文章基本信息

标题：Comprehensive diffusion MRI dataset for in vivo human brain microstructure mapping using 300 mT/m gradients
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作者：Qiyuan Tian ; Qiuyun Fan ; Thomas Witzel 等
期刊名称：Scientific Data
电子版ISSN：2052-4463
出版年度：2022
卷号：9
期号：1
页码：1-11
DOI：10.1038/s41597-021-01092-6
语种：English
出版社：Nature Publishing Group
摘要：Strong gradient systems can improve the signal-to-noise ratio of difusion MRI measurements and enable a wider range of acquisition parameters that are benefcial for microstructural imaging . We present a comprehensive difusion MRI dataset of 26 healthy participants acquired on the MGH-USC 3T Connectome scanner equipped with 300 mT/m maximum gradient strength and a custom-built 64-channel head coil . For each participant, the one-hour long acquisition systematically sampled the accessible difusion measurement space, including two difusion times (19 and 49 ms), eight gradient strengths linearly spaced between 30 mT/m and 290 mT/m for each difusion time, and 32 or 64 uniformly distributed directions . The difusion MRI data were preprocessed to correct for gradient nonlinearity, eddy currents, and susceptibility induced distortions . In addition, scan/rescan data from a subset of seven individuals were also acquired and provided . The MGH Connectome Difusion Microstructure Dataset (CDMD) may serve as a test bed for the development of new data analysis methods, such as fber orientation estimation, tractography and microstructural modelling .