CS-Net
importedsoftware/cs-net
CS-Net (MICCAI 2019) and CS2-Net (MedIA 2020)
Machine-generated from the listed sources and not yet reviewed by a human.
- Category
- Software & Systems
- Subcategory
- unknown
- License
- MIT(osi)
- Status
- maintained
- Maturity
- deployed
- Organization
- iMED-Lab
- Country
- unknown
- Homepage
- unknown
- Repository
- github.com/iMED-Lab/CS-Net
- Documentation
- unknown
- Tags
- deep-learning · medical-imaging · pytorch · 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.
- CBIM-Medical-Image-Segmentationmedical-imaging · pytorch · segmentation
A PyTorch framework for medical image segmentation
- fetal-head-clinical-aimedical-imaging · pytorch · segmentation
End-to-end clinical AI for fetal head circumference measurement — 4-phase pipeline: Residual U-Net (Dice 97.75%), Pseudo-LDDM v2 cine synthesis, temporal attention, structured pruning. Deployed on…
- Medical-Transformermedical-imaging · pytorch · segmentation
Official Pytorch Code for "Medical Transformer: Gated Axial-Attention for Medical Image Segmentation" - MICCAI 2021
- 3dMRISegmentationpytorch · segmentation
Code for NeuroImage: Clinical paper "Automatic post-stroke lesion segmentation on MR images using 3D residual convolutional neural network."
- CMU-Netpytorch · segmentation
[ISBI 2023] Official Pytorch implementation of "CMU-Net: A Strong ConvMixer-based Medical Ultrasound Image Segmentation Network"
- DAEFormerpytorch · segmentation
[MICCAI 2023] DAE-Former: Dual Attention-guided Efficient Transformer for Medical Image Segmentation
- api.github.com/repos/iMED-Lab/CS-Netretrieved 2026-08-05 · via github-api
Machine-imported from GitHub search. Last push 2025-08-13, 110 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/61.json→ .entries["cs-net"]
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