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G.-Z. Yang et al. (Eds.): MICCAI 2009, Part II, LNCS 5762, pp. 474481, 2009. Springer-Verlag Berlin Heidelberg 2009
 

Summary: G.-Z. Yang et al. (Eds.): MICCAI 2009, Part II, LNCS 5762, pp. 474481, 2009.
Springer-Verlag Berlin Heidelberg 2009
A Fuzzy Region-Based Hidden Markov Model for
Partial-Volume Classification in Brain MRI
Albert Huang1
, Rafeef Abugharbieh1
, and Roger Tam2
1
Department of Electrical and Computer Engineering
{alberth,rafeef}@ece.ubc.ca
2
Department of Radiology, The University of British Columbia, Vancouver, B.C., Canada
roger@msmri.medicine.ubc.ca
Abstract. We present a novel fuzzy region-based hidden Markov model
(frbHMM) for unsupervised partial-volume classification in brain magnetic
resonance images (MRIs). The primary contribution is an efficient graphical
representation of 3D image data in which irregularly-shaped image regions
have memberships to a number of classes rather than one discrete class. Our
model groups voxels into regions for efficient processing, but also refines the
region boundaries to the voxel level for optimal accuracy. This strategy is most

  

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

 

Collections: Biology and Medicine; Computer Technologies and Information Sciences