Hayit Greenspan
Cited by
Cited by
Blobworld: Image segmentation using expectation-maximization and its application to image querying
C Carson, S Belongie, H Greenspan, J Malik
IEEE Transactions on pattern analysis and machine intelligence 24 (8), 1026-1038, 2002
Guest editorial deep learning in medical imaging: Overview and future promise of an exciting new technique
H Greenspan, B Van Ginneken, RM Summers
IEEE transactions on medical imaging 35 (5), 1153-1159, 2016
GAN-based synthetic medical image augmentation for increased CNN performance in liver lesion classification
M Frid-Adar, I Diamant, E Klang, M Amitai, J Goldberger, H Greenspan
Neurocomputing 321, 321-331, 2018
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
Rapid ai development cycle for the coronavirus (covid-19) pandemic: Initial results for automated detection & patient monitoring using deep learning ct image analysis
O Gozes, M Frid-Adar, H Greenspan, PD Browning, H Zhang, W Ji, ...
arXiv preprint arXiv:2003.05037, 2020
Synthetic data augmentation using GAN for improved liver lesion classification
M Frid-Adar, E Klang, M Amitai, J Goldberger, H Greenspan
2018 IEEE 15th international symposium on biomedical imaging (ISBI 2018 …, 2018
Color-and texture-based image segmentation using EM and its application to content-based image retrieval
S Belongie, C Carson, H Greenspan, J Malik
Sixth International Conference on Computer Vision (IEEE Cat. No. 98CH36271 …, 1998
Deep Learning in Medical Image Analysis and Multimodal Learning for Clinical Decision Support: Third International Workshop, DLMIA 2017, and 7th International Workshop, ML-CDS …
MJ Cardoso, T Arbel, G Carneiro, T Syeda-Mahmood, JMRS Tavares, ...
Springer, 2017
A review of deep learning in medical imaging: Imaging traits, technology trends, case studies with progress highlights, and future promises
SK Zhou, H Greenspan, C Davatzikos, JS Duncan, B Van Ginneken, ...
Proceedings of the IEEE 109 (5), 820-838, 2021
Super-resolution in medical imaging
H Greenspan
The computer journal 52 (1), 43-63, 2009
An efficient image similarity measure based on approximations of KL-divergence between two Gaussian mixtures
Goldberger, Greenspan
Proceedings Ninth IEEE International conference on computer vision, 487-493 …, 2003
Content-based image retrieval in radiology: current status and future directions
CB Akgül, DL Rubin, S Napel, CF Beaulieu, H Greenspan, B Acar
Journal of digital imaging 24, 208-222, 2011
Chest pathology detection using deep learning with non-medical training
Y Bar, I Diamant, L Wolf, S Lieberman, E Konen, H Greenspan
2015 IEEE 12th international symposium on biomedical imaging (ISBI), 294-297, 2015
Region-based image querying
C Carson, S Belongie, H Greenspan, J Malik
1997 Proceedings IEEE Workshop on Content-Based Access of Image and Video …, 1997
Convolutional neural networks for radiologic images: a radiologist’s guide
S Soffer, A Ben-Cohen, O Shimon, MM Amitai, H Greenspan, E Klang
Radiology 290 (3), 590-606, 2019
Deep learning with non-medical training used for chest pathology identification
Y Bar, I Diamant, L Wolf, H Greenspan
Medical Imaging 2015: Computer-Aided Diagnosis 9414, 215-221, 2015
Content-based image retrieval in medical applications
TM Lehmann, MO Güld, C Thies, B Fischer, K Spitzer, D Keysers, H Ney, ...
Methods of information in medicine 43 (04), 354-361, 2004
Image enhancement by nonlinear extrapolation in frequency space
H Greenspan, CH Anderson, S Akber
IEEE Transactions on Image Processing 9 (6), 1035-1048, 2000
Overcomplete steerable pyramid filters and rotation invariance
Greenspan, Belongie, Perona, Rakshit
1994 Proceedings of IEEE Conference on Computer Vision and Pattern …, 1994
MRI inter-slice reconstruction using super-resolution
H Greenspan, G Oz, N Kiryati, S Peled
Magnetic resonance imaging 20 (5), 437-446, 2002
The system can't perform the operation now. Try again later.
Articles 1–20