Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T.

Journal: Magnetic resonance in medicine

Published Date: Apr 4, 2024

Abstract

PURPOSE: To 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.

Authors

Junyu Wang

Department of Biomedical Engineering, University of Virginia, Charlottesville, Virginia, USA.
Michael Salerno

Department of Medicine, University of Virginia, Charlottesville, VA, USA.

Keywords

Adult Algorithms Artifacts Deep Learning Female Heart Humans Image Processing, Computer-Assisted Imaging, Three-Dimensional Male Motion Myocardial Perfusion Imaging Prospective Studies Signal-To-Noise Ratio

External Resources

View on PubMed Access via DOI PubMed (38576068)

Deep learning-based rapid image reconstruction and motion correction for high-resolution cartesian first-pass myocardial perfusion imaging at 3T.

Abstract

Authors

Keywords

External Resources

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