|3-D convolutional encoder-decoder network for low-dose CT via transfer learning from a 2-D trained network|
H Shan, Y Zhang, Q Yang, U Kruger, MK Kalra, L Sun, W Cong, G Wang
IEEE Transactions on Medical Imaging 37 (6), 1522-1534, 2018
|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, 2020
|Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstruction|
H Shan, A Padole, F Homayounieh, U Kruger, RD Khera, C Nitiwarangkul, ...
Nature Machine Intelligence 1 (6), 269-276, 2019
|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
|Multi-task GANs for view-specific feature learning in gait recognition|
Y He, J Zhang, H Shan, L Wang
IEEE Transactions on Information Forensics and Security 14 (1), 102-113, 2019
|On interpretability of artificial neural networks: A survey|
FL Fan, J Xiong, M Li, G Wang
IEEE Transactions on Radiation and Plasma Medical Sciences, 2021
|Super-resolution MRI and CT through GAN-CIRCLE|
Q Lyu, C You, H Shan, Y Zhang, G Wang
Developments in X-Ray Tomography XII 11113, 111130X, 2019
|Deep learning methods for CT image-domain metal artifact reduction|
L Gjesteby, Q Yang, Y Xi, H Shan, B Claus, Y Jin, B De Man, G Wang
Developments in X-ray Tomography XI 10391, 147-152, 2017
|Multi-Contrast Super-Resolution MRI Through a Progressive Network|
Q Lyu, H Shan, C Steber, C Helis, C Whitlow, M Chan, G Wang
IEEE Transactions on Medical Imaging, 2020
|MRI super-resolution with ensemble learning and complementary priors|
Q Lyu, H Shan, G Wang
IEEE Transactions on Computational Imaging 6, 2020
|Quadratic Autoencoder (Q-AE) for Low-dose CT Denoising|
F Fan, H Shan, MK Kalra, R Singh, G Qian, M Getzin, Y Teng, J Hahn, ...
IEEE Transactions on Medical Imaging 39 (6), 2035-2050, 2020
|A Method of Rapid Quantification of Patient‐Specific Organ Doses for CT Using Deep‐Learning based Multi‐Organ Segmentation and GPU‐accelerated Monte Carlo Dose Computing|
Z Peng, X Fang, P Yan, H Shan, T Liu, X Pei, G Wang, B Liu, MK Kalra, ...
Medical Physics, 2020
|Shape and margin-aware lung nodule classification in low-dose CT images via soft activation mapping|
Y Lei, Y Tian, H Shan, J Zhang, G Wang, MK Kalra
Medical Image Analysis 60, 101628, 2020
|Deep neural network for CT metal artifact reduction with a perceptual loss function|
L Gjesteby, H Shan, Q Yang, Y Xi, B Claus, Y Jin, B De Man, G Wang
In Proceedings of The Fifth International Conference on Image Formation in X …, 2018
|Optimized collusion prevention for online exams during social distancing|
M Li, L Luo, S Sikdar, NI Nizam, S Gao, H Shan, M Kruger, U Kruger, ...
npj Science of Learning 6 (1), 1-9, 2021
|PFA-GAN: Progressive Face Aging with Generative Adversarial Network|
Z Huang, S Chen, J Zhang, H Shan
IEEE Transactions on Information Forensics and Security, 2021
|Stabilizing deep tomographic reconstruction: Part A. Hybrid framework and experimental results|
W Wu, D Hu, W Cong, H Shan, S Wang, C Niu, P Yan, H Yu, ...
Patterns, 100474, 2022
|When age-invariant face recognition meets face age synthesis: A multi-task learning framework|
Z Huang, J Zhang, H Shan
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
|Synergizing medical imaging and radiotherapy with deep learning|
H Shan, X Jia, P Yan, Y Li, H Paganetti, G Wang
Machine Learning: Science and Technology 1 (2), 021001, 2020
|A dual-stream deep convolutional network for reducing metal streak artifacts in CT images|
L Gjesteby, H Shan, Q Yang, Y Xi, Y Jin, D Giantsoudi, H Paganetti, ...
Physics in Medicine & Biology 64 (23), 235003, 2019