Grace Gang, PhD

Assistant Research Professor

Office: Traylor 605
Lab: The Advanced Imaging Algorithms and Instrumentation Laboratory


PhD, Biomedical Engineering, University of Toronto, 2014
BASc, Engineering Science, University of Toronto, 2008

Research Interests

Dr. Gang’s research interests are in quantitative performance modeling and optimization of medical imaging systems. Topics include: (1) signal and noise propagation through image formation and post processing (e.g., linear and nonlinear reconstruction, machine learning processing), (2) relating image properties to diagnostic decisions made by human or machine observers based on statistical decision theory, and (3) novel system design and optimization guided by imaging science.

Publications Search

From Pub Med   |   Google Scholar Profile

Selected Publications

Gang GJ, Mao A, Wang W, Siewerdsen JH, Mathews A, Kawamoto S, Levinson R, and Stayman JW, “Dynamic Fluence Modulation in Computed Tomography using Multiple Aperture Devices”, Physics in medicine and biology, 64(10), 105024, (2019).

Gang GJ, Siewerdsen JH, and Stayman JW, “Task-Driven Optimization of Fluence Field and Regularization for Model-Based Iterative Reconstruction in Computed Tomography”, IEEE Transaction on Medical Imaging, 36(12), 2424-2435, (2017).

Gang GJ, Stayman JW, Zbijewski W, and Siewerdsen JH, “Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation,” Medical Physics, 41(8), 081902 (2014).

Gang GJ, Lee J, Stayman JW, Tward DJ, Zbijewski W, Prince JL, and Siewerdsen JH, “Analysis of Fourier-domain task-based detectability index in tomosynthesis and cone-beam CT in relation to human observer performance,” Med. Phys. 38(4): 1754 – 1768 (2011).

Gang GJ, Tward DJ, Lee J, and Siewerdsen JH, “Anatomical background and generalized detectability in tomosynthesis and cone-beam CT,” Med. Phys. 37(5): 1948-1965 (2010).