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首页> 外文期刊>Computerized Medical Imaging and Graphics: The Official Jounal of the Computerized Medical Imaging Society >Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT.
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Computer-aided differentiation of malignant from benign solitary pulmonary nodules imaged by high-resolution CT.

机译:高分辨率CT成像对恶性与良性孤立性肺结节的计算机辅助鉴别。

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摘要

We investigated the possibility of using computer analysis of high-resolution CT images to radiologically classify the shape of pulmonary nodules. From a total of 107 HRCT images of solid, solitary pulmonary nodules with prior differentiation as benign (n=55) or malignant (n=52), we extracted the desired pulmonary nodules and calculated two quantitative parameters for characterizing nodules: circularity and second central moment. Using discriminant analysis for two thresholds in differentiating malignant from benign states resulted in a sensitivity of 76.9%, a specificity of 80%, a positive predictive value of 78.4%, and a negative predictive value of 78.6%.
机译:我们调查了使用高分辨率CT图像的计算机分析对肺结节的形状进行放射学分类的可能性。从总共107例先天分化为良性(n = 55)或恶性(n = 52)的实性,孤立性肺结节的HRCT图像中,我们提取了所需的肺结节并计算了两个表征结节的定量参数:圆度和第二中心时刻。对两个阈值进行判别分析以区分恶性与良性状态,其敏感性为76.9%,特异性为80%,阳性预测值为78.4%,阴性预测值为78.6%。

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