Maryellen L. Giger, PhD (University of Chicago) – AI+Science Schmidt Fellows Speaker Series

Organized by the University of Chicago’s Eric and Wendy Schmidt AI in Science Postdoctoral Fellowship Program.

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 neural networks 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.  This presentation will discuss some history, development, validation, database needs, and ultimate future implementation of AI in the clinical radiology workflow including examples from breast cancer and COVID-19, and the creation and benefits of MIDRC (midrc.org). 

Agenda
4:30pm – 5:15pm: Presentation
5:15pm – 5:30pm: Q&A
5:30pm – 6:00pm: Reception

Maryellen L. Giger, PhD:  Maryellen Giger, Ph.D. is the A.N. Pritzker Distinguished Service Professor of Radiology, Committee on
Medical Physics, and the College at the University of Chicago. She has been working, for decades, on computer-aided diagnosis/machine learning/deep learning in medical imaging for cancer, thoracic diseases, neuro-imaging, and other diseases diagnosis and management. Her AI research in cancer
(breast cancer, thyroid cancer) for risk assessment, diagnosis, prognosis, and therapeutic response has yielded various translated components, and she has used these “virtual biopsies” in imaging-genomics  association studies. She has extended her AI in medical imaging research to include the analysis of
COVID-19 on CT and chest radiographs, and is contact PI on the NIBIB-funded Medical Imaging and Data Resource Center (MIDRC; midrc.org), which has ingested more than 300,000 medical imaging studies, with currently more than 150,000 imaging studies publicly available for use by AI investigators. Giger has more than 280 peer-reviewed publications and has more than 30 patents, and has mentored over 100 graduate students, residents, medical students, and undergraduate students. Giger is a former president of AAPM and of SPIE; a past member of the NIBIB Advisory Council of NIH; and is the Editor-in-Chief of
the Journal of Medical Imaging. She is a member of the National Academy of Engineering (NAE), a
recipient of the AAPM William D. Coolidge Gold Medal, the SPIE Director’s Award, the SPIE Harrison H.
Barrett Award in Medical Imaging, the RSNA’s Honored Educator Award, and the RSNA’s Outstanding
Researcher Award, and is a Fellow of AAPM, AIMBE, SPIE, SBMR, IEEE, IAMBE, and COS. In 2013, Giger
was named by the International Congress on Medical Physics (ICMP) as one of the 50 medical physicists
with the most impact on the field in the last 50 years. Giger was cofounder of Quantitative Insights [now
Qlarity Imaging], which produced QuantX, the first FDA-cleared, machine-learning driven CADx (AI-
aided) system.

Meeting location
William Eckhardt Research Center. Room 401
5640 S Ellis Avenue, Chicago, IL 60637
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Parking
Campus North Parking
5505 S Ellis Ave
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