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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.Translational Vision Science & Technology|January 14, 2022
Progression of cRORA (Complete RPE and Outer Retinal Atrophy) in Dry Age-Related Macular Degeneration Measured Using SD-OCTOr Shmueli, Roei Yehuda, Adi Szeskin, et al.Medical Image Analysis|July 1, 2021
A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scansAdi Szeskin, Roei Yehuda, Or Shmueli, 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.Bioengineering (Basel, Switzerland)|August 29, 2024
Measuring Geographic Atrophy Area Using Column-Based Machine Learning Software on Spectral-Domain Optical Coherence Tomography versus Fundus Auto FluorescenceOr Shmueli, Adi Szeskin, Ilan Benhamou, et al.Journal of Thoracic Imaging|January 14, 2025
Metastatic Lung Lesion Changes in Follow-up Chest CT: The Advantage of Deep Learning Simultaneous Analysis of Prior and Current Scans With SimU-NetNeta Kenneth Portal, Shalom Rochman, Adi Szeskin, et al.Medical Image Analysis|July 20, 2019
Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findingsYigal Shenkman, Bilal Qutteineh, Leo Joskowicz, et al.European Radiology|July 22, 2023
Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1Leo Joskowicz, Adi Szeskin, Shalom Rochman, et al.Medical Image Analysis|December 8, 2022
The Liver Tumor Segmentation Benchmark (LiTS)Patrick Bilic, Patrick Christ, Hongwei Bran Li, et al.Pageof 1