基于改进多尺度LBP算法的肝脏CT图像特征提取方法  

Liver CT Image Feature Extraction Method Based on Improved Multi-scale LBP Algorithm

作　　者：刘晓虹 朱玉全[1] 刘哲[1] 宋余庆[1] 朱彦 袁德琪 LIU Xiao-hong;ZHU Yu-quan;LIU Zhe;SONG Yu-qing;ZHU Yan;YUAN De-qi(Department of Computer Science and Communication Engineering,University of Jiangsu,Zhenjiang,Jiangsu 212000,China)

机构地区：[1]江苏大学计算机科学与通信工程学院,江苏镇江212000

出　　处：《计算机科学》2019年第3期125-130,共6页Computer Science

基　　金：国家自然科学基金(61772242;61572239);国家自然科学基金青年基金(61402204);江苏大学高级人才科研启动基金(14JDG141);中国博士后面上项目(2017M611737);镇江市社会发展项目(SH2016029);镇江市卫生计生科技重点项目(SHW2017019);江苏高校"青蓝工程"资助

摘　　要：针对高阶方向导数局部二值模式(DLBP)算法会丢失部分高尺度邻域信息的缺陷,提出一种基于改进多尺度LBP算法(MSLBP)的肝脏CT图像特征提取方法。该方法首先对肝脏CT图像进行预处理,并提取正异常ROI区域,然后利用改进的多尺度LBP特征提取方法提取特征,将高阶尺度采样点信息融合其邻域相关点信息作为该采样点的最终信息参与运算,同时利用对角线区域求平均操作,突出了邻域像素点之间的关系特征,从更大范围描述肝脏图像的纹理信息,最后进行分类。实验结果表明:所提方法的准确率可达到90.1%,相比原始的LBP特征提取方法提高了8.7%,有一定的临床应用意义,可用于医生的辅助诊断。Liver cancer,Malignant liver tumors,can be divided into primary and secondary categories.Recent census data prove that the current annual mortality of liver cancer has ranked third in the world.The diagnosis of early liver di- sease is beneficial to the treatment of liver cancer.The local binary pattern(LBP) algorithm has been widely used in the diagnosis of liver lesions.Although the traditional LBP method is simple,efficient,and easy to understand,but it lacks multi-scale information which leads to incomplete information description and lack of key information.In view of the defect that high order directional derivative local binary pattern(DLBP) algorithm will lose key information,extended multi-scale LBP algorithm(MSLBP) was proposed.The method firstly preprocesses the liver CT image to extract ROI region,then uses the extended multi-scale LBP feature extraction method to extract features.This method fuses the high-order sampling point information with its neighboring point information as the final information of the sampling point to participate in the operation.At the same time,the operation of averaging the diagonal regions highlights the neighborhood and describes the texture information of the liver image from a larger range.Finally,the classification algorithm is executed.The experimental results show that the accuracy of the proposed method can reach 90.1%,which is 8.7% higher than the original LBP feature extraction method.It has certain clinical application significance and can be used to help doctors diagnose.In the image preprocessing section,since medical images are different from natural images,the DICOM images gotten from hospital cannot be used directly.The first step of image preprocessing is to set Pixel Padding Value to zero.The second step of image preprocessing is converting pixel values to CT values using the equation 7 in section 2.1 according to header file information of the DICOM image.Then,an improved multi-scale LBP feature extraction was performed.The multi-scale feature is extract

关 键 词：特征提取 局部二值模式 多尺度 纹理分析 医学图像 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]