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

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

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

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 classifi ed 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 Con fi guration Coeffi cients (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 classi fi ers 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.


 


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  • Model: PROJ7773
  • 999 Units in Stock
  • Manufactured by: ClickMyProjects

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This product was added to our catalog on Friday 11 August, 2017.

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