Samuel G. Armato

Samuel Armato is a medical physicist and cancer imaging researcher who created the Lung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI), the most widely used public dataset for lung nodule detection AI research. This carefully annotated CT dataset of lung nodules with radiologist consensus markings has been used to train and validate hundreds of AI algorithms for lung cancer detection and has accelerated the field of computer-aided diagnosis. Armato has contributed extensively to evaluation methodology for AI in radiology, including observer performance analysis and free-response ROC methods critical for validation of cancer detection systems.