The following information was submitted:
Transactions: WSEAS TRANSACTIONS ON CIRCUITS AND SYSTEMS
Transactions ID Number: 27-569
Full Name: Daniele Casali
Position: Doctor (Researcher)
Age: ON
Sex: Male
Address: Via del Politecnico, 1
Country: ITALY
Tel:
Tel prefix:
Fax:
E-mail address: daniele.casali@uniroma2.it
Other E-mails:
Title of the Paper: Realtime Retinal Vessel Segmentation by means of a CNN-based system
Authors as they appear in the Paper: Renzo Perfetti, Elisa ricci, Daniele Casali, Giovanni Costantini
Email addresses of all the authors: perfetti@diei.unipg.it, elisa.ricci@diei.unipg.it, daniele.casali@uniroma2.it, costantini@uniroma2.it
Number of paper pages: 10
Abstract: In order to design a real time system for performing a retinal vessel segmentation, we present method that can be implemented with cellular neural networks (CNNs). CNN is kind of neural network that can be very efficiently implemented on an analog chip, and allow us to operate in real-time. The algorithm is based on linear, space-invariant 3x3 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.
Keywords: Cellular neural networks, line detection, vessel segmentation, retinal imaging
EXTENSION of the file: .rtf
Special (Invited) Session: A CNN based algorithm for Retinal Vessel Segmentation
Organizer of the Session: 591-553
How Did you learn about congress:
IP ADDRESS: 160.80.81.59
