56 citations · 118 across the 11 of their papers we have counts for
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eess.IV2021★ 1 cited
Learning-based Motion Artifact Removal Networks (LEARN) for Quantitative Mapping
Xiaojian Xu, Satya V. V. N. Kothapalli, Jiaming Liu +4
Purpose: To introduce two novel learning-based motion artifact removal networks (LEARN) for the estimation of quantitative motion- and -inhomogeneity-corrected maps…
eess.IV2021★ 33 cited
SGD-Net: Efficient Model-Based Deep Learning with Theoretical Guarantees
Jiaming Liu, Yu Sun, Weijie Gan +3
Deep unfolding networks have recently gained popularity in the context of solving imaging inverse problems. However, the computational and memory complexity of data-consistency lay…