Fully-automated, multi-stage hippocampus mapping in very mild Alzheimer disease

Lei Wang, Ali Khan, John G. Csernansky, Bruce Fischl, Michael I. Miller, John C. Morris, M. Faisal Beg

Research output: Contribution to journalArticle

22 Scopus citations

Abstract

Landmark-based high-dimensional diffeomorphic maps of the hippocampus (although accurate) is highly-dependent on rater's anatomic knowledge of the hippocampus in the magnetic resonance images. It is therefore vulnerable to rater drift and errors if substantial amount of effort is not spent on quality assurance, training, and re-training. A fully-automated, FreeSurfer-initialized large-deformation diffeomorphic metric mapping procedure of small brain substructures, including the hippocampus, has been previously developed and validated in small samples. In this report, we demonstrate that this fully-automated pipeline can be used in place of the landmark-based procedure in a large-sample clinical study to produce similar statistical outcomes. Some direct comparisons of the two procedures are also presented.

Original languageEnglish
Pages (from-to)541-548
Number of pages8
JournalHippocampus
Volume19
Issue number6
DOIs
StatePublished - Jun 2009

Keywords

  • Automated segmentation
  • Computational anatomy
  • FreeSurfer
  • MR imaging

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