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Research on Technologies of Computer Aided Diagnosis for Solitary Pulmonary Nodule Based on CT Images

机译:基于CT图像的孤立性肺结节计算机辅助诊断技术研究

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The paper proposed an algorithm for detecting solitary pulmonary nodules. It can achieve a good distinction between pulmonary nodules and non-nodules. And the algorithm can improve the accuracy of the subsequent classification of pulmonary nodules. We use the DICOM standard chest CT sequential images in the LIDC-IDRI image library as objects investigated. The results show that the method of this study achieves a good preliminary classification between real pulmonary nodules and non-nodules. The sensitivity of the result is 96.0%, the specificity is 96.55%, the false-positive rate is 2.30%, the false-negative rate is 6.0%. Among these indexes, the most important index is specificity. In contrast the existing method, specificity can improve 3% to 4%.
机译:本文提出了一种检测孤立性肺结节的算法。它可以在肺结节和非结节之间达到良好的区别。并且该算法可以提高随后分类的肺结节分类的准确性。我们在LIDC-IDRI图像库中使用DICOM标准胸部CT顺序图像作为调查的对象。结果表明,该研究的方法实现了真实肺结核和非结节之间的良好初步分类。结果的灵敏度为96.0%,特异性为96.55%,假阳性率为2.30%,假负率为6.0%。在这些指标中,最重要的指数是特异性。相反,现有方法,特异性可以提高3%至4%。

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