11,
  author = {Reza Zahiri Azar and Orcun Goksel and Septimiu E. Salcudean},
  title = {Comparison Between 2-D Cross Correlation With 2-D Sub-Sampling and 2-D Tracking Using Beam Steering},
  journal = {IEEE Trans Ultrasonics, Ferroelectrics, and Frequency Control},
  year = {2011},
  volume = {58},
  number = {8},
  pages = {1534-7},
  doi = {10.1109/TUFFC.2011.1978}
}
[*] Hani Eskandari, Orcun Goksel, Septimiu E. Salcudean, and Robert Rohling: "Bandpass Sampling of High Frequency Tissue Motion", IEEE Trans Ultrasonics, Ferroelectrics, and Frequency Control 58(7):1332-43, Jul 2011.  
Abstract: The characterization of tissue viscoelastic properties requires the measurement of tissue motion over a region of interest at frequencies that significantly exceed the frame rates of conventional ultrasound systems. In this paper, we propose that the bandpass sampling technique be applied to tissue motion sampling. With this approach, high-frequency signals limited to a frequency band can be sampled and reconstructed without aliasing at a sampling frequency that is lower than the Nyquist rate. We first review this approach and discuss the selection of the tissue excitation frequency band and of the feasible sampling frequencies that allow signal reconstruction without aliasing. We then demonstrate the approach using simulations based on the finite element method and ultrasound simulations. Finally, we perform experiments on tissue-mimicking materials and demonstrate accurate motion estimation using a lower sampling rate than that required by the conventional sampling theorem. The estimated displacements were used to measure the elasticity and viscosity in a phantom in which an inclusion has been correctly delineated. Thus, with bandpass sampling, it is feasible to use conventional beamforming on diagnostic ultrasound systems to perform high-frequency dynamic elastography. The method is simple to implement because it does not require beam interleaving, additional hardware, or synchronization.
BibTeX:
@article{Eskandari_bandpass_11,
  author = {Hani Eskandari and Orcun Goksel and Septimiu E. Salcudean and Robert Rohling},
  title = {Bandpass Sampling of High Frequency Tissue Motion},
  journal = {IEEE Trans Ultrasonics, Ferroelectrics, and Frequency Control},
  year = {2011},
  volume = {58},
  number = {7},
  pages = {1332-43},
  doi = {10.1109/TUFFC.2011.1953}
}
[*]Orcun Goksel, Kirill Sapchuk, and Septimiu E. Salcudean: "Haptic Simulator for Prostate Brachytherapy with Simulated Needle and Probe Interaction", IEEE Trans Haptics 4(3):188-198, May 2011.  

* Featured on the issue cover page

Abstract: This paper presents a haptic simulator for prostate brachytherapy. Both needle insertion and the manipulation of the transrectal ultrasound (TRUS) probe are controlled via haptic devices. Tissue interaction forces that are computed by a deformable tissue model based on the finite element method (FEM) are rendered to the user by these devices. The needle insertion simulation employs 3D models of needle flexibility and asymmetric tip bevel. The needle-tissue simulation allows a trainee to practice needle insertion and targeting. The TRUS-tissue interaction simulation allows a trainee to practice the 3D intraoperative TRUS placement for registration with the preoperative volume study and to practice TRUS axial translation and rotation for imaging needles during insertions. Approaches to computational acceleration for real-time haptic performance are presented. Trade-offs between accuracy and speed are discussed. A graphics-card implementation of the numerically intensive mesh-adaptation operation is also presented. The simulator can be used for training, rehearsal, and treatment planning.
BibTeX:
@article{Goksel_haptic_11,
  author = {Orcun Goksel and Kirill Sapchuk and Septimiu E. Salcudean},
  title = {Haptic Simulator for Prostate Brachytherapy with Simulated Needle and Probe Interaction},
  journal = {IEEE Trans Haptics},
  year = {2011},
  volume = {4},
  number = {3},
  pages = {188-198},
  doi = {10.1109/TOH.2011.34}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "Image-Based Variational Meshing", IEEE Trans Medical Imaging 30(1):11-21, Jan 2011.  
Abstract: In medical simulations involving tissue deformation, the finite element method (FEM) is a widely used technique, where the size, shape, and placement of the elements in a model are important factors that affect the interpolation and numerical errors of a solution. Conventional model generation schemes for FEM consist of a segmentation step delineating the anatomy followed by a meshing step generating elements conforming to this segmentation. In this paper, a single-step model generation technique is proposed based on optimization. Starting from an initial mesh covering the domain of interest, the mesh nodes are adjusted to minimize an objective function which penalizes intra-element intensity variations and poor element geometry for the entire mesh. Trade-offs between mesh geometry quality and intra-element variance are achieved by adjusting the relative weights of the geometric and intensity variation components of the cost function. This meshing approach enables a more accurate rendering of shapes with fewer elements and provides more accurate models for deformation simulation, especially when the image intensities represent a mechanical feature of the tissue such as the elastic modulus. The use of the proposed mesh optimization is demonstrated in 2D and 3D on synthetic phantoms, MR images of the brain, and CT images of the kidney. A comparison with previous meshing techniques that do not account for image intensity is also provided demonstrating the benefits of our approach.
BibTeX:
@article{Goksel_image-based_11,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {Image-Based Variational Meshing},
  journal = {IEEE Trans Medical Imaging},
  year = {2011},
  volume = {30},
  number = {1},
  pages = {11-21},
  doi = {10.1109/TMI.2010.2055884}
}
[*] Reza Zahiri-Azar, Orcun Goksel, and Septimiu E. Salcudean: "Sub-sample Displacement Estimation from Digitized Ultrasound RF Signals Using Multi-Dimensional Polynomial Fitting of the Cross-correlation Function", IEEE Trans Ultrasonics, Ferroelectrics, and Frequency Control 57(11):2403-20, Nov 2010.  
Abstract: A widely used time-domain technique for motion or delay estimation between digitized ultrasound RF signals involves the maximization of a discrete pattern-matching function, usually the cross-correlation. To achieve sub-sample accuracy, the discrete pattern-matching function is interpolated using the values at the discrete maximizer and adjacent samples. In prior work, only 1-D fit, applied separately along the axial, lateral, and elevational axes, has been used to estimate the sub-sample motion in 1-D, 2-D, and 3-D. In this paper, we explore the use of 2-D and 3-D polynomial fitting for this purpose. We quantify the estimation error in noise-free simulations using Field II and experiments with a commercial ultrasound machine. In simulated 2-D translational motions, function fitting with quartic spline polynomials leads to maximum bias of 0.2% of the sample spacing in the axial direction and 0.4% of the sample spacing in the lateral direction, corresponding to 38 nm and 1.31 um, respectively. The maximum standard deviations were approximately 1% of the sample spacing in both the axial and the lateral directions, corresponding to 193 nm axially and 4.43 um laterally. In simulated 1% axial strain, the same function fitting leads to mean absolute displacement estimation errors of 255 nm in the axial direction and 4.77 um in the lateral direction. In experiments with a linear array transducer, 2-D quartic spline fitting leads to maximum bias of 458 nm and 6.27 um in the axial and the lateral directions, respectively. These results are more than one order of magnitude smaller than those obtained with separate 1-D fit when applied to the same data set. Simulations and experiments in 3-D yield similar results when comparing 3-D polynomial fitting with 1-D fitting along the axial, lateral, and elevational directions.
BibTeX:
@article{Zahiri-Azar_sub-sample_10,
  author = {Reza Zahiri-Azar and Orcun Goksel and Septimiu E. Salcudean},
  title = {Sub-sample Displacement Estimation from Digitized Ultrasound RF Signals Using Multi-Dimensional Polynomial Fitting of the Cross-correlation Function},
  journal = {IEEE Trans Ultrasonics, Ferroelectrics, and Frequency Control},
  year = {2010},
  volume = {57},
  number = {11},
  pages = {2403-20},
  doi = {10.1109/TUFFC.2010.1708}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "B-Mode Ultrasound Image Simulation in Deformable 3-D Medium", IEEE Trans Medical Imaging 28(11):1657-69, Nov 2009.  
Abstract: This paper presents an algorithm for fast image synthesis inside deformed volumes. Given the node displacements of a mesh and a reference 3-D image dataset of a predeformed volume, the method first maps the image pixels that need to be synthesized from the deformed configuration to the nominal predeformed configuration, where the pixel intensities are obtained easily through interpolation in the regular-grid structure of the reference voxel volume. This mapping requires the identification of the mesh element enclosing each pixel for every image frame. To accelerate this point location operation, a fast method of projecting the deformed mesh on image pixels is introduced in this paper. The method presented was implemented for ultrasound B-mode image simulation of a synthetic tissue phantom. The phantom deformation as a result of ultrasound probe motion was modeled using the finite element method. Experimental images of the phantom under deformation were then compared with the corresponding synthesized images using sum of squared differences and mutual information metrics. Both this quantitative comparison and a qualitative assessment show that realistic images can be synthesized using the proposed technique. An ultrasound examination system was also implemented to demonstrate that real-time image synthesis with the proposed technique can be successfully integrated into a haptic simulation.
BibTeX:
@article{Goksel_b-mode_09,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {B-Mode Ultrasound Image Simulation in Deformable 3-D Medium},
  journal = {IEEE Trans Medical Imaging},
  year = {2009},
  volume = {28},
  number = {11},
  pages = {1657-69},
  doi = {10.1109/TMI.2009.2016561}
}
[*]Orcun Goksel, Ehsan Dehghan, and Septimiu E. Salcudean: "Modeling and Simulation of Flexible Needles", Medical Engineering and Physics 31(9):1069-78, Nov 2009.  
Abstract: Needle insertion is performed in many clinical and therapeutic procedures. Tissue displacement and needle bending which result from needle�tissue interaction make accurate targeting difficult. For performing physicians to gain essential needle targeting skills, needle insertion simulators can be used for training. An accurate needle bending model is essential for such simulators. These bending models are also needed for needle path planning. In this paper, three different models are presented to simulate the deformations of a needle. The first two models use the finite element method and take the geometric nonlinearity into account. The third model is a series of rigid bars connected by angular springs. The models were compared to recorded deformations during experiments of applying lateral tip forces on a brachytherapy needle. The model parameters were identified and the simulation results were compared to the experimental data. The results show that the angular spring model, which is computationally the most efficient model, is also the most accurate in modeling the bending of the brachytherapy needle.
BibTeX:
@article{Goksel_modeling_09,
  author = {Orcun Goksel and Ehsan Dehghan and Septimiu E. Salcudean},
  title = {Modeling and Simulation of Flexible Needles},
  journal = {Medical Engineering and Physics},
  year = {2009},
  volume = {31},
  number = {9},
  pages = {1069-78},
  doi = {10.1016/j.medengphy.2009.07.007}
}
[*]Orcun Goksel, Septimiu E. Salcudean, and Simon P. DiMaio: "3D Simulation of Needle-Tissue Interaction with Application to Prostate Brachytherapy", Computer Aided Surgery 11(6):279-288, Nov 2006.  
Abstract: This paper presents a needle-tissue interaction model that is a 3D extension of prior work based on needle and tissue models discretized using the Finite Element Method. The use of flexible needles necessitates remeshing the tissue during insertion, since simple mesh-node snapping to the tip can be detrimental to the simulation. In this paper, node repositioning and node addition are the two methods of mesh modification examined for coarse meshes. Our focus is on numerical approaches for fast implementation of these techniques. Although the two approaches compared, namely the Woodbury formula (matrix inversion lemma) and the boundary condition switches, have the same computational complexity, the Woodbury formula is shown to perform faster due to its cache-efficient order of operations. Furthermore, node addition is applied in constant time for both approaches, whereas node repositioning requires longer and variable computational times. A method for rendering the needle forces during simulated insertions into a 3D prostate model has been implemented. Combined with a detailed anatomical segmentation, this will be useful in teaching the practice of prostate brachytherapy. Issues related to discretization of such coupled (e.g., needle-tissue) models are also discussed.
BibTeX:
@article{Goksel_3d_06,
  author = {Orcun Goksel and Septimiu E. Salcudean and Simon P. DiMaio},
  title = {3D Simulation of Needle-Tissue Interaction with Application to Prostate Brachytherapy},
  journal = {Computer Aided Surgery},
  year = {2006},
  volume = {11},
  number = {6},
  pages = {279-288},
  doi = {10.3109/10929080601089997}
}
[*] Danny G. French, James Morris, Mira Keyes, Orcun Goksel, and Septimiu E. Salcudean: "Computing Intraoperative Dosimetry for Prostate Brachytherapy Using TRUS and Fluoroscopy", Academic Radiology 12(10):1262-72, Oct 2005.  
Abstract: Rationale and Objectives: There is a need to provide real-time dosimetric feedback during prostate brachytherapy based on the location of the implanted seeds. The objective of our approach is to develop a system to accurately locate seeds with minimal impact on the current protocol for prostate brachytherapy and without additional imaging equipment. Materials and Methods: A new approach for intraoperatively computing dosimetry for prostate brachytherapy is presented. The approach uses transrectal ultrasound (TRUS) and fluoroscopic images. A fluoroscopic image of the TRUS probe is required to register the fluoroscopic and ultrasound images. The C-arm is not moved during the procedure and all images are acquired from the same C-arm angles. A needle path is interpolated for each needle based on the location of the needle tip in TRUS images and the known entry point of the needle. Throughout the procedure, fluoroscopic images are acquired to determine the coronal plane coordinates of the seeds and the remaining coordinate of each seed is computed from the needle path. For accurate results, intraoperative seed motion tracking is advised and a method to achieve such tracking is also presented. Results: Experimentally, the TRUS and fluoroscopic images are registered with a mean and maximum error of 1.3 mm and 5.8 mm, respectively. In a phantom, 12 seeds are located using our approach and compared with the known locations, with a mean error in the x, y, and z direction of 0.96 mm, 0.33, and 0.68 mm, respectively, and a corresponding maximum error of 1.85 mm, 0.56 mm, and 1.63 mm. Experimental results show motion tracking in the y-direction with submillimeter accuracy. The feasibility of our approach is tested on five cases of clinical data using a semiautomated version of our system and the resulting dosimetry is compared with that found using postoperative computed tomography images. The D90 and V100 metrics computed using our approach and the computed tomography images differ by a maximum of 16.6% and 1.7%, respectively. Conclusions: TRUS can be combined with single pose fluoroscopic images to compute delivered dose intraoperatively for prostate brachytherapy. Phantom results demonstrate the accuracy of the method and preliminary clinical results show its potential.
BibTeX:
@article{French_computing_05,
  author = {Danny G. French and James Morris and Mira Keyes and Orcun Goksel and Septimiu E. Salcudean},
  title = {Computing Intraoperative Dosimetry for Prostate Brachytherapy Using TRUS and Fluoroscopy},
  journal = {Academic Radiology},
  year = {2005},
  volume = {12},
  number = {10},
  pages = {1262-72},
  doi = {10.1016/j.acra.2005.05.026}
}

