Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction.
Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction.
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DOI：
10.1016/j.neuroimage.2018.09.073
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发表时间：
2019-01-01
期刊：
影响因子：
5.7
通讯作者：
Andersson JLR
中科院分区：
文献类型：
--
作者：
Bastiani M;Cottaar M;Fitzgibbon SP;Suri S;Alfaro-Almagro F;Sotiropoulos SN;Jbabdi S;Andersson JLR
扩散MRI数据可能受到硬件和受试者相关伪影的影响，这些伪影可能对下游分析产生不利影响。因此，自动化质量控制（QC）非常重要，特别是在目视QC不实用的大人群研究中。在这项工作中，我们介绍了一个自动化的扩散MRI质量控制框架的单个主题和组的研究。QC基于一种用于运动和失真校正的全面的非参数方法：FSL EDDY，它使我们能够提取一组丰富的QC指标，这些指标对不同类型的伪影既敏感又特定。提供了两种不同的工具：QUAD（DMRI质量评估），用于单个受试者QC和SQUAD（DMRI研究质量评估），旨在实现小组QC并促进交叉研究协调工作。两个工具自动执行扩散MRI数据的QC。自动生成用于目视检查和数据库的单个受试者报告。组数据库和报告允许在研究内和研究之间比较受试者。分类和连续变量可用于更新报告。
Diffusion MRI data can be affected by hardware and subject-related artefacts that can adversely affect downstream analyses. Therefore, automated quality control (QC) is of great importance, especially in large population studies where visual QC is not practical. In this work, we introduce an automated diffusion MRI QC framework for single subject and group studies. The QC is based on a comprehensive, non-parametric approach for movement and distortion correction: FSL EDDY, which allows us to extract a rich set of QC metrics that are both sensitive and specific to different types of artefacts. Two different tools are presented: QUAD (QUality Assessment for DMRI), for single subject QC and SQUAD (Study-wise QUality Assessment for DMRI), which is designed to enable group QC and facilitate cross-studies harmonisation efforts. Two tools to automatically perform QC of diffusion MRI data. Automated generation of single subject reports for visual inspection and database. Group databases and reports allow to compare subjects within and between studies. Categorical and continuous variables can be used to update the reports.
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影响因子：
5.7
作者：
Jenkinson, M;Bannister, P;Smith, S
通讯作者：
Smith, S
影响因子：
5.7
作者：
Bastiani M;Cottaar M;Dikranian K;Ghosh A;Zhang H;Alexander DC;Behrens TE;Jbabdi S;Sotiropoulos SN
通讯作者：
Sotiropoulos SN
影响因子：
4.8
作者：
Kochunov P;Dickie EW;Viviano JD;Turner J;Kingsley PB;Jahanshad N;Thompson PM;Ryan MC;Fieremans E;Novikov D;Veraart J;Hong EL;Malhotra AK;Buchanan RW;Chavez S;Voineskos AN
通讯作者：
Voineskos AN
影响因子：
3.3
作者：
JEZZARD, P;BALABAN, RS
通讯作者：
BALABAN, RS
影响因子：
5.7
作者：
Andersson JLR;Graham MS;Drobnjak I;Zhang H;Campbell J
通讯作者：
Campbell J