NoCodeSeg
importeddata/nocodeseg
🔬 Code-free deep segmentation for computational pathology
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Data & Standards
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- dormant
- Maturity
- deployed
- Organization
- unknown
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/andreped/NoCodeSeg
- Documentation
- unknown
- Tags
- annotation · convolutional-neural-networks · cpp · deep-learning · deepmib · digital-pathology · fastpathology · java
- 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.
- FAST-Pathologyconvolutional-neural-networks · digital-pathology · fastpathology
⚡ Open-source software for deep learning-based digital pathology
- breast-epithelium-segmentationdigital-pathology · fastpathology
🌸 Breast epithelium segmentation through IHC-guided supervision
- FP-DSA-plugindigital-pathology · fastpathology
Digital Slide Archive plugin to enable FAST deployment of pretrained CNNs for digital pathology
- MuTILs_Panopticconvolutional-neural-networks · digital-pathology
Amgad M, Salgado R, Cooper LA. A panoptic segmentation approach for tumor-infiltrating lymphocyte assessment: development of the MuTILs model and PanopTILs dataset. medRxiv 2022.01.08.22268814.
- Glands-detectionconvolutional-neural-networks · digital-pathology
🧠 A deep learning algorithm based on convolutional neural networks to detect glandular cells in digitalized biopsies of the prostate.
- H2G-Netconvolutional-neural-networks · digital-pathology
🚀 H2G-Net: Segmentation of breast cancer region from whole slide images
- api.github.com/repos/andreped/NoCodeSegretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2024-06-14, 58 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/4.json→ .entries["nocodeseg"]
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