Maryellen L. 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 is also the Vice-Chair of Radiology (Basic Science Research) and the immediate past Director of the CAMPEP-accredited Graduate Programs in Medical Physics/ Chair of the Committee on Medical Physics at the University.
For over 30 years, she has conducted research on computer-aided diagnosis, including computer vision, machine learning, and deep learning, in the areas of breast cancer, lung cancer, prostate cancer, lupus, and bone diseases, and now COVID-19.
Over her career, she has served on various NIH, DOD, and other funding agencies’ study sections, and is now a member of the NIBIB Advisory Council of NIH.
She is a former president of the American Association of Physicists in Medicine and a former president of the SPIE (the International Society of Optics and Photonics) and is the inaugural Editor-in-Chief of the SPIE Journal of Medical Imaging.
She is a member of the National Academy of Engineering (NAE) and was awarded the William D. Coolidge Gold Medal from the American Association of Physicists in Medicine, the highest award given by the AAPM. She is a Fellow of AAPM, AIMBE, SPIE, SBMR, IEEE, COS, and IAMBE, a recipient of the EMBS Academic Career Achievement Award, the SPIE Director's Award, the SPIE Harrison H. Barrett Award in Medical Imaging, the RSNA Honored Educator Award, and the RSNA Outstanding Researcher Award, and was a Hagler Institute Fellow at Texas A&M University. 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. In 2018, she received the iBIO iCON Innovator award.
She has more than 260 peer-reviewed publications (over 450 publications), has more than 30 patents and has mentored over 100 graduate students, residents, medical students, and undergraduate students.
Her research in computational image-based analyses of breast cancer for risk assessment, diagnosis, prognosis, and response to therapy has yielded various translated components, and she is now using these image-based phenotypes, i.e., these “virtual biopsies” in imaging genomics association studies for discovery.
She has now 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 NIH NIBIB-funded Medical Imaging and Data Resource Center (MIDRC; midrc.org).
She was a cofounder of Quantitative Insights, Inc., which started through the 2009-2010 New Venture Challenge at the University of Chicago. QI produced QuantX, which in 2017, became the first FDA-cleared, machine-learning-driven system to aid in cancer diagnosis (CADx). In 2019, QuantX was named one of TIME magazine's inventions of the year, and was bought by Qlarity Imaging.
University of Chicago
Chicago, IL
PhD - medical physics
1985
University of Exeter
Exeter, England
MSc - physics
1979
Illinois Benedictine College
Lisle, IL
BS - physics, math, health science
1978
Predicting intensive care need for COVID-19 patients using deep learning on chest radiography.
Predicting intensive care need for COVID-19 patients using deep learning on chest radiography. J Med Imaging (Bellingham). 2023 Jul; 10(4):044504.
PMID: 37608852
Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI.
Role of sureness in evaluating AI/CADx: Lesion-based repeatability of machine learning classification performance on breast MRI. Med Phys. 2023 Aug 21.
PMID: 37602841
Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons.
Longitudinal assessment of demographic representativeness in the Medical Imaging and Data Resource Center open data commons. J Med Imaging (Bellingham). 2023 Nov; 10(6):61105.
PMID: 37469387
Radiomic and deep learning characterization of breast parenchyma on full field digital mammograms and specimen radiographs: a pilot study of a potential cancer field effect.
Radiomic and deep learning characterization of breast parenchyma on full field digital mammograms and specimen radiographs: a pilot study of a potential cancer field effect. J Med Imaging (Bellingham). 2023 Jul; 10(4):044501.
PMID: 37426053
Machine learning with multimodal data for COVID-19.
Machine learning with multimodal data for COVID-19. Heliyon. 2023 Jul; 9(7):e17934.
PMID: 37483733
Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment.
Toward fairness in artificial intelligence for medical image analysis: identification and mitigation of potential biases in the roadmap from data collection to model deployment. J Med Imaging (Bellingham). 2023 Nov; 10(6):061104.
PMID: 37125409
Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk Prediction.
Temporal Machine Learning Analysis of Prior Mammograms for Breast Cancer Risk Prediction. Cancers (Basel). 2023 Apr 04; 15(7).
PMID: 37046802
MIDRC CRP10 AI interface-an integrated tool for exploring, testing and visualization of AI models.
MIDRC CRP10 AI interface-an integrated tool for exploring, testing and visualization of AI models. Phys Med Biol. 2023 03 23; 68(7).
PMID: 36716497
Patient-specific fetal radiation dosimetry for pregnant patients undergoing abdominal and pelvic CT imaging.
Patient-specific fetal radiation dosimetry for pregnant patients undergoing abdominal and pelvic CT imaging. Med Phys. 2023 Jun; 50(6):3801-3815.
PMID: 36799714
Evaluation of emphysema on thoracic low-dose CTs through attention-based multiple instance deep learning.
Evaluation of emphysema on thoracic low-dose CTs through attention-based multiple instance deep learning. Sci Rep. 2023 Jan 21; 13(1):1187.
PMID: 36681685
Harrison H. Barrett Award in Medical Imaging
SPIE
2022
Lifetime Achievement Award
SDAMPP (Society of Directors of Academic Medical Physics Programs)
2022
Honored Educator Award
RSNA
2022
Outstanding Researcher Award
RSNA
2022
Aunt Minnie Finalist for Most Influential Radiology Researcher
Aunt Minnie
2022
Fellow
Chinese Optical Society (COS)
2021
Directors' Award
SPIE
2021
Distinguished Investigator Award (senior faculty category)
BSD, University of Chicago
2021
Honored Educator Award
RSNA
2020
Lifetime Achievement Award
Upstate New York chapter of the AAPM (UNYAPM)
2020
Fellow
IAMBE (International Academy of Medical & Biological Engineering)
2019
Top 100 Inventions of 2019, for QuantX
TIME magazine
2019
Fellow
Society of Breast MRI (SBMR)
2018
Crain's Chicago Notable Women in Education
Crain's Chicago
2018
iCON Innovator Award
IBIO Institute
2018
Hagler Institute Fellow
Texas A & M University
2017 - 2020
Fellow
IEEE
2016
Academic Career Achievement Award
Engineering in Medicine and Biology Society (EMBS)
2016
Visionary Award
Benedictine University
2015
William D. Coolidge Gold Medal
American Association of Physicists in Medicine (AAPM)
2015
Distinguished Investigator
Academy of Radiology Research
2015
Fellow
SPIE
2014
Distinguished Science Alumni Award
Benedictine University
2014
Named by the International Congress on Medical Physics (ICMP) as one of the 50 medical physicists wi
2013
Elected National Academy of Engineering
National Academy of Engineering
2010
Excellence Award
University of Chicago Paul Hodges Alumni Society
2009
Distinguished Alumni Award
Benedictine University
2006
Senior Member
IEEE
2005
Third Vice President (Honorary)
RSNA
2005
Fellow
AAPM
2001
Fellow
AIMBE
2000
Stauffer Award, Academic Radiology
1995
Sylvia Sorkin Greenfield Award
AAPM
1995
First Place Award, Young Investigators' Symposium
AAPM
1985
B.S. summa cum laude
Illinois Benedictine College
1978
Procopian Award
Illinois Benedictine College
1978
Rotary International Fellowship
1978 - 1979
Rev. Shonka, O.S.B. Scholarship Award in Physics
Illinois Benedictine College
1977
President's Scholarship Award
Illinois Benedictine College
1975 - 1977