Program Information
Evaluation of a Real-Time Positioning Assistance Simulator System for Skull Radiography Using the Microsoft Kinect
T Kurata1*, M Ono1 , K Kozono1 , R Fukuyoshi1 , S Sato1 , F Toyofuku2 , (1) Department of Health Sciences, Graduate School of Medical Sciences, Kyushu University, Fukuoka, Japan, (2) Department of Health Sciences,Faculty of Medical Sciences, Kyushu University, Fukuoka, Japan
Presentations
SU-E-J-66 Sunday 3:00PM - 6:00PM Room: Exhibit HallPurpose:
The purpose of this study is to investigate the feasibility of a low cost, small size positioning assistance simulator system for skull radiography using the Microsoft Kinect sensor. A conventional radiographic simulator system can only measure the three-dimensional coordinates of an x-ray tube using angle sensors, but not measure the movement of the subject. Therefore, in this study, we developed a real-time simulator system using the Microsoft Kinect to measure both the x-ray tube and the subject, and evaluated its accuracy and feasibility by comparing the simulated and the measured x-ray images.
Methods:
This system can track a head phantom by using Face Tracking, which is one of the functions of the Kinect. The relative relationship between the Kinect and the head phantom was measured and the projection image was calculated by using the ray casting method, and by using three-dimensional CT head data with 220 slices at 512 x 512 pixels. X-ray images were thus obtained by using a computed radiography (CR) system. We could then compare the simulated projection images with the measured x-ray images from 0 degrees to 45 degrees at increments of 15 degrees by calculating the cross correlation coefficient C.
Results:
The calculation time of the simulated projection images was almost real-time (within 1 second) by using the Graphics Processing Unit(GPU). The cross-correlation coefficients C are: 0.916; 0.909; 0.891; and, 0.886 at 0, 15, 30, and 45 degrees, respectively. As a result, there were strong correlations between the simulated and measured images.
Conclusion:
This system can be used to perform head positioning more easily and accurately. It is expected that this system will be useful for learning radiographic techniques by students. Moreover, it could also be used for predicting the actual x-ray image prior to x-ray exposure in clinical environments.
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