In this paper an automatic unsupervised method for the segmentation of retinal vessels is proposed. Three features are extracted from the tested image. The features are scaled down by a factor of 2 and mapped into a Self-Organizing Map. A modified Fuzzy C-Means clustering algorithm is used to divide the neuron units of the map in 2 classes. The entire image is again input for the Self-Organizing Map and the class of each pixel will be the class of its best matching unit in the Self-Organizing Map. Finally, the vessel network is post-processed using a hill climbing strategy on the connected components of the segmented image. The experimental evaluation on the DRIVE database shows accurate extraction of vessels network and a good agreement between our segmentation and the ground truth. The mean accuracy, 0.9482 with a standard deviation of 0.0075, is outperforming the manual segmentation rates obtained by other widely used unsupervised methods. A good kappa value of 0.6565 is comparable with state-of-the-art supervised or unsupervised approaches.
Lupascu, C., & Tegolo, D. (2011). Stable Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and a Modified Fuzzy C-Means Clustering. In Lecture Notes in Artificial Intelligence (LNAI 6857), Subseries of Lecture Notes in Computer Science (LNCS), Springer-Verlag Berlin Heidelberg 2011 (pp.244-252). Anna Maria Fanelli – Witold Pedrycz – Alfredo Petrosino.
Autori: | Lupascu, C.; Tegolo, D. |
Titolo: | Stable Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and a Modified Fuzzy C-Means Clustering |
Settore Scientifico Disciplinare: | Settore INF/01 - Informatica |
Data di creazione: | 2011-08 |
Nome del convegno: | WILF 2011 |
Luogo del convegno: | Trani, Italy |
Anno del convegno: | 29-31 Agosto 2011 |
Numero del convegno: | 11 |
Data di pubblicazione: | 2011 |
Numero di pagine: | 9 |
Digital Object Identifier (DOI): | http://dx.doi.org/10.1007/978-3-642-23713-3_31 |
Citazione: | Lupascu, C., & Tegolo, D. (2011). Stable Automatic Unsupervised Segmentation of Retinal Vessels Using Self-Organizing Maps and a Modified Fuzzy C-Means Clustering. In Lecture Notes in Artificial Intelligence (LNAI 6857), Subseries of Lecture Notes in Computer Science (LNCS), Springer-Verlag Berlin Heidelberg 2011 (pp.244-252). Anna Maria Fanelli – Witold Pedrycz – Alfredo Petrosino. |
Tipologia: | 0 - Proceedings (TIPOLOGIA NON ATTIVA) |
Appare nelle tipologie: | 0 - Proceedings (TIPOLOGIA NON ATTIVA) |
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