This is an official release of the paper Boundary-aware Transformers for Skin Lesion Segmentation.
Boundary-aware Transformers for Skin Lesion Segmentation,
Jiacheng Wang, Lan Wei, Liansheng Wang, Qichao Zhou, Lei Zhu, Jing Qin
In: Medical Image Computing and Computer Assisted Intervention (MICCAI), 2021
[arXiv][Bibetex]
- [5/27 2022] We have released a more powerful XBound-Former with clearer concept and codes.
- [11/15 2021] We have released the point map data.
- [11/08 2021] We have released the training / testing codes.
- Network
- Pre-processing
- Training Codes
- MS
For more details or any questions, please feel easy to contact us by email ([email protected]).
Please download the dataset from ISIC challenge and PH2 website.
Please run:
$ python src/process_resize.py
$ python src/process_point.py
You need to change the File Path to your own.
For your convenience, we release the processed maps and the dataset division.
Please download them from Baidu Disk (code:kmqr) or Google Drive
The file names are equal to the original image names.
Download the pretrained weight for PH2 dataset from Google Drive.
$ python test.py --dataset isic2016
Method | Dice | IoU | HD95 | ASSD |
---|---|---|---|---|
Lee et al. | 0.918 | 0.843 | - | - |
BAT (paper) | 0.921 | 0.858 | - | - |
If you find BAT useful in your research, please consider citing:
@inproceedings{wang2021boundary,
title={Boundary-Aware Transformers for Skin Lesion Segmentation},
author={Wang, Jiacheng and Wei, Lan and Wang, Liansheng and Zhou, Qichao and Zhu, Lei and Qin, Jing},
booktitle={International Conference on Medical Image Computing and Computer-Assisted Intervention},
pages={206--216},
year={2021},
organization={Springer}
}