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2020 – today
- 2025
[j15]Hadar Hezi
, Matan Gelber, Alexander Balabanov, Yosef E. Maruvka, Moti Freiman:
CIMIL-CRC: A clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H&E stained images. Comput. Methods Programs Biomed. 259: 108513 (2025)- 2024
- [j14]Samah Khawaled, Moti Freiman:
NPB-REC: A non-parametric Bayesian deep-learning approach for undersampled MRI reconstruction with uncertainty estimation. Artif. Intell. Medicine 149: 102798 (2024) - [j13]Nitzan Avidan, Moti Freiman:
MA-RECON: Mask-aware deep-neural-network for robust fast MRI k-space interpolation. Comput. Methods Programs Biomed. 244: 107942 (2024) - [c39]Liam Hazan, Naama Gavrielov, Roi Reichart, Talar Hagopian, Mary-Louise C. Greer, Ruth Cytter-Kuint, Gili Focht, Dan Turner, Moti Freiman:
Leveraging Prompt-Learning for Structured Information Extraction from Crohn's Disease Radiology Reports in a Low-Resource Language. ClinicalNLP@NAACL 2024: 301-309 - [c38]Shir Nitzan, Maya Gilad, Moti Freiman:
Automated Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy From DWI Data. ISBI 2024: 1-5 - [e2]Klaus Drechsler, Cristina Oyarzun Laura, Moti Freiman, Yufei Chen, Stefan Wesarg, Marius Erdt:
Clinical Image-Based Procedures - 13th International Workshop, CLIP 2024, Held in Conjunction with MICCAI 2024, Marrakesh, Morocco, October 6, 2024, Proceedings. Lecture Notes in Computer Science 15196, Springer 2024, ISBN 978-3-031-73082-5 [contents] - [i28]Noga Kertes, Yael Zaffrani-Reznikov, Onur Afacan, Sila Kurugol, Simon K. Warfield, Moti Freiman:
IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data. CoRR abs/2401.07126 (2024) - [i27]Hadar Hezi, Matan Gelber, Alexander Balabanov, Yosef E. Maruvka, Moti Freiman:
CIMIL-CRC: a clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H\&E stained images. CoRR abs/2401.16131 (2024) - [i26]Samah Khawaled, Simon K. Warfield, Moti Freiman:
A self-attention model for robust rigid slice-to-volume registration of functional MRI. CoRR abs/2404.04546 (2024) - [i25]Samah Khawaled, Moti Freiman:
NPB-REC: A Non-parametric Bayesian Deep-learning Approach for Undersampled MRI Reconstruction with Uncertainty Estimation. CoRR abs/2404.04550 (2024) - [i24]Shir Nitzan, Maya Gilad, Moti Freiman:
Automated Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy from DWI Data. CoRR abs/2404.05061 (2024) - [i23]Liam Hazan, Gili Focht, Naama Gavrielov, Roi Reichart, Talar Hagopian, Mary-Louise C. Greer, Ruth Cytter-Kuint, Dan Turner, Moti Freiman:
Leveraging Prompt-Learning for Structured Information Extraction from Crohn's Disease Radiology Reports in a Low-Resource Language. CoRR abs/2405.01682 (2024) - [i22]Eyal Hanania, Ilya Volovik, Daphna Link-Sourani, Israel Cohen, Moti Freiman:
MBSS-T1: Model-Based Self-Supervised Motion Correction for Robust Cardiac T1 Mapping. CoRR abs/2408.11992 (2024) - [i21]Rotem Benisty, Yevgenia Shteynman, Moshe Porat, Anat Illivitzki, Moti Freiman:
SIMPLE: Simultaneous Multi-Plane Self-Supervised Learning for Isotropic MRI Restoration from Anisotropic Data. CoRR abs/2408.13065 (2024) - [i20]Sharon Peled, Yosef E. Maruvka, Moti Freiman:
Multi-Cohort Framework with Cohort-Aware Attention and Adversarial Mutual-Information Minimization for Whole Slide Image Classification. CoRR abs/2409.11119 (2024) - 2023
