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基于模糊速度函数的活动轮廓模型的肺结节分割
引用本文:陈侃, 李彬, 田联房. 基于模糊速度函数的活动轮廓模型的肺结节分割. 自动化学报, 2013, 39(8): 1257-1264. doi: 10.3724/SP.J.1004.2013.01257
作者姓名:陈侃  李彬  田联房
作者单位:1.华南理工大学自动化科学与工程学院 广州 510640
基金项目:国家自然科学基金(61273249);广东省自然科学基金(S2012010009886,S2011010005811);教育部高等学校博士学科点专项科研基金资助项目(200805610018);粤港关键领域重点突破项目(佛山2010Z11);华南理工大学国家人体组织功能重建工程技术研究中心以及广东省生物医学工程重点实验室资助课题;自主系统与网络控制教育部重点实验室资助~~
摘    要:肺结节是肺癌在早期阶段的表现形式. 利用计算机辅助诊断(Computer-aided diagnosis, CAD)技术对血管粘连型肺结节和磨玻璃型肺结节进行检测, 需要对这两类肺结节进行准确的分割. 目前基于传统活动轮廓模型的肺结节分割算法, 存在边界泄露现象. 对此, 本文提出一种基于模糊速度函数的活动轮廓模型的肺结节分割算法. 首先, 采用结合灰度特征和局部形态特征的模糊聚类算法, 计算模糊速度函数中的模糊隶属度; 其次, 将模糊速度函数引入到活动轮廓模型中, 在肺结节的边界处, 该速度函数为零, 轮廓曲线停止演变, 从而完成肺结节的分割. 实验结果表明, 本文提出的算法可以精确地分割血管粘连肺结节和磨玻璃型肺结节.

关 键 词:肺结节分割   计算机辅助诊断   活动轮廓模型   模糊速度函数   模糊聚类算法
收稿时间:2012-06-18
修稿时间:2012-10-31

A Segmentation Algorithm of Pulmonary Nodules Using Active Contour Model Based on Fuzzy Speed Function
CHEN Kan, LI Bin, TIAN Lian-Fang. A Segmentation Algorithm of Pulmonary Nodules Using Active Contour Model Based on Fuzzy Speed Function. ACTA AUTOMATICA SINICA, 2013, 39(8): 1257-1264. doi: 10.3724/SP.J.1004.2013.01257
Authors:CHEN Kan  LI Bin  TIAN Lian-Fang
Affiliation:1. School of Automation Science and Engineering, South China University of Technology, Guangzhou 510640
Abstract:Pulmonary nodules are potential manifestation of lung cancer. In order to detect juxta-vascular pulmonary nodules and ground glass opacity pulmonary nodules in computer-aided diagnosis (CAD) system, the above two types of pulmonary nodules need to be accurately segmented. At present, the segmentation algorithm of pulmonary nodules using traditional active contour model may cause boundary leakage. In order to avoid this phenomenon, a new segmentation algorithm of pulmonary nodules using active contour model based on fuzzy speed function is proposed in this paper. First, the fuzzy membership degree in fuzzy speed function is calculated by using the fuzzy clustering algorithm, which uses gray feature and local shape index. Second, a fuzzy speed function is incorporated into the active contour model. At the boundary of pulmonary nodules, tbe fuzzy speed function equals zero and the evolution of the contour curve stops, so that the accurate segmentation of pulmonary nodules is completed. Experimental results show that the proposed algorithm can achieve accurate segmentation of juxta-vascular pulmonary nodules and ground glass opacity pulmonary nodules.
Keywords:Pulmonary nodules segmentation  computer-aided diagnosis (CAD)  active contour model  fuzzy speed function  fuzzy clustering algorithm
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