“Objective Assessment of Medical Image Quality – Does AI change our paradigm?”
Hosted by the Department of Biomedical Engineering (BME)
BME Day 2022! Please join us for student design presentations, and presentations on award-winning graduate student research, outreach and leadership that highlight the impact of WashU BME in 2021-2022. View BME 401 Senior Design Class project webpages here.
Schedule of Events:
Continental Breakfast
8:30-10:30 a.m. | Whitaker Hall Atrium
Register using link above
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TRACK 1:
Senior Design Group Poster Presentations (odd numbered groups)
9-10:30 a.m. | Whitaker Hall Atrium
Senior Design Group Poster Presentations (even numbered groups)
10:30 a.m.-12 p.m. | Whitaker Hall Atrium
TRACK 2:
PhD Student Award-Winning Presentations | 9:30-10:30 a.m.
PhD Leadership and Outreach Awards | 10:45-11:15 a.m.
Whitaker 100 and via Zoom
Register for Zoom link here
New Faculty Presentation: Ismael Seáñez
“Spinal cord neuromodulation for rehabilitation and studies in motor control”
11:15-11:45 a.m. | Whitaker 100 and via Zoom
Register for Zoom link here
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Lunch
12-1 p.m. | Whitaker Hall
Register using link above
Senior Design Award Presentation
1-1:15 p.m. | Whitaker 100
Frank C. P. and Grace C. Yin Distinguished Lecture: Kyle J. Myers
1:15-2 p.m. | Whitaker 100
For more information click here
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.
For inquiries contact Molly Olten.
