Modified Differential Box Counting in Breast Masses for Bioinformatics Applications

作     者：S.Sathiya Devi S.Vidivelli 

作者机构：University College of Engineering-BIT CampusTrichyIndia Anna UniversityChennaiTamilnaduIndia 

出 版 物：《Computers, Materials & Continua》 (计算机、材料和连续体（英文）)

年 卷 期：2022年第70卷第2期

页      面：3049-3066页

核心收录：

学科分类：1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

主　　题：Breast cancer computer-aided diagnosis K-nearest neighbour mammograms modified differential box counting support vector machine 

摘      要：Breast cancer is one of the common invasive cancers and stands at second position for death after lung *** present research work is useful in image processing for characterizing shape and gray-scale *** proposed Modified Differential Box Counting(MDBC)extract Fractal features such as Fractal Dimension(FD),Lacunarity,and Succolarity for shape *** traditional DBC method,the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different *** problem is overcome by the proposedMDBCmethod that uses box over counting and under counting that covers the whole image with required *** MDBC method,the suitable box size selection and Under Counting Shifting rule computation handles over counting *** advantage of the model is that the proposed MDBC work with recently developed methods showed that our method outperforms automatic detection and *** extracted features are fed to K-Nearest Neighbour(KNN)and Support Vector Machine(SVM)categorizes the mammograms into normal,benign,and *** method is tested on mini MIAS datasets yields good results with improved accuracy of 93%,whereas the existing FD,GLCM,Texture and Shape feature method has 91%accuracy.