Moti Freiman

1.4k total citations
69 papers, 874 citations indexed

About

Moti Freiman is a scholar working on Radiology, Nuclear Medicine and Imaging, Computer Vision and Pattern Recognition and Surgery. According to data from OpenAlex, Moti Freiman has authored 69 papers receiving a total of 874 indexed citations (citations by other indexed papers that have themselves been cited), including 39 papers in Radiology, Nuclear Medicine and Imaging, 25 papers in Computer Vision and Pattern Recognition and 10 papers in Surgery. Recurrent topics in Moti Freiman's work include Medical Image Segmentation Techniques (18 papers), MRI in cancer diagnosis (14 papers) and Radiomics and Machine Learning in Medical Imaging (14 papers). Moti Freiman is often cited by papers focused on Medical Image Segmentation Techniques (18 papers), MRI in cancer diagnosis (14 papers) and Radiomics and Machine Learning in Medical Imaging (14 papers). Moti Freiman collaborates with scholars based in Israel, United States and Germany. Moti Freiman's co-authors include Leo Joskowicz, Simon K. Warfield, Jeannette M. Pérez-Rosselló, Michael J. Callahan, Robert V. Mulkern, Jacob Sosna, Reuben R. Shamir, Yigal Shoshan, Stephan D. Voss and David M. Broday and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American College of Cardiology and PLoS ONE.

In The Last Decade

Moti Freiman

64 papers receiving 850 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Moti Freiman Israel	18	443	222	163	139	85	69	874
Fajin Dong China	15	335 0.8×	111 0.5×	192 1.2×	153 1.1×	148 1.7×	99	1.0k
Mario Ceresa Spain	14	195 0.4×	71 0.3×	127 0.8×	82 0.6×	45 0.5×	49	683
Yih Miin Liew Malaysia	16	364 0.8×	102 0.5×	318 2.0×	126 0.9×	222 2.6×	52	794
Alexander D. Weston United States	12	475 1.1×	105 0.5×	203 1.2×	165 1.2×	67 0.8×	25	973
Shahein Tajmir United States	13	505 1.1×	99 0.4×	244 1.5×	131 0.9×	26 0.3×	19	1.2k
Alfiia Galimzianova United States	8	438 1.0×	379 1.7×	157 1.0×	39 0.3×	56 0.7×	15	1.0k
Robert M. Cothren United States	14	461 1.0×	76 0.3×	422 2.6×	287 2.1×	53 0.6×	31	1.1k
Mellisa Damodaram United Kingdom	14	205 0.5×	171 0.8×	43 0.3×	68 0.5×	46 0.5×	18	895
Hanns‐Christian Breit Switzerland	11	541 1.2×	82 0.4×	278 1.7×	91 0.7×	62 0.7×	41	797
Sheng‐Wei Chang Taiwan	12	91 0.2×	55 0.2×	160 1.0×	41 0.3×	76 0.9×	23	811

Countries citing papers authored by Moti Freiman

Since Specialization

Citations

This map shows the geographic impact of Moti Freiman's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Moti Freiman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Moti Freiman more than expected).

Fields of papers citing papers by Moti Freiman

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Moti Freiman. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Moti Freiman. The network helps show where Moti Freiman may publish in the future.

Co-authorship network of co-authors of Moti Freiman

This figure shows the co-authorship network connecting the top 25 collaborators of Moti Freiman. A scholar is included among the top collaborators of Moti Freiman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Moti Freiman. Moti Freiman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Kennedy, John A., et al.. (2025). Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment. Medical & Biological Engineering & Computing. 63(6). 1715–1730. 1 indexed citations

Cohen, Israel, et al.. (2024). Deep-learning-based Group-wise Motion Correction for Myocardial T1 Mapping. Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition. 1 indexed citations

Atia, Ohad, Shira Greenfeld, Revital Kariv, et al.. (2024). Predictors of Complicated Disease Course in Children and Adults With Ulcerative Colitis: A Nationwide Study From the epi-IIRN. Inflammatory Bowel Diseases. 31(3). 655–664. 3 indexed citations

Freiman, Moti, et al.. (2024). NPB-REC: A non-parametric Bayesian deep-learning approach for undersampled MRI reconstruction with uncertainty estimation. Artificial Intelligence in Medicine. 149. 102798–102798. 3 indexed citations

Freiman, Moti, et al.. (2024). LUNet: deep learning for the segmentation of arterioles and venules in high resolution fundus images. Physiological Measurement. 45(5). 55002–55002. 6 indexed citations

