active-segmentation
importedsoftware/active-segmentation
ActiveSegmentation: A Simulation Framework for Benchmarking Active Learning Strategies for 3D Medical Image Segmentation
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- AGPL-3.0(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- HealthML
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/HealthML/active-segmentation
- Documentation
- unknown
- Tags
- 3d-image-segmentation · active-learning · deep-learning · medical-image-segmentation · medical-imaging · pytorch · pytorch-lightning · semantic-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.
- biom3d3d-image-segmentation · medical-imaging
Easy Volumetric Segmentation with Deep Learning
- MONAILabelactive-learning · medical-imaging · pytorch
MONAI Label is an intelligent open source image labeling and learning tool.
- mmsegmentationmedical-image-segmentation · pytorch · semantic-segmentation
OpenMMLab Semantic Segmentation Toolbox and Benchmark.
- medico-sammedical-image-segmentation · medical-imaging · semantic-segmentation
Segment Anything for Medical Imaging
- region_based_active_learningactive-learning · medical-image-segmentation
On uncertainty estimation in active learning for image segmentation
- CBIM-Medical-Image-Segmentationmedical-image-segmentation · medical-imaging · pytorch
A PyTorch framework for medical image segmentation
- api.github.com/repos/HealthML/active-segmentationretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2022-07-05, 20 stars, license reported as AGPL-3.0. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/36.json→ .entries["active-segmentation"]
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