For more details click here

Fully Convolutional Network and Sparsity-Based Dictionary Learning for Liver Lesion Detection in CT Examinations. Ben-Cohen, A., Klang, E., Kerpel, A., Konen, E., Amitai, M., Greenspan, H. (2017). Neurocomputing. (Link)

CT Image-based Decision Support System for Categorization of Liver Metastases Into Primary Cancer Sites. Ben-Cohen, A., Klang, E., Diamant, I., Rozendorn, N., Raskin, S.P., Konen, E., Amitai, M., & Greenspan, H. (2017). Academic Radiology.(Link)

Virtual PET Images from CT Data Using Deep Convolutional Networks: Initial Results. Ben-Cohen, A., Klang, E., Raskin, S.P., Amitai, M., & Greenspan, H. (2017). Simulation and Synthesis in Medical Imaging- MICCAI 2017. Springer.(PDF)

Fully Convolutional Network for Liver Segmentation and Lesions Detection. Ben-Cohen, A., Diamant, I., Klang, E., Amitai, M., & Greenspan, H. (2016). 2nd workshop on deep learning in medical image analysis- MICCAI 2016. Springer.(PDF)

Sparsity-based liver metastases detection using learned dictionaries. Ben-Cohen, A., Klang, E., Amitai, M., & Greenspan, H. (2016). ISBI 2016.(PDF)

Automatic detection and segmentation of liver metastatic lesions on serial CT examinations. Ben-Cohen, A., Diamant, I., Klang, E., Amitai, M., & Greenspan, H. (2014, March). In SPIE Medical Imaging proceedings.(PDF)

Automated method for detection and segmentation of liver metastatic lesions in follow-up CT examinations. Ben-Cohen, A., Klang, E., Diamant, I.,Rozendorn, N., Amitai, M., & Greenspan, H. (2015). SPIE Journal of Medical Imaging.