G
Guang Li
Researcher at Rensselaer Polytechnic Institute
Publications - 10
Citations - 721
Guang Li is an academic researcher from Rensselaer Polytechnic Institute. The author has contributed to research in topics: Imaging phantom & Image restoration. The author has an hindex of 4, co-authored 8 publications receiving 377 citations. Previous affiliations of Guang Li include Southeast University.
Papers
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Journal ArticleDOI
CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE)
Chenyu You,Wenxiang Cong,Michael W. Vannier,Punam K. Saha,Eric A. Hoffman,Ge Wang,Guang Li,Yi Zhang,Xiaoliu Zhang,Hongming Shan,Mengzhou Li,Shenghong Ju,Zhen Zhao,Zhuiyang Zhang +13 more
TL;DR: Wang et al. as mentioned in this paper proposed a semi-supervised deep learning approach to recover high-resolution (HR) CT images from low resolution (LR) counterparts by enforcing the cycle-consistency in terms of the Wasserstein distance.
Journal ArticleDOI
CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)
Chenyu You,Guang Li,Yi Zhang,Xiaoliu Zhang,Hongming Shan,Shenghong Ju,Zhen Zhao,Zhuiyang Zhang,Wenxiang Cong,Michael W. Vannier,Punam K. Saha,Ge Wang +11 more
TL;DR: In this article, a semi-supervised deep learning approach was proposed to recover high-resolution (HR) CT images from low resolution (LR) counterparts by enforcing the cycle-consistency in terms of Wasserstein distance to establish a nonlinear end-to-end mapping from noisy LR input images to denoised and deblurred HR outputs.
Journal ArticleDOI
Structurally-Sensitive Multi-Scale Deep Neural Network for Low-Dose CT Denoising
Chenyu You,Qingsong Yang,Hongming Shan,Lars Gjesteby,Guang Li,Shenghong Ju,Zhuiyang Zhang,Zhen Zhao,Yi Zhang,Wenxiang Cong,Ge Wang +10 more
TL;DR: This paper proposes a novel 3-D noise reduction method, called structurally sensitive multi-scale generative adversarial net, to improve the low-dose CT image quality, which incorporates3-D volumetric information to improved the image quality.
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A novel calibration method incorporating nonlinear optimization and ball-bearing markers for cone-beam CT with a parameterized trajectory.
TL;DR: The proposed novel calibration method demonstrates higher calibration accuracy and more robustness than the benchmark algorithm, and can obtain accurate geometric parameters of a CBCT system with a circular trajectory.
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Novel Detection Scheme for X-Ray Small-Angle Scattering
TL;DR: A new “collimation” design dedicated to capture a small-angle scattering radiographic image directly, which carries critical pathological information for differentiation between normal and abnormal tissues is proposed.