Comparative Exudate Classification using Support Vector Machines and Neural Networks

A Osareh, M Mirmehdi, B Thomas, R Markham

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

92 Citations (Scopus)

Abstract

Abstract. After segmenting candidate exudates regions in colour retinal images we present and compare two methods for their classification. The Neural Network based approach performs marginally better than the Support Vector Machine based approach, but we show that the latter are more flexible given criteria such as control of sensitivity and specificity rates. We present classification results for different learning algorithms for the Neural Net and use both hard and soft margins for the Support Vector Machines. We also present ROC curves to examine the trade-off between the sensitivity and specificity of the classifiers.
Translated title of the contributionComparative Exudate Classification using Support Vector Machines and Neural Networks
Original languageEnglish
Title of host publicationUnknown
EditorsT. Dohi, R. Kikinis
PublisherSpringer Berlin Heidelberg
Pages413 - 420
Number of pages7
Publication statusPublished - Sep 2002

Bibliographical note

Conference Proceedings/Title of Journal: 5th International Conference on Medical Image Computing and Computer-Assisted Intervention

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