Consistent reconstruction of cortical surfaces from longitudinal brain MR images

Gang Li, Jingxin Nie, Guorong Wu, Yaping Wang, Dinggang Shen

Research output: Contribution to journalArticle

62 Citations (Scopus)

Abstract

Accurate and consistent reconstruction of cortical surfaces from longitudinal human brain MR images is of great importance in studying longitudinal subtle change of the cerebral cortex. This paper presents a novel deformable surface method for consistent and accurate reconstruction of inner, central and outer cortical surfaces from longitudinal brain MR images. Specifically, the cortical surfaces of the group-mean image of all aligned longitudinal images of the same subject are first reconstructed by a deformable surface method, which is driven by a force derived from the Laplace's equation. And then the longitudinal cortical surfaces are consistently reconstructed by jointly deforming the cortical surfaces of the group-mean image to all longitudinal images. The proposed method has been successfully applied to two sets of longitudinal human brain MR images. Both qualitative and quantitative experimental results demonstrate the accuracy and consistency of the proposed method. Furthermore, the reconstructed longitudinal cortical surfaces are used to measure the longitudinal changes of cortical thickness in both normal and diseased groups, where the overall decline trend of cortical thickness has been clearly observed. Meanwhile, the longitudinal cortical thickness also shows its potential in distinguishing different clinical groups.

Original languageEnglish
Pages (from-to)3805-3820
Number of pages16
JournalNeuroImage
Volume59
Issue number4
DOIs
Publication statusPublished - 2012 Feb 15

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Keywords

  • Cortical surface reconstruction
  • Longitudinal cortical surface
  • Longitudinal cortical thickness

ASJC Scopus subject areas

  • Neurology
  • Cognitive Neuroscience

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