Book Chapters:

[*] Philipp Fürnstahl, Andreas Schweizer, Matthias Graf, Lazaros Vlachopoulos, Sandro Fucentese, Stephan Wirth, Ladislav Nagy, Gabor Szekely, and Orcun Goksel: "Surgical Treatment of Long-bone Deformities: 3D Preoperative Planning and Patient-specific Instrumentation", In Computational Radiology for Orthopaedic Interventions, ed. Guoyan Zheng and Shuo Li, pp. 123-149, Springer, 2016.  
Abstract: Congenital or posttraumatic bone deformity may lead to reduced range
of motion, joint instability, pain, and osteoarthritis. The conventional
joint-preserving therapy for such deformities is corrective osteotomy
� the anatomical reduction or realignment of bones with fixation.
In this procedure, the bone is cut and its fragments are correctly
realigned and stabilized with an implant to secure their position
during bone healing. Corrective osteotomy is an elective procedure
scheduled in advance, providing sufficient time for careful diagnosis
and operation planning. Accordingly, computer-based methods have
become very popular for its preoperative planning. These methods
can improve precision not only by enabling the surgeon to quantify
deformities and to simulate the intervention preoperatively in three
dimensions, but also by generating a surgical plan of the required
correction. However, generation of complex surgical plans is still
a major challenge, requiring sophisticated techniques and profound
clinical expertise. In addition to preoperative planning, computer-based
approaches can also be used to support surgeons during the course
of interventions. In particular, since recent advances in additive
manufacturing technology have enabled cost-effective production of
patient- and intervention-specific osteotomy instruments, customized
interventions can thus be planned for and performed using such instruments.
In this chapter, state of the art and future perspectives of computer-assisted
deformity-correction surgery of the upper and lower extremities are
presented. We elaborate on the benefits and pitfalls of different
approaches based on our own experience in treating over 150 patients
with three-dimensional preoperative planning and patient-specific
instrumentation.
BibTeX:
@incollection{Fuernstahl_surgical_16,
  author = {Philipp F\"urnstahl and Andreas Schweizer and Matthias Graf and Lazaros Vlachopoulos and Sandro Fucentese and Stephan Wirth and Ladislav Nagy and Gabor Szekely and Orcun Goksel},
  title = {Surgical Treatment of Long-bone Deformities: 3D Preoperative Planning and Patient-specific Instrumentation},
  booktitle = {Computational Radiology for Orthopaedic Interventions},
  editor = {Guoyan Zheng and Shuo Li},
  publisher = {Springer},
  year = {2016},
  pages = {123-149},
  url = {http://www.springer.com/us/book/9783319234816},
  doi = {10.1007/978-3-319-23482-3_7}
}
[*]Orçun Göksel and Gabor Székely: "Computational Support for Intraoperative Imaging and IGT", In Intraoperative Imaging and Image-Guided Therapy, ed. Ferenc A. Jolesz, pp. 63-77, Springer, New York, Jan 2014.  
Abstract: Technology and computers are omnipresent in our daily lives today,
in which they play a decisive role, even if they are often invisible,
seamlessly integrated into our surrounding and the objects we use
every day. Image-guided therapy is certainly not an exception to
this. Nowadays practically all imaging devices rely on computer support,
commonly used for the purpose of controlling medical devices, for
post-processing acquired raw data to turn them into images, and for
transmitting resulting digital data for storage or further use. Furthermore,
many therapeutic devices are equipped with sophisticated sensors
and actuators, which are also controlled by computers. Indeed, software
support today is an intrinsic component of all phases of therapy.
In this chapter, we provide an overview of tools and technologies
that are used as the building blocks of almost every computational
support system in image-guided therapy. The tools introduced in this
chapter include segmentation, registration, localization, simulation,
model generation, visualization, robotic tools, and man�machine interfaces.
The use of such tools in preoperative planning and intraoperative
surgical support is then described and exemplified on typical treatment
scenarios.
BibTeX:
@incollection{Goksel_computational_14,
  author = {Or\c{c}un G\"oksel and Gabor Sz\'ekely},
  title = {Computational Support for Intraoperative Imaging and IGT},
  booktitle = {Intraoperative Imaging and Image-Guided Therapy},
  editor = {Ferenc A. Jolesz},
  publisher = {Springer},
  year = {2014},
  pages = {63-77},
  doi = {10.1007/978-1-4614-7657-3_4}
}
[*] Septimiu E. Salcudean, Ramin S. Sahebjavaher, Orcun Goksel, Ali Baghani, Sara S. Mahdavi, Guy Nir, Ralph Sinkus, and Mehdi Moradi: "Biomechanical Modeling of the Prostate for Procedure Guidance and Simulation", In Soft Tissue Biomechanical Modeling for Computer Assisted Surgery, ed. Yohan Payan, pp. 169-198, v 11, Springer, Heidelberg, 2012.  
Abstract: Biomechanical models of the prostate have a number of potential applications
in the diagnosis and management of prostate cancer. Most importantly,
it has been shown in several studies that cancerous prostate tissue
has different viscoelastic properties than normal prostate tissue:
it is typically stiffer (higher storage modulus) and more viscous
(higher loss modulus). If a strong correlation can be obtained between
malignant tissue and its viscoelastic properties, then all commonly
practiced prostate cancer procedures�biopsies, surgery and radiation
treatment�can be improved by elasticity imaging. The elastic properties
of the prostate and peri-prostatic tissue can also be used in procedure
planning, even if such elastic properties do not show strong correlation
to cancer. This chapter starts with an introduction to the prostate
anatomy, prostate cancer, and a description of the most common procedures
and their clinical needs. It continues by presenting the potential
impact of elasticity imaging on these procedures. A brief survey
of elastography techniques is presented next, with a sampling of
some prostate elastography results to date. We describe two of the
systems that we developed for the acquisition of prostate ultrasound
and magnetic resonance elastography images and summarize our results
to date. We show that these elasticity images can be used for prostate
segmentation and cross-modality image registration. Furthermore,
we show how prostate region deformation models can be used in the
development of a prostate brachytherapy simulator which can also
be used in the planning of needle insertions that account for deformation.
BibTeX:
@incollection{Salcudean_biomechanical_12,
  author = {Septimiu E. Salcudean and Ramin S. Sahebjavaher and Orcun Goksel and Ali Baghani and Sara S. Mahdavi and Guy Nir and Ralph Sinkus and Mehdi Moradi},
  title = {Biomechanical Modeling of the Prostate for Procedure Guidance and Simulation},
  booktitle = {Soft Tissue Biomechanical Modeling for Computer Assisted Surgery},
  editor = {Yohan Payan},
  publisher = {Springer},
  year = {2012},
  volume = {11},
  pages = {169-198},
  doi = {10.1007/978-3-642-29014-5}
}
[*]Orcun Goksel, Antonio Foncubierta-Rodríguez, Oscar Alfonso Jiménez del Toro, Henning Müller, Georg Langs, Marc-André Weber, Bjoern Menze, Ivan Eggel, Katharina Gruenberg, Marianne Winterstein, Markus Holzer, Markus Krenn, Georgios Kontokotsios, Sokratis Metallidis, Roger Schaer, Abdel Aziz Taha, András Jakab, Tomàs Salas Fernandez, and Allan Hanbury: "Overview of the VISCERAL Challenge at ISBI 2015", In Proceedings of VISCERAL Challenge at ISBI, ed. Orcun Goksel et al., pp. 6-11 (1390), CEUR-WS, Apr 2015.  
Abstract: This is an overview paper describing the data and evaluation scheme
of the VISCERAL Segmentation Challenge at ISBI 2015. The challenge
was organized on a cloud-based virtualmachine environment, where
each participant could develop and submit their algorithms. The dataset
contains up to 20 anatomical structures annotated in a training and
a test set consisting of CT and MR images with and without contrast
enhancement. The test-set is not accessible to participants, and
the organizers run the virtual-machines with submitted segmentation
methods on the test data. The results of the evaluation are then
presented to the participant, who can opt to make it public on the
challenge leaderboard displaying 20 segmentation quality metrics
per-organ and permodality. Dice coefficient and mean-surface distance
are presented herein as representative quality metrics. As a continuous
evaluation platform, our segmentation challenge leaderboard will
be open beyond the duration of the VISCERAL project.
BibTeX:
@incollection{Goksel_overview_15,
  author = {Orcun Goksel and Antonio Foncubierta--Rodr\'iguez and Oscar Alfonso Jim\'enez del Toro and Henning M\"uller and Georg Langs and Marc-Andr\'e Weber and Bjoern Menze and Ivan Eggel and Katharina Gruenberg and Marianne Winterstein and Markus Holzer and Markus Krenn and Georgios Kontokotsios and Sokratis Metallidis and Roger Schaer and Abdel Aziz Taha and Andr\'as Jakab and Tom\`as Salas Fernandez and Allan Hanbury},
  title = {Overview of the VISCERAL Challenge at ISBI 2015},
  booktitle = {Proceedings of VISCERAL Challenge at ISBI},
  editor = {Orcun Goksel et al.},
  publisher = {CEUR-WS},
  year = {2015},
  number = {1390},
  pages = {6--11},
  url = {http://ceur-ws.org/Vol-1390/visceralISBI15-0.pdf}
}
[*] Oscar Alfonso Jiménez del Toro, Orcun Goksel, Bjoern Menze, Henning Müller, Georg Langs, Marc-André Weber, Ivan Eggel, Katharina Gruenberg, Markus Holzer, András Jakab, Georgios Kotsios-Kontokotsios, Markus Krenn, Tomàs Salas Fernandez, Roger Schaer, Abdel Aziz Taha, Marianne Winterstein, and Allan Hanbury: "VISCERAL - VISual Concept Extraction challenge in RAdioLogy : ISBI 2014 Challenge Organization", In VISCERAL Challenge at ISBI, ed. Orcun Goksel, pp. 6-15 (1194), CEUR-WS, May 2014.  
Abstract: The VISual Concept Extraction challenge in RAdioLogy (VISCERAL) project
has been developed as a cloud-based infrastructure for the evaluation
of medical image data in large data sets. As part of this project,
the ISBI 2014 (International Symposium for Biomedical Imaging) challenge
was organized using the VISCERAL data set and shared cloud-framework.
Two tasks were selected to exploit and compare multiple state-of-the-art
solutions designed for big data medical image analysis. Segmentation
and landmark localization results from the submitted algorithms were
compared to manually annotated ground truth in the VISCERAL data
set. This paper presents an overview of the challenge setup and data
set used as well as the evaluation metrics from the various results
submitted to the challenge. The participants presented their algorithms
during an organized session at ISBI 2014. There were lively discussions
in which the importance of comparing approaches on tasks sharing
a common data set was highlighted.
BibTeX:
@incollection{Jimenez_visceral_14,
  author = {Jim\'enez del Toro, Oscar Alfonso and Orcun Goksel and Bjoern Menze and Henning M\"uller and Georg Langs and Marc-Andr\'e Weber and Ivan Eggel and Katharina Gruenberg and Markus Holzer and Andr\'as Jakab and Georgios Kotsios-Kontokotsios and Markus Krenn and Tom\`as Salas Fernandez and Roger Schaer and Abdel Aziz Taha and Marianne Winterstein and Allan Hanbury},
  title = {VISCERAL - VISual Concept Extraction challenge in RAdioLogy : ISBI 2014 Challenge Organization},
  booktitle = {VISCERAL Challenge at ISBI},
  editor = {Orcun Goksel},
  publisher = {CEUR-WS},
  year = {2014},
  number = {1194},
  pages = {6-15},
  url = {http://ceur-ws.org/Vol-1194/visceralISBI14-0.pdf}
}

Refereed Conferences:

