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},
}