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首页> 外文期刊>Pattern Recognition: The Journal of the Pattern Recognition Society >Computer aided erosions and osteophytes detection based on hand radiographs
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Computer aided erosions and osteophytes detection based on hand radiographs

机译:基于手部射线照相的计算机辅助侵蚀和骨赘检测

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摘要

In this paper we present a computer system to detect erosions and osteophytes from hand radiographs, the most common symptoms of rheumatic diseases. The designed, implemented and verified algorithm uses techniques of image processing, image analysis and pattern recognition. In the stages of image processing and image analysis, the locations of metacarpal bones, the outlines of finger bones, the locations and outlines of joints and finally the borders of joint surfaces are identified. In the pattern recognition stage, a shape description language is used for each border of the joint surface to detect the locations of erosions and osteophytes on hand radiographs. The presented algorithm expands on those known from the literature, because besides erosions it also detects osteophytes. Moreover, in contrast to previous systems, it analyses proximal interphalangeal joints and distal interphalangeal joints. The obtained results are satisfactory and very promising. The joints are successfully located in 983% of cases. The average mean distance between the borders pointed out by radiologists and obtained from the system varies between 0.094 mm and 0.157 mm, while the sensitivity and the specificity equal around 70% in most of the cases. Therefore, it can become a basis for the diagnosis of certain diseases. (C) 2015 Elsevier Ltd. All rights reserved.
机译:在本文中,我们介绍了一种计算机系统,可从手部X光片(风湿病最常见的症状)中检测出糜烂和骨赘。设计,实施和验证的算法使用图像处理,图像分析和模式识别技术。在图像处理和图像分析的阶段,确定掌骨的位置,手指骨骼的轮廓,关节的位置和轮廓以及关节表面的边界。在模式识别阶段,将形状描述语言用于关节表面的每个边界,以检测手部X射线照片上的糜烂和骨赘的位置。提出的算法是对文献中已知算法的扩展,因为除了侵蚀之外,它还可以检测骨赘。此外,与以前的系统相比,它可以分析近端指间关节和远端指间关节。所获得的结果令人满意并且非常有希望。在983%的病例中成功定位了关节。放射线学家指出并从系统获得的边界之间的平均平均距离在0.094毫米至0.157毫米之间变化,而在大多数情况下,灵敏度和特异性约为70%。因此,它可以成为诊断某些疾病的基础。 (C)2015 Elsevier Ltd.保留所有权利。

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