A real‐time respiratory motion monitoring system using <scp>KINECT</scp>: Proof of concept

Xia, Jie; Siochi, R

doi:10.1118/1.4704644

Cited by 88 publications

(67 citation statements)

References 3 publications

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“…Kinect sensors can identify the motion of phantoms and volunteers, particularly periodic respiratory motion 8 , 11 . Our future work includes a patient study where the Kinect v2 system will be assessed as an alternative to visual monitoring for a voluntary breathing hold method for breast cancer patients (21) .…”

Section: Discussionmentioning

confidence: 99%

“…Whilst these provide no information about the internal anatomy of the patient, they may be used in conjunction with ionizing radiation imaging to provide frequent or continuous monitoring throughout the radiation delivery, as they do not contribute to the radiation dose burden. Recently some groups have investigated surface monitoring for radiotherapy and PET imaging using consumer‐grade sensors designed for the entertainment industry — the Microsoft Kinect devices 7 , 8 , 9 , 10 , 11 , 12 , 13 , 14 , 15 . The potential advantage of commercial off‐the‐shelf (COTS) devices is the low cost (less than

~ $ 1,400

for a Kinect device and accessories compared to upwards of $250,000 for the commercial medical systems), thus enabling many sensors in many rooms, depending on the application.…”

Section: Introductionmentioning

confidence: 99%

“…Hsu et al (16) demonstrated the important of assessing EMI for real‐time ultrasound tracking during radiotherapy delivery. Previous proof of concept reports of Kinect systems in radiotherapy have not provided any information or data on the effect of EMI due to the operation of the linear accelerator, or the need for USB 3.0 active (repeater) cables which are required to carry the signal from Kinect v2 sensors beyond 3 meters 7 , 8 , 9 , 10 , 11 , 12 . Robustness to EMI, and operation at a distance, are necessary for these sensors to be a feasible option for real‐time monitoring from the control area during radiation delivery for radiotherapy treatment.…”

Section: Introductionmentioning

confidence: 99%

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The feasibility of using Microsoft Kinect v2 sensors during radiotherapy delivery

Edmunds

Bashforth

Tahavori

et al. 2016

J Applied Clin Med Phys

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Consumer‐grade distance sensors, such as the Microsoft Kinect devices (v1 and v2), have been investigated for use as marker‐free motion monitoring systems for radiotherapy. The radiotherapy delivery environment is challenging for such sensors because of the proximity to electromagnetic interference (EMI) from the pulse forming network which fires the magnetron and electron gun of a linear accelerator (linac) during radiation delivery, as well as the requirement to operate them from the control area. This work investigated whether using Kinect v2 sensors as motion monitors was feasible during radiation delivery. Three sensors were used each with a 12 m USB 3.0 active cable which replaced the supplied 3 m USB 3.0 cable. Distance output data from the Kinect v2 sensors was recorded under four conditions of linac operation: (i) powered up only, (ii) pulse forming network operating with no radiation, (iii) pulse repetition frequency varied between 6 Hz and 400 Hz, (iv) dose rate varied between 50 and 1450 monitor units (MU) per minute. A solid water block was used as an object and imaged when static, moved in a set of steps from 0.6 m to 2.0 m from the sensor and moving dynamically in two sinusoidal‐like trajectories. Few additional image artifacts were observed and there was no impact on the tracking of the motion patterns (root mean squared accuracy of 1.4 and 1.1 mm, respectively). The sensors’ distance accuracy varied by 2.0 to 3.8 mm (1.2 to 1.4 mm post distance calibration) across the range measured; the precision was 1 mm. There was minimal effect from the EMI on the distance calibration data: 0 mm or 1 mm reported distance change (2 mm maximum change at one position). Kinect v2 sensors operated with 12 m USB 3.0 active cables appear robust to the radiotherapy treatment environment.PACS number(s): 87.53 JW, 87.55 N‐, 87.63 L‐

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Section: Discussionmentioning

confidence: 99%

~ $ 1,400

for a Kinect device and accessories compared to upwards of $250,000 for the commercial medical systems), thus enabling many sensors in many rooms, depending on the application.…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

The feasibility of using Microsoft Kinect v2 sensors during radiotherapy delivery

