Hongming Shan
Hongming Shan
Verified email at fudan.edu.cn - Homepage
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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, 2019
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
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, 103910W, 2017
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 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
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
On Interpretability of Artificial Neural Networks: A Survey
F Fan, J Xiong, M Li, G Wang
arXiv preprint arXiv:2001.02522, 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
MRI super-resolution with ensemble learning and complementary priors
Q Lyu, H Shan, G Wang
IEEE Transactions on Computational Imaging 6, 2020
Enhancing transferability of features from pretrained deep neural networks for lung nodule classification
H Shan, G Wang, MK Kalra, RC de Souza, J Zhang
Proceedings of the 2017 International Conference on Fully Three-Dimensional …, 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
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, 2019
Dual network architecture for few-view CT-trained on ImageNet data and transferred for medical imaging
H Xie, H Shan, W Cong, X Zhang, S Liu, R Ning, G Wang
Developments in X-Ray Tomography XII 11113, 111130V, 2019
Deep-learning-based breast CT for radiation dose reduction
W Cong, H Shan, X Zhang, S Liu, R Ning, G Wang
Developments in X-Ray Tomography XII 11113, 111131L, 2019
Accelerated Correction of Reflection Artifacts by Deep Neural Networks in Photo-Acoustic Tomography
H Shan, G Wang, Y Yang
Applied Sciences 9 (13), 2615, 2019
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 two‐dimensional feasibility study of deep learning‐based feature detection and characterization directly from CT sinograms
Q De Man, E Haneda, B Claus, P Fitzgerald, B De Man, G Qian, H Shan, ...
Medical Physics 46 (12), e790-e800, 2019
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