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

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.