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Automated analysis of retinal images
Piotr Jasiobedzki*, Chris J Taylor† and John NH Bruntc
* Department of Computer Science, University of Toronto, Toronto M5S 1A4, Canada
† Department of Medical Biophysics, University of Manchester, Manchester M13 9PT, UK
c Medical Physics Department, Clatterhridge Centre for Oncology, Bebington, Merseyside 1,63 4JY, UK
Received 23 June 1992. Available online 10 June 2003.
We describe a method for segmenting retinal images into irregularly shaped primary regions which are bounded by vessels and other structures. Boundaries are classified using grey level models. We define a process of merging primary regions into large patches using image properties such as texture and intensity, and semantic interpretations of boundaries and their measured properties. The degree to which each merged region is perfused by microcapillaries is assessed using a texture measurement. The method which makes extensive use of morphological processing depends on a limited number of parameters which have natural physical interpretations. We obtain good agreements with expert analyses of the images.
Author Keywords: retinal images; mathematical morphology; texture; vessels
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Volume 11, Issue 3 , April 1993, Pages 139-144 |
33 of 40 |
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