Abstract
Optical Coherence Tomography (OCT) of the retina allow high resolution and non-invasive imaging for diagnosis of macular diseases such as Age Related Macular Degeneration (ARMD). The aim of this work is to suppress the speckle noise, segment the retinal pigment epithelium layer and identify the possibilities for diagnosis of ARMD by curve fitting method. Speckle pattern, which is multiplicative in nature, degrades the quality of OCT images. Bilateral and homomorphic-wavelet filters are adopted to minimize the speckle noise in OCT images. The performance of these filters is tested on a set of OCT images collected from an open source database. The experimental results prove that homomorphic-wavelet filter is better in reducing the speckle noise. Structural changes of retinal pigment epithelium layer, a key factor of ARMD, is identified by Graph-based method, which is utilized further in diagnosis of ARMD by curve fitting method. The sum of squares due to error (SSE) values of ARMD images are very higher compared to normal images, which can be used as a feature for diagnosis.
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