(Sunday, 7/14/2019)
Room: ePoster Forums
Purpose: This work presents initial assessment of optical motion monitoring system using Raspberry Pi® computer and CMU Pixy2® image sensors. Such monitoring system could be used for real time patient motion monitoring during SBRT/SRS/SRT as an inexpensive alternative to the currently used external patient motion monitoring systems.
Methods: Raspberry Pi computer, two Pixy2 image sensors and a 3D-printed BB on a precision moving platform were used to assess the sensitivity, precision and accuracy of this motion monitoring system. Pixy2 image sensor has a frame rate of 60 Hz and uses a color-based filtering algorithm to detect objects. A colored BB was placed on the precision moving platform to be detected by Pixy2 camera, and two such image sensors were placed at different angle (ideally orthogonal) with respect to each other in order to detect BB motion in all 3 directions.
Results: Observed accuracy/precision of the camera was ~0.4/0.4mm for the system when the distance between the image sensor and BB was 10cm; and ~1.8/2.0mm when the distance was 30cm. The detection of the BB by the image sensor was strongly dependent on the lighting conditions, and for the different distances between the BB and cameras parameters of the image sensors had to be tweaked in order to get best possible BB detection by the algorithm.
Conclusion: As expected, higher precision/accuracy for this motion monitoring system is observed with smaller distances between the image sensors and BBs, so for the best results camera should be positioned as close as possible to the BB. The accuracy and precision of this system allows it to be used as a cost-effective and easy-to-use external motion monitoring device when there is no other system available in the clinic, and when patient motion could cause adverse dosimetric effects, i.e. during highly conformal treatments like SRS/SBRT.
Keywords
Patient Movement, Image Visualization
Taxonomy
TH- External beam- photons: Motion management (intrafraction)
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