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. Author manuscript; available in PMC: 2021 Aug 28.
Published in final edited form as: Magn Reson Med. 2019 Aug 23;83(2):712–730. doi: 10.1002/mrm.27954

FIGURE 1.

FIGURE 1

Overview of the proposed workflow for automated inline perfusion flow mapping. After raw k-space data are reconstructed, resulting low resolution AIF and high-resolution perfusion images go through the MOCO step, which allows the free-breathing acquisition. The AIF image series was inputted to LV blood pool detection and resulting signals were corrected for T2* signal loss. The surface coil inhomogeneity was corrected by normalized perfusion series with PD images. Both T2* corrected AIF signal and normalized MOCO perfusion images are converted into [Gd] unit by a LUT conversion. Finally, AIF Gd curve and perfusion Gd images are inputted into flow mapping step for pixel-wise myocardial flow mapping