Decision Support System for Diagnosis of Irregular Fovea

作     者：Ghulam Ali Mallah Jamil Ahmed Muhammad Irshad Nazeer Mazhar Ali Dootio Hidayatullah Shaikh Aadil Jameel 

作者机构：Shah Abdul Latif UniversityKhairpur77150Pakistan Sukkur IBA UniversitySukkur7720Pakistan Shaheed Benazir UniversityLayari Karachi77202Pakistan 

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

年 卷 期：2022年第71卷第6期

页      面：5343-5353页

核心收录：

学科分类：08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：The thankful to the Department of Ophthalmology  Health Department  Kamber  Pakistan providing datasets and annotation of class label attributes 

主　　题：Machine learning deep belief neural network eye disease fovea 

摘      要：Detection of abnormalities in human eye is one of the wellestablished research areas of Machine *** Learning techniques are widely used for the diagnosis of RetinalDiseases(RD).Fovea is one of the significant parts of retina which would be prevented before the involvement of Perforated Blood Vessels(PBV).Retinopathy Images(RI)contains sufficient information to classify structural changes incurred upon PBV but Macular Features(MF)and Fovea Features(FF)are very difficult to detect because features ofMFand FF could be found with Similar Color Movements(SCM)with minor *** paper presents novel method for the diagnosis of Irregular Fovea(IF)to assist the doctors in diagnosis of irregular *** considering all above problems this paper proposes a three-layer decision support system to explore the hindsight knowledge of RI and to solve the classification problem of *** first layer involves data preparation,the second layer builds the decision model to extract the hidden patterns of fundus images by using Deep Belief Neural Network(DBN)and the third layer visualizes the results by using confusion *** paper contributes a data preparation algorithm for irregular fovea and a highest estimated classification accuracy measured about 96.90%.