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CT texture analysis using the filtration-histogram method: what do the measurements mean?

机译:使用过滤直方图方法进行CT纹理分析:测量值是什么意思?

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摘要

Analysis of texture within tumours on computed tomography (CT) is emerging as a potentially useful tool in assessing prognosis and treatment response for patients with cancer. This article illustrates the image and histological features that correlate with CT texture parameters obtained from tumours using the filtration-histogram approach, which comprises image filtration to highlight image features of a specified size followed by histogram analysis for quantification. Computer modelling can be used to generate texture parameters for a range of simple hypothetical images with specified image features. The model results are useful in explaining relationships between image features and texture parameters. The main image features that can be related to texture parameters are the number of objects highlighted by the filter, the brightness and/or contrast of highlighted objects relative to background attenuation, and the variability of brightness/contrast of highlighted objects. These relationships are also demonstrable by texture analysis of clinical CT images. The results of computer modelling may facilitate the interpretation of the reported associations between CT texture and histopathology in human tumours. The histogram parameters derived during the filtration-histogram method of CT texture analysis have specific relationships with a range of image features. Knowledge of these relationships can assist the understanding of results obtained from clinical CT texture analysis studies in oncology.
机译:在计算机断层扫描(CT)上分析肿瘤内的纹理正在成为评估癌症患者预后和治疗反应的潜在有用工具。本文介绍了使用过滤直方图方法与从肿瘤获得的CT纹理参数相关的图像和组织学特征,该方法包括图像过滤以突出显示指定大小的图像特征,然后进行直方图分析以进行量化。计算机建模可用于为具有指定图像特征的一系列简单假设图像生成纹理参数。模型结果对于解释图像特征和纹理参数之间的关系很有用。可以与纹理参数相关的主要图像特征是过滤器突出显示的对象数量,突出显示的对象相对于背景衰减的亮度和/或对比度以及突出显示的对象的亮度/对比度的可变性。通过临床CT图像的纹理分析也可以证明这些关系。计算机建模的结果可能有助于解释人肿瘤中CT纹理与组织病理学之间报道的关联。在CT纹理分析的过滤直方图方法期间得出的直方图参数与一系列图像特征具有特定的关系。这些关系的知识可以帮助理解从肿瘤学中的临床CT纹理分析研究获得的结果。

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