CASF-Net: A Cross-attention and Cross-scale Fusion Network designed for Medical Image Segmentation.
This code has been tested on a personal laptop with Intel i7-10700H 3.8-GHz processor, 32-GB RAM, an NVIDIA GTX3060Ti graphic card, Python 3.6, PyTorch 9.1, CUDA 10.1, and cuDNN 8.3.
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Kvasir-SEG Dataset: Segmented Polyp Dataset for Computer Aided Gastrointestinal Disease Detection
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ISIC 2018: ISIC 2018 Challenge
Place the datasets into the 'data' directory.
Download models (loading models), pretrained models (loading model parameters), and result maps:
Place the related documents into the 'models' directory.
python XX.py
The results will be saved in the 'snapshots' directory.
Some of the codes in this repository are borrowed from:
If you have any questions, please contact hiderhao@gmail.com.