Pulmonary nodule detection using chest CT images
Pulmonary nodule detection using chest CT images
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DOI：
10.1034/j.1600-0455.2003.00061.x
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发表时间：
2003-05-01
期刊：
影响因子：
1.3
通讯作者：
Park, JW
中科院分区：
文献类型：
--
作者：
Kim, DY;Kim, JH;Park, JW
目的：材料和方法：采用灰度阈值法从背景中分割出胸腔，然后从胸壁和纵隔中分割出肺实质。采用可变形模型分割肺边界，并与阈值分割法的分割结果进行比较。从分割的肺实质中提取具有高灰度值的病变。所选病变包括结节、血管和部分容积效应。根据所选病灶的大小、实性、平均值、标准差和相关系数等鉴别特征来区分真结节和假结节。利用真实结节的纹理特征，跟踪分割的肺边界的轮廓跟踪方法被应用于检测邻近胸膜表面的近胸膜结节。对每个确定的结节进行体积和圆度计算。识别的结节按体积降序排列。结果：计算机辅助诊断肺结节检出率为96%，无假阳性。结论：计算机辅助诊断方法对肺结节的检出有一定的实用价值，并能反映出肺结节的特征。
Purpose: Automated methods for the detection of pulmonary nodules and nodule volume calculation on CT are described.Material and Methods: Gray-level threshold methods were used to segment the thorax from the background and then the lung parenchyma from the thoracic wall and mediastinum. A deformable model was applied to segment the lung boundaries, and the segmentation results were compared with the thresholding method. The lesions that had high gray values were extracted from the segmented lung parenchyma. The selected lesions included nodules, blood vessels and partial volume effects. The discriminating features such as size, solid shape, average, standard deviation and correlation coefficient of selected lesions were used to distinguish true nodules from pseudolesions. With texture features of true nodules, the contour-following method, which tracks the segmented lung boundaries, was applied to detect juxtapleural nodules that were contiguous to the pleural surface. Volume and circularity calculations were performed for each identified nodule. The identified nodules were sorted in descending order of volume. These methods were applied to 827 image slices of 24 cases.Results: Computer-aided diagnosis gave a nodule detection sensitivity of 96% and no false-positive findings.Conclusion: The computer-aided diagnosis scheme was useful for pulmonary nodule detection and gave characteristics of detected nodules.