Automatic Recognition of Exudative Maculopathy using Fuzzy C-Means Clustering and Neural Networks

A Osareh, M Mirmehdi, B Thomas, R Markham

Research output: Chapter in Book/Report/Conference proceedingConference Contribution (Conference Proceeding)

Abstract

Retinal exudates are typically manifested as spatially random yellow/white patches of varying sizes and shapes. They are a characteristic feature of retinal diseases such as diabetic maculopathy. An automatic method for the detection of exudate regions is introduced comprising image colour normalisation, enhancing the contrast between the objects and background, segmenting the colour retinal image into homogenous regions using Fuzzy C-Means clustering, and classifying the regions into exudates and non exudates patches using a neural network. Experimental results indicate that we are able to achieve 92\% sensitivity and 82\% specificity.
Translated title of the contributionAutomatic Recognition of Exudative Maculopathy using Fuzzy C-Means Clustering and Neural Networks
Original languageEnglish
Title of host publicationUnknown
EditorsE Claridge, J Bamber
PublisherBMVA Press
Pages49 - 52
Number of pages3
Publication statusPublished - Jul 2001

Bibliographical note

Conference Proceedings/Title of Journal: Medical Image Understanding and Analysis

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