A retinal vessel segmentation method based on cellular neural networks (CNNs) is proposed. TheCNNdesign is characterized by a virtual template expansion obtained through a multistep operation. It is based on linear space-invariant 3 X 3 templates and can be realized using existing chip prototypes like the ACE16K. The proposed design is capable of performing vessel segmentation within a short computation time. It was tested on a publicly available database of color images of the retina, using receiver operating characteristic curves. The simulation results show good performance comparable with that of the best existing methods.
Cellular Neural Networks With Virtual Template Expansion for Retinal Vessel Segmentation
Giovanni Costantini
2007
Abstract
A retinal vessel segmentation method based on cellular neural networks (CNNs) is proposed. TheCNNdesign is characterized by a virtual template expansion obtained through a multistep operation. It is based on linear space-invariant 3 X 3 templates and can be realized using existing chip prototypes like the ACE16K. The proposed design is capable of performing vessel segmentation within a short computation time. It was tested on a publicly available database of color images of the retina, using receiver operating characteristic curves. The simulation results show good performance comparable with that of the best existing methods.File in questo prodotto:
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