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本文引用的文献

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Automatic labeling of cortical sulci for the human fetal brain based on spatio-temporal information of gyrification.基于脑回时空信息的胎儿大脑皮质脑沟自动标记
Neuroimage. 2019 Mar;188:473-482. doi: 10.1016/j.neuroimage.2018.12.023. Epub 2018 Dec 12.
2
Reproducibility and intercorrelation of graph theoretical measures in structural brain connectivity networks.结构脑连接网络中图论度量的可重复性和相关性。
Med Image Anal. 2019 Feb;52:56-67. doi: 10.1016/j.media.2018.10.009. Epub 2018 Oct 26.
3
TractSeg - Fast and accurate white matter tract segmentation.TractSeg-快速准确的白质束分割。
Neuroimage. 2018 Dec;183:239-253. doi: 10.1016/j.neuroimage.2018.07.070. Epub 2018 Aug 4.
4
Analytic tractography: A closed-form solution for estimating local white matter connectivity with diffusion MRI.分析轨迹:用弥散磁共振成像估计局部白质连通性的闭式解。
Neuroimage. 2018 Apr 1;169:473-484. doi: 10.1016/j.neuroimage.2017.12.039. Epub 2017 Dec 22.
5
Human Fetal Brain Connectome: Structural Network Development from Middle Fetal Stage to Birth.人类胎儿脑连接组:从中孕期到出生的结构网络发育
Front Neurosci. 2017 Oct 13;11:561. doi: 10.3389/fnins.2017.00561. eCollection 2017.
6
Gyri of the human parietal lobe: Volumes, spatial extents, automatic labelling, and probabilistic atlases.人类顶叶脑回:体积、空间范围、自动标记和概率图谱。
PLoS One. 2017 Aug 28;12(8):e0180866. doi: 10.1371/journal.pone.0180866. eCollection 2017.
7
Spatiotemporal Relationship of Brain Pathways during Human Fetal Development Using High-Angular Resolution Diffusion MR Imaging and Histology.利用高角分辨率扩散磁共振成像和组织学研究人类胎儿发育过程中脑通路的时空关系
Front Neurosci. 2017 Jul 11;11:348. doi: 10.3389/fnins.2017.00348. eCollection 2017.
8
diffusion tensor imaging of the fetal brain: A reproducibility study.胎儿脑弥散张量成像:一项可重复性研究。
Neuroimage Clin. 2017 Jun 9;15:601-612. doi: 10.1016/j.nicl.2017.06.013. eCollection 2017.
9
Concurrent white matter bundles and grey matter networks using independent component analysis.基于独立成分分析的白质束和灰质网络的并发研究。
Neuroimage. 2018 Apr 15;170:296-306. doi: 10.1016/j.neuroimage.2017.05.012. Epub 2017 May 14.
10
Temporal slice registration and robust diffusion-tensor reconstruction for improved fetal brain structural connectivity analysis.用于改进胎儿脑结构连接性分析的时间切片配准和稳健扩散张量重建
Neuroimage. 2017 Aug 1;156:475-488. doi: 10.1016/j.neuroimage.2017.04.033. Epub 2017 Apr 19.

发育中的人类胎儿大脑连接组构建与量化中的挑战与机遇

Challenges and Opportunities in Connectome Construction and Quantification in the Developing Human Fetal Brain.

作者信息

Hunt David, Dighe Manjiri, Gatenby Christopher, Studholme Colin

机构信息

Department of Pediatrics.

Department of Radiology.

出版信息

Top Magn Reson Imaging. 2019 Oct;28(5):265-273. doi: 10.1097/RMR.0000000000000212.

DOI:10.1097/RMR.0000000000000212
PMID:31592993
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6788770/
Abstract

The white matter structure of the human brain undergoes critical developmental milestones in utero, which we can observe noninvasively using diffusion-weighted magnetic resonance imaging. In order to understand this fascinating developmental process, we must establish the variability inherent in such a challenging imaging environment and how measurable quantities can be transformed into meaningful connectomes. We review techniques for reconstructing and studying the brain connectome and explore promising opportunities for in utero studies that could lead to more accurate measurement of structural properties and allow for more refined and insightful analyses of the fetal brain. Opportunities for more sophisticated analyses of the properties of the brain and its dynamic changes have emerged in recent years, based on the development of iterative techniques to reconstruct motion-corrupted diffusion-weighted data. Although reconstruction quality is greatly improved, the treatment of fundamental quantities like edge strength requires careful treatment because of the specific challenges of imaging in utero. There are intriguing challenges to overcome, from those in analysis due to both imaging limitations and the significant changes in structural connectivity, to further image processing to address the specific properties of the target anatomy and quantification into a developmental connectome.

摘要

人类大脑的白质结构在子宫内经历关键的发育里程碑,我们可以使用扩散加权磁共振成像进行无创观察。为了理解这一迷人的发育过程,我们必须确定在如此具有挑战性的成像环境中固有的变异性,以及如何将可测量的量转化为有意义的连接组。我们回顾了用于重建和研究大脑连接组的技术,并探索子宫内研究的有前景的机会,这些研究可能导致对结构特性进行更准确的测量,并允许对胎儿大脑进行更精细和有见地的分析。近年来,基于迭代技术的发展,用于重建运动受损的扩散加权数据,出现了对大脑特性及其动态变化进行更复杂分析的机会。尽管重建质量有了很大提高,但由于子宫内成像的特定挑战,像边缘强度这样的基本量的处理需要谨慎对待。从由于成像限制和结构连接性的显著变化而在分析中遇到的挑战,到进一步的图像处理以解决目标解剖结构的特定特性并量化为发育连接组,都有有趣的挑战需要克服。