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synapse-unet-light
hung2903/synapse-unet-light
synapse-unet-light is a machine learning model from hung2903. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
This model is a lightweight U-Net trained on the Synapse multi-organ CT dataset. It is designed to run on low-resource hardware (GTX 1650, 4GB VRAM) and CPU.
Access
Public
Updated Feb 1, 2026
Repo size
17.3 MB
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Repo makeup
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.pth17.3 MB · 100%
At a glance
- Access
- Public
- Created
- Feb 1, 2026
- Updated
- Feb 1, 2026
- SHA
- 25e5ab81
Model card
From the Hugging Face model README
Synapse Multi-Organ Segmentation (Lightweight U-Net)
This model is a lightweight U-Net trained on the Synapse multi-organ CT dataset. It is designed to run on low-resource hardware (GTX 1650, 4GB VRAM) and CPU.
Model Details
- Architecture: U-Net (Filters: 32, 64, 128, 256)
- Input: 256x256 Axial CT Clices (Windowed [-125, 275], Normalized [0,1])
- Classes: 9 (Background + 8 organs)
Usage
Run with the provided app.py in the linked GitHub repository.
model = UNet(n_channels=1, n_classes=9)
model.load_state_dict(torch.load("best_model.pth"))
Dataset
Synapse Multi-Organ Segmentation Challenge. License: Review original dataset license.
- Created
- Feb 1, 2026
- Updated
- Feb 1, 2026