NDLI: Automatic Segmentation of the Papilla in a Fundus Image Based on the C-V Model and a Shape Restraint

Content Provider	IEEE Xplore Digital Library
Author	Yandong Tang Xiaomao Li von Freyberg, A. Goch, G.
Copyright Year	2006
Description	Author affiliation: Shenyang Inst. of Autom., Chinese Acad. of Sci., Beijing (Yandong Tang; Xiaomao Li)
Abstract	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
Sponsorship	IEEE CPS
Starting Page	183
Ending Page	186
File Size	209520
Page Count	4
File Format	PDF
ISBN	0769525210
ISSN	10514651
DOI	10.1109/ICPR.2006.307
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-08-20
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Capacitance-voltage characteristics Shape Biomedical imaging Computer vision Image quality Robustness Biomedical optical imaging Level set Image processing
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition

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