no code implementations • 29 Jun 2019 • Amir Bar, Michal Mauda, Yoni Turner, Michal Safadi, Eldad Elnekave
Head CT is one of the most commonly performed imaging studied in the Emergency Department setting and Intracranial hemorrhage (ICH) is among the most critical and timesensitive findings to be detected on Head CT. We present BloodNet, a deep learning architecture designed for optimal triaging of Head CTs, with the goal of decreasing the time from CT acquisition to accurate ICH detection.