Cited by 250Medical Image Segmentation TechniquesAdvanced Neuroimaging Techniques and ApplicationsAdvanced MRI Techniques and Applications

Measurement of cortical thickness using an automated 3-D algorithm: a validation study

Kabani, Noor, Le Goualher, Georges, MacDonald, David, Evans, Alan C.·2001·NeuroImage

Abstract

A validation study was conducted to assess the accuracy of the algorithm developed by MacDonald et al. (1999) for measuring cortical thickness. This algorithm automatically determines the cortical thickness by 3-D extraction of the inner and outer surfaces of the cerebral cortex from an MRI scan. A manual method of tagging the grey-csf and grey-white interface was used on 20 regions (10 cortical areas found in each hemisphere) in 40 MRIs of the brain to validate the algorithm. The regions were chosen throughout the cortex to get broad assessment of the algorithm's performance. Accuracy was determined by an anatomist tagging the csf-grey and grey-white borders of selected gyri and by allowing the algorithm to determine the csf-grey and grey-white borders and the corresponding cortical thickness of the same region. Results from the manual and automatic methods were statistically compared using overall ANOVA and paired t tests for each region. The manual and automatic methods were in agreement for all but 4 of the 20 regions tested. The four regions where there were significant differences between the two methods were the insula left and right, the right cuneus, and the right parahippocampus. We conclude that the automatic algorithm is valid for most of the cortex and provides a viable alternative to manual methods of determining cortical thickness in vivo. However, caution should be taken when measuring the regions mentioned previously where the results of the algorithm can be biased by surrounding grey structures.

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Crossref · 10.1006/nimg.2000.0652

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  • The CLASP cortical thickness algorithm has been validated using manual measurements and simulation approaches.

    “Validation of the CLASP cortical thickness algorithm has been done using both manual measurements (Kabani et al. 2001) and simulation approaches (Lerch and Evans 2005;Lee et al. 2006).”

    From Developmental Changes in Organization of Structural Brain Networks (2013) · cites this paper as Kabani et al. 2001

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References 16 · Cited by 250

Authors
Kabani, N., Le Goualher, G., MacDonald, D., & Evans, A. C.
Affiliations
Montreal Neurological Institute and Hospital (CA)
Corresponding author
Kabani, Noor
Venue
NeuroImage
Publisher
Elsevier BV
Published
2001-02
Volume
13
Issue
2
Pages
375-380
ISSN
1053-8119 (ISSN-L)
OpenAlex
W1967337284
Cited by
250
References
16
Citations by year
2025: 2 · 2024: 2 · 2023: 4 · 2022: 4 · 2021: 9 · 2020: 8 · 2019: 7 · 2018: 9 · 2017: 11 · 2016: 16 · 2015: 19 · 2014: 14 · 2013: 21 · 2012: 13
FWCI
6.06
Type
journal article
Language
en
Open access
closed
Locations
  • NeuroImage (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced Neuroimaging Techniques and Applications
  • Health Sciences › Medicine › Radiology, Nuclear Medicine and Imaging › Advanced MRI Techniques and Applications
Keywords
cortical thickness, algorithm validation, insula, cuneus, parahippocampal gyrus, brain MRI
MeSH terms
Adult, Algorithms, Automation, Cerebral Cortex, Humans, Magnetic Resonance Imaging, Imaging, Three-Dimensional

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