In many older adults, it is very common to observe Age related Macular degeneration which ultimately results in a medical condition called Choroidal Neo-Vascularization (CNV). It is characterized by having loss of linearity in the retinal image, fusiform thickening, and disruption of blood vessels in Retinal Pigment Epithelium (RPE) layer and thus results in vision loss. The images obtained from fluorescein angiography are further processed using digital image processing techniques and the results are obtained stating whether the person is suffering from the disease or not. Using parametric modeling of the intensity variation, the factors such as peak amount of the fluorescein that accumulates in the early stage, middle stage and late stage of the images are obtained. The end result which are the parameters obtained from the images, are fed to a Neural classifier. It classifies the quantized image parameters into occult CNV and classical CNV. This will tend to show whether the particular disease is dangerous and in the final stage or in the starting stage.

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Age Related Macular Degeneration (amd Fluorescein Angiography (fa) Choroidal Neo-vascularization (cnv) Image Registration Neural Classifier.