- [j12]Hadas Ben-Atya, Moti Freiman:
P2T2: A physically-primed deep-neural-network approach for robust T2 distribution estimation from quantitative T2-weighted MRI. Comput. Medical Imaging Graph. 107: 102240 (2023) - [c37]Nitzan Avidan, Moti Freiman:
Deep Learning-Based Fast MRI Reconstruction: Improving Generalization for Clinical Translation. CLIP/FAIMI/EPIMI@MICCAI 2023: 59-69 - [c36]Guy Shani, Moti Freiman, Yosef E. Maruvka:
An Efficient and Accurate Neural Network Tool for Finding Correlation Between Gene Expression and Histological Images. CLIP/FAIMI/EPIMI@MICCAI 2023: 81-88 - [c35]Maya Fichmann Levital, Samah Khawaled, Yufei Chen, John A. Kennedy, Moti Freiman:
Uncertainty Assessment in Whole-Body Low Dose Pet Reconstruction Using Non-Parametric Bayesian Deep Learning Approach. ISBI 2023: 1-5 - [c34]Eyal Hanania, Ilya Volovik, Lilach Barkat, Israel Cohen, Moti Freiman:
PCMC-T1: Free-Breathing Myocardial T1 Mapping with Physically-Constrained Motion Correction. MICCAI (7) 2023: 226-235 - [e1]Stefan Wesarg, Esther Puyol-Antón, John S. H. Baxter, Marius Erdt, Klaus Drechsler, Cristina Oyarzun Laura, Moti Freiman, Yufei Chen, Islem Rekik, Roy Eagleson, Aasa Feragen, Andrew P. King, Veronika Cheplygina, Melanie Ganz-Benjaminsen, Enzo Ferrante, Ben Glocker, Daniel Moyer, Eike Petersen:
Clinical Image-Based Procedures, Fairness of AI in Medical Imaging, and Ethical and Philosophical Issues in Medical Imaging - 12th International Workshop, CLIP 2023 1st International Workshop, FAIMI 2023 and 2nd International Workshop, EPIMI 2023 Vancouver, BC, Canada, October 8 and October 12, 2023 Proceedings. Lecture Notes in Computer Science 14242, Springer 2023, ISBN 978-3-031-45248-2 [contents] - [i19]Hadar Hezi, Daniel Shats, Daniel Gurevich, Yosef E. Maruvka, Moti Freiman:
Biologically-primed deep neural network improves colorectal Cancer Molecular subtypes prediction from H&E stained images. CoRR abs/2303.14703 (2023) - [i18]Eyal Hanania, Ilya Volovik, Lilach Barkat, Israel Cohen, Moti Freiman:
PCMC-T1: Free-breathing myocardial T1 mapping with Physically-Constrained Motion Correction. CoRR abs/2308.11281 (2023) - [i17]Jonathan Fhima, Jan Van Eijgen, Hana Kulenovic, Valérie Debeuf, Marie Vangilbergen, Marie-Isaline Billen, Heloïse Brackenier, Moti Freiman, Ingeborg Stalmans, Joachim A. Behar:
LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images. CoRR abs/2309.05780 (2023) - 2022
- [j11]Samah Khawaled, Moti Freiman:
NPBDREG: Uncertainty assessment in diffeomorphic brain MRI registration using a non-parametric Bayesian deep-learning based approach. Comput. Medical Imaging Graph. 99: 102087 (2022) - [j10]Itai Guez, Gili Focht, Mary-Louise C. Greer, Ruth Cytter-Kuint, Li-Tal Pratt, Denise A. Castro, Dan Turner, Anne M. Griffiths, Moti Freiman:
Development of a multimodal machine-learning fusion model to non-invasively assess ileal Crohn's disease endoscopic activity. Comput. Methods Programs Biomed. 227: 107207 (2022) - [c33]Jonathan Fhima, Jan Van Eijgen, Moti Freiman, Ingeborg Stalmans, Joachim A. Behar:
Lirot.ai: A Novel Platform for Crowd-Sourcing Retinal Image Segmentations. CinC 2022: 1-4 - [c32]Jonathan Fhima, Jan Van Eijgen, Ingeborg Stalmans, Yevgeniy Men, Moti Freiman, Joachim A. Behar:
