A novel retinal vessel detection approach based on multiple deep convolution neural networks

dc.contributor.author	Guo, Yanhui
dc.contributor.author	Budak, Umit
dc.contributor.author	Sengur, Abdulkadir
dc.date.accessioned	16/12/21 12:07
dc.date.available	16/12/21 12:07
dc.date.issued	2018
dc.identifier.issn	0169-2607
dc.identifier.uri	http://dspace.beu.edu.tr:8080/xmlui/handle/20.500.12643/10207
dc.identifier.uri	https://doi.org/10.1016/j.cmpb.2018.10.021
dc.description.abstract	Background and objective: Computer aided detection (CAD) offers an efficient way to assist doctors to interpret fundus images. In a CAD system, retinal vessel (RV) detection is a crucial step to identify the retinal disease regions. However, RV detection
dc.language.iso	English
dc.publisher	Elsevıer Ireland Ltd
dc.source	Computer Methods And Programs In Bıomedıcıne
dc.title	A novel retinal vessel detection approach based on multiple deep convolution neural networks
dc.type	Article
dc.identifier.startpage	43
dc.identifier.endpage	48
dc.identifier.doi	10.1016/j.cmpb.2018.10.021
dc.identifier.wos	WOS:000451903100006
dc.identifier.volume	167

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