About: Thickness related textural properties of retinal nerve fiber layer in color fundus images

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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	Images of ocular fundus are routinely utilized in ophthalmology. Since an examination using fundus camera is relatively fast and cheap procedure, it can be used as a proper diagnostic tool for screening of retinal diseases such as the glaucoma. One of the glaucoma symptoms is progressive atrophy of the retinal nerve fiber layer (RNFL) resulting in variations of the RNFL thickness. Here, we introduce a novel approach to capture these variations using computer-aided analysis of the RNFL textural appearance in standard and easily available color fundus images. The proposed method uses the features based on Gaussian Markov random fields and local binary patterns, together with various regression models for prediction of the RNFL thickness. The approach allows description of the changes in RNFL texture, directly reflecting variations in the RNFL thickness. Evaluation of the method is carried out on 16 normal (healthy) and 8 glaucomatous eyes. We achieved significant correlation (normals: R=0.72, p<0.05, gl Images of ocular fundus are routinely utilized in ophthalmology. Since an examination using fundus camera is relatively fast and cheap procedure, it can be used as a proper diagnostic tool for screening of retinal diseases such as the glaucoma. One of the glaucoma symptoms is progressive atrophy of the retinal nerve fiber layer (RNFL) resulting in variations of the RNFL thickness. Here, we introduce a novel approach to capture these variations using computer-aided analysis of the RNFL textural appearance in standard and easily available color fundus images. The proposed method uses the features based on Gaussian Markov random fields and local binary patterns, together with various regression models for prediction of the RNFL thickness. The approach allows description of the changes in RNFL texture, directly reflecting variations in the RNFL thickness. Evaluation of the method is carried out on 16 normal (healthy) and 8 glaucomatous eyes. We achieved significant correlation (normals: R=0.72, p<0.05, gl (en)
Title	Thickness related textural properties of retinal nerve fiber layer in color fundus images Thickness related textural properties of retinal nerve fiber layer in color fundus images (en)
skos:prefLabel	Thickness related textural properties of retinal nerve fiber layer in color fundus images Thickness related textural properties of retinal nerve fiber layer in color fundus images (en)
skos:notation	RIV/00216305:26220/14:PU109541!RIV15-MSM-26220___
http://linked.open...avai/riv/aktivita	P S
http://linked.open...avai/riv/aktivity	P(ED1.100/02/0123), S
http://linked.open...iv/cisloPeriodika	6
http://linked.open...vai/riv/dodaniDat	2015
http://linked.open...aciTvurceVysledku	Gazárek, Jiří Kolář, Radim Odstrčilík, Jan Jan, Jiří Lamoš, Martin Kuna, Zdeněk Vodáková, Martina Ronzhina, Marina
http://linked.open.../riv/druhVysledku	J - Článek v odborném periodiku
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	50427
http://linked.open...ai/riv/idVysledku	RIV/00216305:26220/14:PU109541
http://linked.open...riv/jazykVysledku	eng - angličtina
http://linked.open.../riv/klicovaSlova	Glaucoma, Retinal nerve fiber layer, Texture analysis, Fundus images, Local binary patterns, Markov random fields (en)
http://linked.open.../riv/klicoveSlovo	Markov random fields Fundus images Retinal nerve fiber layer Texture analysis Local binary patterns Glaucoma
http://linked.open...odStatuVydavatele	US - Spojené státy americké
http://linked.open...ontrolniKodProRIV	[504B94E3D7F7]
http://linked.open...i/riv/nazevZdroje	COMPUTERIZED MEDICAL IMAGING AND GRAPHICS
http://linked.open...in/vavai/riv/obor	JD
http://linked.open...ichTvurcuVysledku	8 (xsd:int)
http://linked.open...cetTvurcuVysledku	14 (xsd:int)
http://linked.open...vavai/riv/projekt	St. Anne´s University Hospital Brno - International Clinical Research Center (FNUSA-ICRC)
http://linked.open...UplatneniVysledku	2014
http://linked.open...v/svazekPeriodika	38
http://linked.open...iv/tvurceVysledku	Budai, Attila Gazárek, Jiří Jan, Jiří Kolář, Radim Kuběna, Tomáš Odstrčilík, Jan Lamoš, Martin Ronzhina, Marina Kuna, Zdeněk Vodáková, Martina Tornow, Ralf-Peter Laemmer, Robert Mayer, Markus A. Černošek, Pavel
issn	0895-6111
number of pages	9 (xsd:int)
http://bibframe.org/vocab/doi	10.1016/j.compmedimag.2014.05.005
http://localhost/t...ganizacniJednotka	26220

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