Automated quality control for within and between studies diffusion MRI data using a non-parametric framework for movement and distortion correction
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 automat...
| Автори: | , , , , , , , |
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| Формат: | Journal article |
| Мова: | English |
| Опубліковано: |
Elsevier
2018
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