Brain tissue segmentation of fetal MR images

Détails

ID Serval
serval:BIB_4C9AF0C608CE
Type
Actes de conférence (partie): contribution originale à la littérature scientifique, publiée à l'occasion de conférences scientifiques, dans un ouvrage de compte-rendu (proceedings), ou dans l'édition spéciale d'un journal reconnu (conference proceedings).
Collection
Publications
Institution
Titre
Brain tissue segmentation of fetal MR images
Titre de la conférence
MICCAI 2009, 12th International Conference on Medical Image Computing and Computer Assisted Intervention
Auteur⸱e⸱s
Bach Cuadra M., Schaer M., Andre A., Guibaud L., Eliez S., Thiran J.P.
Adresse
London, United-Kingdom, September 20-24, 2009
Statut éditorial
Publié
Date de publication
2009
Langue
anglais
Résumé
We present a segmentation method for fetal brain tissuesof T2w MR images, based on the well known ExpectationMaximization Markov Random Field (EM- MRF) scheme. Ourmain contribution is an intensity model composed of 7Gaussian distribution designed to deal with the largeintensity variability of fetal brain tissues. The secondmain contribution is a 3-steps MRF model that introducesboth local spatial and anatomical priors given by acortical distance map. Preliminary results on 4 subjectsare presented and evaluated in comparison to manualsegmentations showing that our methodology cansuccessfully be applied to such data, dealing with largeintensity variability within brain tissues and partialvolume (PV).
Mots-clé
Fetal Magnetic Resonance Imaging, Brain tissue segmentation, Statistical classification, CIBM-SPC
Création de la notice
29/11/2011 17:40
Dernière modification de la notice
20/08/2019 15:01
Données d'usage