Communications of the ACM
Computer Accurately Identifies and Delineates Breast Cancers on Digital Tissue Slides
A deep-learning computer network developed through research led by Case Western Reserve University was 100% accurate in determining whether invasive forms of breast cancer were present in whole biopsy slides.
Credit: Case Western Reserve University
Researchers at Case Western Reserve University have developed a deep-learning computer network which they say is 100% accurate in determining whether invasive forms of breast cancer were present in whole biopsy slides.
In addition, the researchers say the network correctly made the same determination in each individual pixel of the slide 97% of the time, rendering near-exact delineations of the tumors.
The researchers trained the deep-learning network on 400 biopsy images downloaded from multiple hospitals, and afterward they presented the network with 200 new images from the Cancer Genome Atlas and University Hospitals Cleveland Medical Center. Network training took about two weeks, and identifying the presence and exact location of cancer took about 20 to 25 minutes each.
"It will take time to get up to 20 years of practice and training of a pathologist to identify complex cases and mimics, such as adenosis," says Case Western professor Anant Madabushi.
From Case Western Reserve University
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