Automatic Visual Detection of Incorrect Endoscope Adaptions in Chemical Disinfection Devices

Timo Brune, Björn Brune, Sascha Eschborn, Klaus Brinker

Abstract

This paper presents a complete analyzing system for detecting incorrect endoscope adaptions prior to the use of chemical disinfection devices to guarantee hygienic standards and to save resources. The adaptions are detected visually with the help of an image registration algorithm based on feature detection algorithms. On top of the processing pipeline, we implemented a k-nearest neighbor algorithm to predict the status of the adaption. The proposed approach shows good results in detecting the adaptions correctly.

References

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Paper Citation


in Harvard Style

Brune T., Brune B., Eschborn S. and Brinker K. (2017). Automatic Visual Detection of Incorrect Endoscope Adaptions in Chemical Disinfection Devices . In Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017) ISBN 978-989-758-213-4, pages 305-312. DOI: 10.5220/0006143003050312


in Bibtex Style

@conference{healthinf17,
author={Timo Brune and Björn Brune and Sascha Eschborn and Klaus Brinker},
title={Automatic Visual Detection of Incorrect Endoscope Adaptions in Chemical Disinfection Devices},
booktitle={Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)},
year={2017},
pages={305-312},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006143003050312},
isbn={978-989-758-213-4},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 10th International Joint Conference on Biomedical Engineering Systems and Technologies - Volume 5: HEALTHINF, (BIOSTEC 2017)
TI - Automatic Visual Detection of Incorrect Endoscope Adaptions in Chemical Disinfection Devices
SN - 978-989-758-213-4
AU - Brune T.
AU - Brune B.
AU - Eschborn S.
AU - Brinker K.
PY - 2017
SP - 305
EP - 312
DO - 10.5220/0006143003050312