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本文引用的文献

1
Fast Fiber Orientation Estimation in Diffusion MRI from kq-Space Sampling and Anatomical Priors.基于kq空间采样和解剖学先验知识的扩散磁共振成像中快速纤维方向估计
J Imaging. 2021 Oct 27;7(11):226. doi: 10.3390/jimaging7110226.
2
A Multi-Tissue Global Estimation Framework for Asymmetric Fiber Orientation Distributions.一种用于非对称纤维取向分布的多组织全局估计框架。
Med Image Comput Comput Assist Interv. 2018 Sep;11072:45-52. doi: 10.1007/978-3-030-00931-1_6. Epub 2018 Sep 13.
3
Asymmetry Spectrum Imaging for Baby Diffusion Tractography.用于婴儿扩散张量成像的不对称频谱成像
Inf Process Med Imaging. 2019 Jun;11492:319-331. doi: 10.1007/978-3-030-20351-1_24. Epub 2019 May 22.
4
Joint spatial-angular sparse coding for dMRI with separable dictionaries.基于可分离字典的弥散磁共振成像的联合空间角度稀疏编码。
Med Image Anal. 2018 Aug;48:25-42. doi: 10.1016/j.media.2018.05.002. Epub 2018 May 25.
5
Asymmetric Orientation Distribution Functions (AODFs) revealing intravoxel geometry in diffusion MRI.用于揭示扩散磁共振成像中体素内几何结构的非对称取向分布函数(AODFs)。
Magn Reson Imaging. 2018 Jun;49:145-158. doi: 10.1016/j.mri.2018.03.006. Epub 2018 Mar 14.
6
Confirmation of a gyral bias in diffusion MRI fiber tractography.弥散磁共振纤维束成像中脑回偏侧性的确认。
Hum Brain Mapp. 2018 Mar;39(3):1449-1466. doi: 10.1002/hbm.23936. Epub 2017 Dec 19.
7
Surface-enhanced tractography (SET).表面增强示踪技术(SET)。
Neuroimage. 2018 Apr 1;169:524-539. doi: 10.1016/j.neuroimage.2017.12.036. Epub 2017 Dec 16.
8
The challenge of mapping the human connectome based on diffusion tractography.基于弥散张量成像的人类连接组图谱绘制挑战。
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9
Diffusion MRI fiber tractography of the brain.脑弥散磁共振成像纤维束追踪技术。
NMR Biomed. 2019 Apr;32(4):e3785. doi: 10.1002/nbm.3785. Epub 2017 Sep 25.
10
Improved tractography using asymmetric fibre orientation distributions.使用非对称纤维方向分布提高轨迹追踪。
Neuroimage. 2017 Sep;158:205-218. doi: 10.1016/j.neuroimage.2017.06.050. Epub 2017 Jun 29.

通过不对称纤维方向分布减轻皮层束轨迹中的回波偏倚。

Mitigating gyral bias in cortical tractography via asymmetric fiber orientation distributions.

机构信息

Department of Radiology and Biomedical Research Imaging Center (BRIC) University of North Carolina at Chapel Hill, NC, U.S.A.

Department of Radiology and Biomedical Research Imaging Center (BRIC) University of North Carolina at Chapel Hill, NC, U.S.A.

出版信息

Med Image Anal. 2020 Jan;59:101543. doi: 10.1016/j.media.2019.101543. Epub 2019 Sep 13.

DOI:10.1016/j.media.2019.101543
PMID:31670139
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6935166/
Abstract

Diffusion tractography in brain connectomics often involves tracing axonal trajectories across gray-white matter boundaries in gyral blades of complex cortical convolutions. To date, gyral bias is observed in most tractography algorithms with streamlines predominantly terminating at gyral crowns instead of sulcal banks. This work demonstrates that asymmetric fiber orientation distribution functions (AFODFs), computed via a multi-tissue global estimation framework, can mitigate the effects of gyral bias, enabling fiber streamlines at gyral blades to make sharper turns into the cortical gray matter. We use ex-vivo data of an adult rhesus macaque and in-vivo data from the Human Connectome Project (HCP) to show that the fiber streamlines given by AFODFs bend more naturally into the cortex than the conventional symmetric FODFs in typical gyral blades. We demonstrate that AFODF tractography improves cortico-cortical connectivity and provides highly consistent outcomes between two different field strengths (3T and 7T).

摘要

脑连接组学中的弥散张量成像通常涉及在复杂皮质脑回的脑回叶的灰白质边界处追踪轴突轨迹。迄今为止,大多数追踪算法都存在脑回偏向性,即流线主要终止于脑回顶部,而不是脑沟底部。本研究表明,通过多组织全局估计框架计算的不对称纤维方向分布函数(AFODFs)可以减轻脑回偏向性的影响,使脑回叶上的纤维流线能够更自然地向皮质灰质急转弯。我们使用成年恒河猴的离体数据和人类连接组计划(HCP)的体内数据,表明与传统的对称 FODFs 相比,AFODFs 给出的纤维流线在典型脑回叶中更自然地弯曲进入皮质。我们证明了 AFODF 追踪可以改善皮质间连接,并在两种不同场强(3T 和 7T)之间提供高度一致的结果。