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A Shape-based Glaucoma Index for Tomographic Images

Author

Listed:
  • Gordana Derado
  • Kanti Mardia
  • Vic Patrangenaru
  • Hilary Thompson

Abstract

We examine the use of Confocal Laser Tomographic images for detecting glaucoma. From the clinical aspect, the optic nerve head's (ONH) area contains all the relevant information on glaucoma. The shape of ONH is approximately a skewed cup. We summarize its shape by three biological landmarks on the neural-rim and the fourth landmark as the point of the maximum depth, which is approximately the point where the optic nerve enters this eye cup. These four landmarks are extracted from the images related to some Rhesus monkeys before and after inducing glaucoma. Previous analysis on Bookstein shape coordinates of these four landmarks revealed only marginally significant findings. From clinical experience, it is believed that the ratio depth to diameter of the eye cup provides a useful measure of the shape change. We consider the bootstrap distribution of this normalized 'depth' (G) and give evidence that it provides an appropriate measure of the shape change. This measure G is labelled as the glaucoma index. Further experiments are in progress to validate its use for glaucoma in humans.

Suggested Citation

  • Gordana Derado & Kanti Mardia & Vic Patrangenaru & Hilary Thompson, 2004. "A Shape-based Glaucoma Index for Tomographic Images," Journal of Applied Statistics, Taylor & Francis Journals, vol. 31(10), pages 1241-1248.
  • Handle: RePEc:taf:japsta:v:31:y:2004:i:10:p:1241-1248
    DOI: 10.1080/0266476042000285486
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    Citations

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    Cited by:

    1. Crane, M. & Patrangenaru, V., 2011. "Random change on a Lie group and mean glaucomatous projective shape change detection from stereo pair images," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 225-237, February.
    2. Bandulasiri, Ananda & Bhattacharya, Rabi N. & Patrangenaru, Vic, 2009. "Nonparametric inference for extrinsic means on size-and-(reflection)-shape manifolds with applications in medical imaging," Journal of Multivariate Analysis, Elsevier, vol. 100(9), pages 1867-1882, October.

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