About: Automatic no-reference quality assessment for retinal fundus images using vessel segmentation

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About: Automatic no-reference quality assessment for retinal fundus images using vessel segmentation Goto Sponge NotDistinct Permalink

An Entity of Type : http://linked.opendata.cz/ontology/domain/vavai/Vysledek, within Data Space : linked.opendata.cz associated with source document(s)

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rdf:type	skos:Concept http://linked.opendata.cz/ontology/domain/vavai/Vysledek
Description	Fundus imaging is the most commonly used modality to collect information about the human eye background. Objective and quantitative assessment of quality for the acquired images is essential for manual, computer-aided and fully automatic diagnosis. In this paper, we present a noreference quality metric to quantify image noise and blur and its application to fundus image quality assessment. The proposed metric takes the vessel tree visible on the retina as guidance to determine an image quality score. In our experiments, the performance of this approach is demonstrated by correlation analysis with the established full-reference metrics peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM). We found a Spearman rank correlation for PSNR and SSIM of 0.89 and 0.91. For real data, our metric correlates reasonable to a human observer, indicating high agreement to human visual perception. Fundus imaging is the most commonly used modality to collect information about the human eye background. Objective and quantitative assessment of quality for the acquired images is essential for manual, computer-aided and fully automatic diagnosis. In this paper, we present a noreference quality metric to quantify image noise and blur and its application to fundus image quality assessment. The proposed metric takes the vessel tree visible on the retina as guidance to determine an image quality score. In our experiments, the performance of this approach is demonstrated by correlation analysis with the established full-reference metrics peak-signal-to-noise ratio (PSNR) and structural similarity (SSIM). We found a Spearman rank correlation for PSNR and SSIM of 0.89 and 0.91. For real data, our metric correlates reasonable to a human observer, indicating high agreement to human visual perception. (en)
Title	Automatic no-reference quality assessment for retinal fundus images using vessel segmentation Automatic no-reference quality assessment for retinal fundus images using vessel segmentation (en)
skos:prefLabel	Automatic no-reference quality assessment for retinal fundus images using vessel segmentation Automatic no-reference quality assessment for retinal fundus images using vessel segmentation (en)
skos:notation	RIV/00216305:26220/13:PU103693!RIV15-MSM-26220___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(7AMB12DE002), S
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Odstrčilík, Jan
http://linked.open.../riv/druhVysledku	D - Článek ve sborníku
http://linked.open...iv/duvernostUdaju	S - Úplné a pravdivé údaje nepodléhající ochraně podle zvláštních právních předpisů
http://linked.open...titaPredkladatele	Vysoké učení technické v Brně / Fakulta elektrotechniky a komunikačních technologií
http://linked.open...dnocenehoVysledku	62618
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/13:PU103693
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	fundus images, image quality assesment, fundus camera, blood vessel segmentation (en)
http://linked.open.../riv/klicoveSlovo	blood vessel segmentation image quality assesment fundus camera fundus images
http://linked.open...ontrolniKodProRIV	[665A1685DDC7]
http://linked.open...v/mistoKonaniAkce	Porto, Portugalsko
http://linked.open...i/riv/mistoVydani	Porto, Portugalsko
http://linked.open...i/riv/nazevZdroje	26th IEEE International Symposium on Computer-Based Medical Systems
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	1 (xsd:int)
http://linked.open...cetTvurcuVysledku	6 (xsd:int)
http://linked.open...vavai/riv/projekt	Extraction of novel disease specific features from fundus images
http://linked.open...UplatneniVysledku	2013
http://linked.open...iv/tvurceVysledku	Budai, Attila Hornegger, Joachim Michelson, Georg Odstrčilík, Jan Kraus, Martin Köhler, Thomas
http://linked.open...vavai/riv/typAkce	WRD - Světová
http://linked.open.../riv/zahajeniAkce	2013-06-20 (xsd:date)
number of pages	6 (xsd:int)
http://purl.org/ne...btex#hasPublisher	University of Porto
https://schema.org/isbn	978-1-4799-1053-3
http://localhost/t...ganizacniJednotka	26220

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