A hardware-implementable system for retinal vessel segmentation

Authors:
Giovanni Costantini;Daniele Casali;Massimiliano Todisco
Affiliations:
Department of Electronic Engineering, University of Rome "Tor Vergata", Italy;Department of Electronic Engineering, University of Rome "Tor Vergata", Italy;Department of Electronic Engineering, University of Rome "Tor Vergata", Italy
Venue:
ICCOMP'10 Proceedings of the 14th WSEAS international conference on Computers: part of the 14th WSEAS CSCC multiconference - Volume II
Year:
2010

Citing 1
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Abstract

A retinal vessel segmentation method based on cellular neural networks (CNNs) is proposed. The CNN design is characterized by a virtual template expansion obtained through a multi-step operation. It is based on linear, space-invariant 3×3 templates, and can be realized using real-life devices with minor changes. The proposed design is capable to perform vessel segmentation within short computation time. It was tested on a publicly available database of color images of the retina, using receiver operating characteristic (ROC) curves. The simulation results show the good performance, comparable with the best existing methods.