May 2007
Volume 48, Issue 13
Free
ARVO Annual Meeting Abstract  |   May 2007
Automated Extraction of Optic Nerve Head Parameters From Stereoscopic Optic Nerve Head Photographs
Author Affiliations & Notes
  • J. Xu
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • H. Ishikawa
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • G. Wollstein
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • K. Sung
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • L. Kagemann, Jr.
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • R. A. Bilonick
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • J. S. Kim
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • M. L. Gabriele
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • K. A. Townsend
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • J. S. Schuman
    UPMC Eye Center, Eye and Ear Institute, Ophthalmology and Visual Science Research Center, Department of Ophthalmology, University of Pittsburgh School of Medicine, Pittsbugh, Pennsylvania
  • Footnotes
    Commercial Relationships J. Xu, None; H. Ishikawa, Carl Zeiss Meditec, Inc., R; G. Wollstein, Carl Zeiss Meditec, Inc., R; K. Sung, None; L. Kagemann, None; R.A. Bilonick, None; J.S. Kim, None; M.L. Gabriele, None; K.A. Townsend, None; J.S. Schuman, Carl Zeiss Meditec, Inc., P; Alcon; Allergan; Carl Zeiss Meditec, Inc.; Merck; Optoview; Heidelberg Engineering, F; Alcon; Allergan; Carl Zeiss Meditec, Inc.; Clarity; Merck; Heidelberg Engineering, R.
  • Footnotes
    Support NIH RO1-EY13178-06, P30-EY08098; The Eye and Ear Foundation (Pittsburgh, PA), and an unrestricted grant from Research to Prevent Blindness
Investigative Ophthalmology & Visual Science May 2007, Vol.48, 3312. doi:
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    • Get Citation

      J. Xu, H. Ishikawa, G. Wollstein, K. Sung, L. Kagemann, Jr., R. A. Bilonick, J. S. Kim, M. L. Gabriele, K. A. Townsend, J. S. Schuman; Automated Extraction of Optic Nerve Head Parameters From Stereoscopic Optic Nerve Head Photographs. Invest. Ophthalmol. Vis. Sci. 2007;48(13):3312.

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

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Abstract

Purpose:: To develop an automated system to define optic nerve head (ONH) and cup margins on stereo disc photographs and to evaluate its performance in comparison with human expert assessment.

Methods:: Stereo disc photos were taken using Nidek 3Dx camera. Fully automated detection of the ONH margin was performed using a software program of our own design. A 3-dimensional (3D) model of the ONH was generated by detecting corresponding points on a pair of stereo images. A deformable model technique was applied on the 3D model to automatically extract the cup margin. Three glaucoma specialists manually defined the ONH and cup margins in a randomized masked fashion. The majority opinion of the expert defined margins was compared with the automatically generated ONH measurements. Disc area, cup area, cup-to-disc (C/D) area ratio and C/D vertical ratio were computed based on both machine and expert defined margins. Areas under the receiver operating characteristic curve (AROC) were calculated using only healthy and glaucomatous eyes to test the glaucoma discriminating ability of each parameter.

Results:: 1 eye of each of 63 consecutive patients were enrolled (24 healthy, 19 glaucoma suspect, and 20 glaucomatous eyes). All ONH measurements based on machine defined margins showed a high correlation with the expert defined margins (R2 0.78 for disc area, 0.52 for cup area, 0.21 for C/D area ratio, 0.29 for vertical C/D ratio, all p≤0.0001, Pearson correlation). No significant difference was found in glaucoma discriminating ability between machine and human defined margins (AROC 0.87 vs 0.85 for C/D area ratio, AROC 0.89 vs 0.86 for vertical C/D ratio, respectively, both p>0.6 for the comparison of AROCs between methods).

Conclusions:: Fully automated ONH assessment of stereo disc photos performed as well as human experts in glaucoma discriminating performance and quantification of disc and cup area. The automated method provides an objective and quantitative option for ONH evaluation using widely available disc photographs.

Clinical Trial:: www.clinicaltrials.gov NCT00343746

Keywords: optic disc • depth • image processing 
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