About this Class

Join Dr. Maryellen L. Giger at the April NCI Imaging and Informatics Community Webinar for a discussion on the development, validation, database needs, and ultimate future implementation of artificial intelligence (AI) in the clinical radiology workflow, which will include case studies of breast cancer and COVID-19. AI in medical imaging involves research in task-based discovery, predictive modeling, and robust clinical translation. Quantitative radiomic analyses, an extension of computer-aided detection and computer-aided diagnosis methods, are yielding novel image-based tumor characteristics, (i.e., signatures that may ultimately contribute to the design of patient-specific cancer diagnostics and treatments). Beyond human-engineered features, deep convolutional neural networks (CNN) are being investigated in the diagnosis of disease through radiography, ultrasound, and MRIs. The method of extracting characteristic radiomic features of a lesion and/or background can be referred to as “virtual biopsies.” For radiologists, various AI methods are evolving with the potential to aid as second, concurrent, or primary autonomous readers. In addition, performance evaluations, as well as considerations of robustness and repeatability, are necessary to enable translation.