Deep learning‐based rapid image reconstruction and motion correction for high‐resolution cartesian first‐pass myocardial perfusion imaging at 3T
Junyu Wang,
Michael Salerno
Abstract:PurposeTo develop and evaluate a deep learning (DL) ‐based rapid image reconstruction and motion correction technique for high‐resolution Cartesian first‐pass myocardial perfusion imaging at 3T with whole‐heart coverage for both single‐slice (SS) and simultaneous multi‐slice (SMS) acquisitions.Methods3D physics‐driven unrolled network architectures were utilized for the reconstruction of high‐resolution Cartesian perfusion imaging. The SS and SMS multiband (MB) = 2 networks were trained from 135 slices from 20… Show more
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