Mammograms save lives by detecting breast cancer early, except when they don’t. Breast cancer is the most common cancer among women, and the second leading cause of cancer death. But mammograms, the standard screening for the disease, miss one in five cancers, according to the U.S. National Cancer Institute. Or they may indicate cancer when it’s not there — a false positive — forcing women to endure needless procedures and anxiety.
“In 20 years of collecting (digital) mammograms, we know they don’t work the way they’re supposed to,” said Dr. Dexter Hadley, a professor of pediatrics, pathology, and laboratory medicine with the Institute for Computational Health Sciences at the University of California, San Francisco. Hadley, who is an engineer as well as a physician, is working to change that. He and his colleagues at UCSF are using GPU-accelerated deep learning to improve mammogram accuracy.
