Robot-Assisted Image-Guided Targeting for Minimally Invasive Neurosurgery: Planning, Registration, and In-vitro Experiment. - Ruby Shamir; Moti Freiman; Leo Joskowicz; Moshe Shoham; Ephraim Zehavi; Yigal Shoshan (MICCAI (2), 2005)

Liver metastasis early detection using fMRI based statistical model. - Moti Freiman; Yifat Edrei; Eitan Gross; Leo Joskowicz; Rinat Abramovitch (ISBI, 2008)

Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach. - Moti Freiman; Yifat Edrei; Yehonatan Sela; Yitzchak Shmidmayer; Eitan Gross; Leo Joskowicz; Rinat Abramovitch (MICCAI (1), 2008)

A Bayesian Approach for Liver Analysis: Algorithm and Validation Study. - Moti Freiman; Ofer Eliassaf; Yoav Taieb; Leo Joskowicz; Jacob Sosna (MICCAI (1), 2008)

An iterative Bayesian approach for nearly automatic liver segmentation: algorithm and validation. - Moti Freiman; Ofer Eliassaf; Yoav Taieb; Leo Joskowicz; Yusef Azraq; Jacob Sosna (Int. J. Comput. Assist. Radiol. Surg., 2008)

Vessels-Cut: A Graph Based Approach to Patient-Specific Carotid Arteries Modeling. - Moti Freiman; Noah Broide; Miriam Natanzon; Einav Namer; Ofek Shilon; Lior Weizman; Leo Joskowicz; Jacob Sosna (3DPH, 2009)

A variational method for vessels segmentation: algorithm and application to liver vessels visualization. - Moti Freiman; Leo Joskowicz; Jacob Sosna (Image-Guided Procedures, 2009)

Curvelet-based sampling for accurate and efficient multimodal image registration. - M. N. Safran; Moti Freiman; Michael Werman; Leo Joskowicz (Image Processing, 2009)

An iterative model-constrained graph-cut algorithm for abdominal aortic aneurysm thrombus segmentation. - Moti Freiman; Steven J. Esses; Leo Joskowicz; Jacob Sosna (ISBI, 2010)

Multi-class SVM model for fMRI-based classification and grading of liver fibrosis. - Moti Freiman; Yehonatan Sela; Yifat Edrei; Orit Pappo; Leo Joskowicz; Rinat Abramovitch (Computer-Aided Diagnosis, 2010)

Non-parametric Iterative Model Constraint Graph min-cut for Automatic Kidney Segmentation. - Moti Freiman; Achia Kronman; Steven J. Esses; Leo Joskowicz; Jacob Sosna (MICCAI (3), 2010)

Affinity-based constraint optimization for nearly-automatic vessel segmentation. - Ofir Cooper; Moti Freiman; Leo Joskowicz; Dani Lischinski (Image Processing, 2010)

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.). - Moti Freiman (2010)

Demons registration with local affine adaptive regularization: application to registration of abdominal structures. - Moti Freiman; Stephan D. Voss; Simon K. Warfield (ISBI, 2011)

Quantitative Body DW-MRI Biomarkers Uncertainty Estimation Using Unscented Wild-Bootstrap. - Moti Freiman; Stephan D. Voss; Robert V. Mulkern; Jeannette M. Perez-Rossello; Simon K. Warfield (MICCAI (2), 2011)

Abdominal Images Non-rigid Registration Using Local-Affine Diffeomorphic Demons. - Moti Freiman; Stephan D. Voss; Simon K. Warfield (Abdominal Imaging, 2011)

Spectral-based 2D/3D X-ray to CT image rigid registration. - Moti Freiman; Ofir Pele; Aviv Hurvitz; Michael Werman; Leo Joskowicz (Image-Guided Procedures, 2011)

Liver tumors segmentation from CTA images using voxels classification and affinity constraint propagation. - Moti Freiman; Ofir Cooper; Dani Lischinski; Leo Joskowicz (Int. J. Comput. Assist. Radiol. Surg., 2011)

A curvelet-based patient-specific prior for accurate multi-modal brain image rigid registration. - Moti Freiman; Michael Werman; Leo Joskowicz (Medical Image Anal., 2011)

Evaluation framework for carotid bifurcation lumen segmentation and stenosis grading. - 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; et al. (Medical Image Anal., 2011)

fMRI-Based Hierarchical SVM Model for the Classification and Grading of Liver Fibrosis. - Yehonatan Sela; Moti Freiman; Elia Dery; Yifat Edrei; Rifaat Safadi; Orit Pappo; Leo Joskowicz; Rinat Abramovitch (IEEE Trans. Biomed. Eng., 2011)

