A stochastic approach to improve macula detection in retinal images

Antal, Bálint and Hajdu, András: A stochastic approach to improve macula detection in retinal images. In: Acta cybernetica, (20) 1. pp. 5-15. (2011)

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Abstract

In this paper, we present an approach to improve detectors used in medical image processing by fine-tuning their parameters for a certain dataset. The proposed algorithm uses a stochastic search algorithm to deal with large search spaces. We investigate the effectiveness of this approach by evaluating it on an actual clinical application. Namely, we present promising results with outperforming four state-of-the-art algorithms used for the detection of the center of the sharp vision (macula) in digital fundus images.

Item Type: Article
Journal or Publication Title: Acta cybernetica
Date: 2011
Volume: 20
Number: 1
ISSN: 0324-721X
Page Range: pp. 5-15
Language: angol
Event Title: Conference on Hungarian Computational Linguistics, 7., 2010, Szeged
DOI: https://doi.org/10.14232/actacyb.20.1.2011.2
Uncontrolled Keywords: Természettudomány, Informatika, Orvostudomány
Additional Information: Bibliogr.: p. 14-15.; Abstract
Date Deposited: 2016. Oct. 15. 12:24
Last Modified: 2018. Jun. 05. 13:15
URI: http://acta.bibl.u-szeged.hu/id/eprint/12895

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