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Dong Liang

7 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • last author5

Across the 6 of 7 papers where every author was matched, so the position is known.

fields
  • eess.IV4
  • cs.CV2
  • cs.LG1
ORCID 0000-0001-6257-0875
same name
  • Dong Liang — 14 papers, h 10
  • Dong Liang — 10 papers, h 3
  • Dong Liang — 7 papers, h 3
  • Dong Liang — 5 papers, h 17
  • Dong Liang — 5 papers, h 2
  • Dong Liang — 5 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20202022
most citedSelf-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction

17 citations · 27 across the 7 of their papers we have counts for

collaborators
Showing eess.IVShow all

4 papers · 1 filter

eess.IV2022★ 17 cited

Self-Score: Self-Supervised Learning on Score-Based Models for MRI Reconstruction

Zhuo-Xu Cui, Chentao Cao, Shaonan Liu +5

Recently, score-based diffusion models have shown satisfactory performance in MRI reconstruction. Most of these methods require a large amount of fully sampled MRI data as a traini…

eess.IV2022★ 2 cited

One-shot Generative Prior in Hankel-k-space for Parallel Imaging Reconstruction

Hong Peng, Chen Jiang, Jing Cheng +4

Magnetic resonance imaging serves as an essential tool for clinical diagnosis. However, it suffers from a long acquisition time. The utilization of deep learning, especially the de…

eess.IV2021★ 1 cited

Deep Manifold Learning for Dynamic MR Imaging

Ziwen Ke, Zhuo-Xu Cui, Wenqi Huang +8

Purpose: To develop a deep learning method on a nonlinear manifold to explore the temporal redundancy of dynamic signals to reconstruct cardiac MRI data from highly undersampled me…

eess.IV2020★ 2 cited

Deep Low-rank Prior in Dynamic MR Imaging

Ziwen Ke, Wenqi Huang, Jing Cheng +8

The deep learning methods have achieved attractive performance in dynamic MR cine imaging. However, all of these methods are only driven by the sparse prior of MR images, while the…

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