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Machine Learning for Accelerated MR Image Reconstruction

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If you have a question about this talk, please contact Yury Korolev.

In the past years, we have seen enormous developments of learning-based image reconstruction to push the acceleration factor of MR acquisitions to new limits. In this talk, I provide an overview of how machine learning can be used for accelerated MR image reconstruction and discuss selected examples, including Variational Networks and Σ-net, in more detail. Finally, we discuss open challenges regarding training data and evaluation.

This talk is part of the Cambridge Image Analysis Seminars series.

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