Depth-based shape-analysis

Med Image Comput Comput Assist Interv. 2014;17(Pt 3):17-24. doi: 10.1007/978-3-319-10443-0_3.

Abstract

In this paper we propose a new method for shape analysis based on the depth-ordering of shapes. We use this depth-ordering to non-parametrically define depth with respect to a normal control population. This allows us to quantify differences with respect to "normality". We combine this approach with a permutation test allowing it to test for localized shape differences. The method is evaluated on a synthetically generated striatum dataset as well as on a real caudate dataset.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Algorithms*
  • Brain / pathology*
  • Epilepsy / pathology*
  • Female
  • Humans
  • Image Enhancement / methods
  • Image Interpretation, Computer-Assisted / methods*
  • Imaging, Three-Dimensional / methods*
  • Pattern Recognition, Automated / methods*
  • Reproducibility of Results
  • Schizotypal Personality Disorder / pathology*
  • Sensitivity and Specificity