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Diffusion model is the most advanced method in image generation and has beensuccessfully applied to MRI reconstruction. However, the existing methods donot consider the characteristics of multi-coil acquisition of MRI data.Therefore, we give a new diffusion model, called SPIRiT-Diffusion, based on theSPIRiT iterative reconstruction algorithm. Specifically, SPIRiT-Diffusioncharacterizes the prior distribution of coil-by-coil images by score matchingand characterizes the k-space redundant prior between coils based onself-consistency. With sufficient prior constraint utilized, we achievesuperior reconstruction results on the joint Intracranial and Carotid VesselWall imaging dataset.

SPIRiT-Diffusion: SPIRiT-driven Score-Based Generative Modeling for Vessel Wall imaging