Estimating local surface complexity maps using spherical harmonic reconstructions

Rachel Aine Yotter, Paul M. Thompson, Igor Nenadic, Christian Gaser

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Cortical surface complexity is a potential structural marker for certain diseases such as schizophrenia. In this study, we developed a measure of fractal dimension (FD) calculated from lowpass-filtered spherical harmonic brain surface reconstructions. A local FD measure was also computed at each vertex in a cortical surface mesh, visualizing local variations in surface complexity over the brain surface. We analyzed the surface complexity for 87 patients with DSM-IV schizophrenia (with stable psychopathology and treated with antipsychotic medication) and 108 matched healthy controls. The global FD for the right hemisphere in the schizophrenic group was significantly lower than that in controls. Local FD maps showed that the lower complexity was mainly due to differences in the prefrontal cortex.

Original languageEnglish
Title of host publicationMedical Image Computing and Computer-Assisted Intervention, MICCAI2010 - 13th International Conference, Proceedings
Pages169-176
Number of pages8
EditionPART 2
DOIs
StatePublished - 2010
Externally publishedYes
Event13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010 - Beijing, China
Duration: 20 Sep 201024 Sep 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume6362 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference13th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2010
Country/TerritoryChina
CityBeijing
Period20/09/1024/09/10

Keywords

  • MRI
  • fractal dimension
  • schizophrenia
  • spherical harmonics
  • surface complexity

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