NDLI: Segmentation 3D+t d'images IRM cérébrales par une chaîne de Markov 4D

Content Provider	Semantic Scholar
Author	Lavigne, Francois Collet, Christophe Armspach, Jean-Paul
Copyright Year	2014
Abstract	Ces dernieres annees, beaucoup de methodes semiautomatiques ont ete developpees afin d'aider les praticiens dans leur diagnostic des maladies cerebrales ; malgre tout le probleme reste complexe. Dans cet article, nous proposons une methode de segmentation simultanee des structures cerebrales de deux images IRM 3D multimodales prises a deux instants differents (acquisition longitudinale). Cette segmentation repose sur une Chaine de Markov Cachee (CMC) permettant de prendre en compte la correlation temporelle en plus de l'information de voisinage spatial, une correction du biais est realisee. Pour augmenter la robustesse de la methode, nous utilisons l'estimateur de vraisemblance tamisee (EVT), afin de detecter d'eventuelles lesions sans affecter la segmentation. La methode a ete validee sur des images IRM 3D+t simulees de la base BrainWeb.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://hal.archives-ouvertes.fr/hal-00988732/document
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article

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