Geometric Computation of Human Gyrification Indexes from Magnetic Resonance Images

Abstract

Human Brains are highly convoluted surfaces with multiple folds. To characterize the complexity of these folds and their relationship with neurological and psychiatric conditions, different techniques have been developed to quantify the folding patterns and gyrification of the brain. In this work, we propose a new geometric approach to measure the local gyrification of human brains from magnetic resonance images (MRI). This approach is based on intrinsic 3D measurements that relate the local brain surface area to the corresponding area of a tightly wrapped sheet. These quantities are efficiently and accurately computed solving geometric partial differential equations. The presentation of the geometric framework is complemented with experimental results for brain complexity in typically developing children and adolescents. Using this novel approach, we provide evidence for developmental alterations in brain surface complexity throughout childhood and adolescence.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2009
Accession Number
ADA513236

Entities

People

  • Chiu-yen Kao
  • Guillermo Sapiro
  • Marcus Schmidt
  • Shu Su
  • Tonya White

Organizations

  • University of Minnesota

Tags

DTIC Thesaurus Topics

  • Age Groups
  • Algorithms
  • Brain
  • Cerebral Cortex
  • Cognition
  • Computational Science
  • Computations
  • Curvature
  • Data Analysis
  • Geometry
  • Magnetic Resonance
  • Mathematics
  • Psychiatry
  • Resonance
  • Statistical Analysis
  • Three Dimensional
  • Two Dimensional

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