Patient positioning method based on binary image correlation between two edge images for proton-beam radiation therapy

• Published in: Medical physics (Lancaster) 2005-10, Vol.32 (10), p.3106-3111
• Main Authors: Sawada, Akira, Yoda, Kiyoshi, Numano, Masumi, Futami, Yasuyuki, Yamashita, Haruo, Murayama, Shigeyuki, Tsugami, Hironobu
• Format: Article
• Language: English
• Subjects: ACCURACY; ALGORITHMS; Artificial Intelligence; BEAM POSITION; Canny edge; ERRORS; HEAD; Humans; Image Enhancement - methods; Image Interpretation, Computer-Assisted - methods; IMAGE PROCESSING; LUNGS; normalized binary image correlation; patient positioning; PATIENTS; Pattern Recognition, Automated - methods; Posture; PROTON BEAMS; Protons - therapeutic use; RADIOLOGY AND NUCLEAR MEDICINE; RADIOTHERAPY; Radiotherapy - methods; Radiotherapy, Computer-Assisted - methods; Reproducibility of Results; Sensitivity and Specificity; Signal Processing, Computer-Assisted; SIMULATION; Statistics as Topic; Subtraction Technique; VALIDATION; X RADIATION
• ISSN: 0094-2405; 2473-4209
• DOI: 10.1118/1.2042247

A new technique based on normalized binary image correlation between two edge images has been proposed for positioning proton-beam radiotherapy patients. A Canny edge detector was used to extract two edge images from a reference x-ray image and a test x-ray image of a patient before positioning. While translating and rotating the edged test image, the absolute value of the normalized binary image correlation between the two edge images is iteratively maximized. Each time before rotation, dilation is applied to the edged test image to avoid a steep reduction of the image correlation. To evaluate robustness of the proposed method, a simulation has been carried out using 240 simulated edged head front-view images extracted from a reference image by varying parameters of the Canny algorithm with a given range of rotation angles and translation amounts in x and y directions. It was shown that resulting registration errors have an accuracy of one pixel in x and y directions and zero degrees in rotation, even when the number of edge pixels significantly differs between the edged reference image and the edged simulation image. Subsequently, positioning experiments using several sets of head, lung, and hip data have been performed. We have observed that the differences of translation and rotation between manual positioning and the proposed method were within one pixel in translation and one degree in rotation. From the results of the validation study, it can be concluded that a significant reduction in workload for the physicians and technicians can be achieved with this method.