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)

[thumbnail of actacyb_20_1_2011_2.pdf]
Cikk, tanulmány, mű

Download (569kB) | Preview


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: English
Place of Publication: Szeged
Event Title: Conference on Hungarian Computational Linguistics (7.) (2010) (Szeged)
Related URLs: http://acta.bibl.u-szeged.hu/38531/
DOI: 10.14232/actacyb.20.1.2011.2
Uncontrolled Keywords: Számítástechnika, Szemészet, Orvostudomány - számítógép alkalmazása
Additional Information: Bibliogr.: p. 14-15. ; összefoglalás angol nyelven
Subjects: 01. Natural sciences
01. Natural sciences > 01.02. Computer and information sciences
03. Medical and health sciences
03. Medical and health sciences > 03.02. Clinical medicine
Date Deposited: 2016. Oct. 15. 12:24
Last Modified: 2022. Jun. 17. 13:25
URI: http://acta.bibl.u-szeged.hu/id/eprint/12895

Actions (login required)

View Item View Item