Journal
World Journal of Cardiology
Publication Date
7-26-2025
Volume
17
Issue
7
First Page
108745
Last Page
108745
Document Type
Open Access Publication
DOI
10.4330/wjc.v17.i7.108745
Rights and Permissions
Wang H, Schmieder A, Watkins M, Wang P, Mitchell J, Qamer SZ, Lanza G. Artificial intelligence-assisted compressed sensing CINE enhances the workflow of cardiac magnetic resonance in challenging patients. World J Cardiol. 2025 Jul 26;17(7):108745. doi: 10.4330/wjc.v17.i7.108745 This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Recommended Citation
Wang, Huaijun; Schmieder, Anne; Watkins, Mary; Wang, Pengjun; Mitchell, Joshua; Qamer, S Zyad; and Lanza, Gregory, "Artificial intelligence-assisted compressed sensing CINE enhances the workflow of cardiac magnetic resonance in challenging patients." World Journal of Cardiology. 17, 7. 108745 - 108745. (2025).
https://digitalcommons.wustl.edu/oa_4/5169
Department
ICTS (Institute of Clinical and Translational Sciences)
Additional Links
Supplemental material is available for this article at publisher site.
