SPIC-SSDU adds a sparse parallel-imaging consistency term to the MM-SSDU loss, improving artifact and noise reduction in self-supervised MRI reconstruction at acceleration rates 6 and 8.
Our key innovation involves augmenting the MM-SSDU loss, as defined in (4), with a novel consistency term, which we refer to as sparse parallel imaging consistency
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Sparsity-Driven Parallel Imaging Consistency for Improved Self-Supervised MRI Reconstruction
SPIC-SSDU adds a sparse parallel-imaging consistency term to the MM-SSDU loss, improving artifact and noise reduction in self-supervised MRI reconstruction at acceleration rates 6 and 8.