Reliable Assessment of Perfusivity and Diffusivity from Diffusion Imaging of the Body. - Moti Freiman; Stephan D. Voss; Robert V. Mulkern; Jeannette M. Perez-Rossello; Michael J. Callahan; Simon K. Warfield (MICCAI (1), 2012)

Carotid vasculature modeling from patient CT angiography studies for interventional procedures simulation. - Moti Freiman; Leo Joskowicz; Noah Broide; Miriam Natanzon; E. Nammer; Ofek Shilon; Lior Weizman; Jacob Sosna (Int. J. Comput. Assist. Radiol. Surg., 2012)

Improved Multi B-Value Diffusion-Weighted MRI of the Body by Simultaneous Model Estimation and Image Reconstruction (SMEIR). - Moti Freiman; Onur Afacan; Robert V. Mulkern; Simon K. Warfield (MICCAI (3), 2013)

Spatially Constrained Incoherent Motion (SCIM) Model Improves Quantitative Diffusion-Weighted MRI Analysis of Crohn's Disease Patients. - Vahid Taimouri; Moti Freiman; Onur Afacan; Simon K. Warfield (Abdominal Imaging, 2013)

Reliable estimation of incoherent motion parametric maps from diffusion-weighted MRI using fusion bootstrap moves. - Moti Freiman; Jeannette M. Perez-Rossello; Michael J. Callahan; Stephan D. Voss; Kirsten Ecklund; Robert V. Mulkern; Simon K. Warfield (Medical Image Anal., 2013)

Spatially-Constrained Probability Distribution Model of Incoherent Motion (SPIM) in Diffusion Weighted MRI Signals of Crohn's Disease. - Sila Kurugol; Moti Freiman; Onur Afacan; Jeannette M. Perez-Rossello; Michael J. Callahan; Simon K. Warfield (ABDI@MICCAI, 2014)

Simultaneous Multi-phase Coronary CT Angiography Analysis for Coronary Artery Disease Evaluation. - Yechiel Lamash; Moti Freiman; Liran Goshen (CLIP@MICCAI, 2014)

Structural and diffusion weighted MRI registration for biomarker fusion in Crohn's disease diagnosis. - Vahid Taimouri; Sila Kurugol; Sean Clancy; Moti Freiman; Simon K. Warfield (ISBI, 2015)

Motion Compensated Abdominal Diffusion Weighted MRI by Simultaneous Image Registration and Model Estimation (SIR-ME). - Sila Kurugol; Moti Freiman; Onur Afacan; Liran Domachevsky; Jeannette M. Perez-Rossello; Michael J. Callahan; Simon K. Warfield (MICCAI (3), 2015)

Learning Patient-Specific Lumped Models for Interactive Coronary Blood Flow Simulations. - Hannes Nickisch; Yechiel Lamash; Sven Prevrhal; Moti Freiman; Mani Vembar; Liran Goshen; Holger Schmitt (MICCAI (2), 2015)

Automatic coronary lumen segmentation with partial volume modeling improves lesions' hemodynamic significance assessment. - Moti Freiman; Yechiel Lamash; Guy Gilboa; Hannes Nickisch; Sven Prevrhal; Holger Schmitt; Mani Vembar; Liran Goshen (Image Processing, 2016)

Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI. - Sila Kurugol; Moti Freiman; Onur Afacan; Jeannette M. Perez-Rossello; Michael J. Callahan; Simon K. Warfield (Medical Image Anal., 2016)

Learning a Sparse Database for Patch-Based Medical Image Segmentation. - Moti Freiman; Hannes Nickisch; Holger Schmitt; Pál Maurovich-Horvat; Patrick Donnelly; Mani Vembar; Liran Goshen (Patch-MI@MICCAI, 2017)

Motion-robust parameter estimation in abdominal diffusion-weighted MRI by simultaneous image registration and model estimation. - Sila Kurugol; Moti Freiman; Onur Afacan; Liran Domachevsky; Jeannette M. Perez-Rossello; Michael J. Callahan; Simon K. Warfield (Medical Image Anal., 2017)

Unsupervised Abnormality Detection through Mixed Structure Regularization (MSR) in Deep Sparse Autoencoders. - Moti Freiman; Ravindra Manjeshwar; Liran Goshen (CoRR, 2019)

Improving CCTA based lesions' hemodynamic significance assessment by accounting for partial volume modeling in automatic coronary lumen segmentation. - Moti Freiman; Hannes Nickisch; Sven Prevrhal; Holger Schmitt; Mani Vembar; Pál Maurovich-Horvat; Patrick Donnelly; Liran Goshen (CoRR, 2019)

Unsupervised Deep-Learning Based Deformable Image Registration: A Bayesian Framework. - Samah Khawaled; Moti Freiman (CoRR, 2020)

NPBDREG: A Non-parametric Bayesian Deep-Learning Based Approach for Diffeomorphic Brain MRI Registration. - Samah Khawaled; Moti Freiman (CoRR, 2021)