PVBM: A Python Vasculature Biomarker Toolbox Based on Retinal Blood Vessel Segmentation. ECCV Workshops (3) 2022: 296-312 - [c31]Daniel Shats, Hadar Hezi, Guy Shani, Yosef E. Maruvka, Moti Freiman:
Patient-Level Microsatellite Stability Assessment from Whole Slide Images by Combining Momentum Contrast Learning and Group Patch Embeddings. ECCV Workshops (3) 2022: 454-465 - [c30]Yael Zaffrani-Reznikov, Onur Afacan, Sila Kurugol, Simon K. Warfield, Moti Freiman:
qDWI-Morph: Motion-Compensated Quantitative Diffusion-Weighted MRI Analysis for Fetal Lung Maturity Assessment. ECCV Workshops (3) 2022: 482-494 - [c29]Yaniv Ziselman, Faten Hajali Shinnawi, Mary-Louise C. Greer, Gili Focht, Dan Turner, Moti Freiman:
Gadolinium-Free Crohn's Disease Assessment from Magnetic Resonance Enterography Data. ISBI 2022: 1-5 - [c28]Samah Khawaled, Moti Freiman:
NPB-REC: Non-parametric Assessment of Uncertainty in Deep-Learning-Based MRI Reconstruction from Undersampled Data. MLMIR@MICCAI 2022: 14-23 - [c27]Maya Gilad, Moti Freiman:
PD-DWI: Predicting Response to Neoadjuvant Chemotherapy in Invasive Breast Cancer with Physiologically-Decomposed Diffusion-Weighted MRI Machine-Learning Model. MICCAI (3) 2022: 36-45 - [c26]Noam Korngut, Elad Rotman, Onur Afacan, Sila Kurugol, Yael Zaffrani-Reznikov, Shira Nemirovsky-Rotman, Simon K. Warfield, Moti Freiman:
SUPER-IVIM-DC: Intra-voxel Incoherent Motion Based Fetal Lung Maturity Assessment from Limited DWI Data Using Supervised Learning Coupled with Data-Consistency. MICCAI (2) 2022: 743-752 - [i16]Lilach Barkat, Moti Freiman, Haim Azhari:
Image translation of Ultrasound to Pseudo Anatomical Display Using Artificial Intelligence. CoRR abs/2202.08053 (2022) - [i15]Noam Korngut, Elad Rotman, Onur Afacan, Sila Kurugol, Yael Zaffrani-Reznikov, Shira Nemirovsky-Rotman, Simon K. Warfield, Moti Freiman:
SUPER-IVIM-DC: Intra-voxel incoherent motion based Fetal lung maturity assessment from limited DWI data using supervised learning coupled with data-consistency. CoRR abs/2206.03820 (2022) - [i14]Maya Gilad, Moti Freiman:
PD-DWI: Predicting response to neoadjuvant chemotherapy in invasive breast cancer with Physiologically-Decomposed Diffusion-Weighted MRI machine-learning model. CoRR abs/2206.05695 (2022) - [i13]Jonathan Fhima, Jan Van Eijgen, Ingeborg Stalmans, Yevgeniy Men, Moti Freiman, Joachim A. Behar:
PVBM: A Python Vasculature Biomarker Toolbox Based On Retinal Blood Vessel Segmentation. CoRR abs/2208.00392 (2022) - [i12]Samah Khawaled, Moti Freiman:
NPB-REC: Non-parametric Assessment of Uncertainty in Deep-learning-based MRI Reconstruction from Undersampled Data. CoRR abs/2208.03966 (2022) - [i11]Yael Zaffrani-Reznikov, Onur Afacan, Sila Kurugol, Simon K. Warfield, Moti Freiman:
qDWI-Morph: Motion-compensated quantitative Diffusion-Weighted MRI analysis for fetal lung maturity assessment. CoRR abs/2208.09836 (2022) - [i10]Jonathan Fhima, Jan Van Eijgen, Moti Freiman, Ingeborg Stalmans, Joachim A. Behar:
Lirot.ai: A Novel Platform for Crowd-Sourcing Retinal Image Segmentations. CoRR abs/2208.10100 (2022) - [i9]Daniel Shats, Hadar Hezi, Guy Shani, Yosef E. Maruvka, Moti Freiman:
Patient-level Microsatellite Stability Assessment from Whole Slide Images By Combining Momentum Contrast Learning and Group Patch Embeddings. CoRR abs/2208.10429 (2022) - [i8]Nitzan Avidan, Moti Freiman:
