Shape-based normalization of the corpus callosum for DTI connectivity analysis

Hui Sun, Paul A. Yushkevich, Hui Zhang, Philip A. Cook, Jeffrey T. Duda, Tony J Simon, James C. Gee

Research output: Contribution to journalArticle

15 Scopus citations

Abstract

The continuous medial representation (cm-rep) is an approach that makes it possible to model, normalize, and analyze anatomical structures on the basis of medial geometry. Having recently presented a partial differential equation (PDE)-based approach for 3-D cm-rep modeling [1], here we present an equivalent 2-D approach that involves solving an ordinary differential equation. This paper derives a closed form solution of this equation and shows how Pythagorean hodograph curves can be used to express the solution as a piecewise polynomial function, allowing efficient and robust medial modeling. The utility of the approach in medical image analysis is demonstrated by applying it to the problem of shape-based normalization of the midsagittal section of the corpus callosum. Using diffusion tensor tractography, we show that shapebased normalization aligns subrogions of the corpus callosum, defined by connectivity, more accurately than normalization based on volumetric registration. Furthermore, shape-based normalization helps increase the statistical power of group analysis in an experiment where features derived from diffusion tensor tractography are compared between two cohorts. These results suggest that cm-rep is an appropriate tool for normalizing the corpus callosum in white matter studies.

Original languageEnglish (US)
Pages (from-to)1166-1178
Number of pages13
JournalIEEE Transactions on Medical Imaging
Volume26
Issue number9
DOIs
StatePublished - Sep 2007

Keywords

  • Corpus callosum
  • Geometrical representation
  • Image analysis
  • Medial
  • Medial representation
  • Shape analysis
  • Skeleton

ASJC Scopus subject areas

  • Biomedical Engineering
  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Electrical and Electronic Engineering
  • Computer Science Applications
  • Computational Theory and Mathematics

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