Generalized ellipsoids and anisotropic filtering for segmentation improvement in 3D medical imaging

被引:5
作者
Dosil, R [1 ]
Pardo, XM [1 ]
机构
[1] Univ Santiago de Compostela, Dept Elect & Computac, Santiago De Compostela 15782, Spain
关键词
SUPERQUADRICS; IMAGES; MODELS;
D O I
10.1016/S0262-8856(03)00006-4
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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). (C) 2003 Elsevier Science B.V. All rights reserved.
引用
收藏
页码:325 / 343
页数:19
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