[*] Sergio J Sanabria, Marga B Rominger, Corin F Otesteanu, Farrukh I Sheikh, Volker Klingmueller, and Orcun Goksel: "Can speed of sound be better than conventional elastography for breast characterization?", In Annual Meeting of Radiological Society of North America (RSNA), Chicago, IL, USA, Nov 2017.  accepted
BibTeX:
@inproceedings{Sanabria_can_17,
  author = {Sergio J Sanabria and Marga B Rominger and Corin F Otesteanu and Farrukh I Sheikh and Volker Klingmueller and Orcun Goksel},
  title = {Can speed of sound be better than conventional elastography for breast characterization?},
  booktitle = {Annual Meeting of Radiological Society of North America (RSNA)},
  year = {2017}
}
[*] Pushpak Pati, Murat Arar, Govind Kaigala, Kashyap Aditya, Orcun Goksel, and Maria Gabrani: "Computational Immunohistochemistry: Recipes for Standardization of Immunostaining", In MICCAI, Quebec, QC, Canada, Sep 2017.  accepted
BibTeX:
@inproceedings{Pati_computational_17,
  author = {Pushpak Pati and Murat Arar and Govind Kaigala and Kashyap Aditya and Orcun Goksel and Maria Gabrani},
  title = {Computational Immunohistochemistry: Recipes for Standardization of Immunostaining},
  booktitle = {MICCAI},
  year = {2017}
}
[*] Corin F. Otesteanu, Bhaskara R. Chintada, Edoardo Mazza, Sergio J. Sanabria, and Orcun Goksel: "Quantification of nonlinear elastic constants using polynomials in quasi-incompressible soft solids", In IEEE Int Ultrasonics Symp (IUS), Washington, DC, USA, Sep 2017.  accepted
BibTeX:
@inproceedings{Otesteanu_quantification_17,
  author = {Corin F. Otesteanu and Bhaskara R. Chintada and Edoardo Mazza and Sergio J. Sanabria and Orcun Goksel},
  title = {Quantification of nonlinear elastic constants using polynomials in quasi-incompressible soft solids},
  booktitle = {IEEE Int Ultrasonics Symp (IUS)},
  year = {2017}
}
[*] Bhaskara R. Chintada, Sergio J. Sanabria, Wolfgang Bost, and Orcun Goksel: "Reflector-Based 3D Tomographic Ultrasound Reconstruction: Simulation Study", In IEEE Int Ultrasonics Symp (IUS), Washington, DC, USA, Sep 2017.  accepted
BibTeX:
@inproceedings{Chintada_reflector-based_17,
  author = {Bhaskara R. Chintada and Sergio J. Sanabria and Wolfgang Bost and Orcun Goksel},
  title = {Reflector-Based 3D Tomographic Ultrasound Reconstruction: Simulation Study},
  booktitle = {IEEE Int Ultrasonics Symp (IUS)},
  year = {2017}
}
[*] Fabien Pean, Fabio Carrillo, Philipp Fuernstahl, and Orcun Goksel: "Physical Simulation of the Interosseous Ligaments During Forearm Rotation", In Computer Assisted Orthopaedic Surgery, Aachen, Germany, Jun 2017.  
BibTeX:
@inproceedings{Pean_physical_17,
  author = {Fabien Pean and Fabio Carrillo and Philipp Fuernstahl and Orcun Goksel},
  title = {Physical Simulation of the Interosseous Ligaments During Forearm Rotation},
  booktitle = {Computer Assisted Orthopaedic Surgery},
  year = {2017},
  url = {https://easychair.org/publications/paper/350665}
}
[*] Oliver Mattausch, Elisabeth Ren, Michael Bajka, Kenneth Vanhoey, and Orcun Goksel: "Comparison of Texture Synthesis Methods for Content Generation in Ultrasound Training Simulation", In SPIE Medical Imaging, pp. 1-8, Orlando, FL, USA, Feb 2017.  
Abstract: A key aspect for virtual-reality based ultrasound training
is the plausible simulation of the characteristic noise pattern known as
ultrasonic speckle. The formation of ultrasonic speckle can be approximated
efficiently by convolving the ultrasound point-spread function
(PSF) with a distribution of point scatterers. Recent work extracts the
latter directly from ultrasound images for use in forward simulation, assuming
that the PSF can be known, e.g., from experiments. In this paper,
we investigate the problem of automatically estimating an unknown PSF
for the purpose of ultrasound simulation, such as to use in convolution-based
ultrasound image formation. Our method estimates the PSF directly
from an ultrasound image, based on homomorphic filtering in the
cepstrum domain. It robustly captures local changes in the PSF as a
function of depth, and hence is able to reproduce continuous ultrasound
beam profiles. We compare our method to numerical simulations as the
ground truth to study PSF estimation accuracy, achieving small approximation
errors of 15% FWHM. We also demonstrate simulated in-vivo
images, with beam profiles estimated from real images.
BibTeX:
@inproceedings{Mattausch_comparison_17,
  author = {Oliver Mattausch and Elisabeth Ren and Michael Bajka and Kenneth Vanhoey and Orcun Goksel},
  title = {Comparison of Texture Synthesis Methods for Content Generation in Ultrasound Training Simulation},
  booktitle = {SPIE Medical Imaging},
  year = {2017},
  pages = {1-8},
  doi = {10.1117/12.2250604}
}
[*]Orcun Goksel, Valeria DeLuca, Maxim Makhinya, and Christine Tanner: "Abdominal Motion Tracking and Prediction in 2D Ultrasound", In 4D Treatment Planning (4DTP) Workshop, Groningen, Netherlands, Nov 2016.  
BibTeX:
@inproceedings{Goksel_abdominal_16,
  author = {Orcun Goksel and Valeria DeLuca and Maxim Makhinya and Christine Tanner},
  title = {Abdominal Motion Tracking and Prediction in 2D Ultrasound},
  booktitle = {4D Treatment Planning (4DTP) Workshop},
  year = {2016}
}
[*] Valeriy Vishnevskiy, Christine Tanner, and Orcun Goksel: "Accurate and Fast Deformable Image Registration Allowing For Sliding Interfaces", In 4D Treatment Planning (4DTP) Workshop, Groningen, Netherlands, Nov 2016.  
BibTeX:
@inproceedings{Vishnevskiy_accurate_16,
  author = {Valeriy Vishnevskiy and Christine Tanner and Orcun Goksel},
  title = {Accurate and Fast Deformable Image Registration Allowing For Sliding Interfaces},
  booktitle = {4D Treatment Planning (4DTP) Workshop},
  year = {2016}
}
[*] Sergio J. Sanabria and Orcun Goksel: "Hand-held Sound-Speed Mammography Based on Ultrasound Reflector Tracking", In MICCAI, pp. 568-576, Athens, Greece, Oct 2016.  
Abstract: A novel hand-held speed-of-sound (SoS) imaging method is proposed, which requires only minor hardware extensions to conventional ultrasound (US) B-mode systems. A hand-held reflector is used as a timing reference for US signals. A robust reflector-detection algorithm, based on dynamic programming (DP), achieves unambiguous timing even with 10 dB signal-to-noise ratio in real tissues, successfully detecting delays <100 ns introduced by SoS heterogeneities. An Anisotropically-Weighted Total-Variation (AWTV) regularization based on L1-norm smoothness reconstruction is shown to achieve significant improvements in the delineation of focal lesions. The Contrast-to-noise-ratio (CNR) is improved from 15 dB to 37 dB, and the axial resolution loss from >300% to <15 Experiments with breast-mimicking phantoms and ex-vivo liver samples showed, for hard hypoechogenic inclusions not visible in B-mode US, a high SoS contrast (2.6 with respect to cystic inclusions (0.9 and the background SoS noise (0.6. We also tested our method on a healthy volunteer in a preliminary in-vivo test. The proposed technique demonstrates potential for low-cost and non-ionizing screening, as well as for diagnostics in daily clinical routine.
BibTeX:
@inproceedings{Sanabria_hand-held_16,
  author = {Sergio J. Sanabria and Orcun Goksel},
  title = {Hand-held Sound-Speed Mammography Based on Ultrasound Reflector Tracking},
  booktitle = {MICCAI},
  year = {2016},
  pages = {568-576},
  doi = {10.1007/978-3-319-46720-7_66}
}
[*] Firat Ozdemir, Ece Ozkan, and Orcun Goksel: "Graphical Modeling of Ultrasound Propagation in Tissue for Automatic Bone Segmentation", In MICCAI, pp. 256-264, Athens, Greece, Oct 2016.  
Abstract: Bone surface identification and localization in ultrasound have been widely studied in the contexts of computer-assisted orthopedic surgeries, trauma diagnosis, and post-operative follow-up. Nevertheless, the (semi-)automatic bone surface segmentation methods proposed so far either require manual interaction or complex parametrizations, while failing to deliver accuracy fit for clinical purposes. In this paper, we utilize the physics of ultrasound propagation in human tissue by encoding this in a factor graph formulation for an automatic bone surface segmentation approach. We comparatively evaluate our method on annotated in-vivo ultrasound images of bones from several anatomical locations. Our method yields a root-mean-square error of 0.59 mm, far superior to state-of-the-art approaches.
BibTeX:
@inproceedings{Ozdemir_graphical_16,
  author = {Firat Ozdemir and Ece Ozkan and Orcun Goksel},
  title = {Graphical Modeling of Ultrasound Propagation in Tissue for Automatic Bone Segmentation},
  booktitle = {MICCAI},
  year = {2016},
  pages = {256-264},
  doi = {10.1007/978-3-319-46723-8_30}
}
[*] Christine Tanner, Celine Eggenberger, Barbara Flach, Oliver Mattausch, Michael Bajka, and Orcun Goksel: "4D Reconstruction of Fetal Heart Ultrasound Images in Presence of Fetal Motion", In MICCAI, pp. 593-601, Athens, Greece, Oct 2016.  
Abstract: 4D ultrasound imaging of the fetal heart relies on reconstructions from B-mode images. In the presence of fetal or mother�s motion, current approaches suffer from artifacts. We propose to use many sweeps and exploit the resulting redundancy to recover from motion by reconstructing a 4D image which is consistent in phase, space and time. We first quantified the performance of 7 formulations on simulated data. Reconstructions of the best and baseline approach were then visually compared for 10 in-vivo sequences. Ratings from 4 observers showed that the proposed consistent reconstruction significantly improved image quality.
BibTeX:
@inproceedings{Tanner_4D_16,
  author = {Christine Tanner and Celine Eggenberger and Barbara Flach and Oliver Mattausch and Michael Bajka and Orcun Goksel},
  title = {4D Reconstruction of Fetal Heart Ultrasound Images in Presence of Fetal Motion},
  booktitle = {MICCAI},
  year = {2016},
  pages = {593-601},
  doi = {10.1007/978-3-319-46720-7_69}
}
[*] Oliver Mattausch and Orcun Goksel: "Image-based PSF Estimation for Ultrasound Training Simulation", In MICCAI W Simulation and Synthesis in Medical Imaging (SASHIMI), pp. 23-33, Athens, Greece, Oct 2016.  
Abstract: A key aspect for virtual-reality based ultrasound training is the plausible simulation of the characteristic noise pattern known as ultrasonic speckle. The formation of ultrasonic speckle can be approximated efficiently by convolving the ultrasound point-spread function (PSF) with a distribution of point scatterers. Recent work extracts the latter directly from ultrasound images for use in forward simulation, assuming that the PSF can be known, e.g., from experiments. In this paper, we investigate the problem of automatically estimating an unknown PSF for the purpose of ultrasound simulation, such as to use in convolution-based ultrasound image formation. Our method estimates the PSF directly from an ultrasound image, based on homomorphic filtering in the cepstrum domain. It robustly captures local changes in the PSF as a function of depth, and hence is able to reproduce continuous ultrasound beam profiles. We compare our method to numerical simulations as the ground truth to study PSF estimation accuracy, achieving small approximation errors of <=15% FWHM. We also demonstrate simulated in-vivo images, with beam profiles estimated from real images.
BibTeX:
@inproceedings{Mattausch_image-based_16,
  author = {Oliver Mattausch and Orcun Goksel},
  title = {Image-based PSF Estimation for Ultrasound Training Simulation},
  booktitle = {MICCAI W Simulation and Synthesis in Medical Imaging (SASHIMI)},
  year = {2016},
  pages = {23-33},
  doi = {10.1007/978-3-319-46630-9_3}
}
[*] Barbara Flach, Maxim Makhinya, and Orcun Goksel: "PURE: Panoramic Ultrasound Reconstruction by Seamless Stitching of Volumes", In MICCAI W Simulation and Synthesis in Medical Imaging (SASHIMI), pp. 75-84, Athens, Greece, Oct 2016.  
Abstract: For training sonographers in navigating, acquiring, and interpreting ultrasound images, virtual-reality based simulation offers a safe, extensible, and standardized environment. In data-based training simulations, images from a-priori acquired volumes are displayed to the trainee. To understand the relationship between organs, it is necessary to allow for free exploration of the entire anatomy, which is often not possible with the limited field-of-view (FOV) of a single ultrasound volume. Thus, large FOV ultrasound volumes are of paramount importance. Combining several volumes into one larger volume has also potential utility in many other applications, such as diagnostic and operative guidance. In this work, we propose a method for combining several ultrasound volumes with tracked positions into a single large volume by stitching them in a seamless fashion. For stitching, we determine an optimal cut interface such that each pixel value comes from a single image; preserving the inherent speckle texture and preventing any blurring and degradation from common mean/median binning approaches to combining volumes. The cut interface is found based on image content using graphical models optimized by graph-cut. We show that our method produces panoramic reconstructions with seamless transitions between individual 3D acquisitions. Regarding standard deviation in homogeneous regions we get 1-19% loss of ultrasound texture compared to small 3D volumes while mean value interpolation gives a loss of 15-68 The histograms of our reconstruction match the original histograms of the small 3D volumes almost perfectly with a Chi-squared distance of less than 0.01.
BibTeX:
@inproceedings{Flach_pure_16,
  author = {Barbara Flach and Maxim Makhinya and Orcun Goksel},
  title = {PURE: Panoramic Ultrasound Reconstruction by Seamless Stitching of Volumes},
  booktitle = {MICCAI W Simulation and Synthesis in Medical Imaging (SASHIMI)},
  year = {2016},
  pages = {75-84},
  doi = {10.1007/978-3-319-46630-9_8}
}
[*] Janine Thoma, Firat Ozdemir, and Orcun Goksel: "Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker", In MICCAI W Medical Computer Vision (MCV), pp. 1-11, Athens, Greece, Oct 2016.  
Abstract: MRI segmentation is a challenging task due to low anatomical contrast and large inter-patient variation. We propose a feature-driven automatic segmentation framework, combining voxel-wise classification with a Random-Walker (RW) based spatial regularization. Typically, such steps are treated independently, i.e. classification outcome is maximized without taking into account the regularization to follow. Herein we present a method for selective sampling of training patches, in view of the posterior spatial regularization. This aims to concentrate training samples near desired anatomical boundaries, around which the gain from a subsequent RW regularization will potentially be minimal. This trades of a lower classification accuracy for a higher joint segmentation performance. We compare our proposed sampling strategy to conventional uniform sampling on 20 full-body MR T1 scans from the VISCERAL dataset, both with RW and Markov Random Fields regularizations, showing Dice improvements of upto 12x with the proposed approach.
BibTeX:
@inproceedings{Thoma_automatic_16,
  author = {Janine Thoma and Firat Ozdemir and Orcun Goksel},
  title = {Automatic Segmentation of Abdominal MRI Using Selective Sampling and Random Walker},
  booktitle = {MICCAI W Medical Computer Vision (MCV)},
  year = {2016},
  pages = {1-11}
}
[*] Sergio J Sanabria, Marga Rominger, Corin F. Otesteanu, Edoardo Mazza, and Orcun Goksel: "Non-Linear Characterization of the Liver by Combining Shear and Longitudinal Wave Speed With Strain Observations", In Int Tissue Elasticity Conf (ITEC), Vermont, NE, USA, Oct 2016.  
BibTeX:
@inproceedings{Sanabria_non-linear_16,
  author = {Sergio J Sanabria and Marga Rominger and Corin F. Otesteanu and Edoardo Mazza and Orcun Goksel},
  title = {Non-Linear Characterization of the Liver by Combining Shear and Longitudinal Wave Speed With Strain Observations},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2016}
}
[*] Ece Ozkan and Orcun Goksel: "Compliance Boundary Conditions for Elasticity Reconstruction Using FEM Inverse Problem", In Int Tissue Elasticity Conf (ITEC), Vermont, NE, USA, Oct 2016.  
BibTeX:
@inproceedings{Ozkan_compliance_16,
  author = {Ece Ozkan and Orcun Goksel},
  title = {Compliance Boundary Conditions for Elasticity Reconstruction Using FEM Inverse Problem},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2016}
}
[*] Corin F. Otesteanu, Sergio J Sanabria, and Orcun Goksel: "Low Cost Alternative for Ultrasound Harmonic Elastography", In Int Tissue Elasticity Conf (ITEC), Vermont, NE, USA, Oct 2016.  
BibTeX:
@inproceedings{Otesteanu_low-cost_16,
  author = {Corin F. Otesteanu and Sergio J Sanabria and Orcun Goksel},
  title = {Low Cost Alternative for Ultrasound Harmonic Elastography},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2016}
}
[*] Andreas Kurth, Andreas Tretter, Pascal A. Hager, Sergio Sanabria, Orcun Goksel, Lothar Thiele, and Luca Benini: "Mobile Ultrasound Imaging on Heterogeneous Multi-Core Platform", In ACM/IEEE Symp on Embedded Systems for Real-time Multimedia (ESTIMedia), pp. 9-18, Pittsburgh, USA, Oct 2016.  

