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Presenting on "Objective Assessment of Medical Image Quality – Does AI change our paradigm?"


Kyle J. Myers, PhD, Frank C. P. and Grace C. Yin Distinguished Lecturer in Biomedical Engineering, will speak at 1:15 p.m. CST on Monday, May 2, 2022 in Whitaker 100. 


Abstract: Image Science provides a framework for the objective task-based assessment of image quality. This framework has been used to support the evaluation of medical imaging devices by the US FDA, with examples including the assessment of iterative reconstruction algorithms for computed tomography (CT) and their potential to reduce radiation dose to patients as well as display systems optimized for specific tasks. Deep learning (DL) methods are increasingly being investigated as possible tools for supporting more efficient imaging, that is, a way to preserve image quality while further reducing radiation dose, imaging contrast dose, imaging time, etc. FDA has already seen multiple DL product submissions for such applications as low-dose CT denoising and MR reconstruction in the presence of sparse data sets. My talk will describe the Image Science framework in general, give an overview of FDA’s regulatory pathways for medical imaging devices, discuss programs that support innovation and collaboration, and consider how computational modeling and database development efforts can address knowledge gaps that challenge the evaluation of newer AI-enabled medical imaging submissions.