An adaptive nonlinear diffusion algorithm for filtering medical images.
IEEE Trans Inf Technol Biomed
; 4(4): 298-305, 2000 Dec.
Article
em En
| MEDLINE
| ID: mdl-11206815
ABSTRACT
The nonlinear anisotropic diffusive process has shown the good property of eliminating noise while preserving the accuracy of edges and has been widely used in image processing. However, filtering depends on the threshold of the diffusion process, i.e., the cut-off contrast of edges. The threshold varies from image to image and even from region to region within an image. The problem compounds with intensity distortion and contrast variation. We have developed an adaptive diffusion scheme by applying the Central Limit Theorem to selecting the threshold. Gaussian distribution and Rayleigh distribution are used to estimate the distributions of visual objects in images. Regression under such distributions separates the distribution of the major object from other visual objects in a single-peak histogram. The separation helps to automatically determine the threshold. A fast algorithm is derived for the regression process. The method has been successfully used in filtering various medical images.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Algoritmos
/
Interpretação de Imagem Assistida por Computador
Tipo de estudo:
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2000
Tipo de documento:
Article