Automatic Photoreceptor Detection in In-Vivo Adaptive Optics Retinal Images: Statistical Validation - Télécom Paris
Communication Dans Un Congrès Année : 2012

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

Kevin Loquin
  • Fonction : Auteur
  • PersonId : 1216677
Kiyoko Nakashima
  • Fonction : Auteur
Florence Rossant
  • Fonction : Auteur
Pierre-Yves Boelle
M. Pâques
  • Fonction : Auteur

Résumé

This article presents a photoreceptor detection algorithm ap- plied 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 im- age. This algorithm is validated on a gold standard dataset obtained thanks to manual cones detections made by ophtalmologist physicians.
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Dates et versions

hal-02286293 , version 1 (13-09-2019)

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  • HAL Id : hal-02286293 , version 1

Citer

Kevin Loquin, Isabelle Bloch, Kiyoko Nakashima, Florence Rossant, Pierre-Yves Boelle, et al.. Automatic Photoreceptor Detection in In-Vivo Adaptive Optics Retinal Images: Statistical Validation. International Conference on Image Analysis and Recognition - ICIAR 2012, Jun 2012, Aveiro, Portugal. pp.408-415. ⟨hal-02286293⟩
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