Cited by 2,956Medical Image Segmentation TechniquesFunctional Brain Connectivity StudiesAnatomy and Medical Technology

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Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature

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Destrieux, Christophe, Fischl, Bruce, Dale, Anders, Halgren, Eric·2010·NeuroImage

DOI 10.1016/j.neuroimage.2010.06.010PMC PMC2937159

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Abstract

Precise localization of sulco-gyral structures of the human cerebral cortex is important for the interpretation of morpho-functional data, but requires anatomical expertise and is time consuming because of the brain's geometric complexity. Software developed to automatically identify sulco-gyral structures has improved substantially as a result of techniques providing topologically correct reconstructions permitting inflated views of the human brain. Here we describe a complete parcellation of the cortical surface using standard internationally accepted nomenclature and criteria. This parcellation is available in the FreeSurfer package. First, a computer-assisted hand parcellation classified each vertex as sulcal or gyral, and these were then subparcellated into 74 labels per hemisphere. Twelve datasets were used to develop rules and algorithms (reported here) that produced labels consistent with anatomical rules as well as automated computational parcellation. The final parcellation was used to build an atlas for automatically labeling the whole cerebral cortex. This atlas was used to label an additional 12 datasets, which were found to have good concordance with manual labels. This paper presents a precisely defined method for automatically labeling the cortical surface in standard terminology.

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Authors: Destrieux, C., Fischl, B., Dale, A., & Halgren, E.
Affiliations: Université de Tours (FR)
Harvard University (US)
University of California San Diego (US)
Corresponding author: Destrieux, Christophe
ORCID: Destrieux, Christophe
Fischl, Bruce
Dale, Anders
Halgren, Eric
Venue: NeuroImage
Publisher: Elsevier BV
Published: 2010-10
Volume: 53
Issue: 1
Pages: 1-15
ISSN: 1053-8119 (ISSN-L)
DOI: 10.1016/j.neuroimage.2010.06.010
PMC: PMC2937159
OpenAlex: W2007581301
Cited by: 2,956
References: 41
Citations by year: 2026: 272 · 2025: 328 · 2024: 287 · 2023: 290 · 2022: 291 · 2021: 272 · 2020: 241 · 2019: 188 · 2018: 189 · 2017: 163 · 2016: 130 · 2015: 98 · 2014: 75 · 2013: 62 · 2012: 44
FWCI: 48.65
Type: journal article
Language: en
Open access: green
www.ncbi.nlm.nih.gov
Licence: www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations: NeuroImage (publishedVersion)
PubMed (publishedVersion)
Europe PMC (PubMed Central) (acceptedVersion)
PubMed Central (acceptedVersion)
HAL (submittedVersion)
Funders: Centre Hospitalier Régional et Universitaire de Tours
National Institute for Neurological Disorders and Stroke (R01 NS18741, R01 NS052585)
National Center for Research Resources (P41-RR14075, BIRN002, U24 RR021382)
National Institute for Biomedical Imaging and Bioengineering (R01 EB001550, R01 EB006758, R01 EB009282)
National Institute on Aging (R01 AG02238)
Mental Illness and Neuroscience Discovery (MIND) Institute
National Institutes of Health (U54 EB005149)
Ellison Medical Foundation
Topics: Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Medical Image Segmentation Techniques
Life Sciences › Neuroscience › Cognitive Neuroscience › Functional Brain Connectivity Studies
Physical Sciences › Engineering › Biomedical Engineering › Anatomy and Medical Technology
Keywords: cortical parcellation, FreeSurfer, anatomical terminology, brain surface reconstruction
MeSH terms: Adolescent, Adult, Algorithms, Brain, Computer Simulation, Female, Humans, Image Enhancement, Image Interpretation, Computer-Assisted, Magnetic Resonance Imaging, Male, Models, Anatomic, Terminology as Topic, Pattern Recognition, Automated, Sensitivity and Specificity, Reproducibility of Results, Imaging, Three-Dimensional, Young Adult

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Automatic parcellation of human cortical gyri and sulci using standard anatomical nomenclature

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