Detection of optic disc in retinal images by means of a geometrical model of vessel structure

We present here a new method to identify the position of the optic disc (OD) in retinal fundus images. The method is based on the preliminary detection of the main retinal vessels. All retinal vessels originate from the OD and their path follows a similar directional pattern (parabolic course) in al...

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Bibliographic Details
Published in:IEEE transactions on medical imaging 2004-10, Vol.23 (10), p.1189-1195
Main Authors: Foracchia, M., Grisan, E., Ruggeri, A.
Format: Article
Language:English
Subjects:
Algorithms
Artificial Intelligence
Computer Simulation
Discs
Disks
Fluorescein Angiography - methods
Geometrical optics
Humans
Image Enhancement - methods
Image Interpretation, Computer-Assisted - methods
Information Storage and Retrieval - methods
Mathematical model
Mathematical models
Medical imaging
Models, Biological
Numerical Analysis, Computer-Assisted
Optic Disk - anatomy & histology
Optic Disk - blood supply
Optical detectors
Optimization
Parametric statistics
Pathology
Pattern Recognition, Automated - methods
Reproducibility of Results
Retina
Retinal images
Retinal vessels
Retinal Vessels - anatomy & histology
Sensitivity and Specificity
Signal Processing, Computer-Assisted
Simulated annealing
Solid modeling
Structural discs
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Summary:We present here a new method to identify the position of the optic disc (OD) in retinal fundus images. The method is based on the preliminary detection of the main retinal vessels. All retinal vessels originate from the OD and their path follows a similar directional pattern (parabolic course) in all images. To describe the general direction of retinal vessels at any given position in the image, a geometrical parametric model was proposed, where two of the model parameters are the coordinates of the OD center. Using as experimental data samples of vessel centerline points and corresponding vessel directions, provided by any vessel identification procedure, model parameters were identified by means of a simulated annealing optimization technique. These estimated values provide the coordinates of the center of OD. A Matlab/spl reg/ prototype implementing this method was developed. An evaluation of the proposed procedure was performed using the set of 81 images from the STARE project, containing images from both normal and pathological subjects. The OD position was correctly identified in 79 out of 81 images (98%), even in rather difficult pathological situations.
ISSN:0278-0062
1558-254X
DOI:10.1109/TMI.2004.829331