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2020 – today
- 2025
[j9]Liming Zhong, Ruolin Xiao, Hai Shu
, Kaiyi Zheng, Xinming Li, Yuankui Wu, Jianhua Ma, Qianjin Feng, Wei Yang:
NCCT-to-CECT synthesis with contrast-enhanced knowledge and anatomical perception for multi-organ segmentation in non-contrast CT images. Medical Image Anal. 100: 103397 (2025)- [c13]Yanfeng Yang, Shuai Li, Yingjie Zhang, Zhuoran Sun, Hai Shu, Ziqi Chen, Renming Zhang:
Conditional Diffusion Models Based Conditional Independence Testing. AAAI 2025: 22020-22028 - [i14]Rong Wu, Ziqi Chen, Gen Li, Hai Shu:
Nonlinear Sparse Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data. CoRR abs/2502.18756 (2025) - 2024
- [j8]Liming Zhong, Zeli Chen, Hai Shu, Kaiyi Zheng, Yin Li, Weicui Chen, Yuankui Wu, Jianhua Ma, Qianjin Feng, Wei Yang:
Multi-Scale Tokens-Aware Transformer Network for Multi-Region and Multi-Sequence MR-to-CT Synthesis in a Single Model. IEEE Trans. Medical Imaging 43(2): 794-806 (2024) - [c12]Taehyo Kim, Hai Shu, Qiran Jia, Mony de Leon:
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data. AISTATS 2024: 946-954 - [i13]Hai Shu:
D-CDLF: Decomposition of Common and Distinctive Latent Factors for Multi-view High-dimensional Data. CoRR abs/2407.00730 (2024) - [i12]Tianze Tang, Yanbing Chen, Hai Shu:
3D U-KAN Implementation for Multi-modal MRI Brain Tumor Segmentation. CoRR abs/2408.00273 (2024) - [i11]Zhaoyang Zhang, Hongtu Zhu, Ziqi Chen, Yingjie Zhang, Hai Shu:
Enhancing Missing Data Imputation through Combined Bipartite Graph and Complete Directed Graph. CoRR abs/2411.04907 (2024) - [i10]Yanfeng Yang, Shuai Li, Yingjie Zhang, Zhuoran Sun, Hai Shu, Ziqi Chen, Renming Zhang:
Conditional Diffusion Models Based Conditional Independence Testing. CoRR abs/2412.11744 (2024) - 2023
- [j7]Liming Zhong, Pinyu Huang, Hai Shu, Yin Li, Yiwen Zhang, Qianjin Feng, Yuankui Wu, Wei Yang:
United multi-task learning for abdominal contrast-enhanced CT synthesis through joint deformable registration. Comput. Methods Programs Biomed. 231: 107391 (2023) - [j6]Liming Zhong, Zeli Chen, Hai Shu, Yikai Zheng, Yiwen Zhang, Yuankui Wu, Qianjin Feng, Yin Li, Wei Yang:
QACL: Quartet attention aware closed-loop learning for abdominal MR-to-CT synthesis via simultaneous registration. Medical Image Anal. 83: 102692 (2023) - [j5]Heng Li, Haofeng Liu, Huazhu Fu, Yanwu Xu, Hai Shu, Ke Niu, Yan Hu, Jiang Liu:
A generic fundus image enhancement network boosted by frequency self-supervised representation learning. Medical Image Anal. 90: 102945 (2023) - [j4]Yiwen Zhang, Liming Zhong, Hai Shu, Zhenhui Dai, Kaiyi Zheng, Zefeiyun Chen, Qianjin Feng, Xuetao Wang, Wei Yang:
Cross-Task Feedback Fusion GAN for Joint MR-CT Synthesis and Segmentation of Target and Organs-at-Risk. IEEE Trans. Artif. Intell. 4(5): 1246-1257 (2023) - [c11]Haojin Li, Heng Li, Hai Shu, Jianyu Chen, Yan Hu, Jiang Liu:
Self-Supervision Boosted Retinal Vessel Segmentation for Cross-Domain Data. ISBI 2023: 1-5 - [c10]Yuanming Lin, Heng Li, Haofeng Liu, Hai Shu, Zinan Li, Yan Hu, Jiang Liu:
Domain Adaptative Retinal Image Quality Assessment with Knowledge Distillation Using Competitive Teacher-Student Network. ISBI 2023: 1-5 - [c9]Shuai Li, Yingjie Zhang, Hongtu Zhu, Christina Dan Wang, Hai Shu, Ziqi Chen, Zhuoran Sun, Yanfeng Yang:
K-Nearest-Neighbor Local Sampling Based Conditional Independence Testing. NeurIPS 2023 - [i9]Taehyo Kim, Hai Shu, Qiran Jia, Mony de Leon:
