/KneeLocalizer

Codes for paper: A novel method for automatic localization of joint area on knee plain radiographs by A. Tiulpin et. al.

Primary LanguagePythonMIT LicenseMIT

Code for the paper from SCIA'17: A novel method for automatic localization of joint area on knee plain radiographs

Description

Repository contains the code for an automatic knee joint detection on plain radiographs. It can be used to process very large amount of knee X-rays and generate bounding boxes (up to 6 000 000 per day on a high-end computer).

Our package processes the data in a batch mode using multiple threads. To run in on your machine, you have to install the conda environment. For that, simply execute create_conda_env.sh.

How to run

Run the script as follows:

cd oulukneeloc
python detector.py --path_input <dir with DICOM files> \
                   --fname_output <file to write the results>

Script will produce the bounding boxes of 120mm and save it to the specified file (by default, ../detection_results.txt).

How to cite

If you use our package in your own research, please cite us:

@inproceedings{tiulpin2017novel,
  title={A novel method for automatic localization of joint area on knee plain radiographs},
  author={Tiulpin, Aleksei and Thevenot, Jerome and Rahtu, Esa and Saarakkala, Simo},
  booktitle={Scandinavian Conference on Image Analysis},
  pages={290--301},
  year={2017},
  organization={Springer}
}