Reconstruction of undersampled 3D non‐Cartesian image‐based navigators for coronary MRA using an unrolled deep learning model-Reference-Cited by-同舟云学术

Reconstruction of undersampled 3D non‐Cartesian image‐based navigators for coronary MRA using an unrolled deep learning model

Published:2020-02-03 Issue:2 Volume:84 Page:800-812
ISSN:0740-3194
Container-title:Magnetic Resonance in Medicine
language:en
Short-container-title:Magn Reson Med

Author:

Malavé Mario O.¹^ORCID,Baron Corey A.²^ORCID,Koundinyan Srivathsan P.¹^ORCID,Sandino Christopher M.¹^ORCID,Ong Frank¹,Cheng Joseph Y.¹³,Nishimura Dwight G.¹

Affiliation:

1. Magnetic Resonance Systems Research Laboratory, Department of Electrical Engineering Stanford University Stanford CA

2. Department of Medical Biophysics Western University London ON Canada

3. Department of Radiology Stanford University Stanford CA

Funder

NSF Graduate Research Fellowship Program

GE Healthcare

Publisher

Wiley

Subject

Radiology Nuclear Medicine and imaging

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrm.28177

Reference50 articles.

1. 3D image‐based navigators for coronary MR angiography

2. Free-breathing multiphase whole-heart coronary MR angiography using image-based navigators and three-dimensional cones imaging

3. Alternating repetition time balanced steady state free precession

4. Design and analysis of a practical 3D cones trajectory

5. Nonrigid Motion Correction With 3D Image‐Based Navigators for Coronary MR Angiography

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