In this paper an automatic unsupervised method for retinal vessel segmentation is described. Self-Organizing Map, modified Fuzzy C-Means, STAPLE algorithms and majority voting strategy were adopted to identify a segmentation of the retinal vessels. The performance of the proposed method was evaluated on the DRIVE database.
Lupascu, C., Tegolo, D. (2016). A multiscale approach to automatic and unsupervised retinal vessel segmentation using Self-Organizing Maps. In A. Smrikarov, B. Rachev (a cura di), Computer Systems and Technologies, COMPSYSTECH'16 (pp. 182-189). Association for Computing Machinery [10.1145/2983468.2983478].
A multiscale approach to automatic and unsupervised retinal vessel segmentation using Self-Organizing Maps
LUPASCU, Carmen Alina
;TEGOLO, Domenico
2016-01-01
Abstract
In this paper an automatic unsupervised method for retinal vessel segmentation is described. Self-Organizing Map, modified Fuzzy C-Means, STAPLE algorithms and majority voting strategy were adopted to identify a segmentation of the retinal vessels. The performance of the proposed method was evaluated on the DRIVE database.
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