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001-es BibID:	BIBFORM058689
Első szerző:	Harangi Balázs (programtervező matematikus)
Cím:	Detection of Exudates in Fundus Images Using a Markovian Segmentation Model / Harangi Balázs, Hajdu András
Dátum:	2014
ISSN:	1557-170X
Megjegyzések:	Diabetic retinopathy (DR) is one of the most common causing of vision loss in developed countries. In early stage of DR, some signs like exudates appear in the retinal images. An automatic screening system must be capable to detect these signs properly so that the treatment of the patients may begin in time. The appearance of exudates shows a rich variety regarding their shape and size making automatic detection more challenging. We propose a way for the automatic segmentation of exudates consisting of a candidate extraction step followed by exact contour detection and region-wise classification. More specifically, we extract possible exudate candidates using grayscale morphology and their proper shape is determined by a Markovian segmentation model considering edge information. Finally, we label the candidates as true or false ones by an optimally adjusted SVM classifier. For testing purposes, we considered the publicly available database DiaretDB1, where the proposed method outperformed several state-of-the-art exudate detectors.
Tárgyszavak:	Természettudományok Matematika- és számítástudományok konferenciacikk diabetic rethinopathy exudate detecion active contour
Megjelenés:	Proceedings of the IEE Annual International Conference of the Engineering in Medicine and Biology Society. - 36 (2014), p. 130-133. -
További szerzők:	Hajdu András (1973-) (matematikus, informatikus)
Pályázati támogatás:	TÁMOP 4.2.4.A/ 2-11/1-2012-0001 TÁMOP
Internet cím:	DOI Intézményi repozitóriumban (DEA) tárolt változat
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