Cortical reconstruction using implicit surface evolution: A landmark validation study

Duygu Tosun, Maryam E. Rettmann, Daniel Q. Naiman, Susan M. Resnick, Michael A. Kraut, Jerry L. Prince

Research output: Contribution to journalConference articlepeer-review


A validation study was conducted to assess the accuracy of an algorithm developed for automatic reconstruction of the cerebral cortex from T1-weighted magnetic resonance (MR) brain images. Manually selected landmarks on different sulcal regions throughout the cortex were used to analyze the accuracy of three reconstructed nested surfaces - the inner, central, and pial surfaces. We conclude that the algorithm can find these surfaces with subvoxel accuracy, typically with an accuracy of one third of a voxel, although this varies by brain region and cortical geometry. Parameters were adjusted on the basis of this analysis in order to improve the algorithm's overall performance. 1

Original languageEnglish (US)
Pages (from-to)384-392
Number of pages9
JournalLecture Notes in Computer Science
Issue numberPART 1
StatePublished - 2004
EventMedical Image Computing and Computer-Assisted Intervention, MICCAI 2004 - 7th International Conference, Proceedings - Saint-Malo, France
Duration: Sep 26 2004Sep 29 2004

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


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