Physics-based learning for MRI reconstruction - Recent advances in static and dynamic imaging

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• Kerstin Hammernik (Technical University of Munich)
• Tuesday 13 April 2021, 15:00-16:00
• https://bham-ac-uk.zoom.us/j/3900445385?pwd=Mk1LSmRiUk5STEJMWVl0bE82NTM1QT09.

If you have a question about this talk, please contact Hong Duong.

During the past years, deep learning has evolved tremendously in the research field of MR image reconstruction. In this talk, I will guide you through these developments, ranging from learning advanced image regularization to learning physics-based unrolled optimization, and I will discuss challenges and caveats of deep learning for image reconstruction. I will cover examples ranging from 2D musculoskeletal imaging to higher-dimensional cardiac imaging that will show the vast potential for the future of fast MR image acquisition and reconstruction.

This talk is part of the Data Science and Computational Statistics Seminar series.

This talk is included in these lists:

• Analysis Seminar
• Data Science and Computational Statistics Seminar
• School of Mathematics Events
• https://bham-ac-uk.zoom.us/j/3900445385?pwd=Mk1LSmRiUk5STEJMWVl0bE82NTM1QT09

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