Archivio istituzionale della ricerca dell'Università degli Studi di Palermo

IRIS è il sistema di gestione integrata dei dati della ricerca (persone, pubblicazioni, progetti, attività) adottato dall’Università di Palermo, e ha lo scopo di raccogliere, conservare, documentare, e diffondere ad accesso aperto le informazioni relative alla produzione scientifica degli autori afferenti all’Ateneo.

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 [10.1007/978-3-642-23713-3_31].

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