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Adi Szeskin
Adi Szeskin
Verified email at mail.huji.ac.il
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Cited by
Year
The liver tumor segmentation benchmark (lits)
P Bilic, P Christ, HB Li, E Vorontsov, A Ben-Cohen, G Kaissis, A Szeskin, ...
Medical Image Analysis 84, 102680, 2023
11952023
Automatic detection of new tumors and tumor burden evaluation in longitudinal liver CT scan studies
R Vivanti, A Szeskin, N Lev-Cohain, J Sosna, L Joskowicz
International journal of computer assisted radiology and surgery 12, 1945-1957, 2017
822017
Automated evaluation of human embryo blastulation and implantation potential using deep‐learning
Y Kan-Tor, N Zabari, I Erlich, A Szeskin, T Amitai, D Richter, Y Or, ...
Advanced Intelligent Systems 2 (10), 2000080, 2020
292020
Automatic detection and diagnosis of sacroiliitis in CT scans as incidental findings
Y Shenkman, B Qutteineh, L Joskowicz, A Szeskin, A Yusef, A Mayer, ...
Medical image analysis 57, 165-175, 2019
262019
A column-based deep learning method for the detection and quantification of atrophy associated with AMD in OCT scans
A Szeskin, R Yehuda, O Shmueli, J Levy, L Joskowicz
Medical Image Analysis 72, 102130, 2021
192021
Liver lesion changes analysis in longitudinal CECT scans by simultaneous deep learning voxel classification with SimU-Net
A Szeskin, S Rochman, S Weiss, R Lederman, J Sosna, L Joskowicz
Medical Image Analysis 83, 102675, 2023
172023
Progression of cRORA (complete RPE and outer retinal atrophy) in dry age-related macular degeneration measured using SD-OCT
O Shmueli, R Yehuda, A Szeskin, L Joskowicz, J Levy
Translational Vision Science & Technology 11 (1), 19-19, 2022
162022
Copper interconnections and antennas fabricated by hot-pressing printed copper formate
YS Rosen, Y Lidor, R Balter, A Szeskin, A Awadallah, ...
Flexible and Printed Electronics 2 (3), 035007, 2017
92017
Follow-up of liver metastases: a comparison of deep learning and RECIST 1.1
L Joskowicz, A Szeskin, S Rochman, A Dodi, R Lederman, ...
European Radiology 33 (12), 9320-9327, 2023
62023
Graph-based automatic detection and classification of lesion changes in pairs of CT studies for oncology follow-up
S Rochman, A Szeskin, R Lederman, J Sosna, L Joskowicz
International Journal of Computer Assisted Radiology and Surgery 19 (2), 241-251, 2024
32024
Machine learning classification of retinal atrophy in oct scans
L Joskowicz, A Szeskin, R Yehuda, L Jaime, O Shmueli
US Patent App. 18/564,093, 2024
2024
Measuring Geographic Atrophy Area Using Column-Based Machine Learning Software on Spectral-Domain Optical Coherence Tomography versus Fundus Auto Fluorescence
O Shmueli, A Szeskin, I Benhamou, L Joskowicz, Y Shwartz, J Levy
Bioengineering 11 (8), 849, 2024
2024
Metastatic Lung Lesion Changes in Follow-up Chest CT: The Advantage of Deep Learning Simultaneous Analysis of Prior and Current Scans With SimU-Net
NK Portal, S Rochman, A Szeskin, R Lederman, J Sosna, L Joskowicz
Journal of Thoracic Imaging, 10.1097, 2024
2024
Simultaneous column-based deep learning progression analysis of atrophy associated with AMD in longitudinal OCT studies
A Szeskin, R Yehuda, O Shmueli, J Levy, L Joskowicz
arXiv preprint arXiv:2307.16559, 2023
2023
Automated Testing of Graphics Units by Deep-Learning Detection of Visual Anomalies
L Faivishevsky, A Szeskin, AK Muppalla, SZ Ravid, I Ben Ari, R Laperdon, ...
Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data …, 2021
2021
cRORA progression and its baseline predicting factors
O Shmueli, R Yehuda, A Szeskin, L Joskowicz, J Levy
Investigative Ophthalmology & Visual Science 62 (8), 1888-1888, 2021
2021
Deep learning using embryo preimplantation videos can automatically predict the potential of human embryos to blastulate and implant
Y Ken-Tor, N Zabari, A Szeskin, A Tamar, D Richter, Y Or, Z Shoham, ...
HUMAN REPRODUCTION 35, 103-104, 2020
2020
A Weak Supervision Approach to Detecting Visual Anomalies for Automated Testing of Graphics Units
A Szeskin, L Faivishevsky, AK Muppalla, A Armon, T Hope
NeurIPS 2019, ML4SYS, 2019
2019
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