Jianghao Wu
Orcid: 0000-0001-9743-9316Affiliations:
- University of Electronic Science and Technology of China, School of Mechanical and Electrical Engineering, Chengdu, China
- Shanghai AI Laboratory, China
According to our database1,
Jianghao Wu
authored at least 18 papers
between 2022 and 2025.
Collaborative distances:
Collaborative distances:
Timeline
Legend:
Book In proceedings Article PhD thesis Dataset OtherLinks
Online presence:
-
on orcid.org
-
on github.com
On csauthors.net:
Bibliography
2025
IEEE Trans. Image Process., 2025
SRPL-SFDA: Sam-Guided Reliable Pseudo-Labels For Source-Free Domain Adaptation in medical image segmentation.
Neurocomputing, 2025
GLFC: Unified Global-Local Feature and Contrast Learning with Mamba-Enhanced UNet for Synthetic CT Generation from CBCT.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2025
TEGDA: Test-Time Evaluation-Guided Dynamic Adaptation for Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025
DGHFA: Dynamic Gradient and Hierarchical Feature Alignment for Robust Distillation of Medical VLMs.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025
FDAS: Foundation Model Distillation and Anatomic Structure-Aware Multi-task Learning for Self-Supervised Medical Image Segmentation.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2025, 2025
2024
FPL+: Filtered Pseudo Label-Based Unsupervised Cross-Modality Adaptation for 3D Medical Image Segmentation.
IEEE Trans. Medical Imaging, September, 2024
Unsupervised Domain Adaptation for Abdominal Organ Segmentation Using Pseudo Labels and Organ Attention CycleGAN.
Proceedings of the Fast, Low-Resource, Accurate Robust Organ and Pan-cancer Segmentation, 2024
RPL-SFDA: Reliable Pseudo Label-Guided Source-Free Cross-Modality Adaptation for NPC GTV Segmentation.
Proceedings of the IEEE International Symposium on Biomedical Imaging, 2024
2023
UPL-SFDA: Uncertainty-Aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation.
IEEE Trans. Medical Imaging, December, 2023
A novel one-to-multiple unsupervised domain adaptation framework for abdominal organ segmentation.
Medical Image Anal., August, 2023
TISS-net: Brain tumor image synthesis and segmentation using cascaded dual-task networks and error-prediction consistency.
Neurocomputing, August, 2023
CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation.
Medical Image Anal., 2023
UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation.
CoRR, 2023
MIS-FM: 3D Medical Image Segmentation using Foundation Models Pretrained on a Large-Scale Unannotated Dataset.
CoRR, 2023
UPL-TTA: Uncertainty-Aware Pseudo Label Guided Fully Test Time Adaptation for Fetal Brain Segmentation.
Proceedings of the Information Processing in Medical Imaging, 2023
2022
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwnannoma and Cochlea Segmentation.
CoRR, 2022
FPL-UDA: Filtered Pseudo Label-Based Unsupervised Cross-Modality Adaptation for Vestibular Schwannoma Segmentation.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022