DeepFDR: A Deep Learning-based False Discovery Rate Control Method for Neuroimaging Data. CoRR abs/2310.13349 (2023) - 2022
- [j3]Yuchen Dang, Ziqi Chen, Heng Li, Hai Shu:
A Comparative Study of non-deep Learning, Deep Learning, and Ensemble Learning Methods for Sunspot Number Prediction. Appl. Artif. Intell. 36(1) (2022) - [j2]Hai Shu, Zhe Qu, Hongtu Zhu:
D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multi-view High-dimensional Data. J. Mach. Learn. Res. 23: 169:1-169:64 (2022) - [c8]Hai Shu, Ronghua Shi, Qiran Jia, Hongtu Zhu, Ziqi Chen:
mFI-PSO: A Flexible and Effective Method in Adversarial Image Generation for Deep Neural Networks. IJCNN 2022: 1-8 - [c7]Heng Li, Haofeng Liu, Huazhu Fu, Hai Shu, Yitian Zhao, Xiaoling Luo, Yan Hu, Jiang Liu:
Structure-Consistent Restoration Network for Cataract Fundus Image Enhancement. MICCAI (2) 2022: 487-496 - [i8]Yuchen Dang, Ziqi Chen, Heng Li, Hai Shu:
A comparative study of non-deep learning, deep learning, and ensemble learning methods for sunspot number prediction. CoRR abs/2203.05757 (2022) - [i7]Heng Li, Haofeng Liu, Huazhu Fu, Hai Shu, Yitian Zhao, Xiaoling Luo, Yan Hu, Jiang Liu:
Structure-consistent Restoration Network for Cataract Fundus Image Enhancement. CoRR abs/2206.04684 (2022) - 2021
- [c6]Qiran Jia, Hai Shu:
BiTr-Unet: A CNN-Transformer Combined Network for MRI Brain Tumor Segmentation. BrainLes@MICCAI (2) 2021: 3-14 - [i6]Qiran Jia, Hai Shu:
BiTr-Unet: a CNN-Transformer Combined Network for MRI Brain Tumor Segmentation. CoRR abs/2109.12271 (2021) - 2020
- [j1]Liming Zhong, Tengfei Li, Hai Shu, Chao Huang, Jason M. Johnson, Donald F. Schomer, Ho-Ling Liu, Qianjin Feng, Wei Yang, Hongtu Zhu:
(TS)2WM: Tumor Segmentation and Tract Statistics for Assessing White Matter Integrity with Applications to Glioblastoma Patients. NeuroImage 223: 117368 (2020) - [c5]Jiarui Tang, Tengfei Li, Hai Shu, Hongtu Zhu:
Variational-Autoencoder Regularized 3D MultiResUNet for the BraTS 2020 Brain Tumor Segmentation. BrainLes@MICCAI (2) 2020: 431-440 - [c4]Chenggang Lyu, Hai Shu:
A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation. BrainLes@MICCAI (1) 2020: 435-447 - [i5]Hai Shu, Zhe Qu, Hongtu Zhu:
D-GCCA: Decomposition-based Generalized Canonical Correlation Analysis for Multiple High-dimensional Datasets. CoRR abs/2001.02856 (2020) - [i4]Ronghua Shi, Hai Shu, Hongtu Zhu, Ziqi Chen:
Adversarial Image Generation and Training for Deep Convolutional Neural Networks. CoRR abs/2006.03243 (2020) - [i3]Chenggang Lyu, Hai Shu:
A Two-Stage Cascade Model with Variational Autoencoders and Attention Gates for MRI Brain Tumor Segmentation. CoRR abs/2011.02881 (2020)
2010 – 2019
- 2019
- [c3]Hai Shu, Hongtu Zhu:
Sensitivity Analysis of Deep Neural Networks. AAAI 2019: 4943-4950 - [i2]Hai Shu, Hongtu Zhu:
Sensitivity Analysis of Deep Neural Networks. CoRR abs/1901.07152 (2019) - [i1]Zhe Qu, Hai Shu:
CDPA: Common and Distinctive Pattern Analysis between High-dimensional Datasets. CoRR abs/1912.09989 (2019) - 2018
- [c2]Tengfei Li, Fan Zhou, Ziliang Zhu, Hai Shu, Hongtu Zhu:
A label-fusion-aided convolutional neural network for isointense infant brain tissue segmentation. ISBI 2018: 692-695 - [c1]Lutao Dai, Tengfei Li, Hai Shu, Liming Zhong, Haipeng Shen, Hongtu Zhu:
Automatic Brain Tumor Segmentation with Domain Adaptation. BrainLes@MICCAI (2) 2018: 380-392
Coauthor Index
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