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

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

doi:10.1109/SENSORS43011.2019.8956899

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 proceeding › Conference contribution › Academic › peer-review

2 Citations (Scopus)

462 Downloads (Pure)

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 language	English
Title of host publication	Proceedings of IEEE Sensors Conference 2019
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers
Number of pages	4
ISBN (Electronic)	978-1-7281-1634-1
DOIs	https://doi.org/10.1109/SENSORS43011.2019.8956899
Publication status	Published - Oct 2019
Event	18th IEEE Sensors Conference, SENSORS 2019 - Palais des Congres de Montreal, Montreal, Canada Duration: 27 Oct 2019 → 30 Oct 2019 https://ieee-sensors2019.org/

Conference

Conference	18th IEEE Sensors Conference, SENSORS 2019
Country/Territory	Canada
City	Montreal
Period	27/10/19 → 30/10/19
Internet address	https://ieee-sensors2019.org/

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10.1109/SENSORS43011.2019.8956899

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title = "RGB-D camera based collision prediction and avoidance for X-ray rotational angiography",

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.",

author = "K. İncetan and Rishi Mohan and Henry Stoutjesdijk and Nelson Fernandes and \{de Jager\}, Bram",

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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 Proceedings of IEEE Sensors Conference 2019., 8956899, Institute of Electrical and Electronics Engineers, Piscataway, 18th IEEE Sensors Conference, SENSORS 2019, Montreal, Canada, 27/10/19. https://doi.org/10.1109/SENSORS43011.2019.8956899

RGB-D camera based collision prediction and avoidance for X-ray rotational angiography. / İncetan, K.; Mohan, Rishi; Stoutjesdijk, Henry et al.
Proceedings of IEEE Sensors Conference 2019. Piscataway: Institute of Electrical and Electronics Engineers, 2019. 8956899.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - Mohan, Rishi

AU - Stoutjesdijk, Henry

AU - Fernandes, Nelson

AU - de Jager, Bram

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AB - 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.

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M3 - Conference contribution

BT - Proceedings of IEEE Sensors Conference 2019

PB - Institute of Electrical and Electronics Engineers

CY - Piscataway

T2 - 18th IEEE Sensors Conference, SENSORS 2019

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ER -

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

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RGB-D camera-based clinical workflow optimization for rotational angiography

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