* Best Paper Award

Abstract: Ultrasound imaging is one of the most important medical diagnostic methods. The bulkiness of state-of-the-art high-quality ultrasound devices, however, drastically limits their usability in important application scenarios. In this paper, we show how a portable medical ultrasound device can be built using many-core technology and programmable logic, combining low power consumption with high flexibility. We discuss a typical ultrasound image reconstruction algorithm and how it can be parallelized using a pipelined design that efficiently partitions the workload among heterogeneous processing elements. A special focus lies on the limited memory resources and data bandwidth between components. To tackle both problems, we use floating window buffers and approximate computations, and we minimize lookup table sizes using on-the-fly calculations. We evaluate the design on the Adapteva Parallella platform, which contains a power-efficient 16-core Epiphany coprocessor and a Zynq SoC including a dual-core ARM A9 processor and programmable logic. Experimental results show that parallel beamforming of 128 input channels to a 288x 128 pixel ultrasound image can be achieved on the Parallella at a rate of 5.3 frames per second consuming only 2 watt of dynamic power.
BibTeX:
@inproceedings{Kurth_mobile_16,
  author = {Andreas Kurth and Andreas Tretter and Pascal A. Hager and Sergio Sanabria and Orcun Goksel and Lothar Thiele and Luca Benini},
  title = {Mobile Ultrasound Imaging on Heterogeneous Multi-Core Platform},
  booktitle = {ACM/IEEE Symp on Embedded Systems for Real-time Multimedia (ESTIMedia)},
  year = {2016},
  pages = {9-18},
  doi = {10.1145/2993452.2993565}
}
[*] Ece Ozkan and Orcun Goksel: "Inverse Problem of Ultrasound Beamforming with Sparsity in Time and Frequency Domain", In IEEE Int Ultrasonics Symp (IUS), Tours, France, Sep 2016.  
BibTeX:
@inproceedings{Ozkan_inverse_16,
  author = {Ece Ozkan and Orcun Goksel},
  title = {Inverse Problem of Ultrasound Beamforming with Sparsity in Time and Frequency Domain},
  booktitle = {IEEE Int Ultrasonics Symp (IUS)},
  year = {2016}
}
[*] Oliver Mattausch and Orcun Goksel: "Monte-Carlo Ray-Tracing for Realistic Interactive Ultrasound Simulation", In Eurographics W Visual Computing for Biology and Medicine (VCBM), pp. 1-9, Bergen, Norway, Sep 2016.  

* Best Paper Award

Abstract: Ray-based simulations have been shown to generate impressively realistic ultrasound images in interactive frame rates. Recent efforts used GPU-based surface ray-tracing to simulate complex ultrasound interactions such as multiple reflections and refractions. These methods are restricted to perfectly specular reflections (i.e., following only a single reflective/refractive ray), whereas real tissue exhibits roughness of varying degree at tissue interfaces, causing partly diffuse reflections and refractions. Such surface interactions are significantly more complex and can in general not be handled by such deterministic ray-tracing approaches. However, they can be efficiently computed by Monte-Carlo sampling techniques, where many ray paths are generated with respect to a probability distribution. In this paper we introduce Monte-Carlo ray-tracing for ultrasound. This enables the realistic simulation of ultrasound interactions such as soft shadows and fuzzy reflections. We discuss how to properly weight the contribution of each ray path in order to simulate the behavior of a beamformed ultrasound signal. Tracing many individual rays per transducer element is easily parallelizable on modern GPUs, as opposed to previous approaches based on recursive binary ray-tracing.
BibTeX:
@inproceedings{Mattausch_monte-carlo_16,
  author = {Oliver Mattausch and Orcun Goksel},
  title = {Monte-Carlo Ray-Tracing for Realistic Interactive Ultrasound Simulation},
  booktitle = {Eurographics W Visual Computing for Biology and Medicine (VCBM)},
  year = {2016},
  pages = {1-9},
  doi = {dx.doi.org/10.2312/vcbm.20161285}
}
[*] Xiaoran Chen, Christine Tanner, Orçun Göksel, Gábor Székely, and Valeria Luca: "Temporal Prediction of Respiratory Motion Using a Trained Ensemble of Forecasting Methods", In Medical Imaging and Augmented Reality (MIAR), pp. 383-391, Bern, Switzerland, Aug 2016.  
Abstract: Respiratory motion is a limiting factor during cancer therapy. Although image tracking can facilitate compensation for this motion, system latencies will still reduce the accuracy of tracking-based treatments. We propose a novel approach for temporal prediction of the motion of anatomical targets in the liver, observed from ultrasound sequences. The method is based on an ensemble of six prediction models, including neural networks, which are trained on motion traces and images. Using leave-one-subject-out validation on 24 liver ultrasound 2D sequences from the Challenge on Liver Ultrasound Tracking, the best performance was achieved by the linear regression-based ensemble of all methods with an accuracy of 1.49 (2.39) mm for a latency of 300 (600) ms.
BibTeX:
@inproceedings{Chen_temporal_16,
  author = {Chen, Xiaoran and Tanner, Christine and G\"oksel, Or\ccun and Sz\'ekely, G\'abor and Luca, Valeria},
  title = {Temporal Prediction of Respiratory Motion Using a Trained Ensemble of Forecasting Methods},
  booktitle = {Medical Imaging and Augmented Reality (MIAR)},
  year = {2016},
  pages = {383-391},
  doi = {10.1007/978-3-319-43775-0_35}
}
[*] Corin Felix Otesteanu, Sergio J Sanabria, and Orcun Goksel: "Analysis of Excitation Frequency in Elasticity Reconstruction Using the FEM Inverse-Problem", In IEEE Int Symp Biomedical Imaging (ISBI), pp. 485-8, Prague, Czech Republic, Apr 2016.  
Abstract: Multi-frequency harmonic elastography is a technique that involves applying vibrations to tissues in order to measure their mechanical properties. High speed plane wave ultrasound imaging is used to image dynamic deformations produced by a voice coil actuator on a gelatin phantom with a hard inclusion mimicking a focal lesion (e.g. breast, liver). Tissue displacements are estimated from the echo data and used in a finite element inverse elasticity problem. Until now, mostly one or very few frequencies were used for tissue excitation which could lead to inconclusive or misleading results. In this paper we analyze a broad bandwidth of 100 Hz with a fine 5 Hz step and study the effect of the frequency excitation on the inversion of the inclusion geometry and stiffness ratio with respect to background. The results show the importance of using numerous frequencies for tissue excitation, as focal lesions could be "invisible" or have a deformed structure at certain frequencies.
BibTeX:
@inproceedings{Otesteanu_analysis_16,
  author = {Corin Felix Otesteanu and Sergio J Sanabria and Orcun Goksel},
  title = {Analysis of Excitation Frequency in Elasticity Reconstruction Using the FEM Inverse-Problem},
  booktitle = {IEEE Int Symp Biomedical Imaging (ISBI)},
  year = {2016},
  pages = {485-8},
  doi = {10.1109/ISBI.2016.7493313}
}
[*]Orcun Goksel, Valery Vishnevsky, Alvaro Gomariz Carrillo, and Christine Tanner: "Imaging of Sliding Visceral Interfaces During Breathing", In IEEE Int Symp Biomedical Imaging (ISBI), pp. 298-301, Prague, Czech Republic, Apr 2016.  
BibTeX:
@inproceedings{Goksel_imaging_16,
  author = {Orcun Goksel and Valery Vishnevsky and Alvaro Gomariz Carrillo and Christine Tanner},
  title = {Imaging of Sliding Visceral Interfaces During Breathing},
  booktitle = {IEEE Int Symp Biomedical Imaging (ISBI)},
  year = {2016},
  pages = {298-301},
  doi = {10.1109/ISBI.2016.7493268}
}
[*] Barbara Flach, Maxim Makhinya, and Orcun Goksel: "Model-based Compensation of Tissue Deformation During Data Acquisition for Interpolative Ultrasound Simulation", In IEEE Int Symp Biomed Imaging (ISBI), pp. 502-5, Prague, Czech Republic, Apr 2016.  
BibTeX:
@inproceedings{Flach_model-based_16,
  author = {Barbara Flach and Maxim Makhinya and Orcun Goksel},
  title = {Model-based Compensation of Tissue Deformation During Data Acquisition for Interpolative Ultrasound Simulation},
  booktitle = {IEEE Int Symp Biomed Imaging (ISBI)},
  year = {2016},
  pages = {502-5},
  doi = {10.1109/ISBI.2016.7493317}
}
[*] Maxim Makhinya and Orcun Goksel: "Real-time Tracking of Liver Landmarks in 2D Ultrasound Sequences", In 4D Treatment Planning (4DTP) Workshop, Dresden, Germany, Nov 2015.  

