Topologically controlled segmentation of 3D magnetic resonance images of the head by using morphological operators

Petr Dokládal, Isabelle Bloch, Michel Couprie, Daniel Ruijters, Raquel Urtasun, Line Garnero

Research output: Contribution to journalArticleAcademicpeer-review

41 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)2463-2478
Number of pages16
JournalPattern Recognition
Volume36
Issue number10
DOIs
Publication statusPublished - Oct 2003
Externally publishedYes

Keywords

  • 3D segmentation
  • Brain imaging
  • Mathematical morphology
  • Topological constraints

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