Awesome
Simple Consistency Regularization for SSL-based Medical Image Segmentation
This is the official implementation of the paper titled "An Embarassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation" accepted in IEEE ISBI 2022.
<img src="/ICT-MedSeg-Overall.png" style="margin: 6px;">Running the code
git clone https://github.com/hritam-98/ICT-MedSeg
Requirements
Some important required packages include:
- Pytorch version >=0.4.1.
- TensorBoardX
- Python == 3.6
- Efficientnet-Pytorch
pip install efficientnet_pytorch
- Some basic python packages such as Numpy, Scikit-image, SimpleITK, Scipy ......
Dataset
Download the processed data and put the data in ../data/MMWHS
or ../data/ACDC
, please read and follow the ACDC.md.
Training
Next, to train the model on ACDC, run the following:
python main.py
Testing
To validate the model performance, run the following:
python test.py
Citation
If you find this repository useful, please cite our work as follows:
@misc{basak2022embarrassingly,
title={An Embarrassingly Simple Consistency Regularization Method for Semi-Supervised Medical Image Segmentation},
author={Hritam Basak and Rajarshi Bhattacharya and Rukhshanda Hussain and Agniv Chatterjee},
year={2022},
eprint={2202.00677},
archivePrefix={arXiv},
primaryClass={eess.IV}
}
Acknowledgement
Thanks SSL4MIS for their wonderfurl work. Part of the code is borrowed from them. Please feel free to cite their work:
@misc{luo2020ssl4mis,
title={SSL4MIS},
author={Luo, Xiangde},
year={2020}
}