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A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis

Sánchez, CI, Hornero, R, López, MI, Aboy, M, Poza, J and Abásolo, D (2008) A novel automatic image processing algorithm for detection of hard exudates based on retinal image analysis MED ENG PHYS, 30 (3). 350 - 357. ISSN 1350-4533

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Abstract

We present an automatic image processing algorithm to detect hard exudates. Automatic detection of hard exudates from retinal images is an important problem since hard exudates are associated with diabetic retinopathy and have been found to be one of the most prevalent earliest signs of retinopathy. The algorithm is based on Fisher's linear discriminant analysis and makes use of colour information to perform the classification of retinal exudates. We prospectively assessed the algorithm performance using a database containing 58 retinal images with variable colour, brightness, and quality. Our proposed algorithm obtained a sensitivity of 88% with a mean number of 4.83±4.64 false positives per image using the lesion-based performance evaluation criterion, and achieved an image-based classification accuracy of 100% (sensitivity of 100% and specificity of 100%).

Item Type: Article
Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Medical Engineering and Physics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Medical Engineering and Physics, 30(3), April2008, http://dx.doi.org/10.1016/j.medengphy.2007.04.010
Uncontrolled Keywords: diabetic retinopathy, hard exudates, image processing, retinal images, DIABETIC-RETINOPATHY, FUNDUS IMAGES
Divisions: Faculty of Engineering and Physical Sciences > Mechanical Engineering Sciences
Depositing User: Symplectic Elements
Date Deposited: 29 Oct 2012 20:31
Last Modified: 23 Sep 2013 19:36
URI: http://epubs.surrey.ac.uk/id/eprint/713578

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