改进FCM算法在肺结节自动检测中的应用研究  

Research on Application of Improved FCM Algorithm in Automatic Detection of Pulmonary Nodules

作　　者：廖璠[1] 李瑞昌[1] 刘雅琳[1] 

机构地区：[1]河南中医学院信息技术学院,河南郑州450000

出　　处：《计算机与现代化》2012年第10期41-45,共5页Computer and Modernization

摘　　要：肺结节在CT图像上特征不明显、形态各异,使用计算机进行图像处理自动检测病变区域能够提高肺结节检出率,有助于临床医生判别结节的良恶性。本文提出一种基于视觉注意模型的改进FCM的图像分割方法。实验表明,改进的FCM法应用于计算机辅助诊断中可提高医学诊断的有效性和快速性,提高病灶的检出率,为减少漏诊和误诊起到积极作用。The feature of pulmonary nodules in the CT image is not obvious,the shape and location is different.Computer-aided detection system can increase the amount of detected lung nodules and reduce the number of missed nodules,which can assist the clinicians to distinguish the benign and malignant nodules.This paper presents a new method which is FCM based on the model of visual attention image segmentation.Simulation results show that the method used in computer-aided diagnosis can improve the effectiveness of medical diagnosis,and the detection of the rate of lesions,and it plays a positive effect on the reducing of misdiagnosis and missed diagnosis.

关 键 词：模糊C均值聚类 人类视觉模型 自动检测 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]