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Automatic Photoreceptor Detection in In-Vivo Adaptive Optics Retinal Images: Statistical Validation

  • Kevin Loquin
  • Isabelle Bloch
  • Kiyoko Nakashima
  • Florence Rossant
  • Pierre-Yves Boelle
  • Michel Paques
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7325)

Abstract

This article presents a photoreceptor detection algorithm applied to in-vivo Adaptive Optics (AO) images of the retina obtained from an advanced ophthalmic diagnosis device. Our algorithm is based on a recursive construction of thresholded connected components when the seeds of the recursions are the regional maxima of the deconvoluted image. This algorithm is validated on a gold standard dataset obtained thanks to manual cones detections made by ophtalmologist physicians.

Keywords

Adaptive Optics Photoreceptor detection in vivo diagnosis retina imaging 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Kevin Loquin
    • 1
  • Isabelle Bloch
    • 1
  • Kiyoko Nakashima
    • 2
  • Florence Rossant
    • 3
  • Pierre-Yves Boelle
    • 4
  • Michel Paques
    • 2
  1. 1.Institut Telecom - Telecom ParisTech - CNRS LTCIParisFrance
  2. 2.CIC 503 of the XV-XX Hospital DHOS/INSERMParisFrance
  3. 3.ISEPParisFrance
  4. 4.Hôpital Saint-AntoineParisFrance

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