* Best Poster Award

BibTeX:
@inproceedings{Makhinya_real-time_15,
  author = {Maxim Makhinya and Orcun Goksel},
  title = {Real-time Tracking of Liver Landmarks in 2D Ultrasound Sequences},
  booktitle = {4D Treatment Planning (4DTP) Workshop},
  year = {2015}
}
[*] Maxim Makhinya and Orcun Goksel: "Motion Tracking in 2D Ultrasound Using Vessel Models and Robust Optic-Flow", In MICCAI Challenge on Liver Motion Tracking (CLUST), Munich, Germany, Oct 2015.  
Abstract: Planned delivery of focused therapy is adversely affected by internal
body motion, such as from breathing, which could be mitigated, if
tracked accurately in real-time. By extending an algorithm for superficial
vein tracking, we hereby present a robust real-time motion tracking
method for 2D ultrasound image sequences of the liver. The method
leverages elliptic and template-based models of vessels in the liver,
coupled with a robust optic-flow framework. Potential drifts in this
iterative tracking are corrected when the breathing phase is close
to that of the initial reference frame, detected by comparing the
appearance of tracked feature regions. Results are evaluated on the
CLUST-2015 dataset, with 1.09mm mean and 2.42mm 95th percentile errors
in 24 2D test sequences collected from four different centers.
BibTeX:
@inproceedings{Makhinya_motion_15,
  author = {Maxim Makhinya and Orcun Goksel},
  title = {Motion Tracking in 2D Ultrasound Using Vessel Models and Robust Optic-Flow},
  booktitle = {MICCAI Challenge on Liver Motion Tracking (CLUST)},
  year = {2015},
  url = {http://clust.ethz.ch/opendownload/CLUST2015/makhinya_clust15.pdf}
}
[*] Sergio J. Sanabria, Corin F. Otesteanu, and Orcun Goksel: "Hand-held Sound-speed Imaging for the Reconstruction of Bulk Modulus and Poisson Ratio in a Commercial Tissue-Mimicking Phantom", In Int Tissue Elasticity Conf (ITEC), Verona, Italy, Sep 2015.  
BibTeX:
@inproceedings{Sanabria_hand-held_15,
  author = {Sergio J. Sanabria and Corin F. Otesteanu and Orcun Goksel},
  title = {Hand-held Sound-speed Imaging for the Reconstruction of Bulk Modulus and Poisson Ratio in a Commercial Tissue-Mimicking Phantom},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2015}
}
[*] Sergio J. Sanabria and Orcun Goksel: "Total-Variation Regularization of Hand-held Limited-Angle Sound-Speed Tomography Based on Coherent Reflector for Breast Cancer Detection", In Int Tissue Elasticity Conf (ITEC), Verona, Italy, Sep 2015.  
BibTeX:
@inproceedings{Sanabria_total-variation_15,
  author = {Sergio J. Sanabria and Orcun Goksel},
  title = {Total-Variation Regularization of Hand-held Limited-Angle Sound-Speed Tomography Based on Coherent Reflector for Breast Cancer Detection},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2015}
}
[*] Ece Ozkan and Orcun Goksel: "Compliance Boundary Conditions for Simulating Deformations in a Limited Region of Interest", In IEEE Eng Medicine and Biology Conf (EMBC), pp. 929-32, Milano, Italy, Aug 2015.  
Abstract: Patient-specific models in medical procedures are often limited to
a relatively small region of interest due either to computational
concerns or to the fact that only a part of anatomy could be observed
in the input medical images. Thus, for deformable planning or training
simulations, boundary conditions at the borders of such models are
necessitated. Zero-displacement or -force constraints at outer boundaries
are commonly used, with the assumption that the selected region is
large enough to minimize effects on the deformable behavior inside
the region of interest. This may, however, still result in errors
and does require superfluous elements to extend models. In this work,
a mixed boundary condition type called compliance boundary condition,
is proposed to constrain model boundaries. Different techniques to
define and estimate such constraints are studied in simulation experiments.
Results are presented in 2D and 3D numerical phantoms and a male
pelvic anatomical model.
BibTeX:
@inproceedings{Ozkan_compliance_15,
  author = {Ece Ozkan and Orcun Goksel},
  title = {Compliance Boundary Conditions for Simulating Deformations in a Limited Region of Interest},
  booktitle = {IEEE Eng Medicine and Biology Conf (EMBC)},
  year = {2015},
  pages = {929-32},
  doi = {10.1109/EMBC.2015.7318515}
}
[*] Oliver Mattausch and Orcun Goksel: "Scatterer Reconstruction and Parametrization of Homogeneous Tissue for Ultrasound Image Simulation", In IEEE Eng Medicine and Biology Conf (EMBC), pp. 6350-3, Milano, Italy, Aug 2015.  
Abstract: Numerical simulation of ultrasound images can facilitate the training
of sonographers. A realistic appearance of simulated ultrasonic speckle
is essential for a plausible ultrasound simulation. An efficient
and realistic model for ultrasonic speckle is the convolution of
the ultrasound point-spread function with a parametrized distribution
of point scatterers. Nevertheless, for a given arbitrary tissue,
such scatterer distributions that would generate a realistic image
are not known a priori, and currently there is no principled method
to extract such scatterer patterns for given target tissues to be
simulated. In this paper we propose to solve the inverse problem,
in which an underlying scatterer map for a given sample ultrasound
image is estimated. From such scatterer maps, it is also shown that
a parametrization distribution model can be built, using which other
instances of the same tissue can be simulated by feeding into a standard
speckle generation method. This enables us to synthesize images of
different tissue types from actual ultrasound images to be used in
simulations with arbitrary view angles and transducer settings. We
show in numerical and physical tissue-mimicking phantoms and actual
physical tissue that the appearance of the synthesized images closely
match the real images.
BibTeX:
@inproceedings{Mattausch_scatterer_15,
  author = {Oliver Mattausch and Orcun Goksel},
  title = {Scatterer Reconstruction and Parametrization of Homogeneous Tissue for Ultrasound Image Simulation},
  booktitle = {IEEE Eng Medicine and Biology Conf (EMBC)},
  year = {2015},
  pages = {6350-3},
  doi = {10.1109/EMBC.2015.7319845}
}
[*] Peter Baki, Sergio J. Sanabria, Gabor Kosa, Gabor Szekely, and Orcun Goksel: "Thermal Expansion Imaging for Monitoring Lesion Depth using M-Mode Ultrasound during Cardiac RF Ablation: In-vitro Study", In Information Processing in Computer-Assisted Interventions (IPCAI), Barcelona, Spain, Jun 2015.  
BibTeX:
@inproceedings{Baki_thermal_15t,
  author = {Peter Baki and Sergio J. Sanabria and Gabor Kosa and Gabor Szekely and Orcun Goksel},
  title = {Thermal Expansion Imaging for Monitoring Lesion Depth using M-Mode Ultrasound during Cardiac RF Ablation: In-vitro Study},
  booktitle = {Information Processing in Computer-Assisted Interventions (IPCAI)},
  year = {2015}
}
[*] Valery Vishnevsky, Tobias Gass, Gabor Szekely, Christine Tanner, and Orcun Goksel: "Unsupervised Detection of Local Errors in Image Registration", In IEEE Int Symp Biomedical Imaging (ISBI), pp. 841-4, New York, USA, Apr 2015.  
BibTeX:
@inproceedings{Vishnevsky_unsupervised_15,
  author = {Valery Vishnevsky and Tobias Gass and Gabor Szekely and Christine Tanner and Orcun Goksel},
  title = {Unsupervised Detection of Local Errors in Image Registration},
  booktitle = {IEEE Int Symp Biomedical Imaging (ISBI)},
  year = {2015},
  pages = {841-4},
  doi = {10.1109/ISBI.2015.7164002}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Multi-Atlas Segmentation and Landmark Localization in Images with Large Fields of View", In MICCAI W Medical Computer Vision (MCV): Algorithms for Big Data, pp. 171-80, Boston, MA, USA, Sep 2014.  
BibTeX:
@inproceedings{Gass_multi-atlas_14,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Multi-Atlas Segmentation and Landmark Localization in Images with Large Fields of View},
  booktitle = {MICCAI W Medical Computer Vision (MCV): Algorithms for Big Data},
  year = {2014},
  pages = {171-80},
  doi = {10.1007/978-3-319-13972-2_16}
}
[*] Valeriy Vishnevskiy, Tobias Gass, Gabor Szekely, and Orcun Goksel: "Total Variation Regularization of Displacements in Parametric Image Registration", In MICCAI W Abdominal Imaging: Computational and Clinical Apps, pp. 211-220, Boston, MA, USA, Sep 2014.  

* Best Poster Award at the 4D Treatment Planning Workshop in London, UK (Nov, 2014)