Non Parametric Data Augmentations Improve Deep-Learning based Brain Tumor Segmentation. - Hadas Ben-Atya; Ori Rajchert; Liran Goshen; Moti Freiman (CoRR, 2021)

Lirot.ai: A Novel Platform for Crowd-Sourcing Retinal Image Segmentations. - Jonathan Fhima; Jan Van Eijgen; Moti Freiman; Ingeborg Stalmans; Joachim A. Behar (CinC, 2022)

PVBM: A Python Vasculature Biomarker Toolbox Based on Retinal Blood Vessel Segmentation. - Jonathan Fhima; Jan Van Eijgen; Ingeborg Stalmans; Yevgeniy Men; Moti Freiman; Joachim A. Behar (ECCV Workshops (3), 2022)

Patient-Level Microsatellite Stability Assessment from Whole Slide Images by Combining Momentum Contrast Learning and Group Patch Embeddings. - Daniel Shats; Hadar Hezi; Guy Shani; Yosef E. Maruvka; Moti Freiman (ECCV Workshops (3), 2022)

qDWI-Morph: Motion-Compensated Quantitative Diffusion-Weighted MRI Analysis for Fetal Lung Maturity Assessment. - Yael Zaffrani-Reznikov; Onur Afacan; Sila Kurugol; Simon K. Warfield; Moti Freiman (ECCV Workshops (3), 2022)

Gadolinium-Free Crohn's Disease Assessment from Magnetic Resonance Enterography Data. - Yaniv Ziselman; Faten Hajali Shinnawi; Mary-Louise C. Greer; Gili Focht; Dan Turner; Moti Freiman (ISBI, 2022)

PD-DWI: Predicting Response to Neoadjuvant Chemotherapy in Invasive Breast Cancer with Physiologically-Decomposed Diffusion-Weighted MRI Machine-Learning Model. - Maya Gilad; Moti Freiman (MICCAI (3), 2022)

NPB-REC: Non-parametric Assessment of Uncertainty in Deep-Learning-Based MRI Reconstruction from Undersampled Data. - Samah Khawaled; Moti Freiman (MLMIR@MICCAI, 2022)

SUPER-IVIM-DC: Intra-voxel Incoherent Motion Based Fetal Lung Maturity Assessment from Limited DWI Data Using Supervised Learning Coupled with Data-Consistency. - Noam Korngut; Elad Rotman; Onur Afacan; Sila Kurugol; Yael Zaffrani-Reznikov; Shira Nemirovsky-Rotman; Simon K. Warfield; Moti Freiman (MICCAI (2), 2022)

NPBDREG: Uncertainty assessment in diffeomorphic brain MRI registration using a non-parametric Bayesian deep-learning based approach. - Samah Khawaled; Moti Freiman (Comput. Medical Imaging Graph., 2022)

Development of a multimodal machine-learning fusion model to non-invasively assess ileal Crohn's disease endoscopic activity. - Itai Guez; Gili Focht; Mary-Louise C. Greer; Ruth Cytter-Kuint; Li-Tal Pratt; Denise A. Castro; Dan Turner; Anne M. Griffiths; Moti Freiman (Comput. Methods Programs Biomed., 2022)

Image translation of Ultrasound to Pseudo Anatomical Display Using Artificial Intelligence. - Lilach Barkat; Moti Freiman; Haim Azhari (CoRR, 2022)

Physically-primed deep-neural-networks for generalized undersampled MRI reconstruction. - Nitzan Avidan; Moti Freiman (CoRR, 2022)

P2T2: a Physically-primed deep-neural-network approach for robust T2 distribution estimation from quantitative T2-weighted MRI. - Hadas Ben-Atya; Moti Freiman (CoRR, 2022)

Deep Learning-Based Fast MRI Reconstruction: Improving Generalization for Clinical Translation. - Nitzan Avidan; Moti Freiman (CLIP/FAIMI/EPIMI@MICCAI, 2023)

An Efficient and Accurate Neural Network Tool for Finding Correlation Between Gene Expression and Histological Images. - Guy Shani; Moti Freiman; Yosef E. Maruvka (CLIP/FAIMI/EPIMI@MICCAI, 2023)

Uncertainty Assessment in Whole-Body Low Dose Pet Reconstruction Using Non-Parametric Bayesian Deep Learning Approach. - Maya Fichmann Levital; Samah Khawaled; Yufei Chen 002; John A. Kennedy; Moti Freiman (ISBI, 2023)

PCMC-T1: Free-Breathing Myocardial T1 Mapping with Physically-Constrained Motion Correction. - Eyal Hanania; Ilya Volovik; Lilach Barkat; Israel Cohen; Moti Freiman (MICCAI (7), 2023)

