Retinal analysis from OCT images to identify fluid filled abnormalities

Blindness, being one of the most common disabilities in humans, is often caused due to various infections anterior and posterior regions Human eye. One reasons include a significant variation levels fluid retina This may be excessive fluids or reduction fluids. paper reviews tools assessment designed towards early detection diagnosis such filled abnormalities. The proposed idea has evaluated methodologies that have been implemented using Image processing techniques, beginning from preprocessing classification at different stages. Not only focusing on binary classification, say normal abnormal, other techniques classify input image as Choroidal NeoVascular Membrane (CNVM), Cystoid Macular Edema (CME), Hole (MH) images also validated. Validation speckle noise removal filters classifiers for efficient focused paper.