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

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.

Mots clés

in vivo diagnosis Photoreceptor detection Retina imaging Adaptive Optics

Domaines

Traitement du signal et de l'image [eess.SP]

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https://hal.science/hal-02882938

Soumis le : dimanche 28 juin 2020-09:47:33

Dernière modification le : mercredi 23 octobre 2024-10:30:04

Dates et versions

hal-02882938 , version 1 (28-06-2020)

Identifiants

HAL Id : hal-02882938 , version 1
DOI : 10.1007/978-3-642-31298-4_48

Citer

Kevin Loquin, Isabelle Bloch, Kiyoko Nakashima, Florence Rossant, Pierre-Yves Boëlle, et al.. Automatic Photoreceptor Detection in In-Vivo Adaptive Optics Retinal Images: Statistical Validation. ICIAR, Jun 2012, Aveiro, Portugal. ⟨10.1007/978-3-642-31298-4_48⟩. ⟨hal-02882938⟩

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