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Title: Topologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators
Authors: Dokladal, Petr ×
Bloch, Isabelle
Couprie, Michel
Ruijters, Daniel
Urtasun, Raquel
Garnero, Line #
Issue Date: Oct-2003
Publisher: Pergamon-elsevier science ltd
Series Title: Pattern recognition vol:36 issue:10 pages:2463-2478
Abstract: This paper proposes a new data-driven segmentation technique of 3D T1-weighted magnetic resonance scans of human head. This technique serves to the construction of individual head models. Several structures of the head are extracted. The morphology-oriented approach combined with an extensive use of topological constraints provides a robust and automatic method requiring minimum user intervention. This new approach is suitable to applications where the topology is one of the main constraints. The originality of the approach lies in the satisfaction of such constraints and in an effort towards robustness. (C) 2003 Pattern Recognition Society. Published by Elsevier Ltd. All rights reserved.
Description: Dokladal P., Bloch I., Couprie M., Ruijters D., Urtasun R., Garnero L., ''Topologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators'', Pattern recognition, vol. 36, no. 10, pp. 2463-2478, October 2003.
URI: 
ISSN: 0031-3203
Publication status: published
KU Leuven publication type: IT
Appears in Collections:ESAT - PSI, Processing Speech and Images
× corresponding author
# (joint) last author

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