Automated cell differentiation in multispectral microscopy
ICCOMP'07 Proceedings of the 11th WSEAS International Conference on Computers
IEICE - Transactions on Information and Systems
Robust optic disk segmentation from colour retinal images
Proceedings of the Seventh Indian Conference on Computer Vision, Graphics and Image Processing
Using blood vessels location information in optic disk segmentation
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
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For computer aided Glaucoma diagnostics it is essential to robustly and automatically detect and segment the main regions, e.g. the papilla (optic nerve head), in a fundus image. In this paper an effective method for automatic papilla segmentation based on the C-V model and a shape restraint is proposed. The method is a combination between the C-V model using level sets and the elliptic shape restraint for papilla segmentation. The combination of the level set framework with a shape restraint ensures that the evolving curve stays an ellipse. Experiments verify that the method shows a good performance in detecting the papilla shapes and computing the shape feature parameters within a broad variety of fundus images. The experiment results also show that the method is robust to noise and object deformity.