DocumentCode
1951410
Title
A new method of vascular point detection using artificial neural network
Author
Kader, S. ; Aibinu, A.M. ; Salami, M.J.E.
Author_Institution
Mechatron. Eng. Dept., Int. Islamic Univ., Kuala Lumpur, Malaysia
fYear
2012
fDate
17-19 Dec. 2012
Firstpage
728
Lastpage
733
Abstract
Vascular intersection is an important feature in retina fundus image (RFI). It can be used to monitor the progress of diabetes hence accurately determining vascular point is of utmost important. In this work a new method of vascular point detection using artificial neural network model has been proposed. The method uses a 5×5 window in order to detect the combination of bifurcation and crossover points in a retina fundus image. Simulated images have been used to train the artificial neural network and on convergence the network is used to test (RFI) from DRIVE database. Performance analysis of the system shows that ANN based technique achieves 100% accuracy on simulated images and minimum of 92% accuracy on RFI obtained from DRIVE database.
Keywords
biomedical optical imaging; blood vessels; diseases; eye; learning (artificial intelligence); medical image processing; neural nets; DRIVE database; RFI; artificial neural network model; artificial neural network training; diabetes progression; retina fundus image; simulated images; vascular intersection; vascular point detection method; vessel bifurcation point; vessel crossover point; Artificial Neural Network; Diabetic Retinopathy; Retina; Vascular points;
fLanguage
English
Publisher
ieee
Conference_Titel
Biomedical Engineering and Sciences (IECBES), 2012 IEEE EMBS Conference on
Conference_Location
Langkawi
Print_ISBN
978-1-4673-1664-4
Type
conf
DOI
10.1109/IECBES.2012.6498142
Filename
6498142
Link To Document