Physically-primed deep-neural-networks for generalized undersampled MRI reconstruction. CoRR abs/2209.00462 (2022) - [i7]Hadas Ben-Atya, Moti Freiman:
P2T2: a Physically-primed deep-neural-network approach for robust T2 distribution estimation from quantitative T2-weighted MRI. CoRR abs/2212.04928 (2022) - 2021
- [i6]Samah Khawaled, Moti Freiman:
NPBDREG: A Non-parametric Bayesian Deep-Learning Based Approach for Diffeomorphic Brain MRI Registration. CoRR abs/2108.06771 (2021) - [i5]Hadas Ben-Atya, Ori Rajchert, Liran Goshen, Moti Freiman:
Non Parametric Data Augmentations Improve Deep-Learning based Brain Tumor Segmentation. CoRR abs/2111.12991 (2021) - 2020
- [i4]Samah Khawaled, Moti Freiman:
Unsupervised Deep-Learning Based Deformable Image Registration: A Bayesian Framework. CoRR abs/2008.03949 (2020)
2010 – 2019
- 2019
- [i3]Moti Freiman, Ravindra Manjeshwar, Liran Goshen:
Unsupervised Abnormality Detection through Mixed Structure Regularization (MSR) in Deep Sparse Autoencoders. CoRR abs/1902.11036 (2019) - [i2]Moti Freiman, Hannes Nickisch, Sven Prevrhal, Holger Schmitt, Mani Vembar, Pál Maurovich-Horvat, Patrick Donnelly, Liran Goshen:
Improving CCTA based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation. CoRR abs/1906.09763 (2019) - [i1]Moti Freiman, Hannes Nickisch, Holger Schmitt, Pál Maurovich-Horvat, Patrick Donnelly, Mani Vembar, Liran Goshen:
Learning a sparse database for patch-based medical image segmentation. CoRR abs/1906.10338 (2019) - 2017
- [j9]Sila Kurugol, Moti Freiman, Onur Afacan, Liran Domachevsky, Jeannette M. Perez-Rossello, Michael J. Callahan, Simon K. Warfield:
Motion-robust parameter estimation in abdominal diffusion-weighted MRI by simultaneous image registration and model estimation. Medical Image Anal. 39: 124-132 (2017) - [c25]Moti Freiman, Hannes Nickisch, Holger Schmitt, Pál Maurovich-Horvat, Patrick Donnelly, Mani Vembar, Liran Goshen:
Learning a Sparse Database for Patch-Based Medical Image Segmentation. Patch-MI@MICCAI 2017: 47-54 - 2016
- [j8]Sila Kurugol, Moti Freiman, Onur Afacan, Jeannette M. Perez-Rossello, Michael J. Callahan, Simon K. Warfield:
Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI. Medical Image Anal. 32: 173-183 (2016) - [c24]Moti Freiman, Yechiel Lamash, Guy Gilboa, Hannes Nickisch, Sven Prevrhal, Holger Schmitt, Mani Vembar, Liran Goshen:
Automatic coronary lumen segmentation with partial volume modeling improves lesions' hemodynamic significance assessment. Image Processing 2016: 978403 - 2015
- [c23]Vahid Taimouri, Sila Kurugol, Sean Clancy, Moti Freiman, Simon K. Warfield:
Structural and diffusion weighted MRI registration for biomarker fusion in Crohn's disease diagnosis. ISBI 2015: 592-595 - [c22]Hannes Nickisch, Yechiel Lamash, Sven Prevrhal, Moti Freiman, Mani Vembar, Liran Goshen, Holger Schmitt:
Learning Patient-Specific Lumped Models for Interactive Coronary Blood Flow Simulations. MICCAI (2) 2015: 433-441 - [c21]Sila Kurugol, Moti Freiman, Onur Afacan, Liran Domachevsky, Jeannette M. Perez-Rossello, Michael J. Callahan, Simon K. Warfield:
Motion Compensated Abdominal Diffusion Weighted MRI by Simultaneous Image Registration and Model Estimation (SIR-ME). MICCAI (3) 2015: 501-509 - 2014
