Prof. Dong Liang Profile

Prof. Dong Liang

at Shenzhen Institutes of Advanced Technology CAS

SPIE Involvement:

Author

Publications (16)

Proceedings Article | 7 April 2023 Poster + Paper

Low-dose CT imaging performance of U-Net for varied spatial resolutions

Xin Zhang, Ting Su, Hairong Zheng, Dong Liang, Yongshuai Ge

Proceedings Volume 12463, 1246337 (2023) https://doi.org/10.1117/12.2654163

KEYWORDS: Computed tomography, Lawrencium, Spatial resolution, Image resolution, Education and training, X-ray computed tomography, Biomedical optics, Biological imaging, X-rays, Windows

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Proceedings Article | 7 April 2023 Poster + Paper

MMD-Net: multi-material decomposition network for high quality dual-energy CT imaging

Zisheng Li, Jiongtao Zhu, Ting Su, Dong Liang, Yongshuai Ge

Proceedings Volume 12463, 1246334 (2023) https://doi.org/10.1117/12.2654158

KEYWORDS: Attenuation, Iodine, Computed tomography, Bone, Neural networks, Education and training, X-rays, X-ray computed tomography, Convolution, Analytic models

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Proceedings Article | 4 April 2022 Poster + Paper

Multi-material decomposition in spectral CT with angular tube voltage modulation

Ting Su, Jiongtao Zhu, Jiecheng Yang, Dong Liang, Yongshuai Ge

Proceedings Volume 12031, 120312Q (2022) https://doi.org/10.1117/12.2611728

KEYWORDS: Modulation, X-ray computed tomography, Reconstruction algorithms, X-rays, Data acquisition, Spectral computed tomography

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Proceedings Article | 4 April 2022 Poster + Paper

Quantitative dual-energy CBCT imaging with deep triple-material decomposition

Jiongtao Zhu, Ting Su, Dong Liang, Yongshuai Ge

Proceedings Volume 12031, 1203123 (2022) https://doi.org/10.1117/12.2611698

KEYWORDS: Dual energy imaging, X-rays, Computed tomography, Reconstruction algorithms, Convolutional neural networks, Exact cone beam reconstruction

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Proceedings Article | 4 April 2022 Poster + Paper

Quantitative comparison of dual-energy CT and differential phase contrast CT imaging methods

Xin Zhang, Ting Su, Dongmei Xia, Dong Liang, Yongshuai Ge

Proceedings Volume 12031, 120313P (2022) https://doi.org/10.1117/12.2611688

KEYWORDS: X-ray computed tomography, Spatial resolution, X-rays, Imaging systems, Phase contrast, X-ray imaging, Dual energy imaging

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SPIE Journal Paper | 27 February 2021 Open Access

Accelerating 3D single-molecule localization microscopy using blind sparse inpainting

Sunil Kumar Gaire, Yanhua Wang, Hao Zhang, Dong Liang, Leslie Ying

JBO, Vol. 26, Issue 02, 026501, (February 2021) https://doi.org/10.1117/12.10.1117/1.JBO.26.2.026501

KEYWORDS: 3D image reconstruction, 3D image processing, 3D acquisition, Microscopy, Super resolution, Image processing, Stereoscopy, Image restoration, Computer simulations, Image resolution

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Proceedings Article | 16 March 2020 Paper

Low-dose CT reconstruction with simultaneous sinogram and image domain denoising by deep neural network

Jiongtao Zhu, Ting Su, Xiaolei Deng, Xindong Sun, Hairong Zheng, Dong Liang, Yongshuai Ge

Proceedings Volume 11312, 1131241 (2020) https://doi.org/10.1117/12.2547738

KEYWORDS: X-ray computed tomography, Denoising, Computed tomography, CT reconstruction, Neural networks, Reconstruction algorithms

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Proceedings Article | 16 March 2020 Paper

Dual-energy CT reconstruction using deep mutual-domain knowledge for basis decomposition and denoising

Yikun Zhang, Ting Su, Jiongtao Zhu, Yang Chen, Hairong Zheng, Dong Liang, Yongshuai Ge

Proceedings Volume 11312, 113124C (2020) https://doi.org/10.1117/12.2547736

KEYWORDS: X-ray computed tomography, CT reconstruction, Dual energy imaging

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Proceedings Article | 16 March 2020 Paper

