Connectivity-based segmentation of retinal vessels in eye fundus images
M. Ralló, M. S. Millán
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Base Information
Volume
V50 - N4 / 2017 Ordinario
Reference
359-368
DOI
http://doi.org/10.7149/OPA.50.4.49070
Language
English
Keywords
Eye fundus image, retinal vasculature, blood vessel segmentation, digital image analysis, computer-aided diagnosis.
Abstract
A new unsupervised method for segmentation of objects of diverse nature with the common feature of connectivity (e.g. branching trees or net-shaped objects) is proposed. A preferred application to the vasculature segmentation of retinal images has been illustrated using images from DRIVE database. In the pre-processing stage, the method overcomes the common problem of non-uniform illumination of eye fundus images. The method follows with an iterative algorithm that starts with a seed and adds, at each step, a new vessel segment connected to the previously segmented part. The result preserves the connectivity as a distinct feature of the retinal vessel tree. The segmentation performance is evaluated through common signal detection metrics: sensitivity, specificity and accuracy.
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