Segmentation of 159 anatomical classes for Chest X-Rays.
Project description
Installation
The project is available in PyPI. To install run:
pip install cxas
Running Segmentation from terminal
Segment the anatomy of X-Ray images (.jpg,.png,.dcm) and store the results (npy,json,jpg,png,dicom-seg):
` cxas_segment -i {desired input directory or file} -o {desired output directory} `
Running Feature Extraction from terminal
Extract anatomical features from X-Ray images (.jpg,.png,.dcm) and store the results (.csv):
cxas_feat_extract -i {desired input directory or file} -o {desired output directory} -f {desired features to extract}
Running either from terminal
Extract anatomical features from X-Ray images (.jpg,.png,.dcm) and store the results (.csv):
cxas -i {desired input directory or file} -o {desired output directory} -mode {"segment" or "exract"} -f {required if mode == 'extract'}
Citation
If you use this work or dataset, please cite:
@inproceedings{Seibold_2022_BMVC,
author = {Constantin Marc Seibold and Simon Reiß and M. Saquib Sarfraz and Matthias A. Fink and Victoria Mayer and Jan Sellner and Moon Sung Kim and Klaus H. Maier-Hein and Jens Kleesiek and Rainer Stiefelhagen},
title = {Detailed Annotations of Chest X-Rays via CT Projection for Report Understanding},
booktitle = {33rd British Machine Vision Conference 2022, {BMVC} 2022, London, UK, November 21-24, 2022},
publisher = {{BMVA} Press},
year = {2022},
url = {https://bmvc2022.mpi-inf.mpg.de/0058.pdf}
}
@inproceedings{Seibold_2023_CXAS,
author = {Constantin Seibold, Alexander Jaus, Matthias Fink,
Moon Kim, Simon Reiß, Jens Kleesiek*, Rainer Stiefelhagen*},
title = {Accurate Fine-Grained Segmentation of Human Anatomy in Radiographs via Volumetric Pseudo-Labeling},
year = {2023},
}
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