Pinned Repositories
ATM-22-Related-Work
[MedIA 2023/MICCAI 2022 Grand Challenge]: Airway Tree Modeling (ATM'22) Related Work Collections, also includes the state-of-the-art works on pulmonary airway segmentation and related works.
GBZTJU
Real-Time-Neurosurgical-Instrument-Segmentation
SSC-nnUNet
Accurately and reliably defining organs at risk (OARs) and tumors are the cornerstone of radiation therapy (RT) treatment planning for lung cancer. Almost all segmentation networks based on deep learning techniques rely on fully annotated data with strong supervision. However, existing public imaging datasets encountered in the RT domain frequently include singly labelled tumors or partially labelled organs because annotating full OARs and tumors in CT images is both rigorous and tedious. To utilize labelled data from different sources, we proposed a dual-path semi-supervised conditional nnU-Net for OARs and tumor segmentation that is trained on a union of partially labelled datasets.
ZGBTJU
GuobinZhangTJU's Repositories
GuobinZhangTJU/SSC-nnUNet
Accurately and reliably defining organs at risk (OARs) and tumors are the cornerstone of radiation therapy (RT) treatment planning for lung cancer. Almost all segmentation networks based on deep learning techniques rely on fully annotated data with strong supervision. However, existing public imaging datasets encountered in the RT domain frequently include singly labelled tumors or partially labelled organs because annotating full OARs and tumors in CT images is both rigorous and tedious. To utilize labelled data from different sources, we proposed a dual-path semi-supervised conditional nnU-Net for OARs and tumor segmentation that is trained on a union of partially labelled datasets.
GuobinZhangTJU/GBZTJU
GuobinZhangTJU/Real-Time-Neurosurgical-Instrument-Segmentation
GuobinZhangTJU/ZGBTJU