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license: cc-by-nc-4.0
library_name: pytorch
tags:
- surgical-video
- laparoscopic-cholecystectomy
- critical-view-of-safety
- image-classification
- semantic-segmentation
- knowledge-distillation
---
# EdgeCVS
Models from [**EdgeCVS: Democratization of Surgical AI with a Distilled Edge-Deployable
Critical View of Safety (CVS) Model**](https://papers.miccai.org/miccai-2026/paper/1745_paper.pdf) (MICCAI 2026).
EdgeCVS assesses the three Critical View of Safety criteria in laparoscopic cholecystectomy
from single frames, with a small model distilled from large multi-task teachers that runs in
real time on a CPU.
Code: [github.com/IMSY-DKFZ/edgecvs](https://github.com/IMSY-DKFZ/edgecvs)
## Models
Each model lives in its own folder, named like the code's `exp` option:
| Model (`exp`) | Backbone | Params | Weights | SAGES-CVS 2024 test mAP |
|---|---|---|---|---|
| [`edgecvs-5m`](edgecvs-5m/) | EdgeNeXt-Small | 5.6M | fp16, 11 MB | 66.4 |
```
config.yaml index of the available models
edgecvs-5m/
├── config.yaml model configuration used to build the network
└── edgecvs-5m-fold0.safetensors weights (fold 0, fp16; loaded into an fp32 model)
```
## EdgeCVS-5M
- **Input:** RGB frame, resized to 448×448, ImageNet normalization
- **Output:** probabilities for C1 (two structures), C2 (hepatocystic triangle) and
C3 (cystic plate); optional 7-class anatomy segmentation (background, cystic plate,
hepatocystic triangle, cystic artery, cystic duct, gallbladder, tool)
- **Deployment:** the segmentation head is optional; the classifier alone is used for the CSV
predictions and the speed figures below
## License
CC BY-NC 4.0: the models are trained on data released for non-commercial use.
## Citation
```bibtex
@InProceedings{YamAmi_EdgeCVS_MICCAI2026,
author = { Yamlahi, Amine AND Hennighausen, Jakob AND Hansen, Pascal AND Leeb, David AND Maier-Hein, Lena},
title = { { EdgeCVS: Democratization of surgical AI with a Distilled Edge-Deployable Critical View of Safety (CVS) model } },
booktitle = {Medical Image Computing and Computer Assisted Intervention -- MICCAI 2026},
year = {2026},
publisher = {Springer Nature Switzerland},
volume = {LNCS 16892},
month = {September},
page = {pending}
}
```
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