Jianghao Wu

Orcid: 0000-0001-9743-9316

Affiliations:
  • 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 14 papers between 2022 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

Online presence:

On csauthors.net:

Bibliography

2025
GLFC: Unified Global-Local Feature and Contrast Learning with Mamba-Enhanced UNet for Synthetic CT Generation from CBCT.
CoRR, January, 2025

SRPL-SFDA: Sam-Guided Reliable Pseudo-Labels For Source-Free Domain Adaptation in medical image segmentation.
Neurocomputing, 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


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