- [c20]Sila Kurugol, Moti Freiman, Onur Afacan, Jeannette M. Perez-Rossello, Michael J. Callahan, Simon K. Warfield:
Spatially-Constrained Probability Distribution Model of Incoherent Motion (SPIM) in Diffusion Weighted MRI Signals of Crohn's Disease. ABDI@MICCAI 2014: 117-127 - [c19]Yechiel Lamash, Moti Freiman, Liran Goshen:
Simultaneous Multi-phase Coronary CT Angiography Analysis for Coronary Artery Disease Evaluation. CLIP@MICCAI 2014: 134-141 - 2013
- [j7]Moti Freiman, Jeannette M. Perez-Rossello, Michael J. Callahan, Stephan D. Voss, Kirsten Ecklund, Robert V. Mulkern, Simon K. Warfield:
Reliable estimation of incoherent motion parametric maps from diffusion-weighted MRI using fusion bootstrap moves. Medical Image Anal. 17(3): 325-336 (2013) - [c18]Moti Freiman, Onur Afacan, Robert V. Mulkern, Simon K. Warfield:
Improved Multi B-Value Diffusion-Weighted MRI of the Body by Simultaneous Model Estimation and Image Reconstruction (SMEIR). MICCAI (3) 2013: 1-8 - [c17]Vahid Taimouri, Moti Freiman, Onur Afacan, Simon K. Warfield:
Spatially Constrained Incoherent Motion (SCIM) Model Improves Quantitative Diffusion-Weighted MRI Analysis of Crohn's Disease Patients. Abdominal Imaging 2013: 11-19 - 2012
- [j6]Moti Freiman, Leo Joskowicz, Noah Broide, Miriam Natanzon, E. Nammer, Ofek Shilon, Lior Weizman, Jacob Sosna:
Carotid vasculature modeling from patient CT angiography studies for interventional procedures simulation. Int. J. Comput. Assist. Radiol. Surg. 7(5): 799-812 (2012) - [c16]Moti Freiman, Stephan D. Voss, Robert V. Mulkern, Jeannette M. Perez-Rossello, Michael J. Callahan, Simon K. Warfield:
Reliable Assessment of Perfusivity and Diffusivity from Diffusion Imaging of the Body. MICCAI (1) 2012: 1-9 - 2011
- [j5]Moti Freiman, Ofir Cooper, Dani Lischinski, Leo Joskowicz:
Liver tumors segmentation from CTA images using voxels classification and affinity constraint propagation. Int. J. Comput. Assist. Radiol. Surg. 6(2): 247-255 (2011) - [j4]Moti Freiman, Michael Werman, Leo Joskowicz:
A curvelet-based patient-specific prior for accurate multi-modal brain image rigid registration. Medical Image Anal. 15(1): 125-132 (2011) - [j3]K. Hameeteman, Maria A. Zuluaga, Moti Freiman, Leo Joskowicz, Olivier Cuisenaire, Leonardo Floréz-Valencia, Mehmet Akif Gülsün, Karl Krissian, Julien Mille, Wilbur C. K. Wong, Maciej Orkisz, Hüseyin Tek, Marcela Hernández Hoyos, Fethallah Benmansour, Albert C. S. Chung, Sietske Rozie, M. van Gils, L. van den Borne, Jacob Sosna, Phillip M. Berman, N. Cohen, Philippe Douek, I. Sánchez, M. Aissat, Michiel Schaap, Coert Metz, Gabriel P. Krestin, Aad van der Lugt, Wiro J. Niessen, Theo van Walsum:
Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading. Medical Image Anal. 15(4): 477-488 (2011) - [j2]Yehonatan Sela, Moti Freiman, Elia Dery, Yifat Edrei, Rifaat Safadi, Orit Pappo, Leo Joskowicz, Rinat Abramovitch:
fMRI-Based Hierarchical SVM Model for the Classification and Grading of Liver Fibrosis. IEEE Trans. Biomed. Eng. 58(9): 2574-2581 (2011) - [c15]Moti Freiman, Stephan D. Voss, Simon K. Warfield:
Demons registration with local affine adaptive regularization: application to registration of abdominal structures. ISBI 2011: 1219-1222 - [c14]Moti Freiman, Stephan D. Voss, Robert V. Mulkern, Jeannette M. Perez-Rossello, Simon K. Warfield:
