2024/6/25: 🎉Our method was accepted by MICCAI 2024.
2024/5/21: Add data loader for Skin Lesion Segmentation (ISIC2017).
Install the dependencies of SAM.
Install mmcv-full for CNN encoder.
conda create --name ASPS python=3.8
conda activate ASPS
pip install torch==1.12.1+cu116 torchvision==0.13.1+cu116 torchaudio==0.12.1 --extra-index-url https://download.pytorch.org/whl/cu116
pip install mmcv-full==1.6.2 -f https://download.openmmlab.com/mmcv/dist/cu116/torch1.12/index.html
pip install tqdm
pip install opencv-python
pip install albumentations==1.3.0We conduct extensive experiments on five polyp segmentation datasets following PraNet.
For skin lesion segmentation: following EGE-UNet, needing to modify
from dataset.Segmentation_othertofrom dataset.Segmentation_isicboth intrain.pyandinfer.py.
We used train.py to train our framework.
The --exp_name is the name of the experiment, and --polyp_dir is the path to the training dataset.
python train.py --exp_name '0308_E_L' --polyp_dir "polyp_seg/TrainDataset/"We used infer.py to evaluate our framework.
The --dataset_name is the name of the dataset, and --test_seg_dir is the path to the testing dataset.
python infer.py --exp_name '0308_E_L' --dataset_name 'CVC-300' --test_seg_dir "polyp_seg/TestDataset/CVC-300/"
python infer.py --exp_name '0308_E_L' --dataset_name 'CVC-ClinicDB' --test_seg_dir "polyp_seg/TestDataset/CVC-ClinicDB/"
python infer.py --exp_name '0308_E_L' --dataset_name 'CVC-ColonDB' --test_seg_dir "polyp_seg/TestDataset/CVC-ColonDB/"
python infer.py --exp_name '0308_E_L' --dataset_name 'ETIS-LaribPolypDB' --test_seg_dir "polyp_seg/TestDataset/ETIS-LaribPolypDB/"
python infer.py --exp_name '0308_E_L' --dataset_name 'Kvasir' --test_seg_dir "polyp_seg/TestDataset/Kvasir/" You can directly run the train.sh to train and evaluate our framework.
Note: If using SUN_SEG dataset, the training and evaluating codes are in 'scripts/'.
To inference single image or visualize the results, run vis.py.
| raw image | pred mask | GT |
|---|---|---|
 |
 |
 |
| Name | Repo | Download | Password |
|---|---|---|---|
| MSCAN-B | SegNeXt | https://rec.ustc.edu.cn/share/4c1d2ab0-344e-11ef-b416-0bee023cca0f | 31tz |
| MSCAN-L | SegNeXt | https://rec.ustc.edu.cn/share/18e3cd80-344e-11ef-bbf4-79b40a1f9d5c | pl1v |
| SAM-B-ASPS | https://rec.ustc.edu.cn/share/5e9be4b0-344a-11ef-a151-6b2a0b8eedb8 | li92 | |
| SAM-H-ASPS | https://rec.ustc.edu.cn/share/fc3da400-344a-11ef-b1d5-932017a40fd5 | 3w0g | |
| EfficientSAM-ASPS | EfficientSAM | https://rec.ustc.edu.cn/share/c9696fb0-344a-11ef-b24f-3f1e0faf0fb9 | xoqh |
@article{li2024asps,
title={ASPS: Augmented Segment Anything Model for Polyp Segmentation},
author={Li, Huiqian and Zhang, Dingwen and Yao, Jieru and Han, Longfei and Li, Zhongyu and Han, Junwei},
journal={arXiv preprint arXiv:2407.00718},
year={2024}
}