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AUTOMATIC MRI BRAIN TISSUE SEGMENTATION USING A HYBRID STATISTICAL AND GEOMETRIC MODEL
 

Summary: AUTOMATIC MRI BRAIN TISSUE SEGMENTATION USING A HYBRID STATISTICAL
AND GEOMETRIC MODEL
Albert Huang1
, Rafeef Abugharbieh1
, Roger Tam2
and Anthony Traboulsee2
1
Dept. of Elec. & Comp. Eng., The University of British Columbia, Vancouver, BC, V6T 1Z4, Canada
2
Dept. of Medicine, The University of British Columbia, Vancouver, BC, V6T 1Z3, Canada
ABSTRACT
This paper presents a novel hybrid segmentation technique
incorporating a statistical as well as a geometric model in a
unified segmentation scheme for brain tissue segmentation
of magnetic resonance imaging (MRI) scans. We combine
both voxel probability and image gradient and curvature
information for segmenting gray matter (GM) and white
matter (WM) tissues. Both qualitative and quantitative
results on synthetic and real brain MRI scans indicate
superior and consistent performance when compared with

  

Source: Abugharbieh, Rafeef - Department of Electrical and Computer Engineering, University of British Columbia

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences