Wu Zhou
Orcid: 0000-0002-5917-1723Affiliations:
- Chinese Academy of Sciences, Shenzhen Institutes of Advanced Technology, Key Laboratory of Health Informatics, China
According to our database1,
Wu Zhou
authored at least 20 papers
between 2013 and 2023.
Collaborative distances:
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Bibliography
2023
Correlated and individual feature learning with contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma.
Pattern Recognit., October, 2023
Transformer-Based Tooth Segmentation, Identification and Pulp Calcification Recognition in CBCT.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Triplet-Uncertainty in Multi-Task Deep Learning for Improving Malignancy Characterization of Hepatocellular Carcinoma.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Inter-Modal Conditional-Guided Fusion Network with Transformer for Grading Hepatocellular Carcinoma.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
Teeth and Root Canals Segmentation using Zxyformer with Uncertainty Guidance and Weight Transfer.
Proceedings of the 20th IEEE International Symposium on Biomedical Imaging, 2023
2022
Adaptive Multimodal Fusion With Attention Guided Deep Supervision Net for Grading Hepatocellular Carcinoma.
IEEE J. Biomed. Health Informatics, 2022
DLNLF-net: Denoised local and non-local deep features fusion network for malignancy characterization of hepatocellular carcinoma.
Comput. Methods Programs Biomed., 2022
Attention guided discriminative feature learning and adaptive fusion for grading hepatocellular carcinoma with Contrast-enhanced MR.
Comput. Medical Imaging Graph., 2022
Transformer Based Multi-task Deep Learning with Intravoxel Incoherent Motion Model Fitting for Microvascular Invasion Prediction of Hepatocellular Carcinoma.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2022, 2022
2020
Super-Resolution and Self-Attention with Generative Adversarial Network for Improving Malignancy Characterization of Hepatocellular Carcinoma.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
2019
Similarity Steered Generative Adversarial Network and Adaptive Transfer Learning for Malignancy Characterization of Hepatocellualr Carcinoma.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2019, 2019
Prediction Of Microvascular Invasion Of Hepatocellar Carcinoma With Contrast-Enhanced MR Using 3D CNN And LSTM.
Proceedings of the 16th IEEE International Symposium on Biomedical Imaging, 2019
Discrepancy Steered Conditional Adversarial Network For Deep Feature Based Malignancy Characterization of Hepatocellular Carcinoma.
Proceedings of the 2019 IEEE International Conference on Image Processing, 2019
Improving the malignancy characterization of hepatocellular carcinoma using deeply supervised cross modal transfer learning for non-enhanced MR.
Proceedings of the 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2019
2018
Local and Non-local Deep Feature Fusion for Malignancy Characterization of Hepatocellular Carcinoma.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2018, 2018
3D deep feature fusion in contrast-enhanced MR for malignancy characterization of hepatocellular carcinoma.
Proceedings of the 15th IEEE International Symposium on Biomedical Imaging, 2018
2D and 3D Convolutional Neural Network Fusion for Predicting the Histological Grade of Hepatocellular Carcinoma.
Proceedings of the 24th International Conference on Pattern Recognition, 2018
2017
Malignancy characterization of hepatocellular carcinoma using hybrid texture and deep features.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017
2013
Comput. Math. Methods Medicine, 2013
Comput. Math. Methods Medicine, 2013