Method of Extracting The Choroidal Area and Its Quantitative Analysis on Optical Coherence Tomography Images for the Diagnostics of Eye Diseases

This paper proposes a technology for the extraction of the vascular tissue of the human eye and calculation of the choroidal vascular index on optical coherence tomography (OCT) images. The choroid is one of the most vascularized structures of the human body and plays an indispensable role in the nu...

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Vydané v:	Journal of computer & systems sciences international Ročník 63; číslo 3; s. 503 - 509
Hlavní autori:	Demin, N. S., Ilyasova, N. Yu, Samigullin, R. T.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Moscow Pleiades Publishing 01.06.2024 Springer Nature B.V
Predmet:	Artificial intelligence Blood vessels Control Engineering Eye diseases Image filters Mechatronics Medical imaging Morphology Optical Coherence Tomography Pathology Pattern Recognition and Image Processing Photoreceptors Quantitative analysis Robotics Tomography Vascular tissue choroid quantitative features biomedical images thresholding quantitative analysis optical coherence tomography images
ISSN:	1064-2307, 1555-6530
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Abstract	This paper proposes a technology for the extraction of the vascular tissue of the human eye and calculation of the choroidal vascular index on optical coherence tomography (OCT) images. The choroid is one of the most vascularized structures of the human body and plays an indispensable role in the nutrition of photoreceptors. The applied approach is based on the use of the method of shadow compensation of OCT images with their subsequent filtering and binarization. The technology for isolating the choroidal region and quantitatively assessing the choroidal vascular index (CVI) on OCT images to identify endocrine ophthalmopathy (EOP) is considered. This technology has made it possible to automate the calculation of choroidal vascular index value, which is an important indicator in the study of the vascular layer when diagnosing eye diseases.
AbstractList	This paper proposes a technology for the extraction of the vascular tissue of the human eye and calculation of the choroidal vascular index on optical coherence tomography (OCT) images. The choroid is one of the most vascularized structures of the human body and plays an indispensable role in the nutrition of photoreceptors. The applied approach is based on the use of the method of shadow compensation of OCT images with their subsequent filtering and binarization. The technology for isolating the choroidal region and quantitatively assessing the choroidal vascular index (CVI) on OCT images to identify endocrine ophthalmopathy (EOP) is considered. This technology has made it possible to automate the calculation of choroidal vascular index value, which is an important indicator in the study of the vascular layer when diagnosing eye diseases.
Author	Ilyasova, N. Yu Samigullin, R. T. Demin, N. S.
Author_xml	– sequence: 1 givenname: N. S. surname: Demin fullname: Demin, N. S. email: volfgunus@gmail.com organization: Image Processing Systems Institute, National Research Center “Kurchatov Institute”, Korolev Samara National Research University – sequence: 2 givenname: N. Yu surname: Ilyasova fullname: Ilyasova, N. Yu email: ilyasova.nata@gmail.com organization: Image Processing Systems Institute, National Research Center “Kurchatov Institute”, Korolev Samara National Research University – sequence: 3 givenname: R. T. surname: Samigullin fullname: Samigullin, R. T. email: samigullin.ravil2015@yandex.ru organization: Korolev Samara National Research University
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Cites_doi	10.3390/jcm9020595 10.1111/aos.13442 10.1016/j.survophthal.2018.11.002 10.1371/journal.pone.0146344 10.1136/bjophthalmol-2021-318782 10.1155/2019/4061313 10.1167/iovs.10-6925 10.1364/BOE.412156 10.1016/j.survophthal.2016.02.007 10.1016/j.ajo.2019.03.028 10.1016/j.preteyeres.2020.100829 10.1136/bjophthalmol-2013-303904 10.1167/iovs.16-20191 10.1177/1120672120919341 10.1364/OE.20.004710 10.1364/OE.17.014880 10.1371/journal.pone.0213336 10.1016/j.ophtha.2018.12.033 10.1097/MD.0000000000015421 10.1038/s41598-018-24577-8 10.1007/s00417-014-2840-y 10.1111/aos.13836 10.4274/tjo.10693 10.1016/j.ajo.2016.06.043 10.1364/BOE.7.000816
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Copyright	Pleiades Publishing, Ltd. 2024. ISSN 1064-2307, Journal of Computer and Systems Sciences International, 2024, Vol. 63, No. 3, pp. 503–509. © Pleiades Publishing, Ltd., 2024. Pleiades Publishing, Ltd. 2024.
