Abstract #1058

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

Synopsis

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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