May 2006
Volume 47, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2006
Automated Contour Line Drawing of the Optic Nerve Head Using HRT II Reflectivity Images and Coloured Fundus Images
Author Affiliations & Notes
  • V. Derhartunian
    University of Erlangen, Erlangen, Germany
    Department of Ophthalmology,
  • T. Kern
    University of Erlangen, Erlangen, Germany
    Department of Ophthalmology,
  • R. Chrastek
    University of Erlangen, Erlangen, Germany
    Department of Computer Sciences, Pattern Recognition,
  • J. Hornegger
    University of Erlangen, Erlangen, Germany
    Department of Computer Sciences, Pattern Recognition,
  • M. Faerber
    University of Erlangen, Erlangen, Germany
    Department of Computer Sciences, Database Systems,
  • S. Dornstauder
    University of Erlangen, Erlangen, Germany
    Department of Computer Sciences, Database Systems,
  • W. Adler
    University of Erlangen, Erlangen, Germany
    Department of Biometry and Epidemiology,
  • G. Michelson
    University of Erlangen, Erlangen, Germany
    Department of Ophthalmology,
  • Footnotes
    Commercial Relationships  V. Derhartunian, None; T. Kern, None; R. Chrastek, None; J. Hornegger, None; M. Faerber, None; S. Dornstauder, None; W. Adler, None; G. Michelson, None.
  • Footnotes
    Support  SFB 539 ( German Research Foundation)
Investigative Ophthalmology & Visual Science May 2006, Vol.47, 3359. doi:
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      V. Derhartunian, T. Kern, R. Chrastek, J. Hornegger, M. Faerber, S. Dornstauder, W. Adler, G. Michelson; Automated Contour Line Drawing of the Optic Nerve Head Using HRT II Reflectivity Images and Coloured Fundus Images . Invest. Ophthalmol. Vis. Sci. 2006;47(13):3359.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose: : To compare manual definition of the optic disk in HRT II images with two different novel automated techniques one of which uses HRT II images in conjunction with fundus images.

Methods: : Optic disc images were acquired by laser scanning tomography (HRT II, Heidelberg Engineering) and by fundus digital images (KOWA non–myd alpha D). The contour line was manually (M) drawn by a glaucoma specialist and two automated methods: (AL1 and AL2). The automated methods defined the contour line using either the HRT II image alone –monomodal (AL1) or in conjunction with a colored fundus image – multimodal (AL2). Both automated algorithms were based on pattern recognition algorithms performing morphological operations and detection of anatomical structures. The automated multimodal algorithm (AL2) was based on registration of scanning laser tomography images and fundus photographs. The contour line was primarily generated in fundus images and then projected onto the HRT II image. 91 eyes of 91 patients were examined (45 moderate glaucomas and 46 normal subjects). Parameters defining two and three dimensional optic disc morphology and the Moorfields – and the RB–Discriminant function were calculated (3 sets for each image). Statistical analysis was performed by SPSS 13.0.

Results: : Normal subjects: for M, AL1 and AL2 the disc area was measured as 2.06+–0.52, 2.11+–0.41, 2.1+–0.34 mm², rim area was 1.5+–4.2, 1.5+–3.4, 1.6+–0.43 mm², respectively. Using Moorfields– and RB–Discriminant Function: for M 15.2% and 2% of subjects showed values lower than zero, for AL1 31.1% and 11.1% of subjects showed values lower zero. Glaucoma subjects: for M, AL1 and AL2 the disc area was measured as 2.43+–0.71, 2.41+–0.53, 2.40+–0.65 mm², the rim area was 1.22+–5.3, 1.10+–4.9, 1.34+–0.66 mm² respectively. Using Moorfields– and RB–Discriminant Function: for M 73.3% and 55.6% of subjects showed values lower than zero, for AL1 73.3% and 62.2% of subjects showed values lower zero.

Conclusions: : Both automated algorithms outlining the optic disc margin gave results similar to the manual contour line although there were differences depending upon the sector location. The goal is to achieve the most accurate contour line which could be used as a suggestion for unexperienced HRT II users.

Keywords: optic disc • imaging/image analysis: clinical 
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