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Date
2019Journal
NeuroImagePublisher
Academic Press Inc.Type
Article
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The baby brain is constantly changing due to its active neurodevelopment, and research into the baby brain is one of the frontiers in neuroscience. To help guide neuroscientists and clinicians in their investigation of this frontier, maps of the baby brain, which contain a priori knowledge about neurodevelopment and anatomy, are essential. "Brain atlas" in this review refers to a 3D-brain image with a set of reference labels, such as a parcellation map, as the anatomical reference that guides the mapping of the brain. Recent advancements in scanners, sequences, and motion control methodologies enable the creation of various types of high-resolution baby brain atlases. What is becoming clear is that one atlas is not sufficient to characterize the existing knowledge about the anatomical variations, disease-related anatomical alterations, and the variations in time-dependent changes. In this review, the types and roles of the human baby brain MRI atlases that are currently available are described and discussed, and future directions in the field of developmental neuroscience and its clinical applications are proposed. The potential use of disease-based atlases to characterize clinically relevant information, such as clinical labels, in addition to conventional anatomical labels, is also discussed. Copyright 2018 The AuthorsSponsors
This publication was made possible by grants from the National Institutes of Health ( R01HD065955 , R01MH092535 and P41EB015909 ), and the Fakhri Rad BriteStar award from the Department of Radiology Johns Hopkins University School of Medicine . The contents of this paper are solely the responsibility of the authors and do not necessarily represent the official view of NIH or the authors' affiliated institutions. We thank Ms. Mary McAllister for her help with manuscript editing.Identifier to cite or link to this item
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045547312&doi=10.1016%2fj.neuroimage.2018.04.003&partnerID=40&md5=0a6a209915eba1764a0eb017574f5e31; http://hdl.handle.net/10713/8550ae974a485f413a2113503eed53cd6c53
10.1016/j.neuroimage.2018.04.003