https://github.com/hilab-git/hamil
https://github.com/hilab-git/hamil
Last synced: 10 months ago
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- Host: GitHub
- URL: https://github.com/hilab-git/hamil
- Owner: HiLab-git
- Created: 2023-04-05T03:21:39.000Z (about 3 years ago)
- Default Branch: main
- Last Pushed: 2023-06-09T01:35:50.000Z (almost 3 years ago)
- Last Synced: 2025-04-19T11:17:36.794Z (about 1 year ago)
- Language: Python
- Size: 126 KB
- Stars: 10
- Watchers: 1
- Forks: 0
- Open Issues: 3
-
Metadata Files:
- Readme: README.md
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README
## HAMIL: High-resolution Activation Maps and Interleaved Learning for Weakly Supervised Segmentation of Histopathological Images
This repository provides the code for "HAMIL: High-resolution Activation Maps and Interleaved Learning for Weakly Supervised Segmentation of Histopathological Images"
accepted by TMI 2023.
## Usage
1. To obtain the background masks. (If the background is not white regions, skip this step)
```train_set_root```: training set root, ```gamma_path```: path to save gamma transform for training set, ```gamma_crf_path```: path to save extracted backgrounds for training set,
```
generate_bg_masks.py --train_set_root train_set_root --gamma_path gamma_path --gamma_crf_path gamma_crf_path
```
2. Train classification network
```
train_cls.py --dataset_root dataset_root --gpu 0
```
3. Train segmentation network
```
train_seg.py --dataset_root dataset_root --gpu 0
```
## Citation
```
@article{zhong2023hamil,
title={HAMIL: High-resolution Activation Maps and Interleaved Learning for Weakly Supervised Segmentation of Histopathological Images},
author={Zhong, Lanfeng and Wang, Guotai and Liao, Xin and Zhang, Shaoting},
journal={IEEE Transactions on Medical Imaging},
year={2023},
publisher={IEEE}
}
```
## Acknowledgement
The code of DeepLabv3+ is borrowed from [PuzzleCAM](https://github.com/shjo-april/PuzzleCAM)