RAPID: a Routine Assurance Pipeline for Imaging of Diffusion
RAPID: a Routine Assurance Pipeline for Imaging of Diffusion - De Santis et al. (submitted)
script_to_calculate_SNR calculates the signal-to-noise ratio and returns the optimal parameters for acquiring QA data.
_Input: nifti files of 100 b=0 images
_Output: max b-value and voxel size
script_to_run_QA checks for the linearity of b, the uniformity of Gmax across the field-of-view, the mutual agreement of gradient power across the three logical axes and corrects for gradient mismatches.
_Input: nifti files of diffusion data on phantom acquired using the gradient table Grad_dirs_QA_shuffled.txt
_Output: .mat file of QA with date
script_to_compare_QA_results checks for temporal stability.
_Input: two .mat files of QA results
Cite As
Silvia (2026). RAPID: a Routine Assurance Pipeline for Imaging of Diffusion (https://uk.mathworks.com/matlabcentral/fileexchange/36463-rapid-a-routine-assurance-pipeline-for-imaging-of-diffusion), MATLAB Central File Exchange. Retrieved .
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- Sciences > Neuroscience > Human Brain Mapping > Neuroimaging >
- Image Processing and Computer Vision > Image Processing Toolbox > Image Segmentation and Analysis > Image Quality >
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Acknowledgements
Inspired by: Tools for NIfTI and ANALYZE image
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