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Zhuiyang Zhang

Publications -  5
Citations -  694

Zhuiyang Zhang is an academic researcher. The author has contributed to research in topics: Image restoration & Deep learning. The author has an hindex of 3, co-authored 3 publications receiving 364 citations.

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CT Super-Resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble (GAN-CIRCLE)

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.
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CT Super-resolution GAN Constrained by the Identical, Residual, and Cycle Learning Ensemble(GAN-CIRCLE)

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.
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Structurally-Sensitive Multi-Scale Deep Neural Network for Low-Dose CT Denoising

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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Adding liver R2* quantification to proton density fat fraction MRI of vertebral bone marrow improves the prediction of osteoporosis

TL;DR: The predictive improvement over the use of BM PDFF and other traditional risk factors demonstrates the potential of liver R2* as a biomarker for osteopenia and osteoporosis in healthy women.
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Preoperative evaluation of malignant pancreatobiliary obstruction: A novel technique for multiphase fusion 3D CT images

TL;DR: In this paper , a multiphase fusion 3D images of CT arteriography, portovenography and hepatic venography combined with negative-contrast CT cholangiopancreatography can be done with enhanced multi-phase CT scan using intravenous contrast agent at once.