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...
Main Authors: | Bastiani, M, Cottaar, M, Fitzgibbon, S, Suri, S, Alfaro-Almagro, F, Sotiropoulos, S, Jbabdi, S, Andersson, J |
---|---|
Formato: | Journal article |
Idioma: | English |
Publicado: |
Elsevier
2018
|
Títulos similares
-
Incorporating outlier detection and replacement into a non-parametric framework for movement and distortion correction of diffusion MR images
por: Andersson, J, et al.
Publicado: (2016) -
Towards a comprehensive framework for movement and distortion correction of diffusion MR images: within volume movement
por: Andersson, J, et al.
Publicado: (2017) -
Automated processing pipeline for neonatal diffusion MRI in the developing Human Connectome Project
por: Bastiani, M, et al.
Publicado: (2018) -
Joint modelling of diffusion MRI and microscopy
por: Howard, A, et al.
Publicado: (2019) -
Modelling fibre fanning in diffusion-weighted MRI.
por: Sotiropoulos, SN, et al.
Publicado: (2012)