Variational segmentation of vector-valued images with gradient vector flow.
IEEE Trans Image Process
; 23(11): 4773-85, 2014 Nov.
Article
em En
| MEDLINE
| ID: mdl-25203991
ABSTRACT
In this paper, we extend the gradient vector flow field for robust variational segmentation of vector-valued images. Rather than using scalar edge information, we define a vectorial edge map derived from a weighted local structure tensor of the image that enables the diffusion of the gradient vectors in accurate directions through the 4D gradient vector flow equation. To reduce the contribution of noise in the structure tensor, image channels are weighted according to a blind estimator of contrast. The method is applied to biological volume delineation in dynamic PET imaging, and validated on realistic Monte Carlo simulations of numerical phantoms as well as on real images.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Reologia
/
Algoritmos
/
Encéfalo
/
Interpretação de Imagem Assistida por Computador
/
Imageamento Tridimensional
/
Tomografia por Emissão de Pósitrons
Tipo de estudo:
Diagnostic_studies
Limite:
Humans
Idioma:
En
Revista:
IEEE Trans Image Process
Assunto da revista:
INFORMATICA MEDICA
Ano de publicação:
2014
Tipo de documento:
Article