no code implementations • 26 Jul 2021 • Noa Cahan, Edith M. Marom, Shelly Soffer, Yiftach Barash, Eli Konen, Eyal Klang, Hayit Greenspan
We developed a weakly supervised deep learning algorithm, with an emphasis on a novel attention mechanism, to automatically classify RV strain on CTPA.
no code implementations • 3 Mar 2018 • Maayan Frid-Adar, Idit Diamant, Eyal Klang, Michal Amitai, Jacob Goldberger, Hayit Greenspan
Then we present a novel scheme for liver lesion classification using CNN.
no code implementations • 21 Feb 2018 • Avi Ben-Cohen, Eyal Klang, Stephen P. Raskin, Shelly Soffer, Simona Ben-Haim, Eli Konen, Michal Marianne Amitai, Hayit Greenspan
Quantitative evaluation was conducted using an existing lesion detection software, combining the synthesized PET as a false positive reduction layer for the detection of malignant lesions in the liver.
no code implementations • 8 Jan 2018 • Maayan Frid-Adar, Eyal Klang, Michal Amitai, Jacob Goldberger, Hayit Greenspan
In this paper, we present a data augmentation method that generates synthetic medical images using Generative Adversarial Networks (GANs).
no code implementations • 7 Jan 2018 • Avi Ben-Cohen, Eyal Klang, Michal Marianne Amitai, Jacob Goldberger, Hayit Greenspan
In this work we propose a method for anatomical data augmentation that is based on using slices of computed tomography (CT) examinations that are adjacent to labeled slices as another resource of labeled data for training the network.
no code implementations • 30 Jul 2017 • Avi Ben-Cohen, Eyal Klang, Stephen P. Raskin, Michal Marianne Amitai, Hayit Greenspan
In this work we present a novel system for PET estimation using CT scans.
no code implementations • 19 Jul 2017 • Maayan Frid-Adar, Idit Diamant, Eyal Klang, Michal Amitai, Jacob Goldberger, Hayit Greenspan
Automatic detection of liver lesions in CT images poses a great challenge for researchers.