This abstract presents an AI powered system to perform automated quantitative perfusion flow mapping and analysis on the MR scanner. The key components consist of deep neural network models to a) detect LV on AIF image series and b) segment myocardium to generate AHA bull's eye plot. This solution was implemented in Gadgetron framework and has been deployed to clinical MR scanners. As a result, pixel-wise perfusion flow maps with segmentation of myocardium is automatically generated and available on the MR scanner shortly after the end of data acquisition.
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