Computational MR Imaging in the AI Era
Magnetic Resonance Imaging (MRI) is undergoing a paradigm shift driven by advances in computational techniques and artificial intelligence. This talk will introduce the challenges and opportunities in the area of medical imaging. It will then explore the evolving landscape of computational MRI, where physics-based modeling, signal processing, and machine learning converge to accelerate acquisition, enhance image quality, and enable new diagnostic capabilities. It will start with supervised machine learning approaches, followed by new advances in generative artificial intelligence tools.
Date and Time
Location
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Registration
- Date: 03 Jun 2025
- Time: 11:00 PM UTC to 12:30 AM UTC
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- Starts 17 May 2025 02:59 PM UTC
- Ends 03 June 2025 10:00 PM UTC
- No Admission Charge
Speakers
Dr. Mathews Jacob of University of Virginia
Biography:
Mathews Jacob is a Professor in the Department of Electrical and Computer Engineering at the University of Virginia. His research interests lie in computational medical imaging, with a focus on the intersection of physics-based modeling and machine learning. He received his Ph.D. from the Swiss Federal Institute of Technology and was a Beckman Postdoctoral Fellow at the University of Illinois at Urbana-Champaign. He is the recipient of the NSF CAREER Award, the Research Scholar Award from the American Cancer Society, the Faculty Excellence Award for Research from the University of Iowa, and three IEEE best conference paper awards. He also has served as the general chair of the IEEE International Symposium on Biomedical Imaging in 2020. He is also a Fellow of the IEEE and is a Distinguished Lecturer of the IEEE Signal Processing Society.
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Agenda
7:00 PM - Welcome and Introductions
7:10 PM - Presentation Begins
8:10 PM - Q&A
8:30 PM - Finish
Media
| Pointer to Presentation Slides | This PDF contains a URL that links to the 110 MB slide deck used in the presentation. | 1.99 MiB |