Abstract
The standard geometric or geodesic active contour is a powerful segmentation
method, whose performance however is commonly affected by the presence of weak
edges and noise. Since image modalities of all types in medical imaging are
prone to such outcomes, it is important for geomertic snakes to develop some
level of immunity towards them. In this chapter, a region-aided geometric
snake, enhanced for more tolerance towards weak edges and noise, is
introduced. It is based on the principle of the conjunction of the traditional
gradient flow forces with new region constraints. We refer to this as the
Region-aided Geometric Snake or RAGS. The RAGS formulation is easily extended to
deal with colour images. Quantitive comparisons with other well-known geometric snakes
in synthetic noisy images are presented. We also show the evaluation
of RAGS with application to the localisation of the Optic Disk in colour retinal images.
Many other images are also used to demonstrate the proposed method.
Translated title of the contribution | A Region-Aided Color Geometric Snake |
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Original language | English |
Title of host publication | Handbook of Biomedical Image Analysis: Segmentation Models |
Publisher | Springer US |
Volume | 1 |
ISBN (Print) | 0306485508 |
Publication status | Published - 2005 |
Bibliographical note
Other page information: 535-582Other identifier: 2000225