Quantitative Body DW-MRI Biomarkers Uncertainty Estimation Using Unscented Wild-Bootstrap. MICCAI (2) 2011: 74-81 - [c13]Moti Freiman, Stephan D. Voss, Simon K. Warfield:
Abdominal Images Non-rigid Registration Using Local-Affine Diffeomorphic Demons. Abdominal Imaging 2011: 116-124 - [c12]Moti Freiman, Ofir Pele, Aviv Hurvitz, Michael Werman, Leo Joskowicz:
Spectral-based 2D/3D X-ray to CT image rigid registration. Image-Guided Procedures 2011: 79641B - 2010
- [b1]Moti Freiman:
Shape constraint optimization for medical image segmentation and registration (עם תקציר בעברית ושער נוסף: שילוב מידע גיאומטרי בתהליכי אופטימיזציה לצורך סגמנטציה ורגיסטרציה של תמונות רפואיות.). Hebrew University of Jerusalem, Israel, 2010 - [c11]Moti Freiman, Steven J. Esses, Leo Joskowicz, Jacob Sosna:
An iterative model-constrained graph-cut algorithm for abdominal aortic aneurysm thrombus segmentation. ISBI 2010: 672-675 - [c10]Moti Freiman, Yehonatan Sela, Yifat Edrei, Orit Pappo, Leo Joskowicz, Rinat Abramovitch:
Multi-class SVM model for fMRI-based classification and grading of liver fibrosis. Computer-Aided Diagnosis 2010: 76240S - [c9]Moti Freiman, Achia Kronman, Steven J. Esses, Leo Joskowicz, Jacob Sosna:
Non-parametric Iterative Model Constraint Graph min-cut for Automatic Kidney Segmentation. MICCAI (3) 2010: 73-80 - [c8]Ofir Cooper, Moti Freiman, Leo Joskowicz, Dani Lischinski:
Affinity-based constraint optimization for nearly-automatic vessel segmentation. Image Processing 2010: 76230O
2000 – 2009
- 2009
- [c7]Moti Freiman, Noah Broide, Miriam Natanzon, Einav Namer, Ofek Shilon, Lior Weizman, Leo Joskowicz, Jacob Sosna:
Vessels-Cut: A Graph Based Approach to Patient-Specific Carotid Arteries Modeling. 3DPH 2009: 1-12 - [c6]Moti Freiman, Leo Joskowicz, Jacob Sosna:
A variational method for vessels segmentation: algorithm and application to liver vessels visualization. Image-Guided Procedures 2009: 72610H - [c5]M. N. Safran, Moti Freiman, Michael Werman, Leo Joskowicz:
Curvelet-based sampling for accurate and efficient multimodal image registration. Image Processing 2009: 72590M - 2008
- [j1]Moti Freiman, Ofer Eliassaf, Yoav Taieb, Leo Joskowicz, Yusef Azraq, Jacob Sosna:
An iterative Bayesian approach for nearly automatic liver segmentation: algorithm and validation. Int. J. Comput. Assist. Radiol. Surg. 3(5): 439-446 (2008) - [c4]Moti Freiman, Yifat Edrei, Eitan Gross, Leo Joskowicz, Rinat Abramovitch:
Liver metastasis early detection using fMRI based statistical model. ISBI 2008: 584-587 - [c3]Moti Freiman, Ofer Eliassaf, Yoav Taieb, Leo Joskowicz, Jacob Sosna:
A Bayesian Approach for Liver Analysis: Algorithm and Validation Study. MICCAI (1) 2008: 85-92 - [c2]Moti Freiman, Yifat Edrei, Yehonatan Sela, Yitzchak Shmidmayer, Eitan Gross, Leo Joskowicz, Rinat Abramovitch:
Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach. MICCAI (1) 2008: 93-100 - 2005
- [c1]Ruby Shamir, Moti Freiman, Leo Joskowicz, Moshe Shoham, Ephraim Zehavi, Yigal Shoshan:
Robot-Assisted Image-Guided Targeting for Minimally Invasive Neurosurgery: Planning, Registration, and In-vitro Experiment. MICCAI (2) 2005: 131-138
Coauthor Index
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