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Laviers (7457_CR25) 2014; 252 M. J. Girard (7457_CR16) 2011; 58
References_xml	– reference: MedeirosF. A.JammalA. A.ThompsonA. C.From machine to machine: An OCT-trained deep learning algorithm for objective quantification of glaucomatous damage in fundus photographsOphthalmology201912651352110.1016/j.ophtha.2018.12.033 – reference: GirardM. J.StrouthidisN. G.EthierC. R.MariJ. M.Shadow removal and contrast enhancement in optical coherence tomography images of the human optic nerve headInvest. Ophthalmol. Visual Sci.2011587738774810.1167/iovs.10-6925 – reference: GoraM.KarnowskiK.SzkulmowskiM.Ultra high-speed swept source OCT imaging of the anterior segment of human eye at 200 KHz with adjustable imaging rangeOpt. Express.2009174880489410.1364/OE.17.014880 – reference: CheongH.DevallaS. K.ChuangsuwanichT.OCT-GAN: Single step shadow and noise removal from optical coherence tomography images of the human optic nerve headBiomed. Opt. Express2021121482149810.1364/BOE.412156 – reference: R. Agrawal, J. Ding, and P. Sen, “Exploring choroidal angioarchitecture in health and disease using choroidal vascularity index,” Prog. Retinal Eye Res. 77, 100829 (2020). – reference: VupparaboinaK. K.DansinganiK. K.GoudA.Quantitative shadow compensated optical coherence tomography of choroidal vasculatureSci Rep.20188646110.1038/s41598-018-24577-8 – reference: Y. U. Shin, S. E. Lee, M. H. Kang, S. W. Han, J. H. Yi, and H. Cho, “Evaluation of changes in choroidal thickness and the choroidal vascularity index after hemodialysis in patients with end-stage renal disease by using swept-source optical coherence tomography,” Medicine (Baltimore) 98 (18), e15421 (2019). – reference: SinghS. R.VupparaboinaK. K.GoudA.Choroidal imaging biomarkerSurv. Ophthalmol.20196431233310.1016/j.survophthal.2018.11.002 – reference: NgW. Y.TingD. S. W.AgrawalR.Choroidal structural changes in myopic choroidal neovascularization after treatment with antivascular endothelial growth factor over 1 yearInvest. Ophthalmol. Visual Sci.2016574933493910.1167/iovs.16-20191 – reference: TanK. A.GuptaP.AgarwalA.State of science: Choroidal thickness and systemic healthSurv. Ophthalmol.20166156658110.1016/j.survophthal.2016.02.007 – reference: LaviersH.ZambarakjiH.Enhanced depth imaging-OCT of the choroid: A review of the current literatureGraefe’s Arch. Clin. Exp. Ophthalmol.20142521871188310.1007/s00417-014-2840-y – reference: SezerT.AltınışıkM.Koytakİ. A.ÖzdemirM. H.The choroid and optical coherence tomographyTurk. J. Ophthalmol.201646303710.4274/tjo.10693 – reference: KurodaY.OotoS.YamashiroK.Increased choroidal vascularity in central serous chorioretinopathy quantified using swept-source optical coherence tomographyAm. J. Ophthalmol.201616919920710.1016/j.ajo.2016.06.043 – reference: JiaY.TanO.TokayerJ.Split-spectrum amplitude-decorrelation angiography with optical coherence tomographyOpt. Express2012204710472510.1364/OE.20.004710 – reference: BetzlerB. K.DingJ.WeiX.Choroidal vascularity index: A step towards software as a medical deviceBr. J. Ophthalmol.202210614915510.1136/bjophthalmol-2021-318782 – reference: CopeteS.Flores-MorenoI.MonteroJ. A.DukerJ. S.Ruiz-MorenoJ. M.Direct comparison of spectral-domain and swept-source OCT in the measurement of choroidal thickness in normal eyesBr. J. Ophthalmol.20149833433810.1136/bjophthalmol-2013-303904 – reference: Y. Park and K. J. Cho, “Choroidal vascular index in patients with open angle glaucoma and preperimetric glaucoma,” PLoS One 14 (3), e0213336 (2019). – reference: AgrawalR.WeiX.GoudA.VupparaboinaK. K.JanaS.ChhablaniJ.Influence of scanning area on choroidal vascularity index measurement using optical coherence tomographyActa Ophthalmol.20179577077510.1111/aos.13442 – reference: P. A. Shagalova, A. D. Erofeeva, M. M. Orlova, et al., “Study of image preprocessing algorithms to improve the efficiency of medical image recognition,” Tr. Nizhegorod. Gos. Tech. Univ. im. R.E. 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Snippet	This paper proposes a technology for the extraction of the vascular tissue of the human eye and calculation of the choroidal vascular index on optical...
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SubjectTerms	Artificial intelligence Blood vessels Control Engineering Eye diseases Image filters Mechatronics Medical imaging Morphology Optical Coherence Tomography Pathology Pattern Recognition and Image Processing Photoreceptors Quantitative analysis Robotics Tomography Vascular tissue
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Title	Method of Extracting The Choroidal Area and Its Quantitative Analysis on Optical Coherence Tomography Images for the Diagnostics of Eye Diseases
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