Digital retina imageutilizes a high resolution imaging framework for the viewing of infected eye.It contributes greatly physician accessto retina and helps to identify and manage health conditions such as Alzheimer’s disease (AD), glaucoma, polygenic disorder, and degeneration.Spectral-Domain Optical Coherence Tomography (SD-OCT) is often used in ophthalmology to view the transformation of retina, which is very important for symptom detection and treatment assessment.The sensitive cells of retina are affected by the desire for old aged people, health problems and external environmental resources. It is mainly concentrating on linking the retinal layers of Alzheimer's disease. The defect of retinal patients has been diagnosed by ophthalmologists with totally awareness in the deep calculation of the inner layer in the images of retina.Thispaper clearly shows the automatic analysis method based on SD-OCT images. It recommends a novel technique to extract retinal layer segment from color retina images using chromatographic processes. Applying this method, optical disc and blood vessels, and retinal layers are determined from the retina image after the preprocessing. Exudates are additionally segmented by a blending of metaphorical operation like the retinal layer region's props function and a reconstruction technique. Finally the retinal image segmentation results are compared with retinal reference model. Afterwards, two types of criteria, based on the morphological and geometry referencehave been proposed. This article puts forward a Retinal Extraordinary Standard Decision Making Process (RESDMP) which is often used in the actual calculations and evaluation of multiple SD-OCT images. This paper has provided images of 150 tests image for the simulation of retinal layer analysis, showingthe specificity as 0.93 and the sensitivity of 0.95 and.The proposed method can evaluate the retina layers, without making any delay in the diagnostic process.
Volume 11 | 05-Special Issue
Pages: 2235-2246