BibTeX:
@inproceedings{Vishnevskiy_total_14,
  author = {Valeriy Vishnevskiy and Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Total Variation Regularization of Displacements in Parametric Image Registration},
  booktitle = {MICCAI W Abdominal Imaging: Computational and Clinical Apps},
  year = {2014},
  pages = {211-220},
  doi = {10.1007/978-3-319-13692-9_20}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Registration Fusion using Markov Random Fields", In Workshop on Biomedical Image Registration (WBIR), pp. 213-222, London, UK, Jul 2014.  
Abstract: Image registration is a ubiquitous technique in medical imaging. However,
finding correspondences reliably between images is a difficult task
since the registration problem is ill-posed and registration algorithms
are only capable of finding local optima. This makes it challenging
to find a suitable registration method and parametrization for a
specific application. To alleviate such problems, multiple registrations
can be fused which is typically done by weighted averaging, which
is sensitive to outliers and can not guarantee that registrations
improve. In contrast, in this work we present a Markov random field
based technique which fuses registrations by explicitly minimizing
local dissimilarities of deformed source and target image, while
penalizing non-smooth deformations. We additionally propose a registration
propagation technique which combines multiple registration hypotheses
which are obtained from different indirect paths in a set of mutually
registered images. Our fused registrations are experimentally shown
to improve pair-wise correspondences in terms of average deformation
error (ADE) and target registration error (TRE) as well as improving
post-registration segmentation overlap.
BibTeX:
@inproceedings{Gass_registration_14,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Registration Fusion using Markov Random Fields},
  booktitle = {Workshop on Biomedical Image Registration (WBIR)},
  year = {2014},
  pages = {213-222},
  doi = {10.1007/978-3-319-08554-8_22}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Consistent Dense Correspondences from Pairwise Registrations", In SHAPE Symp on Statistical Shape Models and Applications, pp. 10, Delemont, Switzerland, Jun 2014.  podium
BibTeX:
@inproceedings{Gass_consistent_14,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Consistent Dense Correspondences from Pairwise Registrations},
  booktitle = {SHAPE Symp on Statistical Shape Models and Applications},
  year = {2014},
  pages = {10}
}
[*]Orcun Goksel, Tobias Gass, and Gabor Szekely: "Segmentation and Landmark Localization Based on Multiple Atlases", In IEEE ISBI VISCERAL Challenge, pp. 37-43, Beijing, China, May 2014.  
Abstract: In this work, we present multi-atlas based techniques for both segmentation
and landmark detection. We focus on modality and anatomy independent
techniques to be applied to a wide range of input images, in contrast
to methods customized to a specific anatomy or image modality. For
segmentation, we use label propagation from several atlases to a
target image via a Markov random field (MRF) based registration method,
followed by label fusion by majority voting weighted by local cross-correlations.
For landmark localization, we use a consensus based fusion of location
estimates from several atlases identified by a template-matching
approach. Results in IEEE ISBI 2014 VISCERAL challenge as well as
VISCERAL Anatomy1 challenge are presented herein.
BibTeX:
@inproceedings{Goksel_segmentation_14,
  author = {Orcun Goksel and Tobias Gass and Gabor Szekely},
  title = {Segmentation and Landmark Localization Based on Multiple Atlases},
  booktitle = {IEEE ISBI VISCERAL Challenge},
  year = {2014},
  number = {1194},
  pages = {37-43},
  url = {http://ceur-ws.org/Vol-1194/visceralISBI14-5.pdf}
}
[*] Alessandro Crimi, Maxim Makhinya, Ulrich Baumann, Gabor Szekely, and Orcun Goksel: "Vessel tracking for Ultrasound-based venous pressure measurement", In IEEE Int Symp Biomedical Imaging (ISBI), pp. 306-9, Beijing, China, Apr 2014.  
Abstract: Information concerning central venous pressure (CVP) is crucial in
clinical situations, such as cardiac failure, volume overload, and
sepsis. The measurement of CVP, however, requires insertion of a
catheter through a vein up a vena cava - close to the heart - with
related cost and risk of complications. Peripheral venous pressure
(PVP) measurement is a technique which allows indirect assessment
of CVP without catheterization. However, PVP measurement is cumbersome
since it requires several devices, trained medical personnel, and
is difficult to perform repeatably. Aiming at an automatic venous
pressure measurement system via image-processing, we introduce in
this paper a robust vessel tracking algorithm fit for this purpose.
The proposed algorithm addresses the challenge of tracking compressed
vessels, which is essential for this venous pressure measurement
technique. Given this tracking algorithm, initial PVP measurements
on healthy volunteers are reported.
BibTeX:
@inproceedings{Crimi_vessel_14,
  author = {Alessandro Crimi and Maxim Makhinya and Ulrich Baumann and Gabor Szekely and Orcun Goksel},
  title = {Vessel tracking for Ultrasound-based venous pressure measurement},
  booktitle = {IEEE Int Symp Biomedical Imaging (ISBI)},
  year = {2014},
  pages = {306-9},
  doi = {10.1109/ISBI.2014.6867870}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Detection and correction of inconsistency-based errors in non-rigid registration", In SPIE Medical Imaging, pp. 90341B, San Diego, CA, USA, Feb 2014.  podium
Abstract: In this paper we present a novel post-processing technique to detect
and correct inconsistency-based errors in non-rigid registration.
While deformable registration is ubiquitous in medical image computing,
assessing its quality has yet been an open problem. We propose a
method that predicts local registration errors of existing pairwise
registrations between a set of images, while simultaneously estimating
corrected registrations. In the solution the error is constrained
to be small in areas of high post-registration image similarity,
while local registrations are constrained to be consistent between
direct and indirect registration paths. The latter is a critical
property of an ideal registration process, and has been frequently
used to asses the performance of registration algorithms. In our
work, the consistency is used as a target criterion, for which we
efficiently find a solution using a linear least-squares model on
a coarse grid of registration control points. We show experimentally
that the local errors estimated by our algorithm correlate strongly
with true registration errors in experiments with known, dense ground-truth
deformations. Additionally, the estimated corrected registrations
consistently improve over the initial registrations in terms of average
deformation error or TRE for different registration algorithms on
both simulated and clinical data, independent of modality (MRI/CT),
dimensionality (2D/3D) and employed primary registration method (demons/Markov-randomfield).
BibTeX:
@inproceedings{Gass_detection_14,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Detection and correction of inconsistency-based errors in non-rigid registration},
  booktitle = {SPIE Medical Imaging},
  year = {2014},
  pages = {90341B},
  doi = {10.1117/12.2042757}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Auxiliary anatomical labels for joint segmentation and atlas registration", In SPIE Medical Imaging, pp. 90343T, San Diego, CA, USA, Feb 2014.  poster
Abstract: This paper studies improving joint segmentation and registration by
introducing auxiliary labels for anatomy that has similar appearance
to the target anatomy while not being part of that target. Such auxiliary
labels help avoid false positive labelling of non-target anatomy
by resolving ambiguity. A known registration of a segmented atlas
can help identify where a target segmentation should lie. Conversely,
segmentations of anatomy in two images can help them be better registered.
Joint segmentation and registration is then a method that can leverage
information from both registration and segmentation to help one another.
It has received increasing attention recently in the literature.
Often, merely a single organ of interest is labelled in the atlas.
In the presense of other anatomical structures with similar appearance,
this leads to ambiguity in intensity based segmentation; for example,
when segmenting individual bones in CT images where other bones share
the same intensity profile. To alleviate this problem, we introduce
automatic generation of additional labels in atlas segmentations,
by marking similar-appearance non-target anatomy with an auxiliary
label. Information from the auxiliary-labeled atlas segmentation
is then incorporated by using a novel coherence potential, which
penalizes differences between the deformed atlas segmentation and
the target segmentation estimate. We validated this on a joint segmentation-registration
approach that iteratively alternates between registering an atlas
and segmenting the target image to find a final anatomical segmentation.
The results show that automatic auxiliary labelling outperforms the
same approach using a single label atlasses, for both mandibular
bone segmentation in 3D-CT and corpus callosum segmentation in 2D-MRI.
BibTeX:
@inproceedings{Gass_auxiliary_14,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Auxiliary anatomical labels for joint segmentation and atlas registration},
  booktitle = {SPIE Medical Imaging},
  year = {2014},
  pages = {90343T},
  doi = {10.1117/12.2042876}
}
[*]Orçun Göksel and Gabor Székely: "Improving FEM Inverse Problem Reconstructions By Incorporating All Displacement Observations Using Element Shape Function Interpolations", In Int Tissue Elasticity Conf (ITEC), pp. 78, Lingfield, UK, Oct 2013.  podium
BibTeX:
@inproceedings{Goksel_improving_13,
  author = {Or\c{c}un G\"oksel and Gabor Sz\'ekely},
  title = {Improving FEM Inverse Problem Reconstructions By Incorporating All Displacement Observations Using Element Shape Function Interpolations},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2013},
  pages = {78},
  url = {http://www.elasticityconference.org/PDF/2013/2013ITECProceedings.pdf}
}
[*] Péter Baki, Gabor Székely, and Orçun Göksel: "Thermal Expansion Imaging For Real-time Lesion Depth Assessment During RF Catheter Ablation", In Int Tissue Elasticity Conf (ITEC), pp. 70, Lingfield, UK, Oct 2013.  podium
BibTeX:
@inproceedings{Baki_thermal_13,
  author = {P\'eter Baki and Gabor Sz\'ekely and Or\c{c}un G\"oksel},
  title = {Thermal Expansion Imaging For Real-time Lesion Depth Assessment During RF Catheter Ablation},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2013},
  pages = {70},
  url = {http://www.elasticityconference.org/PDF/2013/2013ITECProceedings.pdf}
}
[*] Kamal Shahim, Orcun Goksel, Philipp Jürgens, and Mauricio Reyes: "Accuracy Improvement In Cranio-Maxillofacial Soft Tissue Simulation Using A Muscle Embedded Meshing Approach", In IEEE Eng Medicine and Biology Conf (EMBC), pp. 7156-9, Osaka, Japan, Jul 2013.  
Abstract: In the presented paper, we propose to improve the state-of-the-art
approach for Cranio-Maxillofacial (CMF) soft tissue simulation by
considering a new image-based meshing approach that accurately models
the interface between different tissue types. The proposed approach
has been initially evaluated on soft tissue deformations of four
patients undergoing CMF surgery using post-operative CT scans. The
results indicate improved prediction and robustness of the surgical
planning outcome when compared to the state-of-the-art method while
decreasing the simulation time.
BibTeX:
@inproceedings{Shahim_accuracy_13,
  author = {Kamal Shahim and Orcun Goksel and Philipp J\"urgens and Mauricio Reyes},
  title = {Accuracy Improvement In Cranio-Maxillofacial Soft Tissue Simulation Using A Muscle Embedded Meshing Approach},
  booktitle = {IEEE Eng Medicine and Biology Conf (EMBC)},
  year = {2013},
  pages = {7156-9},
  doi = {10.1109/EMBC.2013.6611208}
}
[*] Hua Ma, Thomas Coradi, Gabor Szekely, Benjamin Haas, and Orcun Goksel: "Supervised Learning with Global Features for Image Retrieval in Atlas-Based Segmentation of Thoracic CT", In Int Congress on Computer Assisted Radiology and Surgery (CARS), pp. S302, Heidelberg, Germany, Jun 2013.  poster
BibTeX:
@inproceedings{Ma_supervised_13,
  author = {Hua Ma and Thomas Coradi and Gabor Szekely and Benjamin Haas and Orcun Goksel},
  title = {Supervised Learning with Global Features for Image Retrieval in Atlas-Based Segmentation of Thoracic CT},
  booktitle = {Int Congress on Computer Assisted Radiology and Surgery (CARS)},
  year = {2013},
  pages = {S302}
}
[*]Orcun Goksel, Tobias Gass, Valery Vishnevsky, and Gabor Szekely: "Estimation of Atlas-Based Segmentation Outcome: Leveraging Information From Unsegmented Images", In IEEE Int Symp Biomedical Imaging (ISBI), pp. 1203-6, San Francisco, CA, USA, Apr 2013.  podium
Abstract: Segmentation via atlas registration is a common technique in medical
image analysis. Devising estimates of such segmentation outcome has
been of interest in cases with multiple atlases, both for single-atlas
selection and for multi-atlas fusion. This paper studies the estimation
of expected Dice's similarity metric for registering atlas-target
pairs, by employing registration loops with models of such metric
(error) accumulation over these loops. In this framework, the use
of registration information also from unsegmented images is proposed
and is shown to outperform using segmented atlas images alone. We
demonstrate a fast, memory-efficient implementation and single-atlas
selection results using a CT and an MR dataset.
BibTeX:
@inproceedings{Goksel_estimation_13,
  author = {Orcun Goksel and Tobias Gass and Valery Vishnevsky and Gabor Szekely},
  title = {Estimation of Atlas-Based Segmentation Outcome: Leveraging Information From Unsegmented Images},
  booktitle = {IEEE Int Symp Biomedical Imaging (ISBI)},
  year = {2013},
  pages = {1203-6},
  doi = {10.1109/ISBI.2013.6556699}
}
[*]Orcun Goksel, Seokhee Jeon, Matthias Harders, and Gabor Szekely: "Deformable Haptic Model Generation Through Manual Exploration", In IEEE World Haptics Conference, pp. 543-8, Daejeon, South Korea, Apr 2013.  podium
Abstract: Interaction with virtual deformable models is common in several haptic
contexts, such as in medical training simulators. This paper presents
a methodological procedure for the creation of such virtual models
from their real-life counterparts. Both the surface geometry and
the elastic parametrization of an object are reconstructed from position/force
readings during an operator-assisted exploration of the object. A
3D mesh model is then generated from the surface contact points.
The internal elastic modulus is found using the 3D finite element
method. This modeling method is compared with two common 1D elastic
models, namely Kelvin-Voigt and Hunt-Crossley. Results using three
deformable homogeneous silicone samples show successful geometry
reconstruction. 1D model parameterizations exhibit high variation
dependent on geometry and contact location. In contrast, elastic
modulus reconstruction yields a global model parameterization independent
of geometry. Elastic moduli estimated in experiments correlated with
their known values, and were shown to be reproducible among samples
with different geometries.
BibTeX:
@inproceedings{Goksel_deformable_13,
  author = {Orcun Goksel and Seokhee Jeon and Matthias Harders and Gabor Szekely},
  title = {Deformable Haptic Model Generation Through Manual Exploration},
  booktitle = {IEEE World Haptics Conference},
  year = {2013},
  pages = {543-8},
  doi = {10.1109/WHC.2013.6548466}
}
[*] Dimitris Bolis, Andras Jakab, Orcun Goksel, and Gabor Szekely: "On exploiting the connectomics for thalamic nuclei localization: application of pattern recognition techniques", In European Society for Magnetic Resonance in Medicine and Biology (ESMRMB), Lisbon, Portugal, Oct 2012.  poster
BibTeX:
@inproceedings{Bolis_exploiting_12a,
  author = {Dimitris Bolis and Andras Jakab and Orcun Goksel and Gabor Szekely},
  title = {On exploiting the connectomics for thalamic nuclei localization: application of pattern recognition techniques},
  booktitle = {European Society for Magnetic Resonance in Medicine and Biology (ESMRMB)},
  year = {2012}
}
[*] Tobias Gass, Gabor Szekely, and Orcun Goksel: "Semi-supervised Segmentation Using Multiple Segmentation Hypotheses from a Single Atlas", In MICCAI W Medical Computer Vision (MCV), pp. 29-37, Nice, France, Oct 2012.  podium

