Tensor-valued dMRI scripts (b-tensor) ===================================== The scripts for multi-encoding multi-shell multi-tissue CSD (memsmt-CSD) are based on [memst]_. We recommend reading it to understand the scope of the memsmt-CSD problem. Preparing data for this tutorial ******************************** To run lines below, you need a various volumes, b-vector information and masks. The tutorial data is still in preparation, meanwhile you can use this: ` .. code-block:: bash in_dir=where/you/downloaded/tutorial/data in_dir=$in_dir/btensor # For now, the tutorial data only contains the masks. # Other necessary data can be obtained with: scil_data_download -v ERROR cp $HOME/.scilpy/btensor_testdata/* $in_dir/ .. tip:: You may download the complete bash script to run the whole tutorial in one step `⭳ here <../../_static/bash/reconst/btensor_scripts.sh>`_. 1. Computing the frf ******************** If you want to do CSD with b-tensor data, you should start by computing the fiber response functions. This script should run fast (less than 5 minutes on a full brain). The data in this tutorial is small, with default parameters, we would get a warning (Could not find at least 100 voxels for the WM mask.), so we'll set the --min_nvox to 1. .. code-block:: bash scil_frf_memsmt wm_frf.txt gm_frf.txt csf_frf.txt \ --in_dwis $in_dir/dwi_linear.nii.gz $in_dir/dwi_planar.nii.gz $in_dir/dwi_spherical.nii.gz \ --in_bvals $in_dir/linear.bvals $in_dir/planar.bvals $in_dir/spherical.bvals \ --in_bvecs $in_dir/linear.bvecs $in_dir/planar.bvecs $in_dir/spherical.bvecs \ --in_bdeltas 1 -0.5 0 --min_nvox 1 --mask $in_dir/mask.nii.gz \ --mask_wm $in_dir/wm_mask.nii.gz --mask_gm $in_dir/gm_mask.nii.gz \ --mask_csf $in_dir/csf_mask.nii.gz Note. Ignore the warning that some b-values are high. 2. Computing the fODF ********************* Then, you should compute the fODFs and volume fractions. The following command will save a fODF file for each tissue and a volume fractions file. This script should run in about 1-2 hours for a full brain. .. code-block:: bash scil_fodf_memsmt wm_frf.txt gm_frf.txt csf_frf.txt \ --in_dwis $in_dir/dwi_linear.nii.gz $in_dir/dwi_planar.nii.gz $in_dir/dwi_spherical.nii.gz \ --in_bvals $in_dir/linear.bvals $in_dir/planar.bvals $in_dir/spherical.bvals \ --in_bvecs $in_dir/linear.bvecs $in_dir/planar.bvecs $in_dir/spherical.bvecs \ --in_bdeltas 1 -0.5 0 --processes 8 --mask $in_dir/mask.nii.gz The resulting files are: csf_fodf.nii.gz gm_fodf.nii.gz wm_fodf.nii.gz., as well as the volume fraction map: vf.nii.gz and vf_rgb.nii.gz. If you want to do DIVIDE with b-tensor data, you should use the following command. It will save files for the MD, uFA, OP, MK_I, MK_A and MK_T. This script should run in about 1-2 hours for a full brain. .. code-block:: bash scil_btensor_metrics \ --in_dwis $in_dir/dwi_linear.nii.gz $in_dir/dwi_planar.nii.gz $in_dir/dwi_spherical.nii.gz \ --in_bvals $in_dir/linear.bvals $in_dir/planar.bvals $in_dir/spherical.bvals \ --in_bvecs $in_dir/linear.bvecs $in_dir/planar.bvecs $in_dir/spherical.bvecs \ --in_bdeltas 1 -0.5 0 --fa $in_dir/fa.nii.gz --processes 8 --mask $in_dir/mask.nii.gz References ********** .. [memst] P. Karan et al., Bridging the gap between constrained spherical deconvolution and diffusional variance decomposition via tensor-valued diffusion MRI. Medical Image Analysis (2022)