Combining 3D Deformable Models and Level Set Methods for the Segmentation of Abdominal Aortic Aneurysms

In this paper we present a system that combines the benefits of 3D deformable models and level set methods for medical volume segmentation. Our 3D deformable model is a very computationally efficient method for segmenting medical volumes, however it is not currently able to segment features, such as renal arteries, that are small relative to the imaging slice thickness used. Level Set methods are an alternative approach to deformable models that re-pose the volume segmentation problem as the calculation of the steady state of an initial value Partial Differential Equation (PDE) system on a regular rectilinear or cubic mesh. The segmentation obtained is parameterised by the zero value level set of this mesh (analogous to an iso-surface). These methods are very computationally expensive, but have the advantage of being able to segment relatively small features such as renal arteries. The problem domain explored in this paper is the segmentation of arterial structures. The results of t...

• Type: Conference
• Year: 2001
• Where: BMVC
• Authors: Derek R. Magee, Andrew J. Bulpitt, Elizabeth Berry
• Keywords: BMVC 2001, Computer Vision, Deformable Models, Level Set, Level Set Methods