Technical Note: Determination of the optimized image processing and template matching techniques for a patient intrafraction motion monitoring system

Abstract

In this work, the authors determine the optimal template matching method and selection of pixel data for use in a system for monitoring patient intrafraction motion. The motion monitoring system is based on optical tracking of a marker block placed on the patient. The temporal resolution of the system was evaluated with a respiratory motion phantom. The phantom moved the marker with a peak-to-peak amplitude of 0.6-4.0 cm and a period of 1, 3, and 6 s. Three template matching methods were applied: Sum of squared difference (SSD), sum of absolute difference (SAD), and normalized cross-correlation (NCC) using each of four pixel color data schemes (RGB and gray level modified by one of three image processing steps). An in-house algorithm called auto region-of-interest (AutoROI) automatically reset the marker detection region-of-interest to improve the calculation speed. RGB and gray level temporal resolutions were 54.22 ± 10.81 (1 SD) s and 12.70 ± 3.87 (1 SD) s, respectively. The temporal resolution when using SSD and SAD was higher than when using NCC. Positional accuracy was within 1 mm. Both values were within the tolerance specified by AAPM Task Group 142. To avoid misidentification of the marker, a threshold-based self-validation within the marker recognition system was implemented and was found to improve the tracking of motion with a high amplitude and short period. An intrafraction motion monitoring system using SSD or SAD and applied to gray pixel data can achieve high temporal resolution and positional accuracy.