Detection of Macular Degeneration in Retinal Images Based on Texture Segmentation

Abstract

Age-related Macular Degeneration (AMD) is a kind of retinal disease that contains deposits affecting the macula. Macula occupies only 4 % of the retinal region but its effect is severe when it is affected. For many patients, the visual impairment associated with AMD means a loss of independence, depression, and increased financial concerns. Currently, these problems can be resolved using image processing techniques. In the existing system, the algorithm does not address the presence of artifacts in image. Also, it takes more time for the processing of the retinal images. Hence, the proposed system masks the input retinal image during preprocessing and keeps only the retinal part, thereby reducing the processing time. Image processing techniques such as generic quality indicators can be applied to assess the quality of the retinal image and the Gabor filter for detecting the retinal images containing macular degeneration (which leads to AMD). Such a retinal image containing artifacts in macula is identified and used for the medical application. Here, the processing time can be reduced effectively using an optimized method. Finally, the outcome is nature of the image, whether the image’s quality is applicable for medical purpose and whether the retinal image is subjected to AMD.