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Hongming Shan

Showing results (31-40 of 58) with videos related to

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IEEE Transactions on Medical Imaging|January 9, 2024
Quad-Net: Quad-Domain Network for CT Metal Artifact ReductionZilong Li, Qi Gao, Yaping Wu, et al.
IEEE Transactions on Radiation and Plasma Medical Sciences|April 11, 2022
Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image DenoisingYu Gong, Hongming Shan, Yueyang Teng, et al.
IEEE Transactions on Neural Networks and Learning Systems|December 13, 2023
Deep Rank-Consistent Pyramid Model for Enhanced Crowd CountingJiaqi Gao, Zhizhong Huang, Yiming Lei, et al.
IEEE Transactions on Medical Imaging|November 3, 2022
M<sub>3</sub>NAS: Multi-Scale and Multi-Level Memory-Efficient Neural Architecture Search for Low-Dose CT DenoisingZexin Lu, Wenjun Xia, Yongqiang Huang, et al.
IEEE Transactions on Medical Imaging|March 3, 2025
Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact ReductionChenglong Ma, Zilong Li, Yuanlin Li, et al.
IEEE Transactions on Medical Imaging|June 6, 2018
3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained NetworkHongming Shan, Yi Zhang, Qingsong Yang, et al.
IEEE Access : Practical Innovations, Open Solutions|November 30, 2020
Deep Efficient End-to-end Reconstruction (DEER) Network for Few-view Breast CT Image ReconstructionHuidong Xie, Hongming Shan, Wenxiang Cong, et al.
IEEE Transactions on Medical Imaging|April 15, 2021
Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural NetworkQing Lyu, Hongming Shan, Yibin Xie, et al.
IEEE Transactions on Neural Networks and Learning Systems|February 18, 2021
Convolutional Ordinal Regression Forest for Image Ordinal EstimationHaiping Zhu, Hongming Shan, Yuheng Zhang, et al.
Nature Machine Intelligence|November 27, 2020
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstructionHongming Shan, Atul Padole, Fatemeh Homayounieh, et al.
Pageof 6

Showing results (31-40 of 58) with videos related to

Sort By:
Pageof 6
IEEE Transactions on Medical Imaging|January 9, 2024
Quad-Net: Quad-Domain Network for CT Metal Artifact ReductionZilong Li, Qi Gao, Yaping Wu, et al.
IEEE Transactions on Radiation and Plasma Medical Sciences|April 11, 2022
Parameter-Transferred Wasserstein Generative Adversarial Network (PT-WGAN) for Low-Dose PET Image DenoisingYu Gong, Hongming Shan, Yueyang Teng, et al.
IEEE Transactions on Neural Networks and Learning Systems|December 13, 2023
Deep Rank-Consistent Pyramid Model for Enhanced Crowd CountingJiaqi Gao, Zhizhong Huang, Yiming Lei, et al.
IEEE Transactions on Medical Imaging|November 3, 2022
M<sub>3</sub>NAS: Multi-Scale and Multi-Level Memory-Efficient Neural Architecture Search for Low-Dose CT DenoisingZexin Lu, Wenjun Xia, Yongqiang Huang, et al.
IEEE Transactions on Medical Imaging|March 3, 2025
Radiologist-in-the-Loop Self-Training for Generalizable CT Metal Artifact ReductionChenglong Ma, Zilong Li, Yuanlin Li, et al.
IEEE Transactions on Medical Imaging|June 6, 2018
3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained NetworkHongming Shan, Yi Zhang, Qingsong Yang, et al.
IEEE Access : Practical Innovations, Open Solutions|November 30, 2020
Deep Efficient End-to-end Reconstruction (DEER) Network for Few-view Breast CT Image ReconstructionHuidong Xie, Hongming Shan, Wenxiang Cong, et al.
IEEE Transactions on Medical Imaging|April 15, 2021
Cine Cardiac MRI Motion Artifact Reduction Using a Recurrent Neural NetworkQing Lyu, Hongming Shan, Yibin Xie, et al.
IEEE Transactions on Neural Networks and Learning Systems|February 18, 2021
Convolutional Ordinal Regression Forest for Image Ordinal EstimationHaiping Zhu, Hongming Shan, Yuheng Zhang, et al.
Nature Machine Intelligence|November 27, 2020
Competitive performance of a modularized deep neural network compared to commercial algorithms for low-dose CT image reconstructionHongming Shan, Atul Padole, Fatemeh Homayounieh, et al.
Pageof 6