Automatic setup deviation measurements with electronic portal images for pelvic fields

被引:14
作者
Girouard, LM
Pouliot, J
Maldague, X
Zaccarin, A
机构
[1] Ctr Hosp Univ Quebec, Dept Radiat oncol, Quebec City, PQ G1R 2J6, Canada
[2] Univ Laval, Comp Vis & Syst Lab, Dept Elect Engn & Comp Engn, Laval, PQ G1K 7P4, Canada
关键词
prostate treatment; electronic portal imaging; image processing; automatic verification algorithm;
D O I
10.1118/1.598296
中图分类号
R8 [特种医学]; R445 [影像诊断学];
学科分类号
1002 ; 100207 ; 1009 ;
摘要
The purpose of this work was to develop a fully automatic tool for the detection of setup deviation for small pelvic fields using, in external beam radiotherapy, an electronic portal imaging device (EPID). The algorithm processes electronic portal images of prostate cancer patients. No fiducial points or user interventions are needed. Deviation measurements are based on bone edge detection performed with the Laplacian of a Gaussian (LoG) operator. Two bone edge images are then correlated, one of which is a reference image taken as the first fraction image for the purpose of this study. The electronic portal images (EPI) also show band artefacts which are removed using the morphological top-hat transform. The algorithm was first validated with 59 phantom images acquired in clinical treatment conditions with known displacements. The algorithm was then validated with 79 clinical images where bone contours were delineated manually. For the phantom images, the setup deviations were measured with an absolute mean error of 0.59 mm and 0.47 mm with a standard deviation of 0.64 mm and 0.42 mm, horizontally and vertically, respectively. A second validation was performed using clinical prostate cancer images. The measured patient displacements have an absolute mean error of 0.48 mm and 1.41 mm with a standard deviation of 0.58 mm and 1.30 mm in the X and Y directions, respectively, The algorithm execution time on a SUN workstation is 5 a. This algorithm shows good potential as a setup deviation measurement tool in clinical practice. The possibility of using this algorithm combined with decision rules based on statistical observations is very promising. (C) 1998 American Association of Physicists in Medicine.
引用
收藏
页码:1180 / 1185
页数:6
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