Enforcing Monotonic Temporal Evolution in Dry Eye Images

  • Authors:
  • Tamir Yedidya;Peter Carr;Richard Hartley;Jean-Pierre Guillon

  • Affiliations:
  • The Australian National University, and National ICT, Australia;The Australian National University, and National ICT, Australia;The Australian National University, and National ICT, Australia;Faculty of Medicine and Health Sciences, Lions Eye Institute, Australia

  • Venue:
  • MICCAI '09 Proceedings of the 12th International Conference on Medical Image Computing and Computer-Assisted Intervention: Part II
  • Year:
  • 2009

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Abstract

We address the problem of identifying dry areas in the tear film as part of a diagnostic tool for dry-eye syndrome. The requirement is to identify and measure the growth of the dry regions to provide a time-evolving map of degrees of dryness. We segment dry regions using a multi-label graph-cut algorithm on the 3D spatio-temporal volume of frames from a video sequence. To capture the fact that dryness increases over the time of the sequence, we use a time-asymmetric cost function that enforces a constraint that the dryness of each pixel monotonically increases. We demonstrate how this increases our estimation's reliability and robustness. We tested the method on a set of videos and suggest further research using a similar approach.