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Diagnosis of lung nodule using semivariogram and geometric measures in computerized tomography images.

机译:在计算机断层扫描图像中使用半变异函数和几何测量来诊断肺结节。

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摘要

This paper uses the geostatistical function - semivariogram and a set of 3D geometric measures - sphericity index, convexity index, extrinsic and intrinsic curvature index and surface type, to characterize lung nodules as malignant or benign in computerized tomography images. Based on a sample of 31 nodules, 25 benign and 6 malignant, these methods are first analyzed individually and then jointly, with techniques for classification and analysis (stepwise discriminant analysis, leave-one-out and ROC curve). We have concluded that the individual measures and their combinations produce good results in the diagnosis of lung nodules.
机译:本文使用地统计学功能-半变异函数和一组3D几何度量-球形度,凸度指数,外在和固有曲率指数以及表面类型,将肺结节表征为计算机断层扫描图像中的恶性或良性。基于31个结节,25个良性和6个恶性肿瘤的样本,首先对这些方法进行单独分析,然后再结合分类和分析技术(逐步判别分析,留一法和ROC曲线)进行分析。我们得出的结论是,在肺结节的诊断中,单独的措施及其组合可产生良好的结果。

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