Skin Lesion Classification System Using Shearlets

作     者：S.Mohan Kumar T.Kumanan 

作者机构：Department of Computer Science and EngineeringMeenakshi Academy of Higher Education and ResearchChennai600078Tamil NaduIndia 

出 版 物：《Computer Systems Science & Engineering》 (计算机系统科学与工程（英文）)

年 卷 期：2023年第44卷第1期

页      面：833-844页

核心收录：

学科分类：0810[工学-信息与通信工程] 0808[工学-电气工程] 08[工学] 0802[工学-机械工程] 0701[理学-数学] 0811[工学-控制科学与工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The authors received no specific funding for this study 

主　　题：Skin lesion classification non-subsampled shearlet transform sub-band coefficients energy feature support vector machine 

摘      要：The main cause of skin cancer is the ultraviolet radiation of the *** spreads quickly to other body ***,early diagnosis is required to decrease the mortality rate due to skin *** this study,an automatic system for Skin Lesion Classification(SLC)using Non-Subsampled Shearlet Transform(NSST)based energy features and Support Vector Machine(SVM)classifier is ***,the NSST is used for the decomposition of input skin lesion images with different directions like 2,4,8 and *** the NSST’s sub-bands,energy fea-tures are extracted and stored in the feature database for *** classifier is used for the classification of skin lesion *** dermoscopic skin images are obtained from PH^(2) database which comprises of 200 dermoscopic color images with melanocytic *** performances of the SLC system are evaluated using the confusion matrix and Receiver Operating Characteristic(ROC)*** SLC system achieves 96%classification accuracy using NSST’s energy fea-tures obtained from 3^(rd) level with 8-directions.