Automatic Recognition of Exudative Maculopathy using Fuzzy C-Means Clustering and Neural NetworksA. Osareh, M. Mirmehdi, B. Thomas, Richard Markham, Automatic Recognition of Exudative Maculopathy using Fuzzy C-Means Clustering and Neural Networks. Medical Image Understanding and Analysis. E Claridge, J Bamber, (eds.), pp. 49–52. July 2001. PDF, 79 Kbytes.
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.