The subspace-based method, known as SPICE, is an emerging technique that achieves rapid high-resolution MRSI with good SNR. In SPICE, the spectrum at each voxel is represented as a low-dimensional subspace or manifold, where the basis functions or features are learned from training data. The spatial coefficients of the subspace model are estimated by fitting the model to the k-space data for image reconstruction. In this work, we propose to extend the SPICE framework by representing the spatial coefficients of the subspace model using deep image prior for improved image reconstruction.
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