Spark in the Dark: Evaluating Encoder-Decoder Pairs for COVID-19 CT's Semantic Segmentation

See the implementation and the available networks in: Segmentation Models

Installation:

pip install -r requirements.txt

Copy the files inside the scripts to the utils folders inside the lib/python3.6/site-packages/segmentation_models_pytorch folder

Dataset:

Setup a txt file with the images paths as follows for training and validation:

path/to/image1.jpg path/to/mask1.png
path/to/image2.jpg path/to/mask2.png
path/to/image3.jpg path/to/mask3.png

or just the images paths for tests

path/to/image1.jpg
path/to/image2.jpg
path/to/image3.jpg

Setup the config file following the examples in the config folder

Execute:

python main.py --configs config_file.yml

Citation

@inproceedings{sparkinthedark2021,
    author={Krinski, Bruno A. and Ruiz, Daniel V. and Todt, Eduardo},
    booktitle={2021 Latin American Robotics Symposium (LARS), 2021 Brazilian Symposium on Robotics (SBR), and 2021 Workshop on Robotics in Education (WRE)}, 
    title={Spark in the Dark: Evaluating Encoder-Decoder Pairs for COVID-19 CT’s Semantic Segmentation}, 
    year={2021},
    volume={},
    number={},
    pages={198-203},
    doi={10.1109/LARS/SBR/WRE54079.2021.9605461}
}

@inproceedings{lightintheblack2022,
    author = {Bruno Krinski and Daniel Ruiz and Eduardo Todt},
    title = {Light In The Black: An Evaluation of Data Augmentation Techniques for COVID-19 CT’s Semantic Segmentation},
    booktitle = {Anais do XXII Simpósio Brasileiro de Computação Aplicada à Saúde},
    location = {Teresina},
    year = {2022},
    keywords = {},
    issn = {2763-8952},
    pages = {156--167},
    publisher = {SBC},
    address = {Porto Alegre, RS, Brasil},
    doi = {10.5753/sbcas.2022.222495},
    url = {https://sol.sbc.org.br/index.php/sbcas/article/view/21628}
}