A graph cuts-based interactive method for segmentation of magnetic resonance images of meningioma / 南方医科大学学报
Journal of Southern Medical University
;
(12): 1164-1168, 2011.
Artigo
em Chinês
| WPRIM
| ID: wpr-235172
ABSTRACT
For accurate segmentation of the magnetic resonance (MR) images of meningioma, we propose a novel interactive segmentation method based on graph cuts. The high dimensional image features was extracted, and for each pixel, the probabilities of its origin, either the tumor or the background regions, were estimated by exploiting the weighted K-nearest neighborhood classifier. Based on these probabilities, a new energy function was proposed. Finally, a graph cut optimal framework was used for the solution of the energy function. The proposed method was evaluated by application in the segmentation of MR images of meningioma, and the results showed that the method significantly improved the segmentation accuracy compared with the gray level information-based graph cut method.
Texto completo:
DisponíveL
Índice:
WPRIM (Pacífico Ocidental)
Assunto principal:
Patologia
/
Algoritmos
/
Reconhecimento Automatizado de Padrão
/
Inteligência Artificial
/
Imageamento por Ressonância Magnética
/
Interpretação de Imagem Assistida por Computador
/
Aumento da Imagem
/
Imageamento Tridimensional
/
Diagnóstico
/
Neoplasias Meníngeas
Tipo de estudo:
Estudo diagnóstico
Limite:
Humanos
Idioma:
Chinês
Revista:
Journal of Southern Medical University
Ano de publicação:
2011
Tipo de documento:
Artigo
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