Greenspan, Hayit

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2019) · arXiv

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

The Liver Tumor Segmentation Benchmark (LiTS)

Bilic, P., Christ, P., Li, H. B., Vorontsov, E., Ben-Cohen, A., Kaissis, G., Szeskin, A., Jacobs, C., Mamani, G. E. H., Chartrand, G., et al. (2023) · Medical Image Analysis

Medical Image Segmentation TechniquesBrain Tumor Detection and Classification

Cited by 1,412

Chest pathology detection using deep learning with non-medical training

Bar, Y., Diamant, I., Wolf, L., Lieberman, S., Konen, E., & Greenspan, H. (2015) · 2015 IEEE 12th International Symposium on Biomedical Imaging (ISBI)

COVID-19 diagnosis using AIRadiomics and Machine Learning in Medical Imaging

Cited by 392

Content-based image retrieval in radiology: current status and future directions

Akgül, C. B., Rubin, D. L., Napel, S., Beaulieu, C. F., Greenspan, H., & Acar, B. (2011) · Journal of Digital Imaging

Image Retrieval and Classification TechniquesRadiomics and Machine Learning in Medical Imaging

Cited by 388

Radimagenet: an open Radiologic deep learning research Dataset for effective transfer learning

Mei, X., Liu, Z., Robson, P. M., Marinelli, B., Huang, M., Doshi, A., Jacobi, A., Cao, C., Link, K. E., Yang, T., et al. (2022) · Radiology Artificial Intelligence

Artificial Intelligence in Healthcare and EducationDomain Adaptation and Few-Shot Learning

Cited by 341

Cross-modality synthesis from CT to PET using FCN and GAN networks for improved automated lesion detection

Ben-Cohen, A., Klang, E., Raskin, S. P., Soffer, S., Ben-Haim, S., Konen, E., Amitai, M. M., & Greenspan, H. (2019) · Engineering Applications of Artificial Intelligence

Medical Imaging Techniques and ApplicationsGenerative Adversarial Networks and Image Synthesis

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