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Automated segmentation of hippocampal subfields from ultra-high resolution in vivo MRI.

Recent developments in MRI data acquisition technology are starting to yield images that show anatomical features of the hippocampal formation at an unprecedented level of detail, providing the basis for hippocampal subfield measurement. However, a fundamental bottleneck in MRI studies of the hippocampus at the subfield level is that they currently depend on manual segmentation, a laborious process that severely limits the amount of data that can be analyzed. In this article, we present a computational method for segmenting the hippocampal subfields in ultra-high resolution MRI data in a fully automated fashion. Using Bayesian inference, we use a statistical model of image formation around the hippocampal area to obtain automated segmentations. We validate the proposed technique by comparing its segmentations to corresponding manual delineations in ultra-high resolution MRI scans of 10 individuals, and show that automated volume measurements of the larger subfields correlate well with manual volume estimates. Unlike manual segmentations, our automated technique is fully reproducible, and fast enough to enable routine analysis of the hippocampal subfields in large imaging studies.

Pubmed ID: 19405131

Authors

  • Van Leemput K
  • Bakkour A
  • Benner T
  • Wiggins G
  • Wald LL
  • Augustinack J
  • Dickerson BC
  • Golland P
  • Fischl B

Journal

Hippocampus

Publication Data

June 2, 2009

Associated Grants

  • Agency: NCRR NIH HHS, Id: P41 RR013218
  • Agency: NCRR NIH HHS, Id: P41 RR013218-08
  • Agency: NCRR NIH HHS, Id: P41 RR014075
  • Agency: NCRR NIH HHS, Id: P41 RR014075-02
  • Agency: NCRR NIH HHS, Id: P41-RR13218
  • Agency: NCRR NIH HHS, Id: P41-RR14075
  • Agency: NIA NIH HHS, Id: R01 AG029411
  • Agency: NIA NIH HHS, Id: R01 AG029411-02
  • Agency: NIBIB NIH HHS, Id: R01 EB001550
  • Agency: NIBIB NIH HHS, Id: R01 EB001550-03
  • Agency: NIBIB NIH HHS, Id: R01 EB006758
  • Agency: NIBIB NIH HHS, Id: R01 EB006758-03
  • Agency: NINDS NIH HHS, Id: R01 NS051826
  • Agency: NINDS NIH HHS, Id: R01 NS051826
  • Agency: NINDS NIH HHS, Id: R01 NS051826-02
  • Agency: NINDS NIH HHS, Id: R01 NS052585
  • Agency: NINDS NIH HHS, Id: R01 NS052585-01
  • Agency: NINDS NIH HHS, Id: R01 NS052585-01A1
  • Agency: NCRR NIH HHS, Id: R01 RR016594
  • Agency: NCRR NIH HHS, Id: R01 RR016594-01A1
  • Agency: NCRR NIH HHS, Id: R01 RR16594-01A1
  • Agency: NIBIB NIH HHS, Id: R01EB006758
  • Agency: NIA NIH HHS, Id: R21 AG029840
  • Agency: NIA NIH HHS, Id: R21 AG029840-02
  • Agency: NCRR NIH HHS, Id: U24 RR021382
  • Agency: NCRR NIH HHS, Id: U24 RR021382
  • Agency: NCRR NIH HHS, Id: U24 RR021382-03
  • Agency: NIBIB NIH HHS, Id: U54 EB005149
  • Agency: NIBIB NIH HHS, Id: U54 EB005149-010014
  • Agency: NIBIB NIH HHS, Id: U54-EB005149

Mesh Terms

  • Adult
  • Aged
  • Aged, 80 and over
  • Aging
  • Algorithms
  • Alzheimer Disease
  • Automation
  • Bayes Theorem
  • Hippocampus
  • Humans
  • Magnetic Resonance Imaging
  • Middle Aged
  • Organ Size
  • Young Adult