metadata
tags:
- medical-segmentation
- pytorch
- synapse
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.