Keywords: MR Fingerprinting/Synthetic MR, Cardiovascular, Quantitative ImagingThis work introduces a self-supervised deep learning reconstruction for cine Magnetic Resonance Fingerprinting, allowing for simultaneous cardiac phase-resolved T1, T2, and M0 mapping (without motion correction or averaging of data across different phases) and bright-blood and dark-blood cine imaging during a 10-second breathhold, with a temporal resolution (24 phases) comparable to standard cine imaging. Results are presented in simulations using the XCAT phantom and in healthy subjects, where the proposed reconstruction yielded reduced noise, undersampling artifacts, and motion blurring compared to previous low-rank and motion-corrected methods.
How to access this content:
For one year after publication, abstracts and videos are only open to registrants of this annual meeting. Registrants should use their existing login information. Non-registrant access can be purchased via the ISMRM E-Library.
After one year, current ISMRM & ISMRT members get free access to both the abstracts and videos. Non-members and non-registrants must purchase access via the ISMRM E-Library.
After two years, the meeting proceedings (abstracts) are opened to the public and require no login information. Videos remain behind password for access by members, registrants and E-Library customers.
Keywords