Associate Prof. Moti Freiman

Computational MRI Lab

Phone 073-3784147
Email moti.freiman@bm.technion.ac.il
Office Silver Building, Room 239
Link to Lab https://tcml-bme.github.io/

CV

  • 2010 PhD School of Engineering and Computer Science, The Hebrew University of Jerusalem, Israel
  • 2005 MSc (cum laude) School of Engineering and Computer Science, The Hebrew University of Jerusalem, Israel
  • 2003 BSc Department of Mathematics and Computer Science, Bar-Ilan University, Israel
  • 2025 Associate Professor, Faculty of Biomedical Engineering, Technion, Israel
  • 2019 Assistant Professor, Faculty of Biomedical Engineering, Technion, Israel
  • 2013-2019 Staff Research Scientist, Philips Healthcare, Haifa, Israel
  • 2012-2019 Instructor of Radiology, Harvard Medical School, Boston, MA, USA
  • 2012-2015 Staff Scientist, Computational Radiology Lab (Prof. Simon K Warfield), Boston Children’s Hospital, Boston, MA, USA
  • 2010-2012 Post-doctoral research fellow, Computational Radiology Lab (Prof. Simon K Warfield), Boston Children’s Hospital/Harvard Medical School, Boston, MA, USA
  • Gilad M, Partridge SC, Iima M, Rakow-Penner R, Freiman M. Radiomics-based Machine Learning Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Using Physiologically Decomposed Diffusion-weighted MRI, Radiology-Imaging Cancer, Accepted, Jun. 2025, In press.
  • Brock L, Ben-Atya H, Tiwari A, Saab D, Haj N, Folle L, Saar G, Maier A, Freiman M, Vandoorne K. Improved MRI detection of inflammation-induced changes in bone marrow microstructure in mice: a machine learning-enhanced T2 distribution analysis. European Radiology Experimental. 2025 Mar 26;9(1):39.
  • Hanania E, Zehavi-Lenz A, Volovik I, Link-Sourani D, Cohen I and Freiman M. MBSST1: Model-Based Subject Specific Self-Supervised Motion Correction for Robust Cardiac T1 Mapping, Medical Image Analysis, 102:103495, 2025.
  • Kertes N, Zaffrani-Reznikov Y, Afacan O, Kurugol S, Warfield SK and Freiman M. IVIMMorph: Motion-compensated quantitative Intra-voxel Incoherent Motion (IVIM) analysis for functional fetal lung maturity assessment from diffusion-weighted MRI data, Medical Image Analysis, 101: 103445, 2025.
  • Hezi H, Gelber M, Balabanov A, Maruvka YE, Freiman M. CIMIL-CRC: A clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H&E stained images. Computer Methods and Programs in Biomedicine. 2025 Feb;259:108513.
  • Avidan N and Freiman M. MA-RECON: Mask-aware deep-neural-network for robust fast MRI k-space interpolation, Computer Methods and Programs in Biomedicine, 244: 107942, 2024.
  • Khawaled S and Freiman M. NPB-REC: A Non-parametric Bayesian Deep-learning Approach for undersampled MRI Reconstruction, Artificial Intelligence in Medicine, 149: 102798, 2024.
  • Hezi H, Shats D, Gurevich D, Maruvka YE, Freiman M. Exploring the interplay between colorectal cancer subtypes genomic variants and cellular morphology: A deep-learning approach. PLoS One. 2024 Sep 10;19(9): e0309380.
  • Hanania E., Volovik I., Barkat L., Cohen I., Freiman M. (2023). PCMC-T1: Free-Breathing Myocardial T1 Mapping with Physically-Constrained Motion Correction. In Proc. Int. Conf. On Medical Image Computing and Computer-Aided Intervention 2023, Lecture Notes in Computer Science, 2023; 14226: 226-235.
  • Ben-Atya H, Freiman M. P2T2: A physically-primed deep-neural-network approach for robust T2 distribution estimation from quantitative T2-weighted MRI. Comput Med Imaging Graph. 2023; 107:102240.
  • Guez I, Focht G, Greer MC, Cytter-Kuint R, Pratt LT, Castro DA, Turner D, Griffiths AM, Freiman M. Development of a multimodal machine-learning fusion model to non-invasively assess ileal Crohn's disease endoscopic activity. Comput Methods Programs Biomed. 2022; 227:107207.
  • Gilad M, Freiman M. PD-DWI: Predicting response to neoadjuvant chemotherapy in invasive breast cancer with Physiologically-Decomposed Diffusion-Weighted MRI machine-learning model, In Proc. Int. Conf. On Medical Image Computing and Computer-Aided Intervention 2022, Lecture Notes in Computer Science, 2022; 13433: 36-45.
  • Korngut N, Rotman E, Afacan O, Kurugol S, Nemirovsky-Rotman S, Zaafrani0Reznikov Y, Warfield SK, Freiman M. SUPER-IVIM-DC: Intra-voxel incoherent motion based Fetal lung maturity assessment from limited DWI data using supervised learning coupled with data-consistency, In Proc. Int. Conf. On Medical Image Computing and Computer-Aided Intervention 2022, Lecture Notes in Computer Science, 2022; 13803: 482-494.
  • Khawaled S, Freiman M. NPBDREG: Uncertainty Assessment in Diffeomorphic Brain MRI Registration using a Non-parametric Bayesian Deep-Learning Based Approach, Computerized Medical Imaging and Graphics, 2022; 99: 102087.
  • Magnetic resonance Imaging
  • Medical image Analysis and processing
  • Deep-learning
  • Computed Tomography
  • Crohn’s disease
  • Fetal Imaging
  • Cardiac Imaging

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