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首页> 外文期刊>Journal of Medical Engineering >Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity
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Markerless Lung Tumor Motion Tracking by Dynamic Decomposition of X-Ray Image Intensity

机译:X射线图像强度动态分解的无标记肺肿瘤运动跟踪

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We propose a new markerless tracking technique of lung tumor motion by using an X-ray fluoroscopic image sequence for real-time image-guided radiation therapy (IGRT). A core innovation of the new technique is to extract a moving tumor intensity component from the fluoroscopic image intensity. The fluoroscopic intensity is the superimposition of intensity components of all the structures passed through by the X-ray. The tumor can then be extracted by decomposing the fluoroscopic intensity into the tumor intensity component and the others. The decomposition problem for more than two structures is ill posed, but it can be transformed into a well-posed one by temporally accumulating constraints that must be satisfied by the decomposed moving tumor component and the rest of the intensity components. The extracted tumor image can then be used to achieve accurate tumor motion tracking without implanted markers that are widely used in the current tracking techniques. The performance evaluation showed that the extraction error was sufficiently small and the extracted tumor tracking achieved a high and sufficient accuracy less than 1 mm for clinical datasets. These results clearly demonstrate the usefulness of the proposed method for markerless tumor motion tracking.
机译:我们通过使用X射线荧光透视图像序列进行实时图像引导放射治疗(IGRT),提出了一种新的无标记物跟踪肺肿瘤运动的技术。新技术的核心创新是从荧光图像强度中提取运动中的肿瘤强度成分。荧光强度是X射线穿过的所有结构的强度分量的叠加。然后可以通过将荧光强度分解为肿瘤强度成分和其他成分来提取肿瘤。涉及两个以上结构的分解问题是不适当的,但可以通过暂时累积分解运动的肿瘤成分和其余强度成分必须满足的约束条件,将其转化为位置良好的分解问题。然后,提取的肿瘤图像可用于实现精确的肿瘤运动跟踪,而无需植入在当前跟踪技术中广泛使用的标记。性能评估表明,对于临床数据集,提取误差足够小,并且提取的肿瘤追踪达到了小于1mm的足够高的准确度。这些结果清楚地证明了所提出的方法对于无标记肿瘤运动跟踪的有用性。

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