This post was authored by Laura Kurtzman, senior public information representative with UCSF News.
Richly Annotated Training Data Vastly Improves Deep Learning Algorithm’s Accuracy
An algorithm developed by scientists at UC San Francisco and UC Berkeley did better than two out of four expert radiologists at finding tiny brain hemorrhages in head scans—an advance that one day may help doctors treat patients with traumatic brain injuries (TBI), strokes and aneurysms.
The continued increase in diagnostic imaging studies, including 3D imaging studies such as computed tomography (CT), means that radiologists are looking at thousands of images each day, searching for tiny abnormalities that can signal life-threatening emergencies. The number of images from each brain scan can be so large that on a busy day, radiologists may opt to scroll through some large 3D stacks of images…
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