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An automated method for comparing motion artifacts in cine four‐dimensional computed tomography images

机译:一种用于在电影四维计算机断层扫描图像中比较运动伪影的自动方法

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The aim of this study is to develop an automated method to objectively compare motion artifacts in two four‐dimensional computed tomography (4D CT) image sets, and identify the one that would appear to human observers with fewer or smaller artifacts. Our proposed method is based on the difference of the normalized correlation coefficients between edge slices at couch transitions, which we hypothesize may be a suitable metric to identify motion artifacts. We evaluated our method using ten pairs of 4D CT image sets that showed subtle differences in artifacts between images in a pair, which were identifiable by human observers. One set of 4D CT images was sorted using breathing traces in which our clinically implemented 4D CT sorting software miscalculated the respiratory phase, which expectedly led to artifacts in the images. The other set of images consisted of the same images; however, these were sorted using the same breathing traces but with corrected phases. Next we calculated the normalized correlation coefficients between edge slices at all couch transitions for all respiratory phases in both image sets to evaluate for motion artifacts. For nine image set pairs, our method identified the 4D CT sets sorted using the breathing traces with the corrected respiratory phase to result in images with fewer or smaller artifacts, whereas for one image pair, no difference was noted. Two observers independently assessed the accuracy of our method. Both observers identified 9 image sets that were sorted using the breathing traces with corrected respiratory phase as having fewer or smaller artifacts. In summary, using the 4D CT data of ten pairs of 4D CT image sets, we have demonstrated proof of principle that our method is able to replicate the results of two human observers in identifying the image set with fewer or smaller artifacts. PACS number: 87.57.cp; 87.57.N‐
机译:这项研究的目的是开发一种自动方法,以客观地比较两个四维计算机断层扫描(4D CT)图像集中的运动伪像,并识别出伪影更少或较小的人类观察者。我们提出的方法基于沙发过渡处边缘切片之间的归一化相关系数之差,我们认为这可能是识别运动伪影的合适度量。我们使用十对4D CT图像集评估了我们的方法,这些图像集显示了一对图像之间伪影的细微差别,这可由人类观察者识别。使用呼吸轨迹对一组4D CT图像进行了分类,其中我们临床上实现的4D CT分类软件对呼吸相位进行了错误计算,这预计会导致图像中出现伪影。另一组图像由相同的图像组成。但是,这些呼吸是使用相同的呼吸轨迹但经过校正的阶段进行分类的。接下来,我们在两个图像集中所有呼吸阶段的所有沙发过渡处,在边缘切片之间计算归一化相关系数,以评估运动伪影。对于九个图像集,我们的方法确定了使用呼吸迹线和经过校正的呼吸相位进行分类的4D CT集,从而产生的伪像更少或更少,而对于一个图像对,则没有差异。两名观察员独立评估了我们方法的准确性。两位观察者都确定了9个图像集,这些图像集使用具有校正的呼吸相位的呼吸迹线进行了分类,具有较少或较小的伪影。总之,使用十对4D CT图像集的4D CT数据,我们已经证明了原理证明,即我们的方法能够复制两个人类观察者的结果,以识别具有更少或更少伪像的图像集。 PACS编号:87.57.cp; 87.57。

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