A comparison of automated segmentation and manual tracing for quantifying hippocampal and amygdala volumes
Open accessAbstract
Large databases of high-resolution structural MR images are being assembled to quantitatively examine the relationships between brain anatomy, disease progression, treatment regimens, and genetic influences upon brain structure. Quantifying brain structures in such large databases cannot be practically accomplished by expert neuroanatomists using hand-tracing. Rather, this research will depend upon automated methods that reliably and accurately segment and quantify dozens of brain regions. At present, there is little guidance available to help clinical research groups in choosing such tools. Thus, our goal was to compare the performance of two popular and fully automated tools, FSL/FIRST and FreeSurfer, to expert hand tracing in the measurement of the hippocampus and amygdala. Volumes derived from each automated measurement were compared to hand tracing for percent volume overlap, percent volume difference, across-sample correlation, and 3-D group-level shape analysis. In addition, sample size estimates for conducting between-group studies were computed for a range of effect sizes. Compared to hand tracing, hippocampal measurements with FreeSurfer exhibited greater volume overlap, smaller volume difference, and higher correlation than FIRST, and sample size estimates with FreeSurfer were closer to hand tracing. Amygdala measurement with FreeSurfer was also more highly correlated to hand tracing than FIRST, but exhibited a greater volume difference than FIRST. Both techniques had comparable volume overlap and similar sample size estimates. Compared to hand tracing, a 3-D shape analysis of the hippocampus showed FreeSurfer was more accurate than FIRST, particularly in the head and tail. However, FIRST more accurately represented the amygdala shape than FreeSurfer, which inflated its anterior and posterior surfaces.
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FreeSurfer is one of the most reliable automated brain segmentation methods for the amygdala, and its measures correlate highly with expert hand tracings.
“Overall, FreeSurfer provides one of the most reliable automated brain segmentation methods for assessing the amygdala and these measures correlate highly with expert hand tracings (90).”
From Disorganized attachment in infancy predicts greater amygdala volume in adulthood (2016) · cites this paper as [90]
Volumetric changes of the hippocampus that occur with age, with various neuropsychiatric disorders, and also in response to stress are quite heterogeneous.
“While some of the reasons for this may be methodological such as MR image acquisition parameters, post acquisition processing and the method used for volumetric assessment (Geuze et al., 2005; Morey et al., 2009), it is clear that volumetric changes of the hippocampus that occur with age, with various neuropsychiatric disorders, and also in response to stress are quite heterogeneous.”
From Widespread reductions in gray matter volume in depression (2013) · cites this paper as Morey et al., 2009
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- Authors
- Morey, R. A., Petty, C. M., Xu, Y., Pannu Hayes, J., Wagner, H. R., Lewis, D. V., LaBar, K. S., Styner, M., & McCarthy, G.
- Affiliations
- University of North Carolina at Chapel Hill (US)
- Duke University (US)
- Corresponding author
- Morey, Rajendra A.
- Venue
- NeuroImage
- Publisher
- Elsevier BV
- Published
- 2009-04
- Volume
- 45
- Issue
- 3
- Pages
- 855-866
- ISSN
- 1053-8119 (ISSN-L)
- PMC
- PMC2714773
- OpenAlex
- W2129574992
- Cited by
- 540
- References
- 24
- Citations by year
- 2026: 8 · 2025: 15 · 2024: 13 · 2023: 20 · 2022: 23 · 2021: 36 · 2020: 26 · 2019: 40 · 2018: 45 · 2017: 45 · 2016: 43 · 2015: 56 · 2014: 49 · 2013: 39 · 2012: 27
- FWCI
- 26.37
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- NeuroImage (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion, public-domain)
- UNC Libraries
- Funders
- U.S. Department of Veterans Affairs
- National Institutes of Health (5r01ns043209-09, MH60451)
- National Institute of Mental Health (K23MH073091, P50MH60451, P50MH060451)
- National Institute of Neurological Disorders and Stroke (NS 43209, R01-NS043209, 43209, R37NS043209, MH60451)
- NIH Clinical Center
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
- Life Sciences › Neuroscience › Neurology › Brain Tumor Detection and Classification
- Physical Sciences › Engineering › Biomedical Engineering › Medical Imaging and Analysis
- Keywords
- hippocampus, amygdala, brain segmentation, automatic segmentation, manual tracing, FreeSurfer, hippocampal volume, amygdala volume, sample size determination, structural MRI
- MeSH terms
- Amygdala, Automation, Hippocampus, Humans, Image Processing, Computer-Assisted, Magnetic Resonance Imaging
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