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arXiv · 1912.12259

Adaptive-CS-Net: FastMRI with Adaptive Intelligence

Nicola Pezzotti·Elwin de Weerdt·Sahar Yousefi·Mohamed S. Elmahdy·Jeroen van Gemert·Christophe Schülke·Mariya Doneva·Tim Nielsen·Sergey Kastryulin·Boudewijn P. F. Lelieveldt·Matthias J. P. van Osch·Marius Staring
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Abstract

Adaptive intelligence aims at empowering machine learning techniques with the extensive use of domain knowledge. In this work, we present the application of adaptive intelligence to accelerate MR acquisition. Starting from undersampled k-space data, an iterative learning-based reconstruction scheme inspired by compressed sensing theory is used to reconstruct the images. We adopt deep neural networks to refine and correct prior reconstruction assumptions given the training data. Our results show that an adaptive intelligence approach performs better than traditional methods as well as deep learning methods that do not take prior knowledge into account.

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Nicola Pezzotti, Elwin de Weerdt, Sahar Yousefi, Mohamed S. Elmahdy, Jeroen van Gemert, Christophe Schülke, Mariya Doneva, Tim Nielsen, Sergey Kastryulin, Boudewijn P. F. Lelieveldt, Matthias J. P. van Osch, Marius Staring. 2019-12-13. Adaptive-CS-Net: FastMRI with Adaptive Intelligence. https://arxiv.org/abs/1912.12259

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