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001-es BibID:	BIBFORM012441
Első szerző:	Antal Bálint (informatikus)
Cím:	Improving microaneurysm detection in color fundus images by using an optimal combination of preprocessing methods and candidate extractors / Bálint Antal, András Hajdu
Dátum:	2010
Megjegyzések:	In this paper, we present an approach to improve microaneurysm detection in color fundus images. This task is usually realized by candidate extraction, which is followed by a classification step. The proposed method aims to increase the number of true positives in the first phase of the microaneurysm detection process. Thus, we establish a framework for selecting an optimal combination of preprocessing methods and candidate extractors. Our investigation shows that the state-of-the-art candidate extractors provide significantly improved results, when they are optimally combined with preprocessing approaches. We show that this performance can be further increased with an ensemble formed by a globally optimal combination of the preprocessing methods and candidate extractors.
Tárgyszavak:	Műszaki tudományok Informatikai tudományok előadáskivonat Detection process Fundus image Microaneurysms Optimal combination Pre-processing method Preprocessing approaches True positive Signal processing Optimization
Megjelenés:	18th European Signal Processing Conference. - p. 1224-1228
További szerzők:	Hajdu András (1973-) (matematikus, informatikus)
Internet cím:	Intézményi repozitóriumban (DEA) tárolt változat
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