Models of Normal Variation and Local Contrasts in Hippocampal Anatomy

  • Authors:

  • Xinyang Liu;Washington Mio;Yonggang Shi;Ivo Dinov;Xiuwen Liu;Natasha Leporé;Franco Leporé;Madeleine Fortin;Patrice Voss;Maryse Lassonde;Paul M. Thompson

  • Affiliations:

  • Department of Mathematics, Florida State University, Tallahassee, FL 32306;Department of Mathematics, Florida State University, Tallahassee, FL 32306;Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA 90095;Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA 90095;Department of Computer Science, Florida State University, Tallahassee, FL 32306;Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA 90095;Departement de Psychologie, Université de Montréal, Montréal, Canada;Departement de Psychologie, Université de Montréal, Montréal, Canada;Departement de Psychologie, Université de Montréal, Montréal, Canada;Departement de Psychologie, Université de Montréal, Montréal, Canada;Laboratory of Neuro Imaging, UCLA School of Medicine, Los Angeles, CA 90095

  • Venue:
  • MICCAI '08 Proceedings of the 11th International Conference on Medical Image Computing and Computer-Assisted Intervention, Part II
  • Year:
  • 2008

Quantified Score

Hi-index 0.00

Visualization

Abstract

We develop a model of continuous spherical shapes and use it to analyze the anatomy of the hippocampus. To account for the geometry of bends and folds, the model relies on a geodesic metric that is sensitive to first-order deformations. We construct an atlas of the hippocampus as a mean shape and develop statistical models to characterize quantitative and qualitative normal shape variation. We also develop a localization tool to identify local contrasts in the anatomy of different populations. The tool is applied to the detection, characterization and visualization of anatomical differences such as local enlargement and gains in volume on the right hippocampus of blind subjects.