Complex graph convolutional neural networks compared to GRAPPA for reconstruction of undersampled non-Cartesian MRSI
Paul Weiser1, Stanislav Motyka2, Wolfgang Bogner2, and Georg Langs1
1Computational Imaging Research Lab - Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria, 2High Field MR Center - Department of Biomedical Imaging and Image‐Guided Therapy, Medical University of Vienna, Vienna, Austria
In this work a Graph Neural Network for the reconstruction of undersampled k-space data is proposed. The results were evaluated and compared against a state-of-the-art method. Overall, the results suggest that this Deep Learning-based approach for reconstruction is promising.
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