DLWK/GAML

The Code of "GAML: Geometry-Aware Mutual Learning for Polyp Segmentation"

GAML

GAML: Geometry-Aware Mutual Learning for Polyp Segmentation

The code and dataset will be available soon here.

1. Implementation

The proposed architecture is implemented using the PyTorch framework (1.9.0+cu12.3) with a single NVIDIA GeForce RTX 3090 GPU of 24 GB memory.

2. Dataset

We have used the following datasets:

• Kvasir-SEG
• CVC-ClinicDB
• BKAI
• Kvasir-Sessile

🔥NEWS🔥 :

• [2024/02/5]:fire: Release the inference code!"Coming soon."
• [2024/02/4] Create a repository.

Citation

• If you find this work is helpful, please cite our work

@article{wang2022eanet,
  title={EANet: Iterative edge attention network for medical image segmentation},
  author={Wang, Kun and Zhang, Xiaohong and Zhang, Xiangbo and Lu, Yuting and Huang, Sheng and Yang, Dan},
  journal={Pattern Recognition},
  volume={127},
  pages={108636},
  year={2022},
  publisher={Elsevier}
}

@article{wang2023gsal,
  title={GSAL: Geometric Structure Adversarial Learning for Robust Medical Image Segmentation},
  author={Wang, Kun and Zhang, Xiaohong and Lu, Yuting and Zhang, Wei and Huang, Sheng and Yang, Dan},
  journal={Pattern Recognition},
  pages={109596},
  year={2023},
  publisher={Elsevier}
}