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Application of the iris filter for automatic detection of pulmonary nodules on computed tomography images.

机译:虹膜过滤器在计算机断层扫描图像上自动检测肺结节的应用。

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摘要

We have developed a computer-aided diagnosis (CAD) system to detect pulmonary nodules on thin-slice helical computed tomography (CT) images. We have also investigated the capability of an iris filter to discriminate between nodules and false-positive findings. Suspicious regions were characterized with features based on the iris filter output, gray level and morphological features, extracted from the CT images. Functions calculated by linear discriminant analysis (LDA) were used to reduce the number of false-positives. The system was evaluated on CT scans containing 77 pulmonary nodules. The system was trained and evaluated using two completely independent data sets. Results for a test set, evaluated with free-response receiver operating characteristic (FROC) analysis, yielded a sensitivity of 80% at 7.7 false-positives per scan.
机译:我们已经开发了一种计算机辅助诊断(CAD)系统,可以在薄层螺旋计算机断层扫描(CT)图像上检测肺结节。我们还研究了虹膜过滤器区分结节和假阳性结果的能力。可疑区域的特征是基于从CT图像中提取的虹膜滤光片输出,灰度和形态特征。通过线性判别分析(LDA)计算的函数用于减少假阳性的数量。该系统在包含77个肺结节的CT扫描中进行了评估。使用两个完全独立的数据集对系统进行了培训和评估。用自由响应接收器工作特性(FROC)分析评估的测试集结果在每次扫描7.7个假阳性时产生80%的灵敏度。

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