Physics-based learning for MRI reconstruction - Recent advances in static and dynamic imaging, Kerstin Hammernik
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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 MR 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.