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首页> 外文期刊>電子情報通信学会技術研究報告. 医用画像. Medical Imaging >Computerized characterization of contrast enhancement patterns for classifying pulmonary nodules based on dynamic CT images
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Computerized characterization of contrast enhancement patterns for classifying pulmonary nodules based on dynamic CT images

机译:基于动态CT图像的肺结节分类对比增强模式的计算机表征

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This paper presents a computerized classification scheme of pulmonary nodules in contrast enhanced dynamic CT images. Conventionally, we extracted 3-D nodule images by using a deformable surface model. However, there was a limit in segmenting the 3-D nodule images contacted with vessels and bronchi. In order to improve the segmentation accuracy of the 3-D nodule images, we developed a software tool to eliminate the leaked region of the 3-D nodule image due to vessels and bronchi interactively. Using our data set including 68 cases (28 benign and 40 malignant cases), we demonstrate how the segmentation accuracy affects the classification accuracy of our scheme.
机译:本文提出了增强的动态CT图像对比中肺结节的计算机分类方案。按照惯例,我们使用可变形表面模型提取3-D结节图像。但是,分割与血管和支气管接触的3D结节图像是有局限性的。为了提高3D结节图像的分割精度,我们开发了一种软件工具来消除3D结节图像由于血管和支气管的相互作用而泄漏的区域。使用包括68例(28例良性和40例恶性病例)的数据集,我们演示了分割精度如何影响我们方案的分类精度。

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