A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth

Abstract Longitudinal characterization of early brain growth in-utero has been limited by a number of challenges in fetal imaging, the rapid change in size, shape and volume of the developing brain, and the consequent lack of suitable algorithms for fetal brain image analysis. There is a need for an...

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Autores principales:	Ali Gholipour, Caitlin K. Rollins, Clemente Velasco-Annis, Abdelhakim Ouaalam, Alireza Akhondi-Asl, Onur Afacan, Cynthia M. Ortinau, Sean Clancy, Catherine Limperopoulos, Edward Yang, Judy A. Estroff, Simon K. Warfield
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/6b14817351fd4d07a2c01427dc0bd3b7
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spelling	oai:doaj.org-article:6b14817351fd4d07a2c01427dc0bd3b72021-12-02T16:08:13ZA normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth10.1038/s41598-017-00525-w2045-2322https://doaj.org/article/6b14817351fd4d07a2c01427dc0bd3b72017-03-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-00525-whttps://doaj.org/toc/2045-2322Abstract Longitudinal characterization of early brain growth in-utero has been limited by a number of challenges in fetal imaging, the rapid change in size, shape and volume of the developing brain, and the consequent lack of suitable algorithms for fetal brain image analysis. There is a need for an improved digital brain atlas of the spatiotemporal maturation of the fetal brain extending over the key developmental periods. We have developed an algorithm for construction of an unbiased four-dimensional atlas of the developing fetal brain by integrating symmetric diffeomorphic deformable registration in space with kernel regression in age. We applied this new algorithm to construct a spatiotemporal atlas from MRI of 81 normal fetuses scanned between 19 and 39 weeks of gestation and labeled the structures of the developing brain. We evaluated the use of this atlas and additional individual fetal brain MRI atlases for completely automatic multi-atlas segmentation of fetal brain MRI. The atlas is available online as a reference for anatomy and for registration and segmentation, to aid in connectivity analysis, and for groupwise and longitudinal analysis of early brain growth.Ali GholipourCaitlin K. RollinsClemente Velasco-AnnisAbdelhakim OuaalamAlireza Akhondi-AslOnur AfacanCynthia M. OrtinauSean ClancyCatherine LimperopoulosEdward YangJudy A. EstroffSimon K. WarfieldNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-13 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Ali Gholipour Caitlin K. Rollins Clemente Velasco-Annis Abdelhakim Ouaalam Alireza Akhondi-Asl Onur Afacan Cynthia M. Ortinau Sean Clancy Catherine Limperopoulos Edward Yang Judy A. Estroff Simon K. Warfield A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth
description	Abstract Longitudinal characterization of early brain growth in-utero has been limited by a number of challenges in fetal imaging, the rapid change in size, shape and volume of the developing brain, and the consequent lack of suitable algorithms for fetal brain image analysis. There is a need for an improved digital brain atlas of the spatiotemporal maturation of the fetal brain extending over the key developmental periods. We have developed an algorithm for construction of an unbiased four-dimensional atlas of the developing fetal brain by integrating symmetric diffeomorphic deformable registration in space with kernel regression in age. We applied this new algorithm to construct a spatiotemporal atlas from MRI of 81 normal fetuses scanned between 19 and 39 weeks of gestation and labeled the structures of the developing brain. We evaluated the use of this atlas and additional individual fetal brain MRI atlases for completely automatic multi-atlas segmentation of fetal brain MRI. The atlas is available online as a reference for anatomy and for registration and segmentation, to aid in connectivity analysis, and for groupwise and longitudinal analysis of early brain growth.
format	article
author	Ali Gholipour Caitlin K. Rollins Clemente Velasco-Annis Abdelhakim Ouaalam Alireza Akhondi-Asl Onur Afacan Cynthia M. Ortinau Sean Clancy Catherine Limperopoulos Edward Yang Judy A. Estroff Simon K. Warfield
author_facet	Ali Gholipour Caitlin K. Rollins Clemente Velasco-Annis Abdelhakim Ouaalam Alireza Akhondi-Asl Onur Afacan Cynthia M. Ortinau Sean Clancy Catherine Limperopoulos Edward Yang Judy A. Estroff Simon K. Warfield
author_sort	Ali Gholipour
title	A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth
title_short	A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth
title_full	A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth
title_fullStr	A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth
title_full_unstemmed	A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth
title_sort	normative spatiotemporal mri atlas of the fetal brain for automatic segmentation and analysis of early brain growth
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/6b14817351fd4d07a2c01427dc0bd3b7
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A normative spatiotemporal MRI atlas of the fetal brain for automatic segmentation and analysis of early brain growth

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