Keywords: Heart, HeartReal-time cine CMR is an ECG-free free-breathing alternative for functionally assessing the heart. To achieve sufficient spatio-temporal resolutions, these require rapid imaging, e.g. compressed sensing (CS) with radial trajectories. However, at high accelerations, CS may suffer from residual aliasing and temporal blurring. Recently, deep learning (DL) reconstruction has gained immense interest for fast MRI. Yet, for free-breathing real-time cine, where subjects have different breathing and cardiac motion patterns, database learning of spatiotemporal correlations has been difficult. Here, we propose a physics-guided DL reconstruction trained in a subject-specific manner. Proposed method improves image quality compared to database-trained DL and conventional 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