Browsing Multiple Subjects When the Atlas Adaptation Cannot Be Achieved
3D
brain atlas
inter-subject
parcellation atlas
structural approach
visualization
Journal
Frontiers in neuroinformatics
ISSN: 1662-5196
Titre abrégé: Front Neuroinform
Pays: Switzerland
ID NLM: 101477957
Informations de publication
Date de publication:
2022
2022
Historique:
received:
28
10
2021
accepted:
17
01
2022
entrez:
21
3
2022
pubmed:
22
3
2022
medline:
22
3
2022
Statut:
epublish
Résumé
Brain mapping studies often need to identify brain structures or functional circuits into a set of individual brains. To this end, multiple atlases have been published to represent such structures based on different modalities, subject sets, and techniques. The mainstream approach to exploit these atlases consists in spatially deforming each individual data onto a given atlas using dense deformation fields, which supposes the existence of a continuous mapping between atlases and individuals. However, this continuity is not always verified, and this "iconic" approach has limits. We present in this study an alternative, complementary, "structural" approach, which consists in extracting structures from the individual data, and comparing them without deformation. A "structural atlas" is thus a collection of annotated individual data with a common structure nomenclature. It may be used to characterize structure shape variability across individuals or species, or to train machine learning systems. This study exhibits
Identifiants
pubmed: 35311005
doi: 10.3389/fninf.2022.803934
pmc: PMC8928460
doi:
Types de publication
Journal Article
Langues
eng
Pagination
803934Informations de copyright
Copyright © 2022 Rivière, Leprince, Labra, Vindas, Foubet, Cagna, Loh, Hopkins, Balzeau, Mancip, Lebenberg, Cointepas, Coulon and Mangin.
Déclaration de conflit d'intérêts
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
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