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Abstract #2744

Accelerating 3D-T1ρ cartilage imaging using signal compensated low-rank plus sparse matrix decomposition

Yuanyuan Liu1,2, Weitian Chen3, Xin Liu1, Hairong Zheng1, Dong Liang1,2, and Yanjie Zhu1
1Paul C. Lauterbur Research Center for Biomedical Imaging, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 2Research center for Medical AI, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China, 3Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Hong Kong, China

The quantitative 3D-T mapping requires multiple T-weighted images with different spin lock times (TSLs) to obtain the T map, which makes the acquisition time very long. In this work, a signal compensation strategy with low-rank plus sparse model (SCOPE) was used to reconstruct T-weighted images from highly undersampled data. We provide the reconstructed images and the estimated T maps at an acceleration factor up to 8.5 in fast 3D-T cartilage imaging.

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