Literature DB >> 32877840

Group-level cortical surface parcellation with sulcal pits labeling.

Irène Kaltenmark1, Christine Deruelle2, Lucile Brun2, Julien Lefèvre2, Olivier Coulon2, Guillaume Auzias2.   

Abstract

Sulcal pits are the points of maximal depth within the folds of the cortical surface. These shape descriptors give a unique opportunity to access to a rich, fine-scale representation of the geometry and the developmental milestones of the cortical surface. However, using sulcal pits analysis at group level requires new numerical tools to establish inter-subject correspondences. Here, we address this issue by taking advantage of the geometrical information carried by sulcal basins that are the local patches of surfaces surrounding each sulcal pit. Our framework consists in two phases. First, we present a new method to generate a population-specific atlas of this sulcal basins organi- zation as a fold-level parcellation of the cortical surface. Then, we address the labeling of individual sulcal pits and corresponding basins with respect to this atlas. To assess their validity, we applied these methodological advances on two different populations of healthy subjects. The first database of 137 adults allowed us to compare our method to the state-of-the-art and the second database of 209 children, aged between 0 and 18 years, illustrates the adaptability and relevance of our method in the context of pediatric data showing strong variations in cortical volume and folding.
Copyright © 2020 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Cortical folding; Morphometry; Sulcal pits

Mesh:

Year:  2020        PMID: 32877840      PMCID: PMC7908680          DOI: 10.1016/j.media.2020.101749

Source DB:  PubMed          Journal:  Med Image Anal        ISSN: 1361-8415            Impact factor:   8.545


  22 in total

1.  "Sulcal root" generic model: a hypothesis to overcome the variability of the human cortex folding patterns.

Authors:  Jean Régis; Jean-François Mangin; Taku Ochiai; Vincent Frouin; Denis Riviére; Arnaud Cachia; Manabu Tamura; Yves Samson
Journal:  Neurol Med Chir (Tokyo)       Date:  2005-01       Impact factor: 1.742

2.  Depth potential function for folding pattern representation, registration and analysis.

Authors:  Maxime Boucher; Sue Whitesides; Alan Evans
Journal:  Med Image Anal       Date:  2008-10-01       Impact factor: 8.545

3.  Spatial distribution of deep sulcal landmarks and hemispherical asymmetry on the cortical surface.

Authors:  Kiho Im; Hang Joon Jo; Jean-François Mangin; Alan C Evans; Sun I Kim; Jong-Min Lee
Journal:  Cereb Cortex       Date:  2009-06-26       Impact factor: 5.357

4.  Identification of growth seeds in the neonate brain through surfacic Helmholtz decomposition.

Authors:  Julien Lefèvre; François Leroy; Sheraz Khan; Jessica Dubois; Petra S Huppi; Sylvain Baillet; Jean-François Mangin
Journal:  Inf Process Med Imaging       Date:  2009

5.  Cortical surface-based analysis. I. Segmentation and surface reconstruction.

Authors:  A M Dale; B Fischl; M I Sereno
Journal:  Neuroimage       Date:  1999-02       Impact factor: 6.556

6.  Deep sulcal landmarks: algorithmic and conceptual improvements in the definition and extraction of sulcal pits.

Authors:  G Auzias; L Brun; C Deruelle; O Coulon
Journal:  Neuroimage       Date:  2015-02-09       Impact factor: 6.556

7.  Structural graph-based morphometry: A multiscale searchlight framework based on sulcal pits.

Authors:  Sylvain Takerkart; Guillaume Auzias; Lucile Brun; Olivier Coulon
Journal:  Med Image Anal       Date:  2016-05-11       Impact factor: 8.545

Review 8.  Sulcal pits and patterns in developing human brains.

Authors:  Kiho Im; P Ellen Grant
Journal:  Neuroimage       Date:  2018-03-27       Impact factor: 6.556

9.  Spatial distribution and longitudinal development of deep cortical sulcal landmarks in infants.

Authors:  Yu Meng; Gang Li; Weili Lin; John H Gilmore; Dinggang Shen
Journal:  Neuroimage       Date:  2014-06-17       Impact factor: 6.556

10.  The macro-structural variability of the human neocortex.

Authors:  Frithjof Kruggel
Journal:  Neuroimage       Date:  2018-02-02       Impact factor: 6.556

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