ACELoss
importedsoftware/aceloss
Implementations of "Learning Euler's Elastica Model for 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
- HiLab-git
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/HiLab-git/ACELoss
- Documentation
- unknown
- Tags
- active-contour-model · loss-functions · 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.
- 3D-UCapsmedical-image-segmentation
3D-UCaps: 3D Capsules Unet for Volumetric Image Segmentation (MICCAI 2021)
- ACSmedical-image-segmentation
Adversarial Continual Learning for Multi-Domain Hippocampal Segmentation
- active-segmentationmedical-image-segmentation
ActiveSegmentation: A Simulation Framework for Benchmarking Active Learning Strategies for 3D Medical Image Segmentation
- Agentic-Smart-Healthmedical-image-segmentation
Multi-agent system that unifies heterogeneous dental data (CBCT, STL, clinical reports, photos) into a patient Digital Twin built on Gaussian Splatting, with per-region clinical attributes and…
- AgileFormermedical-image-segmentation
This the repo for the paper tiltled "AgileFormer: Spatially Agile Transformer UNet for Medical Image Segmentation"
- AMIGOpymedical-image-segmentation
Software for research and education in medical physics
- api.github.com/repos/HiLab-git/ACELossretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2021-01-10, 75 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/23.json→ .entries["aceloss"]
Entries are sharded 64 ways by a stable hash of the id, so a consumer can find any record without an index.