ROBUST FOVEAL AVASCULAR ZONE SEGMENTATION AND ANATOMICAL FEATURE EXTRACTION FROM OCT-A HANDLING INTER-EXPERT VARIABILITY - CNRS - Centre national de la recherche scientifique Accéder directement au contenu
Communication Dans Un Congrès Année : 2021

ROBUST FOVEAL AVASCULAR ZONE SEGMENTATION AND ANATOMICAL FEATURE EXTRACTION FROM OCT-A HANDLING INTER-EXPERT VARIABILITY

Résumé

The Foveal Avascular Zone (FAZ) is commonly analyzed from OCT-A images to diagnose retinal diseases. When quantitative measures are required, ophthalmologists manually draw the contours of the FAZ and compute several anatomical features from these annotations. However, there is no clear consensus among experts on the FAZ definition in pathological cases. In this work, we developed a novel framework to automatically segment the FAZ based on three different expert annotations to be robust to interexpert variability. A loss based on the Hausdorff Distance was used to specifically address complex pathological FAZ that are usually poorly segmented by automatic methods. We used a dataset of more than 200 images to train and test our model, and we achieved similar or even better segmentation performance than individual experts.
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Dates et versions

hal-03154386 , version 1 (28-02-2021)

Identifiants

  • HAL Id : hal-03154386 , version 1

Citer

Charles Jabour, Damien Garcia, Thibaud Mathis, Olivier Loria, Cédric Rochepeau, et al.. ROBUST FOVEAL AVASCULAR ZONE SEGMENTATION AND ANATOMICAL FEATURE EXTRACTION FROM OCT-A HANDLING INTER-EXPERT VARIABILITY. International Symposium on Biomedical Imaging, Apr 2021, Nice (virtual), France. ⟨hal-03154386⟩
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