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Richard Lederman

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International Journal of Computer Assisted Radiology and Surgery|June 25, 2025
Streamlining the annotation process by radiologists of volumetric medical images with few-shot learningAlina Ryabtsev, Richard Lederman, Jacob Sosna, et al.
The Israel Medical Association Journal : IMAJ|January 22, 2005
Hepatic lymphoma: an imaging approach with emphasis on image-guided needle biopsyLiat Appelbaum, Richard Lederman, Ronit Agid, et al.
International Journal of Computer Assisted Radiology and Surgery|September 13, 2025
Annotation-efficient deep learning detection and measurement of mediastinal lymph nodes in CTAlon Olesinski, Richard Lederman, Yusef Azraq, et al.
International Journal of Computer Assisted Radiology and Surgery|August 4, 2023
Graph-based automatic detection and classification of lesion changes in pairs of CT studies for oncology follow-upShalom Rochman, Adi Szeskin, Richard Lederman, et al.
Journal of Thoracic Imaging|October 17, 2025
Variability in Mediastinal Lymph Node Measurements in Chest Contrast-enhanced CT: Time to Change the Paradigm?Alon Olesinksi, Richard Lederman, Yusef Azraq, et al.
Medical Image Analysis|July 19, 2024
A graph-theoretic approach for the analysis of lesion changes and lesions detection review in longitudinal oncological imagingBeniamin Di Veroli, Richard Lederman, Yigal Shoshan, et al.
European Journal of Radiology|May 29, 2024
Three scans are better than two for follow-up: An automatic method for finding missed and misidentified lesions in cross-sectional follow-up of oncology patientsLeo Joskowicz, Beniamin Di Veroli, Richard Lederman, et al.
Abdominal Radiology (New York)|January 2, 2021
A novel method for estimating the urine drainage time from the renal collecting systemTalia Yeshua, Ori Gleisner, Richard Lederman, et al.
European Journal of Radiology Open|December 5, 2022
Quantitative assessment of renal obstruction in multi-phase CTU using automatic 3D segmentation of the renal parenchyma and renal pelvis: A proof of conceptChanoch Kahn, Isaac Leichter, Richard Lederman, et al.
Medical Image Analysis|November 5, 2022
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-NetAdi Szeskin, Shalom Rochman, Snir Weiss, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
International Journal of Computer Assisted Radiology and Surgery|June 25, 2025
Streamlining the annotation process by radiologists of volumetric medical images with few-shot learningAlina Ryabtsev, Richard Lederman, Jacob Sosna, et al.
The Israel Medical Association Journal : IMAJ|January 22, 2005
Hepatic lymphoma: an imaging approach with emphasis on image-guided needle biopsyLiat Appelbaum, Richard Lederman, Ronit Agid, et al.
International Journal of Computer Assisted Radiology and Surgery|September 13, 2025
Annotation-efficient deep learning detection and measurement of mediastinal lymph nodes in CTAlon Olesinski, Richard Lederman, Yusef Azraq, et al.
International Journal of Computer Assisted Radiology and Surgery|August 4, 2023
Graph-based automatic detection and classification of lesion changes in pairs of CT studies for oncology follow-upShalom Rochman, Adi Szeskin, Richard Lederman, et al.
Journal of Thoracic Imaging|October 17, 2025
Variability in Mediastinal Lymph Node Measurements in Chest Contrast-enhanced CT: Time to Change the Paradigm?Alon Olesinksi, Richard Lederman, Yusef Azraq, et al.
Medical Image Analysis|July 19, 2024
A graph-theoretic approach for the analysis of lesion changes and lesions detection review in longitudinal oncological imagingBeniamin Di Veroli, Richard Lederman, Yigal Shoshan, et al.
European Journal of Radiology|May 29, 2024
Three scans are better than two for follow-up: An automatic method for finding missed and misidentified lesions in cross-sectional follow-up of oncology patientsLeo Joskowicz, Beniamin Di Veroli, Richard Lederman, et al.
Abdominal Radiology (New York)|January 2, 2021
A novel method for estimating the urine drainage time from the renal collecting systemTalia Yeshua, Ori Gleisner, Richard Lederman, et al.
European Journal of Radiology Open|December 5, 2022
Quantitative assessment of renal obstruction in multi-phase CTU using automatic 3D segmentation of the renal parenchyma and renal pelvis: A proof of conceptChanoch Kahn, Isaac Leichter, Richard Lederman, et al.
Medical Image Analysis|November 5, 2022
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-NetAdi Szeskin, Shalom Rochman, Snir Weiss, et al.
Pageof 2