期刊
HIPPOCAMPUS
卷 19, 期 6, 页码 541-548出版社
WILEY-LISS
DOI: 10.1002/hipo.20616
关键词
Computational anatomy; Automated segmentation; MR imaging; FreeSurfer
资金
- NATIONAL CENTER FOR RESEARCH RESOURCES [P41RR015241, UL1RR025741] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE OF MENTAL HEALTH [P50MH071616, R01MH060883] Funding Source: NIH RePORTER
- NATIONAL INSTITUTE ON AGING [R01AG025824, P01AG026276, P50AG005681, P01AG003991] Funding Source: NIH RePORTER
- NCRR NIH HHS [P41 RR015241, UL1 RR025741] Funding Source: Medline
- NIA NIH HHS [P50 AG005681, P01 AG026276, R01 AG025824, P01 AG003991, P01 AG003991-250013, P01 AG026276-050004] Funding Source: Medline
- NIMH NIH HHS [R01 MH060883-10, R01 MH060883, P50 MH071616] Funding Source: Medline
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. (C) 2009 Wiley-Liss, Inc.
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