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首页> 外文期刊>Medical Physics >Evaluation of cost functions for gray value matching of two-dimensional images in radiotherapy.
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Evaluation of cost functions for gray value matching of two-dimensional images in radiotherapy.

机译:放射治疗中二维图像灰度值匹配的成本函数评估。

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摘要

In external beam radiotherapy, portal imaging is applied for verification of the patient setup. Current automatic methods for portal image registration, which are often based on segmentation of anatomical structures, are especially successful for images of the pelvic region. For portal images of more complicated anatomical structures, e.g., lung, these techniques are less successful. It is desirable to have a method for image registration that is applicable for a wide range of treatment sites. In this study, a registration method for two-dimensional (2D) registration of portal and reference images based on intensity values was tested on portal images of various anatomical sites. Tests were performed with and without preprocessing (unsharp mask filtering followed by histogram equalization) for 96 image pairs and six cost functions. The images were obtained from treatments of the rectum, salivary gland, brain, prostate, and lung. To get insight into the behavior of the various cost functions, cost function values were computed for each portal image for 20,000 transformations of the corresponding reference image, translating the reference image in a range of +/- 1 cm and rotating +/- 10 degrees with respect to the clinical match. The automatic match was defined as the transformation associated with the global minimum (found by an exhaustive search). Without preprocessing, the registration reliability was low (less than 27%). With preprocessing, about 90% of the matches were successful, with a difference with our gold standard (manual registration) of about 1 mm and 1 degree SD. All tested cost functions performed similarly. However, the number of local minima using mutual information was larger than for the other tested cost functions. A cost function based on the mean product of the corresponding pixel values had the least number of local minima. In conclusion, gray value based registration of portal images is applicable for a wide range of treatment sites. However, pre-processing of the images is essential.
机译:在外部束放射治疗中,门静脉成像用于验证患者设置。当前用于门户图像配准的自动方法通常基于解剖结构的分割,对于骨盆区域的图像尤其成功。对于更复杂的解剖结构(例如肺)的门静脉图像,这些技术不太成功。希望有一种适用于广泛治疗部位的图像配准方法。在这项研究中,基于强度值的门户和参考图像的二维(2D)配准方法在各种解剖部位的门户图像上进行了测试。对96个图像对和六个成本函数在有无预处理的情况下进行了测试(不清晰的蒙版过滤,然后进行直方图均衡)。这些图像是从直肠,唾液腺,脑,前列腺和肺的治疗中获得的。为了深入了解各种成本函数的行为,针对每个门户网站图像计算了成本函数值,以进行对应参考图像的20,000次转换,在+/- 1 cm的范围内平移参考图像并旋转+/- 10度关于临床匹配。自动匹配定义为与全局最小值相关联的转换(通过详尽搜索找到)。如果不进行预处理,则注册可靠性较低(不到27%)。通过预处理,大约90%的比赛成功了,与我们的黄金标准(手动配准)相差约1毫米和1度SD。所有测试的成本函数的执行情况相似。但是,使用共有信息的局部极小值的数量大于其他经过测试的成本函数的数量。基于相应像素值的平均积的成本函数具有最少的局部最小值。总之,基于灰度值的门户图像配准适用于广泛的治疗部位。但是,图像的预处理是必不可少的。

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