World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
45
Citations
8150
World Ranking
7211
National Ranking
955

Overview

Dong Liang is affiliated with the Chinese Academy of Sciences in China. Their research primarily focuses on the fields of medicine and engineering, with a significant emphasis on radiology, nuclear medicine, and imaging. The subfields most associated with their work include computer vision and pattern recognition, biomedical engineering, radiation, and computational mechanics.

The main topics covered in Dong Liang's research include medical imaging techniques and applications, advanced MRI techniques and applications, advanced X-ray and CT imaging, radiomics and machine learning in medical imaging, sparse and compressive sensing techniques, advanced neuroimaging techniques and applications, and medical image segmentation techniques.

Dong Liang has a substantial body of published works, with frequent publication venues highlighting their contributions. These venues include arXiv (Cornell University), Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition, IEEE Transactions on Medical Imaging, IEEE Transactions on Radiation and Plasma Medical Sciences, and Quantitative Imaging in Medicine and Surgery.

Among a selection of recent papers authored or co-authored by Dong Liang are:

  • Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks, 2020, IEEE Signal Processing Magazine
  • DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution, 2020, Magnetic Resonance Imaging
  • DPIR-Net: Direct PET Image Reconstruction Based on the Wasserstein Generative Adversarial Network, 2020, IEEE Transactions on Radiation and Plasma Medical Sciences
  • Domain generalization on medical imaging classification using episodic training with task augmentation, 2021, Computers in Biology and Medicine
  • CaGAN: A Cycle-Consistent Generative Adversarial Network With Attention for Low-Dose CT Imaging, 2020, IEEE Transactions on Computational Imaging

Collaborations have been an important part of their research output. Frequent co-authors include Hairong Zheng, Yanjie Zhu, Zhuo-Xu Cui, Zhanli Hu, and Jing Cheng.

Best Publications

  • Accelerating magnetic resonance imaging via deep learning

    Shanshan Wang;Zhenghang Su;Leslie Ying;Xi Peng

  • Accelerating SENSE using compressed sensing.

    Dong Liang;Bo Liu;Bo Liu;JiunJie Wang;Leslie Ying

  • Deep Magnetic Resonance Image Reconstruction: Inverse Problems Meet Neural Networks

    Dong Liang;Jing Cheng;Ziwen Ke;Leslie Ying

  • Deep Learning vs. Radiomics for Predicting Axillary Lymph Node Metastasis of Breast Cancer Using Ultrasound Images: Don't Forget the Peritumoral Region.

    Qiuchang Sun;Xiaona Lin;Yuanshen Zhao;Ling Li

  • DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution

    Shanshan Wang;Huitao Cheng;Leslie Ying;Taohui Xiao

  • A 3D densely connected convolution neural network with connection-wise attention mechanism for Alzheimer's disease classification.

    Jie Zhang;Bowen Zheng;Ang Gao;Xin Feng

  • DIMENSION: Dynamic MR imaging with both k‐space and spatial prior knowledge obtained via multi‐supervised network training

    Shanshan Wang;Ziwen Ke;Huitao Cheng;Sen Jia

  • Motion Tracking of the Carotid Artery Wall From Ultrasound Image Sequences: a Nonlinear State-Space Approach

    Zhifan Gao;Yanjie Li;Yuanyuan Sun;Jiayuan Yang

  • Adaptive Dictionary Learning in Sparse Gradient Domain for Image Recovery

    Qiegen Liu;Shanshan Wang;Leslie Ying;Xi Peng

  • k-t ISD: Dynamic cardiac MR imaging using compressed sensing with iterative support detection

    Dong Liang;Edward V R DiBella;Rong Rong Chen;Leslie Ying

  • Nonlinear GRAPPA: A kernel approach to parallel MRI reconstruction

    Yuchou Chang;Dong Liang;Leslie Ying

  • Sensitivity encoding reconstruction with nonlocal total variation regularization.

    Dong Liang;Haifeng Wang;Yuchou Chang;Leslie Ying

  • A facial expression recognition system based on supervised locally linear embedding

    Dong Liang;Jie Yang;Zhonglong Zheng;Yuchou Chang

  • Single-shot T2 mapping using overlapping-echo detachment planar imaging and a deep convolutional neural network.

    Congbo Cai;Chao Wang;Yiqing Zeng;Shuhui Cai

  • Compressed-sensing photoacoustic computed tomography in vivo with partially known support

    Jing Meng;Lihong V. Wang;Leslie Ying;Dong Liang

  • Artifact correction in low-dose dental CT imaging using Wasserstein generative adversarial networks.

    Zhanli Hu;Changhui Jiang;Fengyi Sun;Qiyang Zhang

  • Multiregional radiomics profiling from multiparametric MRI: Identifying an imaging predictor of IDH1 mutation status in glioblastoma.

    Zhi-Cheng Li;Hongmin Bai;Qiuchang Sun;Yuanshen Zhao

  • A Kernel-Based Low-Rank (KLR) Model for Low-Dimensional Manifold Recovery in Highly Accelerated Dynamic MRI

    Ukash Nakarmi;Yanhua Wang;Jingyuan Lyu;Dong Liang

  • DPIR-Net: Direct PET Image Reconstruction Based on the Wasserstein Generative Adversarial Network

    Zhanli Hu;Hengzhi Xue;Qiyang Zhang;Juan Gao

  • Highly Undersampled Magnetic Resonance Image Reconstruction Using Two-Level Bregman Method With Dictionary Updating

    Qiegen Liu;Shanshan Wang;Kun Yang;Jianhua Luo

  • DeepcomplexMRI: Exploiting deep residual network for fast parallel MR imaging with complex convolution

    Shanshan Wang;Huitao Cheng;Leslie Ying;Taohui Xiao

Frequent Co-Authors

Hairong Zheng
Hairong Zheng Chinese Academy of Sciences
Xin Liu
Xin Liu Chinese Academy of Sciences
Leslie Ying
Leslie Ying University at Buffalo, State University of New York
Xi Peng
Xi Peng Sichuan University
Lei Zhang
Lei Zhang Hong Kong Polytechnic University
Yuan-Ting Zhang
Yuan-Ting Zhang City University of Hong Kong
Qiang He
Qiang He Swinburne University of Technology
Edmund Y. Lam
Edmund Y. Lam University of Hong Kong
Xinghao Ding
Xinghao Ding Xiamen University
Jie Yang
Jie Yang RMIT University

If you think any of the details on this page are incorrect, let us know.

Report an issue

We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below:

Related Online Degrees & Career Pathways

Exploring computer science education in the USA offers a variety of flexible options for students with different backgrounds and academic achievements. For those concerned about admission requirements, there are universities for low gpa that provide access to quality online degrees, removing barriers for many prospective learners.

If you’re interested in fast-tracking your CS education, consider enrolling in an online computer science degree that’s designed to help you graduate more quickly. This is ideal for those looking to transition into the job market or pivot careers efficiently.

Many students are also exploring interdisciplinary or related fields. For example, environmental science remains a popular alternative, with a wide range of potential jobs. Discover what jobs can you get with an environmental science degree if you are interested in combining technology with environmental impact.

Budget-conscious learners can find reputable programs among the cheapest online environmental science degree offerings, making a STEM education accessible to more people. These flexible and affordable programs open doors to a range of rewarding career pathways in technology and beyond.

Best Scientists Citing Dong Liang

Trending Scientists