Edmunds

Bashforth

Tahavori

et al. 2016

J Applied Clin Med Phys

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show abstract

“…Previous research into respiratory motion tracking using the Kinect utilized either the Kinect v1 or required a translational marker to be placed on the patient's surface or embedded within clothing worn by the patient,9, 10, 11 similar to other respiratory tracking systems currently available for purchase. The latest version of the Kinect contains higher resolution sensors than the previous model, which helps remove the requirement for a translational marker to track respiratory motion.…”

Section: Introductionmentioning

confidence: 99%

Comparative analysis of respiratory motion tracking using Microsoft Kinect v2 sensor

Silverstein

Snyder

2018

J Applied Clin Med Phys

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PurposeTo present and evaluate a straightforward implementation of a marker‐less, respiratory motion‐tracking process utilizing Kinect v2 camera as a gating tool during 4DCT or during radiotherapy treatments.MethodsUtilizing the depth sensor on the Kinect as well as author written C# code, respiratory motion of a subject was tracked by recording depth values obtained at user selected points on the subject, with each point representing one pixel on the depth image. As a patient breathes, specific anatomical points on the chest/abdomen will move slightly within the depth image across pixels. By tracking how depth values change for a specific pixel, instead of how the anatomical point moves throughout the image, a respiratory trace can be obtained based on changing depth values of the selected pixel. Tracking these values was implemented via marker‐less setup. Varian's RPM system and the Anzai belt system were used in tandem with the Kinect to compare respiratory traces obtained by each using two different subjects.ResultsAnalysis of the depth information from the Kinect for purposes of phase‐ and amplitude‐based binning correlated well with the RPM and Anzai systems. Interquartile Range (IQR) values were obtained comparing times correlated with specific amplitude and phase percentages against each product. The IQR time spans indicated the Kinect would measure specific percentage values within 0.077 s for Subject 1 and 0.164 s for Subject 2 when compared to values obtained with RPM or Anzai. For 4DCT scans, these times correlate to less than 1 mm of couch movement and would create an offset of 1/2 an acquired slice.ConclusionBy tracking depth values of user selected pixels within the depth image, rather than tracking specific anatomical locations, respiratory motion can be tracked and visualized utilizing the Kinect with results comparable to that of the Varian RPM and Anzai belt.

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“…Xia et al showed that a respiratory curve was measured from depth image taken by Kinect v1 [16]. They evaluated the cross correlation coefficients between detected respiratory curves by a Kinect and a strain gauge system.…”

Section: Introductionmentioning

confidence: 99%

Markerless Respiratory Motion Tracking Using Single Depth Camera

Kumagai¹,

Uemura²,

Ishibashi³

et al. 2016

OJMI

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The aim of this study is to propose a novel system that has an ability to detect intra-fractional motion during radiotherapy treatment in real-time using three-dimensional surface taken by a depth camera, Microsoft Kinect v1. Our approach introduces three new aspects for three-dimensional surface tracking in radiotherapy treatment. The first aspect is a new algorithm for noise reduction of depth values. Ueda's algorithm was implemented and enabling a fast least square regression of depth values. The second aspect is an application for detection of patient's motion at multiple points in thracoabdominal regions. The third aspect is an estimation of three-dimensional surface from multiple depth values. For evaluation of noise reduction by Ueda's algorithm, two respiratory patterns are measured by the Kinect as well as a laser range meter. The resulting cross correlation coefficients between the laser range meter and the Kinect were 0.982 for abdominal respiration and 0.995 for breath holding. Moreover, the mean cross correlation coefficients between the signals of our system and the signals of Anzai with respect to participant's respiratory motion were 0.90 for thoracic respiration and 0.93 for abdominal respiration, respectively. These results proved that the performance of the developed system was comparable to existing motion monitoring devices. Reconstruction of three-dimensional surface also enabled us to detect the irregular motion and breathing arrest by comparing the averaged depth with predefined threshold values.

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A real‐time respiratory motion monitoring system using KINECT: Proof of concept

Abstract: It is feasible to use the KINECT for respiratory motion tracking. Traces are similar to those of a clinically used strain gauge system. The KINECT-based system provides a new and economical way to monitor respiratory motion.

Cited by 88 publications

References 3 publications

The feasibility of using Microsoft Kinect v2 sensors during radiotherapy delivery

The feasibility of using Microsoft Kinect v2 sensors during radiotherapy delivery

Comparative analysis of respiratory motion tracking using Microsoft Kinect v2 sensor

Markerless Respiratory Motion Tracking Using Single Depth Camera

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