Keywords: Sparse & Low-Rank Models, Perfusion, First-pass myocardial perfusion; structured low-rank
Motivation: First-pass myocardial perfusion imaging is a powerful tool for assessing coronary artery disease, but needs high levels of undersampling to achieve sufficient spatial coverage, spatiotemporal resolution, and motion robustness.
Goal(s): To develop efficient temporal image reconstruction models which can leverage linear time-invariant models of dynamic contrast enhancement without identifying an arterial input function or assuming tissue transfer function shapes.
Approach: We propose a novel temporal structured low-rank modeling technique to implicitly leverage linear time-invariant models of dynamic contrast enhancement.
Results: Temporal structured low-rank modeling outperforms conventional low-rank methods, especially as a local constraint.
Impact: Temporal structured low-rank modeling has the potential to improve spatial coverage, spatial resolution, and/or motion robustness for first-pass myocardial perfusion MRI.
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