SALT
importedsoftware/salt
Softmax for Arbitrary Label Trees (SALT) is a framework for training segmentation networks using conditional probabilities to model hierarchical relationships in the data.
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- active
- Maturity
- deployed
- Organization
- UMEssen
- Country
- unknown
- Homepage
- ship-ai.ikim.nrw/
- Repository
- github.com/UMEssen/SALT
- Documentation
- unknown
- Tags
- 3d-segmentation · conditional-probabilities · hierarchical-labels · 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.
- SAAMI3d-segmentation · medical-image-segmentation
Automatic segment and generate masks for any 3D medical images using SAM model without prompt
- brainchop3d-segmentation
Brainchop: In-browser 3D MRI rendering and segmentation
- Fast-nnUNet3d-segmentation
This is the official repository for Fast-nnUNet, a new fast model inference framework based on the nnUNet framework implementation.
- MRI-MS-Plaques-Segmentation3d-segmentation
A 3D Attention U-Net model is developed, aimed at segmenting and tracking Multiple Sclerosis lesions in MRI images.
- 3D-UCapsmedical-image-segmentation
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation (MICCAI 2021)
- ACELossmedical-image-segmentation
Implementations of "Learning Euler's Elastica Model for Medical Image Segmentation"
- api.github.com/repos/UMEssen/SALTretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2026-08-03, 82 stars, license reported as MIT. Category and schematic were assigned by keyword heuristics and are unreviewed.
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/v1/entries/1.json→ .entries["salt"]
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