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A new texture analysis method for classification of interstitial lung abnormalities in chest radiography

机译:一种在胸片中分类肺间质异常的新纹理分析方法

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This paper presents a new method called 'Score-Block operation', which is originally from the general image retrieval concept, with k nearest neighbour classifier for automated categorization of interstitial pattern in chest radiographs. Before this method is applied on a chest radiograph, the lung field is extracted from the image and image feature vectors for each region of interest are obtained using power spectrum and Quasi-Gabor filter. There are three problems to solve: padding of the border, quantification of the interstitial abnormalities of chest radiograph and ribs and vessel shadows of lung field. The Score-Block operation solves the first and second problems. The third problem is solved by two partition image databases (PIDB), which are normal partition image database and abnormal partition image database. PIDBs consist of all normal and abnormal partition images including other superimposed organs, so our system is not sensitive to the ribs and vessels shadow.
机译:本文提出了一种称为“得分阻止操作”的新方法,该方法最初是从一般的图像检索概念开始的,它使用k最近邻分类器对胸部X光片中的间隙图案进行自动分类。在将此方法应用于胸部X射线照片之前,先从图像中提取肺野,然后使用功率谱和准Gabor滤波器获得每个感兴趣区域的图像特征向量。要解决三个问题:边界填充,量化胸部X线照片和肋骨间质异常以及肺野的血管阴影。计分块操作解决了第一个和第二个问题。第三个问题是通过两个分区图像数据库(PIDB)解决的,它们是正常分区图像数据库和异常分区图像数据库。 PIDB由所有正常和异常的分区图像(包括其他叠加的器官)组成,因此我们的系统对肋骨和血管阴影不敏感。

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