RAPID: a Routine Assurance Pipeline for Imaging of Diffusion

버전 1.2.0.0 (27.5 KB) 작성자: Silvia
uses diffusion MRI data for Quality Assurance of diffusion acquisitions
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업데이트 날짜: 2012/7/5

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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

인용 양식

Silvia (2024). RAPID: a Routine Assurance Pipeline for Imaging of Diffusion (https://www.mathworks.com/matlabcentral/fileexchange/36463-rapid-a-routine-assurance-pipeline-for-imaging-of-diffusion), MATLAB Central File Exchange. 검색됨 .

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버전 게시됨 릴리스 정보
1.2.0.0

4 Jul 2012 - correction for imaging gradients, to be used with the same geometry of the actual scan to be corrected

1.1.0.0

UPDATE: included a tool to account for imaging gradients in the b-matrix calculation

1.0.0.0