Texture Feature Extraction from Thyroid MR Imaging Using High-Order Derived Mean CLBP

作     者：Zhe Liu Cheng-Jian Qiu Yu-Qing Song Xiao-Hong Liu Juan Wang Victor S.Sheng 

作者机构：School of Computer Science and TelecommunicationJiangsu UniversityZhenjiang 212013China Department of Computer ScienceUniversity of Central ArkansasArkansas 72035U.S.A. 

出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报（英文版）)

年 卷 期：2019年第34卷第1期

页      面：35-46页

核心收录：

学科分类：12[管理学] 1201[管理学-管理科学与工程(可授管理学、工学学位)] 08[工学] 

基　　金：the National Natural Science Foundation of China under Grant Nos_61728205,61772242,61402204, and 61572239 the Natural Science Foundation of Jiangsu Province of China under Grant No.BK20130529 the Research Fund for Advanced Talents of Jiangsu University of China under Grant No.14JDG141 the Science and Technology Project of Zhenjiang City of China under Grant No.SH20140110 the Special Software Development Foundation of Zhenjiang City of China under Grant No.201322 the Science and Technology Support Foundation of Zhenjiang City (Industrial)under Grant No.GY2014013 

主　　题：thyroid magnetic resonance imaging (MRI) local binary pattern texture feature complete local binary pattern (CLBP) 

摘      要：In the field of medical imaging,the traditional local binary pattern (LBP)and its improved algorithms are often sensitive to *** LBPs are solely based on the signal information from local differences,and the binary quantization method oversimplifies the local texture features while disregarding the imaging information from the concaveconvex regions between the high-order pixels and the neighboring sampling ***,we propose an improved Derived Mean Complete Local Binary Pattern (DM_CLBP) algorithm based on high-order *** the DM_CLBP method,the grey value of a single pixel is replaced by the mean grey value of the rectangular area block,and the difference between pixel values in the area is obtained using the second-order differentiation *** on the calculation concept of the complete local binary pattern (CLBP)algorithm,the cascade signs and magnitudes of the two components are encoded and recombined in DM_CLBP using a uniform *** results from the experiments showed that the proposed DM_CLBP descriptors achieved a classification accuracy of 94.4%.Compared with LBP and other improved algorithms,the DM_CLBP algorithm presented in this study can effectively differentiate between lesion areas and normal areas in thyroid MR,(magnetic resonance)images and shows the improved accuracy of area classification.