  Diffusion model is the most advanced method in image generation and has been
successfully applied to MRI reconstruction. However, the existing methods do
not consider the characteristics of multi-coil acquisition of MRI data.
Therefore, we give a new diffusion model, called SPIRiT-Diffusion, based on the
SPIRiT iterative reconstruction algorithm. Specifically, SPIRiT-Diffusion
characterizes the prior distribution of coil-by-coil images by score matching
and characterizes the k-space redundant prior between coils based on
self-consistency. With sufficient prior constraint utilized, we achieve
superior reconstruction results on the joint Intracranial and Carotid Vessel
Wall imaging dataset.
