Atlas of 30 Human Brain Bundles in MNI space

This is a dataset to be used by the RecoBundles algorithm to automatically extract anatomically relevant bundles from tractograms. RecoBundles is available in DIPY (http://dipy.org). The algorithm is explained in the paper:<br><br>Garyfallidis, Eleftherios, et al. "Recognition of white matter bundles using local and global streamline-based registration and clustering." NeuroImage 170 (2017): 283-297.<br>https://www.ncbi.nlm.nih.gov/pubmed/28712994<br>This dataset is curated from the dataset explained in the following paper:<br>Yeh, Fang-Cheng, et al. "Population-averaged atlas of the macroscale human structural connectome and its network topology." NeuroImage 178 (2018): 57-68.<br>https://www.sciencedirect.com/science/article/pii/S1053811918304324<br>All the bundles and trk (Trackvis) files are in MNI space ICBM 2009a.<br>Do contact the DIPY developers at https://gitter.im/nipy/dipy if you need the bundles at ICBM 2009c space.<br>For the Fornix (F) both left and right sides are included in one file. It is possible to easily separate them if you need to. Send an e-mail to [e-mail] to learn how.<br>If you use this dataset please cite Garyfallidis et al. 2017 and Yeh et al. 2018 (see above).<br>Research reported in this publication was supported primarily by the National Institute Of Biomedical Imaging And Bioengineering of the National Institutes of Health under Award Number R01EB027585.<br><br><br><br>Happy RecoBundling!<br>

本数据集供RecoBundles算法使用，用于从纤维束追踪图（tractograms）中自动提取解剖学相关的神经纤维束。RecoBundles已集成于DIPY库（http://dipy.org）。该算法的详细说明参见以下论文：
Garyfallidis, Eleftherios 等. 基于局部和全局流线配准与聚类的白质纤维束识别. 《NeuroImage》, 2017, 170: 283-297.
文献链接：https://www.ncbi.nlm.nih.gov/pubmed/28712994

本数据集系精心整理自下述论文所公布的数据集：
Yeh, Fang-Cheng 等. 人类宏观尺度结构连接组的群体平均图谱及其网络拓扑特性. 《NeuroImage》, 2018, 178: 57-68.
文献链接：https://www.sciencedirect.com/science/article/pii/S1053811918304324

所有神经纤维束及trk（Trackvis）格式文件均采用MNI空间ICBM 2009a标准。若需ICBM 2009c空间的神经纤维束，请通过https://gitter.im/nipy/dipy联系DIPY开发团队。

针对穹窿（Fornix, F），其左右两侧束支均包含于单个文件中，若有需要可轻松将二者分离，可发送邮件至[e-mail]了解具体操作方法。

若您使用本数据集，请引用Garyfallidis等人2017年与Yeh等人2018年的上述论文。

本出版物报道的研究主要由美国国立卫生研究院下属的国立生物医学成像与生物工程研究所资助，资助编号为R01EB027585。

祝您使用RecoBundles顺利！