Procedure to detect anatomical structures in optical fundus images

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Abstract
We present an overview of the design and test of an image processing procedure for detecting all important anatomical structures in color fundus images. These structures are the optic disk, the macula and the retinal network. The algorithm proceeds through five main steps: (1) automatic mask generation using pixels value statistics and color threshold, (2) visual image quality assessment using histogram matching and Canny edge distribution modeling, (3) optic disk localization using pyramidal decomposition, Hausdorff-based template matching and confidence assignment, (4) macula localization using pyramidal decomposition and (5) bessel network tracking using recursive dual edge tracking and connectivity recovering. The procedure has been tested on a database of about 40 color fundus images acquired from a digital non-mydriatic fundus camera. The database is composed of images of various types (macula- and optic disk-centered) and of various visual quality (with or without abnormal bright or dark regions, blurred, etc).

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