DocumentCode
2237410
Title
From global to local, a continuum of shape models with fractal priors
Author
Vemuri, B.C. ; Radisavljevic, A.
Author_Institution
Florida Univ., Gainesville, FL, USA
fYear
1993
fDate
15-17 Jun 1993
Firstpage
307
Lastpage
313
Abstract
A new shape modeling scheme is introduced. It can transform smoothly from local (distributed parameter) to global (lumped parameter) models or vice-versa. The modeling scheme makes use of a hybrid primitive, called the deformable superquadric, constructed in an orthonormal wavelet basis. This multiresolution basis provides the power to continuously transform from local to global shape deformations, and thereby allow for a continuum of shape models-from those with local to those with global shape descriptive power-to be created. The characteristic of continuously transforming from local to global shape deformations allows the generation of fractal surfaces of arbitrary degree that can be useful in describing natural detail. These multiresolution shape models reembedded in a probabilistic framework and used for segmenting anatomical structures in the human brain from magnetic resonance imaging (MRI) data
Keywords
fractals; image recognition; image reconstruction; image segmentation; wavelet transforms; anatomical structures; deformable superquadric; descriptive power; distributed parameter models; fractal priors; fractal surfaces; global models; human brain; hybrid primitive; local models; lumped parameter models; magnetic resonance imaging; multiresolution basis; multiresolution shape models; natural detail; orthonormal wavelet basis; probabilistic framework; shape deformations; Anatomical structure; Brain modeling; Character generation; Deformable models; Fractals; Humans; Image resolution; Image segmentation; Magnetic resonance imaging; Shape;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 1993. Proceedings CVPR '93., 1993 IEEE Computer Society Conference on
Conference_Location
New York, NY
ISSN
1063-6919
Print_ISBN
0-8186-3880-X
Type
conf
DOI
10.1109/CVPR.1993.340964
Filename
340964
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