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Abstract #2979

Pixel-wise quantitative myocardial perfusion mapping with cloud based non-linear iterative reconstruction using Gadgetron framework

Hui Xue1, Sven Plein2, Amedeo Chiribiri3, and Peter Kellman1

1NHLBI, NIH, Bethesda, MD, United States, 2University of Leeds, Leeds, United Kingdom, 3King’s College London, London, United Kingdom

In this abstract, we present a solution to speed up the non-linear reconstruction for myocardial perfusion imaging and demonstrate its clinical usage through the Gadgetron cloud deployed at Microsoft Azure infrastructure. We also achieved pixel-wise myocardial blood flow mapping on the non-linearly reconstructed images, given the computing power on the cloud. All these processing steps were inline integrated on the clinical MR scanners. As a result, the proposed solution allows us to deploy non-linear perfusion imaging with quantitative flow mapping as a clinical application.

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