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利用极值统计分析CT图像上的条纹伪影。

Analysis of streak artefacts on CT images using statistics of extremes.

作者信息

Imai K, Ikeda M, Wada S, Enchi Y, Niimi T

机构信息

Department of Radiological Technology, Nagoya University School of Health Sciences, 1-20 Daikominami 1-chome, Higashi-ku, Nagoya 461-8673, Japan.

出版信息

Br J Radiol. 2007 Nov;80(959):911-8. doi: 10.1259/bjr/93741044.

Abstract

We have analysed the statistical characteristics of streak artefacts on CT images using the statistics of extremes, and have devised a new method of evaluating streak artefacts on CT images. The CT images of four polymer tubes placed on the chest wall of a commercially available chest phantom were used as the target objects for our analysis. 40 parallel line segments with a length of 20 pixels were placed perpendicular to numerous streak artefacts on the polymer tube image, and the largest difference between adjacent CT values in each of the 40 CT value profiles of these line-segments was employed as a feature variable of a streak artefact; these feature variables have been analysed by extreme value theory. Using the mean rank method, a Gumbel distribution was shown to be the most suitable extreme value distribution for the largest difference between adjacent CT values in each CT value profile. This enabled us to demonstrate that the streak artefacts on CT images can be statistically modelled by a Gumbel distribution. Both the location parameter and the scale parameter of the estimated Gumbel probability density distribution were large on the CT slices in which the shoulder bone or liver was included.

摘要

我们使用极值统计分析了CT图像上条纹伪影的统计特征,并设计了一种评估CT图像上条纹伪影的新方法。将放置在市售胸部体模胸壁上的四个聚合物管的CT图像用作我们分析的目标对象。在聚合物管图像上,垂直于众多条纹伪影放置40条长度为20像素的平行线段,并将这些线段的40个CT值剖面中每个剖面相邻CT值之间的最大差值用作条纹伪影的特征变量;这些特征变量已通过极值理论进行分析。使用平均秩方法,对于每个CT值剖面中相邻CT值之间的最大差值,耿贝尔分布被证明是最合适的极值分布。这使我们能够证明CT图像上的条纹伪影可以用耿贝尔分布进行统计建模。在包含肩胛骨或肝脏的CT切片上,估计的耿贝尔概率密度分布的位置参数和尺度参数都很大。

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