Brain Surface Segmentation of Magnetic Resonance Images of the Fetus

Details

Serval ID
serval:BIB_8F7B9DA93190
Type
Inproceedings: an article in a conference proceedings.
Collection
Publications
Institution
Title
Brain Surface Segmentation of Magnetic Resonance Images of the Fetus
Title of the conference
EUSIPCO 2008, 16th European Signal Processing Conference
Author(s)
Ferrario D., Bach C.M., Schaer M., Houhou N., Zosso D., Eliez S., Guibaud L., Thiran J.P.
Address
Lausanne, Switzerland, August 25-29, 2008
Publication state
Published
Issued date
2008
Language
english
Abstract
In this work we present a method for the image analysisof Magnetic Resonance Imaging (MRI) of fetuses. Our goalis to segment the brain surface from multiple volumes(axial, coronal and sagittal acquisitions) of a fetus. Tothis end we propose a two-step approach: first, a FiniteGaussian Mixture Model (FGMM) will segment the image into3 classes: brain, non-brain and mixture voxels. Second, aMarkov Random Field scheme will be applied tore-distribute mixture voxels into either brain ornon-brain tissue. Our main contributions are an adaptedenergy computation and an extended neighborhood frommultiple volumes in the MRF step. Preliminary results onfour fetuses of different gestational ages will be shown.
Keywords
MRI, Segmentation, Markov Random Field,
Publisher's website
Create date
29/11/2011 17:40
Last modification date
20/08/2019 15:53
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