改进的模糊c均值聚类算法用于肺结节的自动检测

2015 8th International Congress on Image and Signal Processing (CISP) Pub Date : 2015-10-01 DOI:10.1109/CISP.2015.7407925

Fan Liao, Chunxia Zhao

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引用次数: 1

摘要

肺结节在CT图像上的图像特征不明显，形状和位置不同。计算机辅助检测系统可以提高肺结节的检出率，降低错误率，有助于临床医生区分良恶性结节。提出了一种基于人类视觉注意模型的改进模糊c均值(FCM)方法。仿真结果表明了该方法在计算机辅助诊断中的效果。

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Improved fuzzy c-means clustering algorithm for automatic detection of lung nodules

The image features of pulmonary nodules in the CT image are inconspicuous, the shape and location is different. Computer-aided detection system can increase the detection rate of lung nodules and reduce the error rate, which can assist the clinicians to distinguish between benign and malignant nodules. This paper presents an improved fuzzy c-means (FCM) method based on the human visual attention model. The simulation result shows the effects of the new method used in computer-aided diagnosis.

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来源期刊

2015 8th International Congress on Image and Signal Processing (CISP)

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