Spatiotemporal Diffusion Model with Paired Sampling for Accelerated Cardiac Cine MRI

• URL: http://arxiv.org/abs/2403.08758v1
• Date: Wed, 13 Mar 2024 17:56:12 GMT
• Title: Spatiotemporal Diffusion Model with Paired Sampling for Accelerated Cardiac Cine MRI
• Authors: Shihan Qiu, Shaoyan Pan, Yikang Liu, Lin Zhao, Jian Xu, Qi Liu, Terrence Chen, Eric Z. Chen, Xiao Chen, Shanhui Sun
• Abstract summary: Current deep learning reconstruction for accelerated MRI suffers from spatial and temporal blurring. A paired sampling strategy substantially reduced artificial noises in the generative results.
• Score: 20.86718191599198
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Current deep learning reconstruction for accelerated cardiac cine MRI suffers from spatial and temporal blurring. We aim to improve image sharpness and motion delineation for cine MRI under high undersampling rates. A spatiotemporal diffusion enhancement model conditional on an existing deep learning reconstruction along with a novel paired sampling strategy was developed. The diffusion model provided sharper tissue boundaries and clearer motion than the original reconstruction in experts evaluation on clinical data. The innovative paired sampling strategy substantially reduced artificial noises in the generative results.

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