* Received one of 3 best paper prizes

Abstract: A semi-supervised segmentation method using a single atlas is presented
in this paper. Traditional atlas-based segmentation suffers from
either a strong bias towards the selected atlas or the need for manual
effort to create multiple atlas images. Similar to semi-supervised
learning in computer vision, we study a method which exploits information
contained in a set of unlabelled images by mutually registering them
non-rigidly and propagating the single atlas segmentation over multiple
such registration paths to each target. These multiple segmentation
hypotheses are then fused by local weighting based on registration
similarity. Our results on two datasets of different anatomies and
image modalities, corpus callosum MR and mandible CT images, show
a significant improvement in segmentation accuracy compared to traditional
single atlas based segmentation. We also show that the bias towards
the selected atlas is minimized using our method. Additionally, we
devise a method for the selection of intermediate targets used for
propagation, in order to reduce the number of necessary inter-target
registrations without loss of final segmentation accuracy.
BibTeX:
@inproceedings{Gass_semi-supervised_12,
  author = {Tobias Gass and Gabor Szekely and Orcun Goksel},
  title = {Semi-supervised Segmentation Using Multiple Segmentation Hypotheses from a Single Atlas},
  booktitle = {MICCAI W Medical Computer Vision (MCV)},
  year = {2012},
  pages = {29-37},
  doi = {10.1007/978-3-642-36620-8_4}
}
[*] Dimitris Bolis, András Jakab, Orçun Göksel, and Gábor Székely: "On Exploiting Connectomics for Thalamic Nuclei Localization: A Supervised Learning Approach", In Int Conf on Machine Learning (ICML) Workshop on Statistics, Machine Learning and Neuroscience, Edinburgh, Scotland, UK, Jul 2012.  
BibTeX:
@inproceedings{Bolis_exploiting_12,
  author = {Dimitris Bolis and Andr\'as Jakab and Or\ccun G\"oksel and G\'abor Sz\'ekely},
  title = {On Exploiting Connectomics for Thalamic Nuclei Localization: A Supervised Learning Approach},
  booktitle = {Int Conf on Machine Learning (ICML) Workshop on Statistics, Machine Learning and Neuroscience},
  year = {2012},
  url = {https://sites.google.com/site/stamlins/proceedings}
}
[*] Dimitris Bolis, Andras Jakab, Orcun Goksel, and Gabor Szekely: "Application of pattern recognition techniques to locate the Vim thalamic nucleus based on thalamocortical tractography", In European Congress on Radiology (ECR), pp. C-1991, Vienna, Austria, Mar 2012.  poster
Abstract: Purpose: During deep brain stimulation and ablative therapies, subcortical
structures are targeted by transferring a stereotactical atlas onto
the patient�s anatomical images. We hypothesize that diffusion tensor
imaging and mapping of thalamocortical connections can serve as surrogate
markers of individual anatomy and can be used to predict specific
targets in the thalamus. Here we demonstrate the application of a
support vector machine (SVM) based tool that is optimized to predict
the location of the ventral intermediate nucleus. Methods and Materials:
Previously, a 3D atlas of the thalamus was non-linearly matched with
an MR template. Anatomical, diffusion tensor MR imaging and probabilistic
thalamocortical tractography to 52 cortical and subcortical areas
were performed for 40 subjects. We assumed that the volume of the
atlas-based Vim nucleus and the same structure of the subjects� coincides
on standardized images in our population and can be used to train
an SVM based classifier to predict the boundaries and volume of the
Vim. Results: Using thalamocortical connectivity distributions and
the distance from the anterior commissure as features, the classifier
was able to reproduce the atlas-based location with 84 % sensitivity
and 74 % specificity. The resulting maps were able to reproduce the
gross borders of the Vim. Conclusion: We have generated patient specific
maps that showed the possible boundaries of the Vim nucleus, this
tool can be evaluated for neurosurgical targeting. We demonstrated
the applicability of this method in cases when purely atlas-based
methods might be insufficient, when the anatomy is disrupted (a tumor
case) or unknown (pediatric cases).
BibTeX:
@inproceedings{Bolis_application_12,
  author = {Dimitris Bolis and Andras Jakab and Orcun Goksel and Gabor Szekely},
  title = {Application of pattern recognition techniques to locate the Vim thalamic nucleus based on thalamocortical tractography},
  booktitle = {European Congress on Radiology (ECR)},
  year = {2012},
  pages = {C-1991}
}
[*] Farheen Taquee, Orcun Goksel, S. Sara Mahdavi, Mira Keyes, W. James Morris, Ingrid Spadinger, and Septimiu Salcudean: "Deformable Prostate Registration from MR and TRUS Images Using Surface Error Driven FEM models", In SPIE Medical Imaging, San Diego, CA, USA, Feb 2012.  
Abstract: The fusion of TransRectal Ultrasound (TRUS) and Magnetic Resonance
(MR) images of the prostate can aid diagnosis and treatment planning
for prostate cancer. Surface segmentations of the prostate are available
in both modalities. Our goal is to develop a 3D deformable registration
method based on these segmentations and a biomechanical model. The
segmented source volume is meshed and a linear finite element model
is created for it. This volume is deformed to the target image volume
by applying surface forces computed by assuming a negative relative
pressure between the non-overlapping regions of the volumes and the
overlapping ones. This pressure drives the model to increase the
volume overlap until the surfaces are aligned. We tested our algorithm
on prostate surfaces extracted from post-operative MR and TRUS images
for 14 patients, using a model with elasticity parameters in the
range reported in the literature for the prostate. We used three
evaluation metrics for validating our technique: the Dice Similarity
Coefficient (DSC) (ideally equal to 1.0), which is a measure of volume
alignment, the volume change in source surface during registration,
which is a measure of volume preservation, and the distance between
the urethras to assess the anatomical correctness of the method.
We obtained a DSC of 0.96�0.02 and a mean distance between the urethras
of 1.5�1.4 mm. The change in the volume of the source surface was
1.5�1.4%. Our results show that this method is a promising tool for
physicallybased deformable surface registration.
BibTeX:
@inproceedings{Taquee_deformable_12,
  author = {Farheen Taquee and Orcun Goksel and S. Sara Mahdavi and Mira Keyes and W. James Morris and Ingrid Spadinger and Septimiu Salcudean},
  title = {Deformable Prostate Registration from MR and TRUS Images Using Surface Error Driven FEM models},
  booktitle = {SPIE Medical Imaging},
  year = {2012},
  doi = {10.1117/12.911688}
}
[*]Orcun Goksel, Kirill Sapchuk, and Septimiu E. Salcudean: "Haptic simulation of needle and probe interaction with tissue for prostate brachytherapy training", In IEEE World Haptics Conference (WHC), pp. 7-12, Jun 2011.  podium
BibTeX:
@inproceedings{Goksel_haptic_11n,
  author = {Orcun Goksel and Kirill Sapchuk and Septimiu E. Salcudean},
  title = {Haptic simulation of needle and probe interaction with tissue for prostate brachytherapy training},
  booktitle = {IEEE World Haptics Conference (WHC)},
  year = {2011},
  pages = {7-12},
  doi = {10.1109/WHC.2011.5945453}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "FEM Simulation of Harmonic Tissue Excitation for Prostate Elastography", In Int Tissue Elasticity Conf (ITEC), pp. 93, Salt Lake City, UT, USA, Oct 2010.  podium
BibTeX:
@inproceedings{Goksel_fem_10,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {FEM Simulation of Harmonic Tissue Excitation for Prostate Elastography},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2010},
  pages = {93}
}
[*] Hani Eskandari, Orcun Goksel, Septimiu E. Salcudean, and Robert Rohling: "Bandpass Sampling of High Frequency Tissue Motion", In Int Tissue Elasticity Conf (ITEC), pp. 71, Salt Lake City, UT, USA, Oct 2010.  podium
BibTeX:
@inproceedings{Eskandari_bandpass_10,
  author = {Hani Eskandari and Orcun Goksel and Septimiu E. Salcudean and Robert Rohling},
  title = {Bandpass Sampling of High Frequency Tissue Motion},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2010},
  pages = {71}
}
[*]Orcun Goksel, Hani Eskandari, and Septimiu E. Salcudean: "Mesh Adaptation for Improving Inverse-Problem Reconstruction", In Int Tissue Elasticity Conf (ITEC), pp. 96, Salt Lake City, UT, USA, Oct 2010.  podium
BibTeX:
@inproceedings{Goksel_mesh_10,
  author = {Orcun Goksel and Hani Eskandari and Septimiu E. Salcudean},
  title = {Mesh Adaptation for Improving Inverse-Problem Reconstruction},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2010},
  pages = {96}
}
[*] Amir Haddadi, Orcun Goksel, Septimiu E. Salcudean, and Keyvan Hashtrudi-Zaad: "On the Controllability of Dynamic Model-Based Needle Insertion in Soft Tissue", In IEEE Eng Medicine and Biology Conf (EMBC), pp. 2287-2291, Buenos Aires, Argentina, Sep 2010.  
Abstract: Soft tissue needle guidance and steering for clinical applications
has been an active topic of research in the past decade. Although
dynamic feedback control of needle insertion systems is expected
to provide more accurate target tracking, it has received little
attention due to the fact that most available models for needle-tissue
interaction do not incorporate the dynamics of motions. In this paper,
we study the controllability of rigid or flexible needles inside
soft tissues using mechanical-based dynamic models. The results have
significant implications on the design of suitable feedback controllers
for different types of needle insertion systems.
BibTeX:
@inproceedings{Haddadi_controllability_10,
  author = {Amir Haddadi and Orcun Goksel and Septimiu E. Salcudean and Keyvan Hashtrudi-Zaad},
  title = {On the Controllability of Dynamic Model-Based Needle Insertion in Soft Tissue},
  booktitle = {IEEE Eng Medicine and Biology Conf (EMBC)},
  year = {2010},
  pages = {2287-2291},
  doi = {10.1109/IEMBS.2010.5627676}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "Haptic Simulator for Prostate Brachytherapy with Simulated Ultrasound", In Int Symp Biomedical Simulation (ISBMS), pp. 150-9, Phoenix, AZ, USA, Jan 2010.  podium
BibTeX:
@inproceedings{Goksel_haptic_10,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {Haptic Simulator for Prostate Brachytherapy with Simulated Ultrasound},
  booktitle = {Int Symp Biomedical Simulation (ISBMS)},
  year = {2010},
  pages = {150-9},
  doi = {10.1007/978-3-642-11615-5_16}
}
[*] Reza Zahiri-Azar, Orcun Goksel, T.S. Yao, Ehsan Dehghan, Joseph Yan, and Septimiu E. Salcudean: "Multi-Dimensional Sub-Sample Motion Estimation: Initial Results", In IEEE Int Ultrasonics Symposium (IUS), Rome, Italy, Sep 2009.  podium
BibTeX:
@inproceedings{Zahiri-Azar_multi-dimensional_09,
  author = {Reza Zahiri-Azar and Orcun Goksel and T.S. Yao and Ehsan Dehghan and Joseph Yan and Septimiu E. Salcudean},
  title = {Multi-Dimensional Sub-Sample Motion Estimation: Initial Results},
  booktitle = {IEEE Int Ultrasonics Symposium (IUS)},
  year = {2009},
  doi = {10.1109/ULTSYM.2009.0595}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "Automatic Prostate Segmentation from Transrectal Ultrasound Elastography Images Using Geometric Active Contours", In Int Tissue Elasticity Conf (ITEC), pp. 34, Vlissingen, Netherlands, Sep 2009.  podium

* One of 8 Student Best Paper Finalists

BibTeX:
@inproceedings{Goksel_automatic_09,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {Automatic Prostate Segmentation from Transrectal Ultrasound Elastography Images Using Geometric Active Contours},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2009},
  pages = {34}
}
[*] Reza Zahiri-Azar, Orcun Goksel, and Septimiu E. Salcudean: "Application of 2D Polynomial Fitting to Beam Steering for Motion Estimation with Sub-Sample Accuracy", In Int Tissue Elasticity Conf (ITEC), pp. 124, Vlissingen, Netherlands, Sep 2009.  podium
BibTeX:
@inproceedings{Zahiri-Azar_application_09,
  author = {Reza Zahiri-Azar and Orcun Goksel and Septimiu E. Salcudean},
  title = {Application of 2D Polynomial Fitting to Beam Steering for Motion Estimation with Sub-Sample Accuracy},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2009},
  pages = {124}
}
[*] Reza Zahiri-Azar, Orcun Goksel, and Septimiu E. Salcudean: "Methods for the Estimation of the Sub-Sample Motion Using Digitized Ultrasound Echo Signals in Three Dimensions", In Int Tissue Elasticity Conf (ITEC), pp. 88, Vlissingen, Netherlands, Sep 2009.  podium
BibTeX:
@inproceedings{Zahiri-Azar_methods_09,
  author = {Reza Zahiri-Azar and Orcun Goksel and Septimiu E. Salcudean},
  title = {Methods for the Estimation of the Sub-Sample Motion Using Digitized Ultrasound Echo Signals in Three Dimensions},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2009},
  pages = {88}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "High-Quality Model Generation for Finite Element Simulation of Tissue Deformation", In MICCAI, pp. 248-256, London, UK, Sep 2009.  poster

* Received one of 15 Hamlyn Robotics Travel Grants

BibTeX:
@inproceedings{Goksel_high-quality_09,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {High-Quality Model Generation for Finite Element Simulation of Tissue Deformation},
  booktitle = {MICCAI},
  year = {2009},
  pages = {248-256},
  doi = {10.1007/978-3-642-04271-3_31}
}
[*] Sara Mahdavi, Orcun Goksel, and Septimiu E. Salcudean: "3D Prostate Segmentation in Ultrasound Images Based on Tapered and Deformed Ellipsoids", In MICCAI, pp. 960-7, London, UK, Sep 2009.  poster
Abstract: Prostate segmentation from trans-rectal transverse B-mode ultrasound
images is required for radiation treatment of prostate cancer. Manual
segmentation is a time-consuming task, the results of which are dependent
on image quality and physicians� experience. This paper introduces
a semi-automatic 3D method based on super-ellipsoidal shapes. It
produces a 3D segmentation in less than 15 seconds using a warped,
tapered ellipsoid fit to the prostate. A study of patient images
shows good performance and repeatability. This method is currently
in clinical use at the Vancouver Cancer Center where it has become
the standard segmentation procedure for low dose-rate brachytherapy
treatment.
BibTeX:
@inproceedings{Mahdavi_3d_09,
  author = {Sara Mahdavi and Orcun Goksel and Septimiu E. Salcudean},
  title = {3D Prostate Segmentation in Ultrasound Images Based on Tapered and Deformed Ellipsoids},
  booktitle = {MICCAI},
  year = {2009},
  pages = {960-7},
  doi = {10.1007/978-3-642-04271-3_116}
}
[*] Reza Zahiri-Azar, Orcun Goksel, T.S. Yao, Ehsan Dehghan, Joseph Yan, and Septimiu E. Salcudean: "Methods for the Estimation of Sub-sample Motion of Digitized Ultrasound Echo Signals in 2D", In IEEE Eng Medicine and Biology Conf (EMBC), pp. 5581-4, Vancouver, BC, Canada, Aug 2008.  podium
BibTeX:
@inproceedings{Zahiri-Azar_methods_08,
  author = {Reza Zahiri-Azar and Orcun Goksel and T.S. Yao and Ehsan Dehghan and Joseph Yan and Septimiu E. Salcudean},
  title = {Methods for the Estimation of Sub-sample Motion of Digitized Ultrasound Echo Signals in 2D},
  booktitle = {IEEE Eng Medicine and Biology Conf (EMBC)},
  year = {2008},
  pages = {5581-4},
  doi = {10.1109/IEMBS.2008.4650479}
}
[*] Reza Zahiri-Azar, Orcun Goksel, and Septimiu E. Salcudean: "Real-Time Tissue Deformation Visualization", In Int Tissue Elasticity Conf (ITEC), pp. 117, Santa Fe, New Mexico, USA, Nov 2007.  podium
BibTeX:
@inproceedings{Zahiri-Azar_real-time_07,
  author = {Reza Zahiri-Azar and Orcun Goksel and Septimiu E. Salcudean},
  title = {Real-Time Tissue Deformation Visualization},
  booktitle = {Int Tissue Elasticity Conf (ITEC)},
  year = {2007},
  pages = {117}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "Real-time Synthesis of Image Slices in Deformed Tissue from Nominal Volume Images", In MICCAI, pp. 401-8, Brisbane, QLD, Australia, Oct 2007.  poster
BibTeX:
@inproceedings{Goksel_real-time_07,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {Real-time Synthesis of Image Slices in Deformed Tissue from Nominal Volume Images},
  booktitle = {MICCAI},
  year = {2007},
  pages = {401-8},
  doi = {10.1007/978-3-540-75757-3_49}
}
[*]Orcun Goksel and Septimiu E. Salcudean: "Fast B-Mode Ultrasound Image Simulation of Deformed Tissue", In IEEE Eng Medicine and Biology Conf (EMBC), pp. 87-90, Lyon, France, Aug 2007.  podium
BibTeX:
@inproceedings{Goksel_fast_07,
  author = {Orcun Goksel and Septimiu E. Salcudean},
  title = {Fast B-Mode Ultrasound Image Simulation of Deformed Tissue},
  booktitle = {IEEE Eng Medicine and Biology Conf (EMBC)},
  year = {2007},
  pages = {87-90},
  doi = {10.1109/IEMBS.2007.4352229}
}
[*]Orcun Goksel, Reza Zahiri-Azar, and Septimiu E. Salcudean: "Simulation of Ultrasound Radio-Frequency Signals in Deformed Tissue for Validation of 2D Motion Estimation with Sub-Sample Accuracy", In IEEE Eng Medicine and Biology Conf (EMBC), pp. 2159-62, Lyon, France, Aug 2007.  poster
BibTeX:
@inproceedings{Goksel_simulation_07,
  author = {Orcun Goksel and Reza Zahiri-Azar and Septimiu E. Salcudean},
  title = {Simulation of Ultrasound Radio-Frequency Signals in Deformed Tissue for Validation of 2D Motion Estimation with Sub-Sample Accuracy},
  booktitle = {IEEE Eng Medicine and Biology Conf (EMBC)},
  year = {2007},
  pages = {2159-62},
  doi = {10.1109/IEMBS.2007.4352750}
}
[*] Ehsan Dehghan, Orcun Goksel, and Septimiu E. Salcudean: "A Comparison of Needle Bending Models", In MICCAI, pp. 305-312, Copenhagen, Denmark, Oct 2006.  poster
Abstract: Modeling the deflection of flexible needles is an essential part of
needle insertion simulation and path planning. In this paper, three
models are compared in terms of accuracy in simulating the bending
of a prostate brachytherapy needle. The first two utilize the finite
element method, one using geometric non-linearity and triangular
plane elements, the other using non-linear beam elements. The third
model uses angular springs to model cantilever deflection. The simulations
are compared with the experimental bent needle configurations. The
models are assessed in terms of geometric conformity using independently
identified and pre-identified model parameters. The results show
that the angular spring model, which is also the simplest, simulates
the needle more accurately than the others.
BibTeX:
@inproceedings{Dehghan_comparison_06,
  author = {Ehsan Dehghan and Orcun Goksel and Septimiu E. Salcudean},
  title = {A Comparison of Needle Bending Models},
  booktitle = {MICCAI},
  year = {2006},
  pages = {305-312},
  doi = {10.1007/11866565_38}
}
[*]Orcun Goksel, Septimiu E. Salcudean, and Robert Rohling: "Image Synthesis of Deformed Tissue with Application to Ultrasound for Prostate Brachytherapy", In Canadian Medical and Biological Engineering Conf (CMBEC), Vancouver, BC, Canada, Jun 2006.  podium, national

