计算机与现代化Issue(10)：41-45,5.DOI:10.3969/j.issn.1006-2475.2012.10.012
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
廖璠 1李瑞昌 1刘雅琳1
作者信息
- 1. 河南中医学院信息技术学院,河南郑州450000
- 折叠
摘要
Abstract
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 13 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 misdiag-nosis and missed diagnosis.关键词
模糊C均值聚类/人类视觉模型/自动检测Key words
fuzzy C-means clustering/ human visual attention model/ computer-aided detection分类
信息技术与安全科学引用本文复制引用
廖璠,李瑞昌,刘雅琳..改进FCM算法在肺结节自动检测中的应用研究[J].计算机与现代化,2012,(10):41-45,5.
