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Retinal vessel segmentation using multi-scale wavelet frame analysis

Noah Lee; Andrew F. Laine; R. Theodore Smith; Mihai Busuoic

Title:
Retinal vessel segmentation using multi-scale wavelet frame analysis
Author(s):
Lee, Noah; Laine, Andrew F.; Smith, R. Theodore; Busuoic, Mihai
Date:
Type:
Presentations
Department:
Biomedical Engineering
Permanent URL:
Abstract:
Fundus imaging is a non-invasive technique for in vivo ophthalmoscopic inspection of retinal disorders. Quantitative information about the vascular network can facilitate clinical diagnosis of retinal diseases [1]. Goal: Segmentation of the vascular network in fundus images for further quantification and post processing as a binary classification into object and background. Approach: We perform an over-complete multi-scale wavelet frame expansion with selective channel rejection in the decomposition tree. Remaining channels undergo wavelet shrinkage and enhancement to separate retinal objects from background. Results: Comparison to expert gradings on a pixel by pixel basis show mean sensitivity and specificity of 0.8 and 0.9.
Subject(s):
Biomedical engineering
Item views:
152
Metadata:
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