孤立性肺结节CT影像的计算机视觉分析  

Computer vision analysis of solitary pulmonary nodules for CT imaging

作　　者：李鹤虹[1] 郑长煌[1] 罗良平[1] 黄力[1] 

机构地区：[1]暨南大学临床医学博士后流动站,广东广州510632

出　　处：《暨南大学学报（自然科学与医学版）》2011年第4期415-418,共4页Journal of Jinan University(Natural Science & Medicine Edition)

基　　金：广东省社会发展科技计划项目(2010B031600104);广东省中医药局科技项目(2010366);2010年中央高校基本科研业务费专项资金项目(11609416)

摘　　要：目的:探讨电子计算机视觉分析对孤立性肺结节的诊断价值。方法:89例经手术病理证实的肺部结节电子计算机断层扫描(CT)图像经过形态学滤波以及二次图像分割,进行标准哈夫(Hough)函数变换,以提取的计算机视觉特征数据来研究孤立性肺结节的影像诊断。结果:恶性结节的最大极径(MaxRho)为(141.79±8.332),良性结节的MaxRho为(83.27±18.35),两者有统计学差异(t=2.339,P=0.02)。恶性结节的峰值为(232.33±26.73),良性结节的峰值为(93.60±22.34),两者有统计学的明显差异(t=4.433,P=0.005)。肺恶性结节的欧拉数为(9.87±2.57),良性结节为(4.18±1.32),两者有统计学的明显差异(t=4.523,P=0.003)。结论:经受试者工作特征(ROC)曲线分析,计算机视觉分析对孤立性肺结节的鉴别具有较高的诊断价值。Aim：To discuss the diagnostic value of the characteristics of computer vision for the solitary pulmonary nodules.Methods： 89 cases of solitary pulmonary nodules confirmed by pathology were selected along with the CT image data obtained under high resolution scan.All cases were processed with multivariant mophological filtering and double segmentation.These characteristics of computer vision were used to distinguish magnetic nodules from the benign nodules after Hough function transformation and skeleton extraction.Results： The data of MaxRho indicated that the MaxRho value of cancerous nodules was（141.79±8.332） and that of benign nodules was（83.27±18.35）,The data has statistical significance（t=2.339,P=0.02）.The Max-valley-sum of magnetic malignant nodules and benign nodules was（232.33±26.73） and（93.60±22.34） respectively（t=4.433,P=0.005）.The value of Eul of cancerous and benign nodules were（9.87±2.57） and（4.18±1.32） respectively（t=4.523,P=0.003）.Conclusion：The diagnostic accuracy of these index were evaluated by receiver operator characteristic curve（ROC） analysis.The characteristics of computer vision,included MaxRho,Max-valley-sum,and eul number can be used to distinguish malignant nodules from benign nodules.

关 键 词：肺结节 诊断 哈夫转换 计算机断层扫描 

分 类 号：R765[医药卫生—耳鼻咽喉科]