Title
Generalized ellipsoids and anisotropic filtering for segmentation improvement in 3D medical imaging
Abstract
Deformable models have demonstrated to be very useful techniques for image segmentation. However, they present several weak points. Two of the main problems with deformable models are the following: (1) results are often dependent on the initial model location, and (2) the generation of image potentials is very sensitive to noise. Modeling and preprocessing methods presented in this paper contribute to solve these problems. We propose an initialization tool to obtain a good approximation to global shape and location of a given object into a 3D image. We also introduce a novel technique for corner preserving anisotropic diffusion filtering to improve contrast and corner measures. This is useful for both guiding initialization (global shape) and subsequent deformation for fine tuning (local shape).
Year
DOI
Venue
2003
10.1016/S0262-8856(03)00006-4
Image and Vision Computing
Keywords
Field
DocType
Registration,Deformable models,Segmentation,Anisotropic diffusion,Surface patch saliency,3D medical images
Anisotropic diffusion,Computer vision,Ellipsoid,Scale-space segmentation,Segmentation,Segmentation-based object categorization,Anisotropic filtering,Image segmentation,Artificial intelligence,Initialization,Mathematics
Journal
Volume
Issue
ISSN
21
4
0262-8856
Citations 
PageRank 
References 
4
0.44
0
Authors
2
Name
Order
Citations
PageRank
Raquel Dosil114510.37
X.M. Pardo2736.75