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Abstract #4050

Voxel-wise Temporal Attention Network and Simulation-Driven Dynamic MRI Sequence Reconstruction

Shouchang Guo1, Jeffrey A. Fessler1, and Douglas C. Noll2
1Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI, United States, 2Biomedical Engineering, University of Michigan, Ann Arbor, MI, United States


Inspired by two open questions of dynamic MRI reconstruction, we propose a novel voxel-wise attention network for temporal modeling for the undersampled reconstruction. The voxel-wise design of the network enables voxel-wise training, and we further propose a two-stage training scheme that pretrains the network with voxel-wise simulated data when dynamics are easy to obtain with physical models. With a factor of 12 undersampling, our proposed model outperforms other reconstructions with higher PSNR and better fMRI performance.

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