CoChat
Sign Up
Cited by 116Medical Image Segmentation TechniquesDementia and Cognitive Impairment ResearchMemory and Neural Mechanisms

The DOI matches its Crossref record; 39 of the 39 references it cites were found in a registry or an index.

In Vivo Hippocampal Measurement and Memory: A Comparison of Manual Tracing and Automated Segmentation in a Large Community-Based Sample

Open access
Cherbuin, Nicolas, Anstey, Kaarin J., Réglade-Meslin, Chantal, Sachdev, Perminder S.·2009·PLoS ONE
DOI 10.1371/journal.pone.0005265PMC PMC2667216
Open this paper in CoChat — free accountOpen PDF

Abstract

While manual tracing is the method of choice in measuring hippocampal volume, its time intensive nature and proneness to human error make automated methods attractive, especially when applied to large samples. Few studies have systematically compared the performance of the two techniques. In this study, we measured hippocampal volumes in a large (N = 403) population-based sample of individuals aged 44-48 years using manual tracing by a trained researcher and automated procedure using Freesurfer (http://surfer.nmr.mgh.harvard.edu) imaging suite. Results showed that absolute hippocampal volumes assessed with these methods were significantly different, with automated measures using the Freesurfer software suite being significantly larger, by 23% for the left and 29% for the right hippocampus. The correlation between the two methods varied from 0.61 to 0.80, with lower correlations for hippocampi with visible abnormalities. Inspection of 2D and 3D models suggested that this difference was largely due to greater inclusion of boundary voxels by the automated method and variations in subiculum/entorhinal segmentation. The correlation between left and right hippocampal volumes was very similar by the two methods. The relationship of hippocampal volumes to selected sociodemographic and cognitive variables was not affected by the measurement method, with each measure showing an association with memory performance and suggesting that both were equally valid for this purpose. This study supports the use of automated measures, based on Freesurfer in this instance, as being sufficiently reliable and valid particularly in the context of larger sample sizes when the research question does not rely on 'true' hippocampal volumes.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0005265

Cites

39 of 39 references verified0 citation errors · 0 not checkable

Statistics

Figures

Figure 1 Examplars of automatically segmented hippocampi rated as a) no or minor defects (defects estimated to be smaller than ∼0.5% of total volume) b) moderate defects (∼0.5–5% of total volume), major defects (greater than 5% of total volume).
Figure 1 Examplars of automatically segmented hippocampi rated as a) no or minor defects (defects estimated to be smaller than ∼0.5% of total volume) b) moderate defects (∼0.5–5% of total volume), major defects (greater than 5% of total volume).CC BY · PubMed Central
Figure 2 Left and right hippocampal volumes measured by manual tracing (green) and automatic segmentation (yellow). ** significant difference at p<.01.
Figure 2 Left and right hippocampal volumes measured by manual tracing (green) and automatic segmentation (yellow). ** significant difference at p<.01.CC BY · PubMed Central
Figure 3 Bland-Altman diagrams plotting the difference in hipocampal volumes computed with the manual and automated methods against their average for each hippocampal pairs for the right (top) and left (bottom) hippocampus. The even scatter suggests there is no systematic error between methodologies beside the difference in absolute volume.
Figure 3 Bland-Altman diagrams plotting the difference in hipocampal volumes computed with the manual and automated methods against their average for each hippocampal pairs for the right (top) and left (bottom) hippocampus. The even scatter suggests there is no systematic error between methodologies beside the difference in absolute volume.CC BY · PubMed Central
Figure 4 Randomly selected 3D models of manually traced (green) and automatically segmented (yellow) hippocampus pairs. The models were produced using the ITK-Snap software package (www.itksnap.org) for the manual tracings and the Slicer package (www.slicer.org) for the automated measures.
Figure 4 Randomly selected 3D models of manually traced (green) and automatically segmented (yellow) hippocampus pairs. The models were produced using the ITK-Snap software package (www.itksnap.org) for the manual tracings and the Slicer package (www.slicer.org) for the automated measures.CC BY · PubMed Central
Figure 5 Manual tracing (left) and automated segmentation (right) of the hippocampus showing boundary differences (1 & 6: CSF inclusions; 2 greater subicular/entorhinal inclusion; 4 & 5 greater partial volume inclusion).
Figure 5 Manual tracing (left) and automated segmentation (right) of the hippocampus showing boundary differences (1 & 6: CSF inclusions; 2 greater subicular/entorhinal inclusion; 4 & 5 greater partial volume inclusion).CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 39 references

Cited by

Sorted by citations

Items 101–116 of 116

Related

See all

Metadata

Authors
Cherbuin, N., Anstey, K. J., Réglade-Meslin, C., & Sachdev, P. S.
Affiliations
  • Australian National University (AU)
  • UNSW Sydney (AU)
Corresponding author
Cherbuin, Nicolas
ORCID
Venue
PLoS ONE
Publisher
Public Library of Science (PLoS)
Published
2009-04-16
Volume
4
Issue
4
Pages
e5265
ISSN
1932-6203 (ISSN-L)
DOI
10.1371/journal.pone.0005265
PMC
PMC2667216
OpenAlex
W2061639197
Cited by
116
References
39
Citations by year
2026: 1 · 2025: 2 · 2024: 2 · 2023: 5 · 2022: 6 · 2021: 4 · 2020: 5 · 2019: 6 · 2018: 8 · 2017: 6 · 2016: 10 · 2015: 13 · 2014: 9 · 2013: 11 · 2012: 7
FWCI
10.30
Type
journal article
Language
en
Open access
Licence
Locations
  • PLoS ONE (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • UNSWorks (University of New South Wales, Sydney, Australia) (submittedVersion, cc-by-nc-nd)
  • UNSWorks (UNSW Sydney) (submittedVersion, cc-by-nc-nd)
  • RePEc: Research Papers in Economics (submittedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • ANU Open Research (Australian National University) (submittedVersion, cc-by)
Funders
  • Australian Rotary Health
  • Medical Research Council
  • National Health and Medical Research Council (973302, 366756, 418020, 157125, 179805)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Health Sciences › Medicine › Psychiatry and Mental health › Dementia and Cognitive Impairment Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Memory and Neural Mechanisms
Keywords
hippocampal volume, FreeSurfer, measurement method comparison, memory performance, community sample
MeSH terms
Adult, Female, Hippocampus, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging, Male, Memory, Middle Aged, Organ Size, Pattern Recognition, Automated, Regression Analysis, Socioeconomic Factors, Imaging, Three-Dimensional

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review