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An adaptive weighting approach for ensemble-based detection of microaneurysms in color fundus images.

作者信息

Antal Bálint, Lázár István, Hajdu András

机构信息

Faculty of Informatics, University of Debrecen, 4010 Debrecen, POB 12, Hungary.

出版信息

Annu Int Conf IEEE Eng Med Biol Soc. 2012;2012:5955-8. doi: 10.1109/EMBC.2012.6347350.

DOI:10.1109/EMBC.2012.6347350
PMID:23367285
Abstract

In this paper, we present an adaptive weighting approach to microaneurysm detector ensembles. The basis of the adaptive weighting approach is the spatial location and contrast of the detected microaneurysm. During training, the performance of ensemble members is measured with a respect to these contextual information, which serves as a basis for the optimal weights assigned to detectors. We have tested this approach on two publicly available datasets, where it showed its competitiveness compared with out previously published ensemble-based approach for microaneurysm detection. Moreover, the proposed approach outperformed all the investigated individual detectors.

摘要

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