Computational neuroanatomy of baby brains: A review.
Brain atlas
Cortical surface
Infant brain
Parcellation
Registration
Segmentation
Journal
NeuroImage
ISSN: 1095-9572
Titre abrégé: Neuroimage
Pays: United States
ID NLM: 9215515
Informations de publication
Date de publication:
15 01 2019
15 01 2019
Historique:
received:
15
10
2017
revised:
23
02
2018
accepted:
19
03
2018
pubmed:
27
3
2018
medline:
6
4
2019
entrez:
26
3
2018
Statut:
ppublish
Résumé
The first postnatal years are an exceptionally dynamic and critical period of structural, functional and connectivity development of the human brain. The increasing availability of non-invasive infant brain MR images provides unprecedented opportunities for accurate and reliable charting of dynamic early brain developmental trajectories in understanding normative and aberrant growth. However, infant brain MR images typically exhibit reduced tissue contrast (especially around 6 months of age), large within-tissue intensity variations, and regionally-heterogeneous, dynamic changes, in comparison with adult brain MR images. Consequently, the existing computational tools developed typically for adult brains are not suitable for infant brain MR image processing. To address these challenges, many infant-tailored computational methods have been proposed for computational neuroanatomy of infant brains. In this review paper, we provide a comprehensive review of the state-of-the-art computational methods for infant brain MRI processing and analysis, which have advanced our understanding of early postnatal brain development. We also summarize publically available infant-dedicated resources, including MRI datasets, computational tools, grand challenges, and brain atlases. Finally, we discuss the limitations in current research and suggest potential future research directions.
Identifiants
pubmed: 29574033
pii: S1053-8119(18)30255-6
doi: 10.1016/j.neuroimage.2018.03.042
pmc: PMC6150852
mid: NIHMS957333
pii:
doi:
Types de publication
Journal Article
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't
Review
Langues
eng
Sous-ensembles de citation
IM
Pagination
906-925Subventions
Organisme : NIMH NIH HHS
ID : R21 MH108914
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS093842
Pays : United States
Organisme : NIMH NIH HHS
ID : K01 MH109773
Pays : United States
Organisme : NIMH NIH HHS
ID : K01 MH107815
Pays : United States
Organisme : NIMH NIH HHS
ID : U01 MH110274
Pays : United States
Organisme : NIMH NIH HHS
ID : R01 MH100217
Pays : United States
Informations de copyright
Copyright © 2018 Elsevier Inc. All rights reserved.
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