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Yi Zhang
Yi Zhang
Verified email at scu.edu.cn
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Year
Low-dose CT with a residual encoder-decoder convolutional neural network
H Chen, Y Zhang, MK Kalra, F Lin, Y Chen, P Liao, J Zhou, G Wang
IEEE transactions on medical imaging 36 (12), 2524-2535, 2017
16982017
Low-dose CT image denoising using a generative adversarial network with Wasserstein distance and perceptual loss
Q Yang, P Yan, Y Zhang, H Yu, Y Shi, X Mou, MK Kalra, Y Zhang, L Sun, ...
IEEE transactions on medical imaging 37 (6), 1348-1357, 2018
15542018
Low-dose CT via convolutional neural network
H Chen, Y Zhang, W Zhang, P Liao, K Li, J Zhou, G Wang
Biomedical optics express 8 (2), 679-694, 2017
8162017
CT super-resolution GAN constrained by the identical, residual, and cycle learning ensemble (GAN-CIRCLE)
C You, G Li, Y Zhang, X Zhang, H Shan, M Li, S Ju, Z Zhao, Z Zhang, ...
IEEE transactions on medical imaging 39 (1), 188-203, 2019
5062019
3D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning from a 2D Trained Network
H Shan, Y Zhang, Q Yang, U Kruger, KM Kalra, L Sun, W Cong, G Wang
IEEE Transactions on Medical Imaging 37 (6), 1522-1534, 2018
4812018
LEARN: Learned experts’ assessment-based reconstruction network for sparse-data CT
H Chen, Y Zhang, Y Chen, J Zhang, W Zhang, H Sun, Y Lv, P Liao, J Zhou, ...
IEEE transactions on medical imaging 37 (6), 1333-1347, 2018
4372018
MD-Recon-Net: a parallel dual-domain convolutional neural network for compressed sensing MRI
M Ran, W Xia, Y Huang, Z Lu, P Bao, Y Liu, H Sun, J Zhou, Y Zhang
IEEE Transactions on Radiation and Plasma Medical Sciences 5 (1), 120-135, 2020
3302020
Structurally-sensitive multi-scale deep neural network for low-dose CT denoising
C You, Q Yang, H Shan, L Gjesteby, G Li, S Ju, Z Zhang, Z Zhao, Y Zhang, ...
IEEE access 6, 41839-41855, 2018
2512018
Low-dose CT denoising with convolutional neural network
H Chen, Y Zhang, W Zhang, P Liao, K Li, J Zhou, G Wang
2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017 …, 2017
1742017
Denoising of 3D magnetic resonance images using a residual encoder–decoder Wasserstein generative adversarial network
M Ran, J Hu, Y Chen, H Chen, H Sun, J Zhou, Y Zhang
Medical image analysis 55, 165-180, 2019
1562019
DU-GAN: Generative adversarial networks with dual-domain U-Net-based discriminators for low-dose CT denoising
Z Huang, J Zhang, Y Zhang, H Shan
IEEE Transactions on Instrumentation and Measurement 71, 1-12, 2021
1512021
Simultaneous denoising and super-resolution of optical coherence tomography images based on generative adversarial network
Y Huang, Z Lu, Z Shao, M Ran, J Zhou, L Fang, Y Zhang
Optics express 27 (9), 12289-12307, 2019
1282019
Convolutional sparse coding for compressed sensing CT reconstruction
P Bao, W Xia, K Yang, W Chen, M Chen, Y Xi, S Niu, J Zhou, H Zhang, ...
IEEE transactions on medical imaging 38 (11), 2607-2619, 2019
1242019
Spectral CT reconstruction with image sparsity and spectral mean
Y Zhang, Y Xi, Q Yang, W Cong, J Zhou, G Wang
IEEE transactions on computational imaging 2 (4), 510-523, 2016
1232016
Discriminative feature representation to improve projection data inconsistency for low dose CT imaging
J Liu, J Ma, Y Zhang, Y Chen, J Yang, H Shu, L Luo, G Coatrieux, W Yang, ...
IEEE transactions on medical imaging 36 (12), 2499-2509, 2017
1172017
Few-view image reconstruction with fractional-order total variation
Y Zhang, W Zhang, Y Lei, J Zhou
JOSA A 31 (5), 981-995, 2014
1122014
Statistical iterative reconstruction using adaptive fractional order regularization
Y Zhang, Y Wang, W Zhang, F Lin, Y Pu, J Zhou
Biomedical optics express 7 (3), 1015-1029, 2016
1012016
A class of fractional-order variational image inpainting models
Y Zhang, YF Pu, JR Hu, JL Zhou
Appl. Math. Inf. Sci 6 (2), 299-306, 2012
972012
Forensic age estimation for pelvic X-ray images using deep learning
Y Li, Z Huang, X Dong, W Liang, H Xue, L Zhang, Y Zhang, Z Deng
European radiology 29, 2322-2329, 2019
932019
Low-dose CT restoration via stacked sparse denoising autoencoders
Y Liu, Y Zhang
Neurocomputing 284, 80-89, 2018
922018
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