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20222025
most citedT2LR-Net: An unrolling network learning transformed tensor low-rank prior for dynamic MR image reconstruction

11 citations · 15 across the 5 of their papers we have counts for

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3 papers · 1 filter

eess.IV2023

Deep unrolling Shrinkage Network for Dynamic MR imaging

Yinghao Zhang, Xiaodi Li, Weihang Li +1

Deep unrolling networks that utilize sparsity priors have achieved great success in dynamic magnetic resonance (MR) imaging. The convolutional neural network (CNN) is usually utili…

eess.IV2022★ 11 cited

T2LR-Net: An unrolling network learning transformed tensor low-rank prior for dynamic MR image reconstruction

Yinghao Zhang, Peng Li, Yue Hu

The tensor low-rank prior has attracted considerable attention in dynamic MR reconstruction. Tensor low-rank methods preserve the inherent high-dimensional structure of data, allow…

eess.IV2022

Dynamic MRI using Learned Transform-based Tensor Low-Rank Network (LTLR-Net)

Yinghao Zhang, Peng Li, Yue Hu

While low-rank matrix prior has been exploited in dynamic MR image reconstruction and has obtained satisfying performance, tensor low-rank models have recently emerged as powerful…