Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Interactive Browsing Systems for Large Image Collections Read chapter Read first chapter

2018 | OriginalPaper | Chapter

Automatization of Eye Fundus Vessel Width Measurements

Authors : Giedrius Stabingis, Jolita Bernatavičienė, Gintautas Dzemyda, Alvydas Paunksnis, Povilas Treigys, Ramutė Vaičaitienė, Lijana Stabingienė

Published in: VipIMAGE 2017

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

Many diseases can be early detected from eye fundus images by several different features. One of the features is the artery and vein ratio. Width measurement is made on the main vessels. The aim of this automatization process is to create a fully automated method for eye fundus analysis. The fully automated system consists of blood vessel tree extraction and optic nerve disc detection in order to perform measurements at the standard place. Vessel tree extraction is complicated in some situations, so the vessel measurement algorithm is developed independently of the extracted blood vessel tree, and the tree is used only for direction enhancement and only when it is available. Vessel measurements are compared with manual measurements, performed by an expert. Automated measurements are not different from the expert’s measurements with the confidence level of 95%. For this investigation, the Optomed OY digital mobile eye fundus camera Smartscope M5 PRO was used, but the algorithm can be used on any type of eye fundus images.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Multimodal Viewing Interface for Skin Ulcers (Leish-MUVI)
next chapter Exploratory Study on Direct Prediction of Diabetes Using Deep Residual Networks
Literature
1.
Kanski, J.J.: Clinical Ophthalmology, 6th edn. Elsevier Health Sciences, London (2007)
2.
3.
Bock, R., Meier, J., Nyl, L.G., Michelson, G.: Glaucoma risk index: automated glaucoma detection from color fundus images. Med. Image Anal. 14(3), 471481 (2010)CrossRef
4.
Buteikienė, D., Paunksnis, A., Barzdžiukas, V., Bernatavičienė, J., Marcinkevičius, V., Treigys, P.: Assessment of the optic nerve disc and excavation parameters of interactive and automated parameterization methods. Informatica 23(3), 335–355 (2012)MathSciNet
5.
Treigys, P., Šaltenis, V., Dzemyda, G., Barzdžiukas, V., Paunksnis, A.: Automated optic nerve disc parameterization. Informatica 19(3), 403–420 (2008)
6.
Odstrcilk, J., Kolar, R., Budai, A., Hornegger, J., Jan, J., Gazarek, J., Kubena, T., Cernosek, P., Svoboda, O., Angelopoulou, E.: Retinal vessel segmentation by improved matched filtering: evaluation on a new high resolution fundus image database. IET Image Process. 7(4), 373383 (2013)MathSciNet
7.
Fraz, P.R.M.M., Hoppe, A., Uyyanonvara, B., Rudnicka, A.R., Owen, C.G., Barman, S.A.: Blood vessel segmentation methodologies in retinal images a survey. Comput. Methods Progr. Biomed. 108, 407433 (2012)
8.
Morgan, A.J., Hosking, S.L.: Non-invasive vascular impedance measures demonstrate ocular vasoconstriction during isometric exercise. Br. J. Ophthalmol. 91(3), 385390 (2007)CrossRef
9.
Mirsharifa, Q., Tajeripoura, F., Pourreza, H.: Automated characterization of blood vessels as arteries and veins in retinal images. Comput. Med. Imagin. Gr. 37(7), 607–617 (2013)CrossRef
10.
Kondermann, C., Kondermann, D., Yan, Y.: Blood vessel classification into arteries and veins in retinal images. In: Proceedings of SPIE, p. 6512 (2007)
11.
Li, X., Wee, W.G.: Retinal vessel detection and measurement for computer-aided medical diagnosis. J. Digit. Imaging 27(1), 120132 (2014)CrossRef
12.
Nguyen, U.T., Bhuiyan, A., Park, L.A., Ramamohanarao, K.: An effective retinal blood vessel segmentation method using multi-scale line detection. Pattern Recognit. 46, 703715 (2013)
13.
Ravishankar, S., Jain, A., Mittal, A.: Automated feature extraction for early detection of diabetic retinopathy in fundus images. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2009) (2009)
14.
Pachiyappan, A., Das, U., Murthy, T., Tatavarti, R.: Automated diagnosis of diabetic retinopathy and glaucoma using fundus and OCT images. Lipids Health Dis. 11(1), 73 (2012)
15.
Stabingis, G., Bernatavičienė, J., Dzemyda, G., Imbrasienė, D., Paunksnis, A.: Automated classification of arteries and veins in the retinal blood vasculature. In: Proceedings of the 11th International Conference on Theoretical & Applied Stochastics. Minsk, Belarus (2016). Computer data analysis and modeling
Metadata
Title
Automatization of Eye Fundus Vessel Width Measurements
Authors
Giedrius Stabingis
Jolita Bernatavičienė
Gintautas Dzemyda
Alvydas Paunksnis
Povilas Treigys
Ramutė Vaičaitienė
Lijana Stabingienė
Copyright Year
2018
Book
VipIMAGE 2017

Print ISBN: 978-3-319-68194-8

Electronic ISBN: 978-3-319-68195-5

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-68195-5_85