一种融合表面波变换与脉冲耦合神经网络的三维肺实质分割算法  

An algorithm for three-dimensional plumonary parenchymal segmentation by integrating surfacelet transform with pulse coupled neural network

作　　者：张华海 白培瑞 郭子杨 杜令豪 李昶 任延德[2] 杨凯 刘庆一 ZHANG Huahai;BAI Peirui;GUO Ziyang;DU Linghao;LI Chang;REN Yande;YANG Kai;LIU Qingyi(College of Electronic and Information Engineering,Shandong University of Science and Technology,Qingdao,Shandong 266590,P.R.China;Department of Radiology,Affiliated Hospital of Qingdao University,Qingdao,Shandong 265000,P.R.China)

机构地区：[1]山东科技大学电子信息工程学院,山东青岛266590 [2]青岛大学附属医院放射科,山东青岛265000

出　　处：《生物医学工程学杂志》2020年第4期630-640,共11页Journal of Biomedical Engineering

基　　金：国家自然科学基金资助项目(61471225)。

摘　　要：针对肺部病变及支气管干扰等因素导致的肺实质分割困难的问题,本文提出一种融合表面波(surfacelet)变换与脉冲耦合神经网络(PCNN)的肺实质分割算法。首先,通过surfacelet变换对三维肺部计算机断层扫描数据进行多尺度多方向分解,利用局部修正拉普拉斯算子选择处理后的子带系数增强图像的边缘特征;然后,经surfacelet逆变换得到增强后的图像作为PCNN的反馈输入;最后,通过循环迭代完成肺实质的分割。所提算法对公开数据集中的样本进行了测试。结果表明,本文算法的分割性能优于surfacelet变换边缘提取算法、三维区域生长算法和三维U形网络(U-NET)算法,能够有效抑制肺部病变及支气管的干扰,得到更完整的肺实质图像。In order to overcome the difficulty in lung parenchymal segmentation due to the factors such as lung disease and bronchial interference,a segmentation algorithm for three-dimensional lung parenchymal is presented based on the integration of surfacelet transform and pulse coupled neural network(PCNN).First,the three-dimensional computed tomography of lungs is decomposed into surfacelet transform domain to obtain multi-scale and multidirectional sub-band information.The edge features are then enhanced by filtering sub-band coefficients using local modified Laplacian operator.Second,surfacelet inverse transform is implemented and the reconstructed image is fed back to the input of PCNN.Finally,iteration process of the PCNN is carried out to obtain final segmentation result.The proposed algorithm is validated on the samples of public dataset.The experimental results demonstrate that the proposed algorithm has superior performance over that of the three-dimensional surfacelet transform edge detection algorithm,the three-dimensional region growing algorithm,and the three-dimensional U-NET algorithm.It can effectively suppress the interference coming from lung lesions and bronchial,and obtain a complete structure of lung parenchyma.

关 键 词：三维医学图像分割 表面波变换 脉冲耦合神经网络 肺实质分割 

分 类 号：TP183[自动化与计算机技术—控制理论与控制工程] TP391.41[自动化与计算机技术—控制科学与工程] R816.41[医药卫生—放射医学]