P2T2: A physically-primed deep-neural-network approach for robust T2 distribution estimation from quantitative T2-weighted MRI. - Hadas Ben-Atya; Moti Freiman (Comput. Medical Imaging Graph., 2023)

Biologically-primed deep neural network improves colorectal Cancer Molecular subtypes prediction from H&E stained images. - Hadar Hezi; Daniel Shats; Daniel Gurevich; Yosef E. Maruvka; Moti Freiman (CoRR, 2023)

LUNet: Deep Learning for the Segmentation of Arterioles and Venules in High Resolution Fundus Images. - Jonathan Fhima; Jan Van Eijgen; Hana Kulenovic; Valérie Debeuf; Marie Vangilbergen; Marie-Isaline Billen; Heloïse Brackenier; Moti Freiman; Ingeborg Stalmans; Joachim A. Behar (CoRR, 2023)

Leveraging Prompt-Learning for Structured Information Extraction from Crohn's Disease Radiology Reports in a Low-Resource Language. - Liam Hazan; Naama Gavrielov; Roi Reichart; Talar Hagopian; Mary-Louise C. Greer; Ruth Cytter-Kuint; Gili Focht; Dan Turner; Moti Freiman (ClinicalNLP@NAACL, 2024)

Automated Prediction of Breast Cancer Response to Neoadjuvant Chemotherapy From DWI Data. - Shir Nitzan; Maya Gilad; Moti Freiman (ISBI, 2024)

NPB-REC: A non-parametric Bayesian deep-learning approach for undersampled MRI reconstruction with uncertainty estimation. - Samah Khawaled; Moti Freiman (Artif. Intell. Medicine, 2024)

MA-RECON: Mask-aware deep-neural-network for robust fast MRI k-space interpolation. - Nitzan Avidan; Moti Freiman (Comput. Methods Programs Biomed., 2024)

A self-attention model for robust rigid slice-to-volume registration of functional MRI. - Samah Khawaled; Simon K. Warfield; Moti Freiman (CoRR, 2024)

MBSS-T1: Model-Based Self-Supervised Motion Correction for Robust Cardiac T1 Mapping. - Eyal Hanania; Ilya Volovik; Daphna Link-Sourani; Israel Cohen; Moti Freiman (CoRR, 2024)

SIMPLE: Simultaneous Multi-Plane Self-Supervised Learning for Isotropic MRI Restoration from Anisotropic Data. - Rotem Benisty; Yevgenia Shteynman; Moshe Porat; Anat Illivitzki; Moti Freiman (CoRR, 2024)

Multi-Cohort Framework with Cohort-Aware Attention and Adversarial Mutual-Information Minimization for Whole Slide Image Classification. - Sharon Peled; Yosef E. Maruvka; Moti Freiman (CoRR, 2024)

CIMIL-CRC: A clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H&E stained images. - Hadar Hezi; Matan Gelber; Alexander Balabanov; Yosef E. Maruvka; Moti Freiman (Comput. Methods Programs Biomed., 2025)

MBSS-T1: Model-based subject-specific self-supervised motion correction for robust cardiac T1 mapping. - Eyal Hanania; Adi Zehavi-Lenz; Ilya Volovik; Daphna Link-Sourani; Israel Cohen; Moti Freiman (Medical Image Anal., 2025)

IVIM-Morph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data. - Noga Kertes; Yael Zaffrani-Reznikov; Onur Afacan; Sila Kurugol; Simon K. Warfield; Moti Freiman (Medical Image Anal., 2025)

Agent-Based Uncertainty Awareness Improves Automated Radiology Report Labeling with an Open-Source Large Language Model. - Hadas Ben-Atya; Naama Gavrielov; Zvi Badash; Gili Focht; Ruth Cytter-Kuint; Talar Hagopian; Dan Turner; Moti Freiman (CoRR, 2025)

T1-PILOT: Optimized Trajectories for T1 Mapping Acceleration. - Tamir Shor; Moti Freiman; Chaim Baskin; Alexander M. Bronstein (CoRR, 2025)

Enhancing Retinal Vessel Segmentation Generalization via Layout-Aware Generative Modelling. - Jonathan Fhima; Jan Van Eijgen; Lennert Beeckmans; Thomas Jacobs; Moti Freiman; Luis Filipe Nakayama; Ingeborg Stalmans; Chaim Baskin; Joachim A. Behar (CoRR, 2025)

PSA-MIL: A Probabilistic Spatial Attention-Based Multiple Instance Learning for Whole Slide Image Classification. - Sharon Peled; Yosef E. Maruvka; Moti Freiman (CoRR, 2025)

Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment. - Maya Fichmann Levital; Samah Khawaled; John A. Kennedy; Moti Freiman (Medical Biol. Eng. Comput., 2025)