Co-BioNet
importedsoftware/co-bionet
[Nature Machine Intelligence Journal] Official pytorch implementation for Uncertainty-Guided Dual-Views for Semi-Supervised Volumetric Medical Image Segmentation
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Repository
- github.com/himashi92/Co-BioNet
- Documentation
- unknown
- Tags
- 3d · adversarial · adversarial-learning · co-training · ct · la · medical · medical-image-segmentation
- Regulatory
- unknown
Top contributors by commit count, from the project’s public repository. Avatars are served by their origin, not stored here. To be removed from this list, open an issue.
Computed from shared tags, weighted so a rare tag counts for more than a common one. These are suggestions, not curated relationships.
- Co-Manifoldco-training · medical-image-segmentation
[Neurocomputing] Official PyTorch implementation for Co-Manifold Learning for Semi-supervised Medical Image Segmentation
- SegANadversarial-learning
SegAN: Semantic Segmentation with Adversarial Learning
- McCaDadversarial
[WACV2025, Early Accepted] McCaD: Multi-Contrast MRI Conditioned, Adaptive Adversarial Diffusion Model for High-Fidelity MRI Synthesis
- MU-Diffadversarial
Official Pytorch implementation for MU-Diff: A Mutual Learning Diffusion Model for Synthetic MRI with Application for Brain lesions
- preclinicaladversarial
Preclinical is an open-source healthcare AI safety testing platform. It simulates realistic adversarial patient interactions against your agent, stores transcripts, and grades outcomes against…
- AlizaMS3d · medical
DICOM Viewer
- api.github.com/repos/himashi92/Co-BioNetretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2023-07-20, 78 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
Not yet verified by a human. Correct this record →
/v1/entries/3.json→ .entries["co-bionet"]
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