Focht, Gili, Mary‐Louise C. Greer, Denise Castro, et al.. (2022). Development of a multimodal machine-learning fusion model to non-invasively assess ileal Crohn’s disease endoscopic activity. Computer Methods and Programs in Biomedicine. 227. 107207–107207. 21 indexed citations

Diemen, Pepijn A. van, Michiel J. Bom, Roel S. Driessen, et al.. (2021). Prognostic Value of RCA Pericoronary Adipose Tissue CT-Attenuation Beyond High-Risk Plaques, Plaque Volume, and Ischemia. JACC. Cardiovascular imaging. 14(8). 1598–1610. 67 indexed citations

Diemen, Pepijn A. van, Michiel J. Bom, Roel S. Driessen, et al.. (2021). THE PROGNOSTIC VALUE OF PERICORONARY ADIPOSE TISSUE CT-ATTENUATION BEYOND HIGH-RISK PLAQUES, PLAQUE VOLUME, AND MYOCARDIAL ISCHEMIA. Journal of the American College of Cardiology. 77(18). 1370–1370. 1 indexed citations

Kurugol, Sila, Moti Freiman, Jeannette M. Pérez-Rosselló, et al.. (2018). Curved planar reformatting and convolutional neural network‐based segmentation of the small bowel for visualization and quantitative assessment of pediatric Crohn's disease from MRI. Journal of Magnetic Resonance Imaging. 49(6). 1565–1576. 28 indexed citations

10.

Kurugol, Sila, Moti Freiman, Onur Afacan, et al.. (2016). Spatially-constrained probability distribution model of incoherent motion (SPIM) for abdominal diffusion-weighted MRI. Medical Image Analysis. 32. 173–183. 16 indexed citations

11.

Afacan, Onur, Jeannette M. Pérez-Rosselló, Michael J. Callahan, et al.. (2015). Spatially constrained incoherent motion method improves diffusion‐weighted MRI signal decay analysis in the liver and spleen. Medical Physics. 42(4). 1895–1903. 22 indexed citations

12.

Freiman, Moti, Onur Afacan, Robert V. Mulkern, & Simon K. Warfield. (2013). Improved Multi B-Value Diffusion-Weighted MRI of the Body by Simultaneous Model Estimation and Image Reconstruction (SMEIR). Lecture notes in computer science. 16(Pt 3). 1–8. 3 indexed citations

13.

Freiman, Moti, Stephan D. Voss, Robert V. Mulkern, et al.. (2012). In vivo assessment of optimal b‐value range for perfusion‐insensitive apparent diffusion coefficient imaging. Medical Physics. 39(8). 4832–4839. 39 indexed citations

14.

Freiman, Moti, Stephan D. Voss, Robert V. Mulkern, et al.. (2012). Reliable Assessment of Perfusivity and Diffusivity from Diffusion Imaging of the Body. Lecture notes in computer science. 15(Pt 1). 1–9. 9 indexed citations

15.

Freiman, Moti, Stephan D. Voss, Robert V. Mulkern, Jeannette M. Pérez-Rosselló, & Simon K. Warfield. (2011). Quantitative Body DW-MRI Biomarkers Uncertainty Estimation Using Unscented Wild-Bootstrap. Lecture notes in computer science. 14(Pt 2). 74–81. 10 indexed citations

16.

Freiman, Moti, et al.. (2010). Liver tumors segmentation from CTA images using voxels classification and affinity constraint propagation. International Journal of Computer Assisted Radiology and Surgery. 6(2). 247–255. 31 indexed citations

17.

Freiman, Moti, Michael Werman, & Leo Joskowicz. (2010). A curvelet-based patient-specific prior for accurate multi-modal brain image rigid registration. Medical Image Analysis. 15(1). 125–132. 18 indexed citations

18.

Freiman, Moti, et al.. (2008). A Bayesian Approach for Liver Analysis: Algorithm and Validation Study. Lecture notes in computer science. 11(Pt 1). 85–92. 19 indexed citations

19.

Freiman, Moti, et al.. (2008). Classification of Suspected Liver Metastases Using fMRI Images: A Machine Learning Approach. Lecture notes in computer science. 11(Pt 1). 93–100. 6 indexed citations

20.

Joskowicz, Leo, Reuben R. Shamir, Moti Freiman, et al.. (2006). Image-guided system with miniature robot for precise positioning and targeting in keyhole neurosurgery. Computer Aided Surgery. 11(4). 181–193. 43 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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