Abstract Although lung cancer is one of the leading causes of cancer deaths worldwide, the chances of survival are higher in the early stages. One of the best tools for diagnosis is computerized tomography. The main problem with this method is that it depends directly on the specialist who is analyzing the image, since the process involved is tiring, and can lead to error. Computer-aided detection systems have emerged as a way to help these specialists. This work presents the use of descriptors based on functional diversity indexes to reduce the number of false positives. Our method can reach an accuracy of 97.73%, a sensitivity of 98.4%, Kappa index of 0.941, and a number of false positives per scan of up to three. Based on the results obtained, the use of a functional diversity index is shown to be a robust method that can be used in a real CAD system.

中文翻译：

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使用功能多样性的计算机断层扫描图像中肺结节的纹理分析

摘要 尽管肺癌是全球癌症死亡的主要原因之一，但早期的生存机会更高。诊断的最佳工具之一是计算机断层扫描。这种方法的主要问题是它直接取决于分析图像的专家，因为所涉及的过程很累，并且可能导致错误。计算机辅助检测系统已成为帮助这些专家的一种方式。这项工作介绍了使用基于功能多样性指数的描述符来减少误报的数量。我们的方法可以达到 97.73% 的准确度、98.4% 的灵敏度、0.941 的 Kappa 指数，以及每次扫描的误报数量高达 3。根据获得的结果，