A new method of vascular point detection using artificial neural network
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...
| Main Authors: | , , |
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| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
IEEE
2012
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/32181/ http://irep.iium.edu.my/32181/ http://irep.iium.edu.my/32181/ http://irep.iium.edu.my/32181/1/A_new_method_of_vascular_point_detection_using.pdf |
| Summary: | 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 5x5 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. |
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