Keywords: Diffusion Reconstruction, AI/ML Image Reconstruction, Self-supervised learning, distortion correction
Motivation: Multi-shot Echo Planar Imaging (msEPI) for diffusion MRI captures detailed anatomy but suffers from phase inconsistencies and susceptibility-induced distortions.
Goal(s): To develop a zero-shot self-supervised reconstruction method that eliminates msEPI distortions using undersampled k-space data from single subject, without external datasets.
Approach: We present ZS-PRIME, the first zero-shot, high-fidelity framework for distortion-free msEPI reconstruction. ZS-PRIME leverages PRIME, a distortion-free multi-echo acquisition where the second echo, at lower resolution and acceleration, provides high-fidelity field maps. CNN-based k-space and image-space regularization ensure phase consistency and anatomical accuracy.
Results: ZS-PRIME outperforms existing methods, including PRIME with LORAKS regularization, delivering high-quality, distortion-free reconstructions, enhancing diffusion MRI fidelity.
Impact: ZS-PRIME combines advanced field map estimation (PRIME) with zero-shot self-supervised training, achieving distortion-free, high-resolution multi-shot diffusion MRI from undersampled data. This obviates the dependency on external training datasets, setting a new benchmark for efficient, high-fidelity diffusion 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