Cancer Screening using Deep Learning

Sad but true: most of radiology is mind-numbing tedium. Radiologists review hundreds of mammograms searching for tiny lesions; they meticulously draw contours around the heart in cardiac MRIs to measure volumes; they rely on manual checklists and decision trees to characterize liver disease. These are repetitive, boring tasks. They take a huge amount of time, leading to large medical bills, and they cause radiologist fatigue, resulting in frequent errors or inconsistencies. Automated decision support, in which the all of the tedious tasks are automated by computerized algorithms, is the holy grail of radiological interpretation. Using the latest deep learning technology in an intelligent cloud platform, Arterys is bringing radiological decision support to hospitals worldwide. We describe one example of our technology, detecting lung nodules in the openly available LIDC lung cancer imaging data set, including our data processing and deep learning strategies.