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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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.
LanguageEnglish
Title of host publication2019 IEEE Sensors Conference
PublisherInstitute of Electrical and Electronics Engineers
Number of pages4
StateAccepted/In press - 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

Fingerprint

Angiography
Cameras
X rays

Cite this

İncetan, K., Mohan, R., Stoutjesdijk, H., Fernandes, N., & de Jager, B. (Accepted/In press). RGB-D camera based collision prediction and avoidance for X-ray rotational angiography. In 2019 IEEE Sensors Conference Institute of Electrical and Electronics Engineers.
İncetan, K. ; Mohan, Rishi ; Stoutjesdijk, Henry ; Fernandes, Nelson ; de Jager, Bram. / RGB-D camera based collision prediction and avoidance for X-ray rotational angiography. 2019 IEEE Sensors Conference. Institute of Electrical and Electronics Engineers, 2019.
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abstract = "Optimal clinical workflow leads to faster treatmenttimes and a potential to cater to a larger number of patients. Akey part of this is preventing collisions between moving medicalsystems and patient. For interventional environments, highspeedrotational angiography (RA) scans are prone to potentialcollisions between the C-arm X-ray system and the patient. Toensure safety, a low speed safety-run is executed before theactual high-speed scan. However, several iterations of the safetyrunare often required before a scan is collision-free leading toa suboptimal clinical work-flow. This work proposes a RGB-Dcamera based collision prediction system which detects collisionsbefore the actual RA scan. Additionally, a motion planner isdesigned to provide appropriate patient repositioning such thatthe collision is avoided. The system is introduced as a first proofof-concept to eliminate the safety-run and improve clinical safetyand workflow.",
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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 2019 IEEE Sensors Conference. Institute of Electrical and Electronics Engineers, IEEE sensors 2019, Montreal, Canada, 27/10/19.

RGB-D camera based collision prediction and avoidance for X-ray rotational angiography. / İncetan, K.; Mohan, Rishi; Stoutjesdijk, Henry; Fernandes, Nelson; de Jager, Bram.

2019 IEEE Sensors Conference. Institute of Electrical and Electronics Engineers, 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

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AU - Fernandes,Nelson

AU - de Jager,Bram

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N2 - Optimal clinical workflow leads to faster treatmenttimes and a potential to cater to a larger number of patients. Akey part of this is preventing collisions between moving medicalsystems and patient. For interventional environments, highspeedrotational angiography (RA) scans are prone to potentialcollisions between the C-arm X-ray system and the patient. Toensure safety, a low speed safety-run is executed before theactual high-speed scan. However, several iterations of the safetyrunare often required before a scan is collision-free leading toa suboptimal clinical work-flow. This work proposes a RGB-Dcamera based collision prediction system which detects collisionsbefore the actual RA scan. Additionally, a motion planner isdesigned to provide appropriate patient repositioning such thatthe collision is avoided. The system is introduced as a first proofof-concept to eliminate the safety-run and improve clinical safetyand workflow.

AB - Optimal clinical workflow leads to faster treatmenttimes and a potential to cater to a larger number of patients. Akey part of this is preventing collisions between moving medicalsystems and patient. For interventional environments, highspeedrotational angiography (RA) scans are prone to potentialcollisions between the C-arm X-ray system and the patient. Toensure safety, a low speed safety-run is executed before theactual high-speed scan. However, several iterations of the safetyrunare often required before a scan is collision-free leading toa suboptimal clinical work-flow. This work proposes a RGB-Dcamera based collision prediction system which detects collisionsbefore the actual RA scan. Additionally, a motion planner isdesigned to provide appropriate patient repositioning such thatthe collision is avoided. The system is introduced as a first proofof-concept to eliminate the safety-run and improve clinical safetyand workflow.

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İncetan K, Mohan R, Stoutjesdijk H, Fernandes N, de Jager B. RGB-D camera based collision prediction and avoidance for X-ray rotational angiography. In 2019 IEEE Sensors Conference. Institute of Electrical and Electronics Engineers. 2019.