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|Title:||A new method of vascular point detection using artificial neural network|
Aibinu, A. M.
Salami, Momoh-Jimoh E.
Artificial Neural Network
|Citation:||Kader, S., Aibinu, A. M., & Salami, M. J. E. (2012, December). A new method of vascular point detection using artificial neural network. In 2012 IEEE-EMBS Conference on Biomedical Engineering and Sciences (pp. 728-733). IEEE.|
|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.|
|Appears in Collections:||Research Articles|
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