基于模板匹配和相似度测量的肺结节检测

Onder Demir, A. Çamurcu
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引用次数: 0

摘要

在这项研究中,我们开发了一种计算机辅助检测系统(CAD)来检测计算机断层扫描图像上的肺结节。采用模板匹配和相似度度量方法对图像预处理技术提取的感兴趣区域是否为节点候选区域进行检验。强度阈值法、距离阈值法和邻域分析是已开发的CAD系统的预处理技术。计算Pearson相关系数、简单匹配系数、Jaccard系数、欧几里得距离和Sokal & Sneath相似系数来衡量候选结节与模板之间的相似度。最后给出了CAD的灵敏度和每片假阳性数。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Lung nodule detection using template matching and similarity measurement
In this study, we developed a computer aided detection system (CAD) to detect lung nodules on computed tomography images. Template matching and similarity measurement methods used for examine whether region of interest which extracted using image pre-processing techniques are nodule candidate. Intensity thresholding, distance thresholding, neighbourhood analysis are preprocessing techniques of the developed CAD system. Pearson's correlation coefficient, simple matching coefficient, Jaccard's coefficient, Euclidean Distance and Sokal & Sneath similarity coeeficient calculated to measure similarity between nodule candidate and the template. Sensitivity of the CAD and number of false positives per slice are given in conclusion.
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