Meeting Banner
Abstract #4710

Rapid Image Reconstruction of Single-Shot Coronary Quiescent-Interval Slice-Selective (QISS) MRA and Late Gadolinium-Enhanced MRI using Deep Learning

Daming Shen1,2, Hassan Haji-Valizadeh1,2, and Daniel Kim1,2

1Biomedical Engineering, Northwestern University, Evanston, IL, United States, 2Radiology, Northwestern University, Chicago, IL, United States

While compressed sensing (CS) enables highly-accelerated cardiac MRI acquisitions, its lengthy image reconstruction may limit clinical translation. Deep learning (DL) is capable reconstructing undersampled images with clinically acceptable reconstruction times. The purpose of this study was to build, train, and validate a deep learning framework for rapidly reconstructing highly-accelerated cardiac MR images, where CS reconstructed images are used as reference.

This abstract and the presentation materials are available to members only; a login is required.

Join Here