A retinal vessel segmentation method based on cel- lular neural networks (CNNs) is proposed. The CNN design is char- acterized by a virtual template expansion obtained through a mul- tistep operation. It is based on linear space-invariant 3 3 tem- plates and can be realized using existing chip prototypes like the ACE16K. The proposed design is capable of performing vessel seg- mentation within a short computation time. It was tested on a pub- licly 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 network with virtual template expansion for retinal vessel segmentation

PERFETTI, Renzo;RICCI, ELISA;
2007

Abstract

A retinal vessel segmentation method based on cel- lular neural networks (CNNs) is proposed. The CNN design is char- acterized by a virtual template expansion obtained through a mul- tistep operation. It is based on linear space-invariant 3 3 tem- plates and can be realized using existing chip prototypes like the ACE16K. The proposed design is capable of performing vessel seg- mentation within a short computation time. It was tested on a pub- licly 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.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11391/28945
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