Kanazawa K, Kawata Y, Niki N, Satoh H, Ohmatsu H, Kakinuma R, Kaneko M, Moriyama N, Eguchi K
Department of Optical Science, University of Tokushima, Japan.
Comput Med Imaging Graph. 1998 Mar-Apr;22(2):157-67. doi: 10.1016/s0895-6111(98)00017-2.
In this paper, we present a computer-assisted automatic diagnostic system for lung cancer that detects nodule candidates at an early stage from helical CT images of the thorax. Our diagnostic system consists of analytical and diagnostic procedures. In the analytical procedure, first we extract the lung and the pulmonary blood vessel regions using the fuzzy clustering algorithm, then we analyze the features of these regions using image-processing techniques. In the diagnostic procedure, we define diagnostic rules utilizing the extracted features which support the determination of the candidate nodule locations. We show the effectiveness of our system by giving the results from its application to image data for mass screening of 450 patients.
在本文中，我们提出了一种用于肺癌的计算机辅助自动诊断系统，该系统可从胸部螺旋CT图像中早期检测出候选结节。我们的诊断系统由分析和诊断程序组成。在分析程序中，首先我们使用模糊聚类算法提取肺部和肺血管区域，然后使用图像处理技术分析这些区域的特征。在诊断程序中，我们利用提取的特征定义诊断规则，以支持确定候选结节的位置。我们通过给出该系统应用于450例患者大规模筛查图像数据的结果，展示了我们系统的有效性。
