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Convolutional Neural Network-Based Classificationof Multiple Retinal Diseases Using Fundus images

Intelligent Automation & Soft Computing 2023年第6期36卷 2607-2622页

作者： Aqsa Aslam Saima Farhan Momina Abdul Khaliq Fatima Anjum Ayesha Afzaal Faria Kanwal Lahore College for Women University Lahore54000Pakistan

Use of deep learning algorithms for the investigation and analysis of medical images has emerged as a powerful *** increase in retinal dis-eases is alarming as it may lead to permanent blindness if left ***-tion of the diagnosis process of retinal diseases not only assists ophthalmologists in correct decision-making but saves time *** researchers have worked on automated retinal disease classification but restricted either to hand-crafted fea-ture selection or binary *** paper presents a deep learning-based approach for the automated classification of multiple retinal diseases using fundus *** this research,the data has been collected and combined from three distinct *** images are preprocessed for enhancing the *** layers of the convolutional neural network(CNN)are used for the automated feature extraction and classification of 20 retinal *** is observed that the results are reliant on the number of *** binary classification(healthy ***),up to 100%accuracy has been *** 16 classes are used(treating stages of a disease as a single class),93.3%accuracy,92%sensitivity and 93%specificity have been obtained *** 20 classes(treating stages of the disease as separate classes),the accuracy,sensitivity and specificity have dropped to 92.4%,92%and 92%respectively.

关键词： Classification convolutional neural network fundus images medical image diagnosis retinal diseases

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