In this pilot study, we aim to analyze MR Fingerprinting (MRF) signal using deep learning network to assess the performance of tissue classification in gliomas. A U-Net based convolutional neural network was trained to learn glioma grades based on the SVD-compressed fingerprint acquired using MRF. Based on data acquired from a 5-minute MRF scan, the method shows great potential to accurately classify glioma grades without the need of image registration and contrast administration.
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