Accuracy, Uncertainty, and Adaptability of Automatic Myocardial ASL Segmentation using Deep CNN

10 Dec 2018Hung P. DoYi GuoAndrew J. YoonKrishna S. Nayak

PURPOSE: To apply deep CNN to the segmentation task in myocardial arterial spin labeled (ASL) perfusion imaging and to develop methods that measure uncertainty and that adapt the CNN model to a specific false positive vs. false negative tradeoff. METHODS: The Monte Carlo dropout (MCD) U-Net was trained on data from 22 subjects and tested on data from 6 heart transplant recipients... (read more)

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