Bayesian detection of the fovea in eye fundus angiographies

This paper is concerned with the automatic detection of the avascular foveal zone (fovea), in eye fundus angiographies. Fluorescein angiography is used in ophthalmic practice to evaluate vascular retinopathies and choroidopathies: sodium ̄uorescein is injected in the arm's cubital vein of the patient and its distribution along retinal vessels at certain times is observed. The proposed methodology is based on Bayesian statistical methods that allow to incorporate the previous knowledge about the eye fundus in the model. The contour of the fovea is modeled by means of a unidimensional Markov chain and the observed intensities are assumed Gaussian and statistically independent between pixels. Two approximations are used in order to estimate the model's parameters: Empirical and Fully Bayesian. Two algorithms have been used in order to estimate the fovea contour: Simulated Annealing (SA) and Iterated Conditional Modes (ICM). This procedure is applied to di€erent cases of diabetic retinopathy and vein occlusions. Ó 1999 Elsevier Science B.V. All rights reserved.