no code implementations • 12 Jul 2021 • Or Bar-Shira, Ahuva Grubstein, Yael Rapson, Dror Suhami, Eli Atar, Keren Peri-Hanania, Ronnie Rosen, Yonina C. Eldar
This study demonstrates the feasibility of in vivo human super resolution, based on a clinical scanner, to increase US specificity for different breast lesions and promotes the use of US in the diagnosis of breast pathologies.
no code implementations • 3 Oct 2020 • Elisha Goldstein, Daphna Keidar, Daniel Yaron, Yair Shachar, Ayelet Blass, Leonid Charbinsky, Israel Aharony, Liza Lifshitz, Dimitri Lumelsky, Ziv Neeman, Matti Mizrachi, Majd Hajouj, Nethanel Eizenbach, Eyal Sela, Chedva S Weiss, Philip Levin, Ofer Benjaminov, Gil N Bachar, Shlomit Tamir, Yael Rapson, Dror Suhami, Amiel A Dror, Naama R Bogot, Ahuva Grubstein, Nogah Shabshin, Yishai M Elyada, Yonina C Eldar
The purpose of this study is to create and evaluate a machine learning model for diagnosis of COVID-19, and to provide a tool for searching for similar patients according to their X-ray scans.