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.
Article
Dans Chinois
| 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.
Texte intégral:
Disponible
Indice:
WPRIM (Pacifique occidental)
Sujet Principal:
Anatomopathologie
/
Algorithmes
/
Reconnaissance automatique des formes
/
Intelligence artificielle
/
Imagerie par résonance magnétique
/
Interprétation d'images assistée par ordinateur
/
Amélioration d'image
/
Imagerie tridimensionnelle
/
Diagnostic
/
Tumeurs des méninges
Type d'étude:
Etude diagnostique
Limites du sujet:
Humains
langue:
Chinois
Texte intégral:
Journal of Southern Medical University
Année:
2011
Type:
Article
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