Reducing the x-ray phase contrast image bias via deep computed signal estimation technique

Yifan Ni, Peizhen Liu, Jianwei Chen, Dong Liang, Jinchuan Guo, Yongshuai Ge

Proceedings Volume 11312, 113121E (2020) https://doi.org/10.1117/12.2547735

KEYWORDS: X-ray imaging, Phase contrast, Convolutional neural networks

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Proceedings Article | 16 March 2020 Paper

Generalized iterative sparse-view CT reconstruction with deep neural network

Ting Su, Xindong Sun, Xiaolei Deng, Hairong Zheng, Dong Liang, Yongshuai Ge

Proceedings Volume 11312, 1131207 (2020) https://doi.org/10.1117/12.2547739

KEYWORDS: Reconstruction algorithms, X-ray computed tomography, Computed tomography, CT reconstruction, Neural networks

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Proceedings Article | 6 May 2019 Paper

Image reconstruction in CT from limited-angle projections

Dou Li, Shanshan Wang, Zemin Cai, Dong Liang, Jianhua Luo

Proceedings Volume 11069, 1106916 (2019) https://doi.org/10.1117/12.2524246

KEYWORDS: Computed tomography, Signal to noise ratio, Image restoration, Data modeling, Fourier transforms, Reconstruction algorithms, Image processing, Image quality, Radon transform, Convolution

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Proceedings Article | 1 March 2019 Paper

Backproject-filter (BPF) CT image reconstruction using convolutional neural network

Qiyang Zhang, Jianwei Chen, Dong Liang, Yongshuai Ge

Proceedings Volume 10948, 1094854 (2019) https://doi.org/10.1117/12.2506454

KEYWORDS: Computed tomography, CT reconstruction, X-ray computed tomography, Convolutional neural networks, Reconstruction algorithms, Deconvolution, Fourier transforms, Spatial resolution, Image restoration, Sensors

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Proceedings Article | 1 March 2019 Paper

Wasserstein generative adversarial networks for motion artifact removal in dental CT imaging

Changhui Jiang, Qiyang Zhang, Yongshuai Ge, Dong Liang, Yongfeng Yang, Xin Liu, Hairong Zheng, Zhanli Hu

Proceedings Volume 10948, 1094836 (2019) https://doi.org/10.1117/12.2511818

KEYWORDS: Computed tomography, Gallium nitride, X-ray computed tomography, Image quality, Neural networks, Head, Image quality standards, Biomedical optics, Data acquisition, Algorithm development

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Proceedings Article | 1 March 2019 Paper

Novel learning-based Moiré artifacts reduction method in x-ray Talbot-Lau differential phase contrast imaging

Jianwei Chen, Jiongtao Zhu, Qiyang Zhang, Dong Liang, Yongshuai Ge

Proceedings Volume 10948, 109484S (2019) https://doi.org/10.1117/12.2506455

KEYWORDS: X-rays, Absorption, Phase contrast, X-ray imaging, Interferometry, Imaging systems, Visibility, Diffraction, Numerical simulations, Signal attenuation

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Proceedings Article | 5 May 2017 Presentation + Paper

A novel hybrid total variation minimization algorithm for compressed sensing

Hongyu Li, Yong Wang, Dong Liang, Leslie Ying

Proceedings Volume 10211, 102110G (2017) https://doi.org/10.1117/12.2261644

KEYWORDS: In vivo imaging, Detection theory, Computer programming, Optimization (mathematics), Brain, Biomedical engineering, Magnetic resonance imaging, Reconstruction algorithms, Compressed sensing, Signal processing, Interference (communication), Image restoration, Yield improvement, Image quality, Medical imaging

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SPIE Journal Paper | 20 January 2015

Undersampling trajectory design for compressed sensing based dynamic contrast-enhanced magnetic resonance imaging

Duan-Duan Liu, Dong Liang, Na Zhang, Xin Liu, Yuan-Ting Zhang

JEI, Vol. 24, Issue 01, 013017, (January 2015) https://doi.org/10.1117/12.10.1117/1.JEI.24.1.013017

KEYWORDS: Magnetic resonance imaging, Computer programming, Compressed sensing, Wavelets, Current controlled current source, Fourier transforms, Spatial resolution, Visualization, Statistical analysis, Biomedical engineering

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Showing 5 of 16 publications

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