qiyuantian/SDnDTI
SDnDTI Tutorial
This project helps neuroimaging researchers design or select optimal diffusion encoding directions for Diffusion Tensor Imaging (DTI) studies. It takes either your experimental design requirements or an existing large DTI dataset as input and outputs a set of optimized diffusion encoding directions (b-vectors). This is intended for scientists and clinicians working with diffusion MRI data who want to improve the quality of their DTI results.
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Use this if you are planning a DTI acquisition and need to design the most effective diffusion encoding directions, or if you have an existing DTI dataset and want to extract a high-quality subset for analysis.
Not ideal if you need a complete DTI processing pipeline that handles all steps from raw data to final tensor estimation, as this focuses specifically on optimizing diffusion encoding directions.
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Jun 22, 2022
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