Hexin Dong
According to our database1,
Hexin Dong
authored at least 13 papers
between 2020 and 2024.
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Bibliography
2024
Multi-Scale Clinical-Guided Binocular Fusion Framework for Predicting New-Onset Hypertension Over a Four-Year Period.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
2023
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation.
Medical Image Anal., 2023
Cluster-Induced Mask Transformers for Effective Opportunistic Gastric Cancer Screening on Non-contrast CT Scans.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
Improved Prognostic Prediction of Pancreatic Cancer Using Multi-phase CT by Integrating Neural Distance and Texture-Aware Transformer.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2023, 2023
MetaViT: Metabolism-Aware Vision Transformer for Differential Diagnosis of Parkinsonism with <sup>18</sup>F-FDG PET.
Proceedings of the Information Processing in Medical Imaging, 2023
Devil is in the Queries: Advancing Mask Transformers for Real-world Medical Image Segmentation and Out-of-Distribution Localization.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023
2022
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation.
CoRR, 2022
Region-Aware Metric Learning for Open World Semantic Segmentation via Meta-Channel Aggregation.
Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022
2021
CoRR, 2021
Unsupervised Domain Adaptation in Semantic Segmentation Based on Pixel Alignment and Self-Training.
CoRR, 2021
DAST: Unsupervised Domain Adaptation in Semantic Segmentation Based on Discriminator Attention and Self-Training.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021
2020
AF-SEG: An Annotation-Free Approach for Image Segmentation by Self-Supervision and Generative Adversarial Network.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020
Annotation-Free Gliomas Segmentation Based on a Few Labeled General Brain Tumor Images.
Proceedings of the 17th IEEE International Symposium on Biomedical Imaging, 2020