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 |
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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 |
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