Agenda of May 2, 2022 meeting


Machine Intelligence/Data Science in Medical Imaging of Breast Cancer and COVID-19 (Maryellen Giger, Ph.D, University of Chicago) Artificial Intelligence in medical imaging involves research in task-based discovery, predictive modeling, and robust clinical translation. Quantitative radiomic analyses, an extension of computer-aided detection (CADe) and computer-aided diagnosis (CADx) 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 on radiography, ultrasound, and MRI. The method of extracting characteristic radiomic features of a lesion and/or background can be referred to as “virtual biopsies”. Various AI methods are evolving as aids to radiologists as a second reader or a concurrent reader, or as a primary autonomous reader. In addition, performance evaluations, as well as considerations of robustness and repeatability, are necessary to enable translation. This presentation will discuss the development, validation, database needs, and ultimate future implementation of AI in the clinical radiology workflow including examples from breast cancer and COVID-19. In addition, aspects of MIDRC (midrc.org) will be discussed. TBD
IDC Update (Ulli Wagner)
TCIA Update (Justin Kirby, John Freymann)
Announcements

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