* First place in the Student Paper Competition

BibTeX:
@inproceedings{Goksel_image_06,
  author = {Orcun Goksel and Septimiu E. Salcudean and Robert Rohling},
  title = {Image Synthesis of Deformed Tissue with Application to Ultrasound for Prostate Brachytherapy},
  booktitle = {Canadian Medical and Biological Engineering Conf (CMBEC)},
  year = {2006}
}
[*]Orcun Goksel, Simon P. DiMaio, Septimiu E. Salcudean, Robert Rohling, and James Morris: "3D Needle-Tissue Interaction Simulation for Prostate Brachytherapy", In MICCAI, pp. 827-834, Palm Springs, CA, USA, Oct 2005.  podium
Abstract: This paper presents a needle-tissue interaction model that is a 3D
extension of a prior work based on the finite element method. The
model is also adapted to accommodate arbitrary meshes so that the
anatomy can effectively be meshed using third-party algorithms. Using
this model a prostate brachytherapy simulator is designed to help
medical residents acquire needle steering skills. This simulation
uses a prostate mesh generated from clinical data segmented as contours
on parallel slices. Node repositioning and addition, which are methods
for achieving needle-tissue coupling, are discussed. In order to
achieve real-time haptic rates, computational approaches to these
methods are compared. Specifically, the benefit of using the Woodbury
formula (matrix inversion lemma) is studied. Our simulation of needle
insertion into a prostate is shown to run faster than 1 kHz.
BibTeX:
@inproceedings{Goksel_3d_05,
  author = {Orcun Goksel and Simon P. DiMaio and Septimiu E. Salcudean and Robert Rohling and James Morris},
  title = {3D Needle-Tissue Interaction Simulation for Prostate Brachytherapy},
  booktitle = {MICCAI},
  year = {2005},
  pages = {827-834},
  doi = {10.1007/11566465_102}
}

Monographs:

[*]Orcun Goksel: "Meshing and Rendering of Patient-Specific Deformation Models With Application to Needle Insertion Simulation", University of British ColumbiaUniversity of British Columbia, 2009.  

* Western Association of Graduate Schools (WAGS) Innovation in Technology Award for the top-ranked dissertation of the year for western North America

BibTeX:
@phdthesis{Goksel_meshing_09,
  author = {Orcun Goksel},
  title = {Meshing and Rendering of Patient-Specific Deformation Models With Application to Needle Insertion Simulation},
  school = {University of British Columbia},
  year = {2009},
  url = {http://hdl.handle.net/2429/17418}
}
[*]Orcun Goksel: "Ultrasound Image and 3D Finite Element based Tissue Deformation Simulator for Prostate Brachytherapy", University of British ColumbiaUniversity of British Columbia, 2005.  
BibTeX:
@mastersthesis{Goksel_ultrasound_05,
  author = {Orcun Goksel},
  title = {Ultrasound Image and 3D Finite Element based Tissue Deformation Simulator for Prostate Brachytherapy},
  school = {University of British Columbia},
  year = {2005},
  url = {http://hdl.handle.net/2429/16194}
}

Other Contributions:

[*]Orcun Goksel, Oscar Alfonso Jiménez del Toro, Antonio Foncubierta, and Henning Müller: "(eds.) Proceedings of the VISCERAL Challenge at ISBI", (1390), Apr 2015.  
BibTeX:
@book{Goksel_visceral_15,
  author = {Orcun Goksel and Jim\'enez del Toro, Oscar Alfonso and Antonio Foncubierta and Henning M\"uller},
  title = {(eds.) Proceedings of the VISCERAL Challenge at ISBI},
  publisher = {CEUR-WS.org},
  year = {2015},
  number = {1390},
  url = {http://ceur-ws.org/Vol-1390/}
}
[*]Orcun Goksel: "(ed.) Proceedings of the VISCERAL Challenge at ISBI", (1194), May 2014.  
BibTeX:
@book{Goksel_visceral_14,
  author = {Orcun Goksel},
  title = {(ed.) Proceedings of the VISCERAL Challenge at ISBI},
  publisher = {CEUR-WS.org},
  year = {2014},
  number = {1194},
  url = {http://ceur-ws.org/Vol-1194}
}
[*] Marcel Lüthi, Remi Blanc, Thomas Albrecht, Tobias Gass, Orcun Goksel, Philippe Büchler, Michael Kistler, Habib Bousleiman, Mauricio Reyes, Philippe Cattin, and Thomas Vetter: "Statismo - A framework for PCA based statistical models", Insight JournalInsight Journal, Jul 2012.  
Abstract: This paper describes the Statismo framework, which is a framework
for PCA based statistical models.Statistical models are used to describe
the variability of an object within a population, learned from a
set of training samples. Originally developed to model shapes, statistical
models are now increasingly used to model the variation in different
kind of data, such as for example images, volumetric meshes or deformation
fields. Statismo has been developed with the following main goals
in mind: 1) To provide generic tools for learning different kinds
of PCA based statistical models, such as shape, appearance or deformations
models. 2) To make the exchange of such models easier among different
research groups and to improve the reproducibility of the models.
3) To allow for easy integration of new methods for model building
into the framework. To achieve the first goal, we have abstracted
all the aspects that are specific to a given model and data representation,
into a user defined class. This does not only make it possible to
use Statismo to create different kinds of PCA models, but also allows
Statismo to be used with any toolkit and data format. To facilitate
data exchange, Statismo defines a storage format based on HDF5, which
includes all the information necessary to use the model, as well
as meta-data about the model creation, which helps to make model
building reproducible. The last goal is achieved by providing a clear
separation between data management, model building and model representation.
In addition to the standard method for building PCA models, Statismo
already includes two recently proposed algorithms for building conditional
models, as well as convenience tools for facilitating cross-validation
studies. Although Statismo has been designed to be independent of
a particular toolkit, special efforts have been made to make it directly
useful for VTK and ITK. Besides supporting model building for most
data representations used by VTK and ITK, it also provides an ITK
transform class, which allows for the integration of Statismo with
the ITK registration framework. This leverages the efforts from the
ITK project to readily access powerful methods for model fitting.
BibTeX:
@techreport{Luethi_statismo_12,
  author = {Marcel L\"uthi and Remi Blanc and Thomas Albrecht and Tobias Gass and Orcun Goksel and Philippe B\"uchler and Michael Kistler and Habib Bousleiman and Mauricio Reyes and Philippe Cattin and Thomas Vetter},
  title = {Statismo - A framework for PCA based statistical models},
  school = {Insight Journal},
  year = {2012},
  url = {http://hdl.handle.net/10380/3371}
}
[*]Orcun Goksel, Septimiu E. Salcudean, and Robert Rohling: "3D Needle-Tissue Interaction Simulation for Prostate Brachytherapy", In Annual Canadian Conference on Intelligent Systems (IS 2005), 2005.  national

* Received the Best Poster Award

BibTeX:
@inproceedings{Goksel_3Dis_05,
  author = {Orcun Goksel and Septimiu E. Salcudean and Robert Rohling},
  title = {3D Needle-Tissue Interaction Simulation for Prostate Brachytherapy},
  booktitle = {Annual Canadian Conference on Intelligent Systems (IS 2005)},
  year = {2005}
}
[*]Orcun Goksel, Septimiu E. Salcudean, and Robert Rohling: "Towards a Prostate Brachytherapy Haptic Simulator", In BC Advanced Systems Institute (ASI) Exchange, 2004.  poster, provincial

* Received the ASI Innovation Award and Communication Awards

BibTeX:
@inproceedings{Goksel_towards_04,
  author = {Orcun Goksel and Septimiu E. Salcudean and Robert Rohling},
  title = {Towards a Prostate Brachytherapy Haptic Simulator},
  booktitle = {BC Advanced Systems Institute (ASI) Exchange},
  year = {2004}
}

Some earlier project highlights are given below. For latest research findings, please see my publication list further below.

Hand-held Ultrasound Imaging of Speed-of-Sound for Breast Examination

ETH Spark Award 2016 for the most promising invention from ETH in year 2015

Excerpt from ETH News:

"The novel ultrasonic measurement can be used to diagnose various tissue changes, in particular to detect tumours. Until now, many tumours could not be seen in an ultrasound. Instead of the standard practice of measuring the backscattering of sound, the new method measures the time taken by an ultrasound wave: the stiffer the tissue, which is the case with tumours, the faster the sound wave passes through the tissue. To do this, the researchers developed their own probe head together with an image processing programme."

Automatic Measurement of Venous Pressure in Ultrasound

Venous pressure is an indication for several clinical situations and therefore its accurate measurement is an invaluable diagnostic tool. It is traditionally measured via catheters inserted into a subclavian or internal jugular vein. The former is known to yield unreliable results, and the latter is impractical, uncomfortable for the patient, and has potential complications.

Our goal is to develop an automatic system for the noninvasive measurement of peripheral venous pressure using ultrasound. This involves an operator pressing gently on the forearm of a patient, while a computer processes ultrasound images along with pressure readings from a sensor placed between the ultrasound transducer and the skin.

Prostate Brachytherapy Simulator (BrachySim)

This is a simulation environment complete with:
  • deformable tissue simulation coupled with long, flexible needle insertion,
  • haptic controlled needle insertion and transrectal ultrasound (TRUS) probe motion,
  • ultrasound simulation from TRUS probe also showing anatomical deformations,
  • real-time fluoroscopy and dosimetry views, with an option to follow clinical therapy plans.
This simulator was presented in:

[Goksel et al., "Prostate Brachytherapy Training with Simulated Ultrasound and Fluoroscopy Images", IEEE TBME, 2013]
[Goksel et al., "Haptic Simulator for Prostate Brachytherapy with Simulated Needle and Probe Interaction", IEEE TOH, 2011]

If the clip on left does not play in your browser, you can [DOWNLOAD CLIP].

The technology is available for licensing.

Ultrasound B-Mode Simulation

Ultrasound is commonly used in clinical settings for diagnosis and interventions owing to its being a real-time, non-invasive, and cost-effective imaging technique. Its training involves several aspects, such as, hand-eye coordination, interpretation of 3D anatomy, and diagnosis of rarely-encountered cases. This group of work targets the training of ultrasound imaging through interpolative B-mode image simulation in a deformable anatomical model, meanwhile the trainee is interacting with it. This work was presented in:
[Goksel & Salcudean, "B-Mode Ultrasound Image Simulation in Deformable 3-D Medium", IEEE TMI, 2009]

If the clip does not play in your browser, you can [DOWNLOAD CLIP].

Elastography

The Finite Element Method (FEM) Inverse Problem allows for formulating the elasticity reconstruction of a deformable medium, such as tissue, as a least-squares problem given observed displacements. Such displacements can be measured in real-time using ultrasound imaging.

On the left, a breast tumor is seen in traditional ultrasound imaging (marked with a plus). Underneath, inverse problem elasticity reconstructions are shown with 256 and 576 adaptively-placed triangular elements. This work was presented in:

[Goksel et al., "Mesh Adaptation for Improving Elasticity Reconstruction using the FEM Inverse Problem", IEEE TMI, 2013]

Variational Image Meshing (VIMesh)

This is the implementation of the meshing technique presented in:
[Goksel & Salcudean, "Image-Based Variational Meshing", IEEE TMI, 2011]

It uses an optimization scheme to generate meshes (specifically for FEM simulation) by discretizing given 3D voxel data such as medical images.

See a clip of mesh fitting to ventricles in an MR image using an earlier version of the code. If the clip does not play in your browser, you can [DOWNLOAD CLIP].

For details, documentation, and downloading a Windows executable with supporting Matlab code, please visit:

Modeling Flexible Needles

In this work, it was shown that the bending of flexible needles can be modeled acurately using angular springs:

[Goksel et al., "Modeling and Simulation of Flexible Needles" Med Eng Phys, 2009]

This model was later used in several works for simulating flexible needle insertion to deformable tissue.

Such a flexible needle model under changing forces can be seen in the video on the left.