Retinal Image Preprocessing: Background and Noise Segmentation
Abstract: Medical imaging is
very popular research area these days and includes computer aided diagnosis of
different diseases by taking digital images as input. Digital retinal images
are used for the screening and diagnosis of diabetic retinopathy, an eye
disease. An automated system for the diagnosis of diabetic retinopathy should
highlight all signs of disease present in the image and in order to improve the
accuracy of the system, the retinal image quality must be improved. In this
article, we present a method to improve the quality of input retinal image and
we consider this method as a preprocessing step in automated diagnosis of
diabetic retinopathy. The preprocessing consists of background estimation and noise
removal from retinal image by applying coarse and fine segmentation. We perform
extensive results to check the validity of proposed preprocessing technique
using standard fundus image database.
Author: Ibaa Jamal, M. Usman
Akram, Anam Tariq
Journal Code: jptkomputergg120080
