期刊
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
卷 37, 期 5-6, 页码 403-408出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.compmedimag.2013.05.001
关键词
Microaneurysm detection; Retinal image processing; Ensemble learning; Context-aware weighting
资金
- European Union
- European Social Fund
- OTKA grant [NK101680]
- National Office for Research and Technology of Hungary [OM-00194/2008, OM-00195/2008, OM-00196/2008]
- [TAMOP-4.2.2.C-11/1/KONV-2012-0001]
In this paper, we present two approaches to improve microaneurysm detector ensembles. First, we provide an approach to select a set of preprocessing methods for a microaneurysm candidate extractor to enhance its detection performance in color fundus images. The performance of the candidate extractor with each preprocessing method is measured in six microaneurysm categories. The best performing preprocessing method for each category is selected and organized into an ensemble-based method. We tested our approach on the publicly available DiaretDB1 database, where the proposed approach led to an improvement regarding the individual approaches. Second, an adaptive weighting approach for microaneurysm detector ensembles is presented.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 respect to these contextual information, which serves as a basis for the optimal weights assigned to the detectors. We have tested this approach on two publicly available datasets, where it showed its competitiveness compared without previously published ensemble-based approach for microaneurysm detection. Moreover, the proposed approach outperformed all the investigated individual detectors. (C) 2013 Elsevier Ltd. All rights reserved.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据