People

Maryellen L. Giger, PhD

  • A.N. Pritzker Professor of Radiology
    Committee on Medical Physics
  • Research and Scholarly Interests: computer-aided diagnosis, machine learning, breast cancer, deep learning, quantitative image analysi
  • Websites: Research Network Profile
  • Contact: l332@uchicago.edu
  • Graduate Program: Medical Physics

Maryellen L. Giger, Ph.D. is the A.N. Pritzker 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.



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 was 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, and IEEE, a recipient of the EMBS Academic Career Achievement Award, and is a current 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 200 peer-reviewed publications (over 300 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 is a cofounder, equity holder, and scientific advisor of Quantitative Insights, Inc., which started through the 2009-2010 New Venture Challenge at the University of Chicago. QI produces QuantX, 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.

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

Radiomics methodology for breast cancer diagnosis using multiparametric magnetic resonance imaging.
Hu Q, Whitney HM, Giger ML. Radiomics methodology for breast cancer diagnosis using multiparametric magnetic resonance imaging. J Med Imaging (Bellingham). 2020 Jul; 7(4):044502.
PMID: 32864390

A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI.
Hu Q, Whitney HM, Giger ML. A deep learning methodology for improved breast cancer diagnosis using multiparametric MRI. Sci Rep. 2020 Jun 29; 10(1):10536.
PMID: 32601367

Harmonization of radiomic features of breast lesions across international DCE-MRI datasets.
Whitney HM, Li H, Ji Y, Liu P, Giger ML. Harmonization of radiomic features of breast lesions across international DCE-MRI datasets. J Med Imaging (Bellingham). 2020 Jan; 7(1):012707.
PMID: 32206682

Deep convolutional neural networks in the classification of dual-energy thoracic radiographic views for efficient workflow: analysis on over 6500 clinical radiographs.
Crosby J, Rhines T, Li F, MacMahon H, Giger M. Deep convolutional neural networks in the classification of dual-energy thoracic radiographic views for efficient workflow: analysis on over 6500 clinical radiographs. J Med Imaging (Bellingham). 2020 Jan; 7(1):016501.
PMID: 32042858

Artificial Intelligence: reshaping the practice of radiological sciences in the 21st century.
El Naqa I, Haider MA, Giger ML, Ten Haken RK. Artificial Intelligence: reshaping the practice of radiological sciences in the 21st century. Br J Radiol. 2020 Feb 01; 93(1106):20190855.
PMID: 31965813

Integrating structured abstracts in the Journal of Medical Imaging.
Giger M. Integrating structured abstracts in the Journal of Medical Imaging. J Med Imaging (Bellingham). 2020 Jan; 7(1):010101.
PMID: 31930155

Tailoring steroids in the treatment of COVID-19 pneumonia assisted by CT scans: three case reports.
Su Y, Han Y, Liu J, Qiu Y, Tan Q, Zhou Z, Yu YZ, Chen J, Giger ML, Lure FYM, Luo Z. Tailoring steroids in the treatment of COVID-19 pneumonia assisted by CT scans: three case reports. J Xray Sci Technol. 2020; 28(5):885-892.
PMID: 32675436

Breast MRI radiomics for the pretreatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients.
Drukker K, Edwards A, Doyle C, Papaioannou J, Kulkarni K, Giger ML. Breast MRI radiomics for the pretreatment prediction of response to neoadjuvant chemotherapy in node-positive breast cancer patients. J Med Imaging (Bellingham). 2019 Jul; 6(3):034502.
PMID: 31592438

Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution.
Ji Y, Li H, Edwards AV, Papaioannou J, Ma W, Liu P, Giger ML. Independent validation of machine learning in diagnosing breast Cancer on magnetic resonance imaging within a single institution. Cancer Imaging. 2019 Sep 18; 19(1):64.
PMID: 31533838

Artificial intelligence in the interpretation of breast cancer on MRI.
Sheth D, Giger ML. Artificial intelligence in the interpretation of breast cancer on MRI. J Magn Reson Imaging. 2020 05; 51(5):1310-1324.
PMID: 31343790

View All Publications

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