deepNeuroSeg
importedsoftware/deepneuroseg
Deep-learning Tool for White Matter (WM) lesions and Claustrum structure segmentation in brain magnetic resonance imaging (MRI).
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
- Homepage
- unknown
- Repository
- github.com/RitaOlenchuk/deepNeuroSeg
- Documentation
- unknown
- Tags
- brain · claustrum · deep-learning · machine-learning · mri · segmentation · white-matter-lesion
- 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.
- ANTsRbrain · mri · segmentation
R interface to the ANTs biomedical image processing library
- BraTSbrain · mri · segmentation
Providing top-performing algorithms from the Brain Tumor Segmentation (BraTS) challenges.
- GOUHFIbrain · mri · segmentation
GOUHFI: novel contrast- and resolution-agnostic segmentation tool for both Ultra-High Field and lower field MRI
- Paint4Brainsbrain · mri · segmentation
A brain MRI segmentation tool that provides accurate robust segmentation of problematic brain regions across the neurodegenerative spectrum. The methodology is generalisable to perform well with the…
- Alzheimer_ensemble_transfer_learningbrain · mri
Alzheimer prediction using Ensemble Transfer Learning
- atlasBREXbrain · mri
atlasBREX: Automated averaged template-derived brain extraction in animal MRI
- api.github.com/repos/RitaOlenchuk/deepNeuroSegretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2021-11-10, 5 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/35.json→ .entries["deepneuroseg"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.