Enhanced Nature Inspired-Support Vector Machine for Glaucoma Detection

作     者：Jahanzaib Latif Shanshan Tu Chuangbai Xiao Anas Bilal Sadaqat Ur Rehman Zohaib Ahmad 

作者机构：Engineering Research Center of Intelligent Perception and Autonomous ControlFaculty of Information TechnologyBeijing University of Technology100124BeijingChina College of Information Science TechnologyHainan Normal UniversityHainan ProvinceHaikou571158China Department of Computer ScienceUniversity of SalfordManchesterUK Faculty of Information Technology Beijing University of Technology Chaoyang DistrictBeijingChina 

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

年 卷 期：2023年第76卷第7期

页      面：1151-1172页

核心收录：

学科分类：0710[理学-生物学] 1002[医学-临床医学] 1001[医学-基础医学(可授医学、理学学位)] 08[工学] 0836[工学-生物工程] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：supported in part by the Beijing Natural Science Foundation(No.4212015) China Ministry of Education-China Mobile Scientific Research Foundation(No.MCM20200102) 

主　　题：Glaucoma detection grey golf optimization support vector machine feature extraction image classification 

摘      要：Glaucoma is a progressive eye disease that can lead to blindness if left *** detection is crucial to prevent vision loss,but current manual scanning methods are expensive,time-consuming,and require specialized *** study presents a novel approach to Glaucoma detection using the Enhanced Grey Wolf Optimized Support Vector Machine(EGWO-SVM)*** proposed method involves preprocessing steps such as removing image noise using the adaptive median filter(AMF)and feature extraction using the previously processed speeded-up robust feature(SURF),histogram of oriented gradients(HOG),and Global *** enhanced Grey Wolf Optimization(GWO)technique is then employed with SVM for *** evaluate the proposed method,we used the online retinal images for glaucoma analysis(ORIGA)database,and it achieved high accuracy,sensitivity,and specificity rates of 94%,92%,and 92%,*** results demonstrate that the proposed method outperforms other current algorithms in detecting the presence or absence of *** study provides a novel and effective approach to Glaucoma detection that can potentially improve the detection process and outcomes.