A structure-based method for on-line matching of portal images for an optimal patient set-up in radiotherapy

F. Kreuder , B. Schreiber , C. Kausch , O. Dössel
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引用次数: 10

Abstract

In radiotherapy, portal images are used to ensure a correct patient position during every radiation session. A reliable on-line verification is of clinical interest to interrupt the radiation in time in case the patient is not at the right position. A great problem for successful image registration is the poor image quality of portal images. They are corrupted by noise and of very low contrast. A method directly based on the grey levels is not sufficient. Therefore a structure-based method was developed which is almost insensitive to distrubances (air bubbles, noise, slowly varying grey levels). In most cases the selection of a region of interest (ROI) can be omitted. Besides the automatical segmentation of the radiation field, only the structures relevant for matching the anatomy are enhanced by using a bandpass filter. It is possible to detect the maximum correlation between different image modalities reliably (simulator image, digitally reconstructed radiograph, portal image). By using Fast Fourier Transformation (FFT), the calculation time is smaller than five seconds, which enables a clinical on-line verification. We have matched 1139 pairs of images of different modalities and various regions of the body (pelvis, nasopharyngeal space, head, lung). The success rate is greater than 95%.

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一种基于结构的门静脉图像在线匹配方法,用于放射治疗中的最佳患者设置
在放射治疗中,门静脉图像用于确保每次放射治疗期间患者的正确位置。一个可靠的在线验证是临床感兴趣的,以便在病人不在正确的位置时及时中断辐射。门户网站图像质量差是影响图像配准成功的一大问题。它们被噪声破坏,对比度很低。直接基于灰度的方法是不够的。因此,开发了一种基于结构的方法,该方法对干扰(气泡、噪声、缓慢变化的灰度)几乎不敏感。在大多数情况下,可以省略感兴趣区域(ROI)的选择。除了对辐射场进行自动分割外,还使用带通滤波器对与解剖匹配相关的结构进行增强。可以可靠地检测不同图像模式之间的最大相关性(模拟器图像,数字重建x线片,门静脉图像)。通过快速傅里叶变换(FFT),计算时间小于5秒,可实现临床在线验证。我们匹配了1139对不同形态和身体不同区域(骨盆、鼻咽间隙、头部、肺部)的图像。成功率大于95%。
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