CRUISE: Cortical reconstruction using implicit surface evolution

Xiao Han, Dzung L. Pham, Duygu Tosun, Maryam E. Rettmann, Chenyang Xu, Jerry Ladd Prince

Research output: Contribution to journalArticle

Abstract

Segmentation and representation of the human cerebral cortex from magnetic resonance (MR) images play an important role in neuroscience and medicine. A successful segmentation method must be robust to various imaging artifacts and produce anatomically meaningful and consistent cortical representations. A method for the automatic reconstruction of the inner, central, and outer surfaces of the cerebral cortex from T1-weighted MR brain images is presented. The method combines a fuzzy tissue classification method, an efficient topology correction algorithm, and a topology-preserving geometric deformable surface model (TGDM). The algorithm is fast and numerically stable, and yields accurate brain surface reconstructions that are guaranteed to be topologically correct and free from self-intersections. Validation results on real MR data are presented to demonstrate the performance of the method.

Original languageEnglish (US)
Pages (from-to)997-1012
Number of pages16
JournalNeuroImage
Volume23
Issue number3
DOIs
Publication statusPublished - Nov 2004

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Keywords

  • Cerebral cortex
  • Cortical reconstruction
  • Human brain mapping
  • Magnetic resonance
  • T1-weighted MR brain images

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Neurology

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