首页> 外文期刊>Physics in medicine and biology. >Computerized method for estimation of the location of a lung tumor on EPID cine images without implanted markers in stereotactic body radiotherapy.
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Computerized method for estimation of the location of a lung tumor on EPID cine images without implanted markers in stereotactic body radiotherapy.

机译:在立体定向身体放疗中无需植入标记物的情况下,在EPID电影图像上评估肺部肿瘤位置的计算机化方法。

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The purpose of this study was to develop a computerized method for estimation of the location of a lung tumor in cine images on an electronic portal imaging device (EPID) without implanted markers during stereotactic body radiotherapy (SBRT). Each tumor region was segmented in the first EPID cine image, i.e., reference portal image, based on a multiple-gray level thresholding technique and a region growing technique, and then the image including the tumor region was cropped as a 'tumor template' image. The tumor location was determined as the position in which the tumor template image took the maximum cross-correlation value within each consecutive portal image, which was acquired in cine mode on the EPID in treatment. EPID images with 512 x 384 pixels (pixel size: 0.56 mm) were acquired at a sampling rate of 0.5 frame s(-1) by using energies of 4, 6 or 10 MV on linear accelerators. We applied our proposed method to EPID cine images (226 frames) of 12 clinical cases (ages: 51-83, mean: 72) with a non-small cell lung cancer. As a result, the average location error between tumor points obtained by our method and the manual method was 1.47 +/- 0.60 mm. This preliminary study suggests that our method based on the tumor template matching technique might be feasible for tracking the location of a lung tumor without implanted markers in SBRT.
机译:这项研究的目的是开发一种计算机化方法,用于在立体定向放射疗法(SBRT)期间在不植入标记物的电子门禁成像设备(EPID)上估计电影图像中肺部肿瘤的位置。基于多灰度级阈值化技术和区域生长技术,在第一张EPID电影图像(即参考门图像)中分割每个肿瘤区域,然后将包含肿瘤区域的图像裁剪为“肿瘤模板”图像。将肿瘤位置确定为肿瘤模板图像在每个连续的门脉图像内取最大互相关值的位置,该位置在治疗模式下在EPID上以电影模式获取。通过在线性加速器上使用4、6或10 MV的能量,以0.5帧s(-1)的采样率获取具有512 x 384像素(像素大小:0.56 mm)的EPID图像。我们将我们提出的方法应用于12例非小细胞肺癌临床病例(年龄:51-83,平均值:72)的EPID电影图像(226帧)。结果,通过我们的方法和手动方法获得的肿瘤点之间的平均位置误差为1.47 +/- 0.60 mm。这项初步研究表明,我们基于肿瘤模板匹配技术的方法对于在SBRT中无需植入标记物的情况下追踪肺部肿瘤的位置可能是可行的。

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