Local configuration pattern features for age-related macular degeneration characterisation and classification

Bhandary, Sulatha V (2015) Local configuration pattern features for age-related macular degeneration characterisation and classification. Computers in Biology and Medicine, 63 (1). pp. 208-218.

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Age-related Macular Degeneration (AMD) is an irreversible and chronic medical condition characterized by drusen, Choroidal Neovascularization (CNV) and Geographic Atrophy (GA). AMD is one of the major causes of visual loss among elderly people. It is caused by the degeneration of cells in the macula which is responsible for central vision. AMD can be dry or wet type, however dry AMD is most common. It is classified into early, intermediate and late AMD. The early detection and treatment may help one to stop the progression of the disease. Automated AMD diagnosis may reduce the screening time of the clinicians. In this work, we have introduced LCP to characterize normal and AMD classes using fundus images. Linear Configuration Coefficients (CC) and Pattern Occurrence (PO) features are extracted from fundus images. These extracted features are ranked using p-value of the t-test and fed to various supervised classifiers viz. Decision Tree (DT), Nearest Neighbour (k-NN), Naive Bayes (NB), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM) to classify normal and AMD classes. The performance of the system is evaluated using both private (Kasturba Medical Hospital, Manipal, India) and public domain datasets viz. Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) using ten-fold cross validation. The proposed approach yielded best performance with a highest average accuracy of 97.78%, sensitivity of 98.00% and specificity of 97.50% for STARE dataset using 22 significant features. Hence, this system can be used as an aiding tool to the clinicians during mass eye screening programs to diagnose AMD.

Item Type: Article
Uncontrolled Keywords: Retina; age-related macular degeneration; fundus imaging; local configuration pattern; support vector machine.
Subjects: Medicine > KMC Manipal > Ophthalmology
Depositing User: KMC Manipal
Date Deposited: 09 Jul 2015 04:30
Last Modified: 09 Jul 2015 04:30
URI: http://eprints.manipal.edu/id/eprint/143298

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