People

Maryellen L. Giger, PhD

  • A.N. Pritzker Distinguished Service Professor of Radiology
  • Research and Scholarly Interests: computer-aided diagnosis, machine learning, breast cancer, deep learning, radiomics, COVID-19
  • Websites: Research Network Profile
  • Contact: l332@uchicago.edu

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, and the SPIE Harrison H. Barrett Award in Medical Imaging, 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).



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

Specific in situ inflammatory states associate with progression to renal failure in lupus nephritis.
Abraham R, Durkee MS, Ai J, Veselits M, Casella G, Asano Y, Chang A, Ko K, Oshinsky C, Peninger E, Giger ML, Clark MR. Specific in situ inflammatory states associate with progression to renal failure in lupus nephritis. J Clin Invest. 2022 07 01; 132(13).
PMID: 35608910

Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset.
Li H, Whitney HM, Ji Y, Edwards A, Papaioannou J, Liu P, Giger ML. Impact of continuous learning on diagnostic breast MRI AI: evaluation on an independent clinical dataset. J Med Imaging (Bellingham). 2022 May; 9(3):034502.
PMID: 35685120

Performance metric curve analysis framework to assess impact of the decision variable threshold, disease prevalence, and dataset variability in two-class classification.
Whitney HM, Drukker K, Giger ML. Performance metric curve analysis framework to assess impact of the decision variable threshold, disease prevalence, and dataset variability in two-class classification. J Med Imaging (Bellingham). 2022 May; 9(3):035502.
PMID: 35656541

A machine-learning algorithm for distinguishing malignant from benign indeterminate thyroid nodules using ultrasound radiomic features.
Keutgen XM, Li H, Memeh K, Conn Busch J, Williams J, Lan L, Sarne D, Finnerty B, Angelos P, Fahey TJ, Giger ML. A machine-learning algorithm for distinguishing malignant from benign indeterminate thyroid nodules using ultrasound radiomic features. J Med Imaging (Bellingham). 2022 May; 9(3):034501.
PMID: 35692282

Comment on "Machine Learning for Early Detection of Hypoxic-Ischemic Brain Injury After Cardiac Arrest" Submitted by Noah Salomon Molinski et al.
Mansour A, Fuhrman JD, Goldenberg FD, Giger ML. Comment on "Machine Learning for Early Detection of Hypoxic-Ischemic Brain Injury After Cardiac Arrest" Submitted by Noah Salomon Molinski et al. Neurocrit Care. 2022 08; 37(1):365-366.
PMID: 35612784

SPIE Computer-Aided Diagnosis conference anniversary review.
Summers RM, Giger ML. SPIE Computer-Aided Diagnosis conference anniversary review. J Med Imaging (Bellingham). 2022 Feb; 9(Suppl 1):012208.
PMID: 35607354

Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration.
Treviño M, Birdsong G, Carrigan A, Choyke P, Drew T, Eckstein M, Fernandez A, Gallas BD, Giger M, Hewitt SM, Horowitz TS, Jiang YV, Kudrick B, Martinez-Conde S, Mitroff S, Nebeling L, Saltz J, Samuelson F, Seltzer SE, Shabestari B, Shankar L, Siegel E, Tilkin M, Trueblood JS, Van Dyke AL, Venkatesan AM, Whitney D, Wolfe JM. Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration. JNCI Cancer Spectr. 2022 01 05; 6(1).
PMID: 35699495

A review of explainable and interpretable AI with applications in COVID-19 imaging.
Fuhrman JD, Gorre N, Hu Q, Li H, El Naqa I, Giger ML. A review of explainable and interpretable AI with applications in COVID-19 imaging. Med Phys. 2022 Jan; 49(1):1-14.
PMID: 34796530

Machine Learning for Early Detection of Hypoxic-Ischemic Brain Injury After Cardiac Arrest.
Mansour A, Fuhrman JD, Ammar FE, Loggini A, Davis J, Lazaridis C, Kramer C, Goldenberg FD, Giger ML. Machine Learning for Early Detection of Hypoxic-Ischemic Brain Injury After Cardiac Arrest. Neurocrit Care. 2022 06; 36(3):974-982.
PMID: 34873672

Report from the RSNA COVID-19 Task Force: COVID-19 Impact on Academic Radiology Research-A Survey of Vice Chairs of Research.
Mossa-Basha M, Krupinski EA, Filippi CG, Sharpe RE, Giger M. Report from the RSNA COVID-19 Task Force: COVID-19 Impact on Academic Radiology Research-A Survey of Vice Chairs of Research. J Am Coll Radiol. 2022 02; 19(2 Pt A):304-309.
PMID: 34919832

View All Publications

Harrison H. Barrett Award in Medical Imaging
SPIE
2022

Fellow
Chinese Optical Society (COS)
2021

Directors' Award
SPIE
2021

Honored Educator Award
RSNA
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