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Comparative Pixel-Level Exudate Recognition in Colour Retinal Images

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Image Analysis and Recognition (ICIAR 2005)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 3656))

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Abstract

Retinal exudates are typically manifested as spatially random yellow/white patches of varying sizes and shapes. They are a visible sign of retinal diseases such as diabetic retinopathy. Following some key preprocessing steps, colour retinal image pixels are classified to exudate and non-exudate classes. K nearest neighbour, Gaussian quadratic and Gaussian mixture model classifiers are investigated within the pixel-level exudate recognition framework. A Gaussian mixture model-based classifier demonstrated the best classification performance with 89.2% sensitivity and 81.0% predictivity in terms of pixel-level accuracy and 92.5% sensitivity and 81.4% specificity in terms of image-based accuracy.

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© 2005 Springer-Verlag Berlin Heidelberg

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Osareh, A., Shadgar, B., Markham, R. (2005). Comparative Pixel-Level Exudate Recognition in Colour Retinal Images. In: Kamel, M., Campilho, A. (eds) Image Analysis and Recognition. ICIAR 2005. Lecture Notes in Computer Science, vol 3656. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11559573_109

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  • DOI: https://doi.org/10.1007/11559573_109

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-29069-8

  • Online ISBN: 978-3-540-31938-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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