RGB-D camera based collision prediction and avoidance for X-ray rotational angiography

K. İncetan, Rishi Mohan, Henry Stoutjesdijk, Nelson Fernandes, Bram de Jager

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Abstract

Optimal clinical workflow leads to faster treatment
times and a potential to cater to a larger number of patients. A
key part of this is preventing collisions between moving medical
systems and patient. For interventional environments, highspeed
rotational angiography (RA) scans are prone to potential
collisions between the C-arm X-ray system and the patient. To
ensure safety, a low speed safety-run is executed before the
actual high-speed scan. However, several iterations of the safetyrun
are often required before a scan is collision-free leading to
a suboptimal clinical work-flow. This work proposes a RGB-D
camera based collision prediction system which detects collisions
before the actual RA scan. Additionally, a motion planner is
designed to provide appropriate patient repositioning such that
the collision is avoided. The system is introduced as a first proofof-
concept to eliminate the safety-run and improve clinical safety
and workflow.
Original languageEnglish
Title of host publicationProceedings of IEEE Sensors Conference 2019
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Number of pages4
ISBN (Electronic)978-1-7281-1634-1
DOIs
Publication statusPublished - Oct 2019
EventIEEE sensors 2019 - Palais des Congres de Montreal, Montreal, Canada
Duration: 27 Oct 201930 Oct 2019
https://ieee-sensors2019.org/

Conference

ConferenceIEEE sensors 2019
CountryCanada
CityMontreal
Period27/10/1930/10/19
Internet address

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  • Cite this

    İncetan, K., Mohan, R., Stoutjesdijk, H., Fernandes, N., & de Jager, B. (2019). RGB-D camera based collision prediction and avoidance for X-ray rotational angiography. In Proceedings of IEEE Sensors Conference 2019 [8956899] Piscataway: Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/SENSORS43011.2019.8956899