If you want julia (and this package) to use multi-threading for faster computation, you have to explicitly tell it to. You can do that either by starting julia with julia --thread auto, or by setting the environment variable JULIA_NUM_THREADS to auto before starting julia. (This will use the total number of CPU threads available on your computer. Alternatively, you can specify a number of threads in place of auto.)

julia> using Fibers

julia> aa = mri_read("/usr/local/freesurfer/dev/subjects/fsaverage/mri/aparc+aseg.mgz");

julia> fa = mri_read("/usr/local/freesurfer/dev/trctrain/hcp/MGH35_HCP_FA_template.nii.gz");

julia> disp(aa)

julia> disp(fa)

By default this will be an axial view, middle slice, first frame. See ?fs.show for how to change what is displayed.

julia> show(aa)

julia> show(fa)

julia> mri_write(aa, "/tmp/aparc+aseg.nii.gz")

julia> mri_write(fa, "/tmp/MGH35_HCP_FA_template.mgz")

julia> ph = mri_read("/opt/nmrdata/PV-7.0.0/ayendiki/Phantom.cO1/5/");

julia> tr = trk_read("/usr/local/freesurfer/dev/trctrain/hcp/mgh_1001/syn/acomm.bbr.prep.trk");

julia> trk_write(tr, "/tmp/acomm.trk")

A gentle introduction to diffusion MRI

Development of this package is supported by the NIH National Institute of Neurologic Disorders and Stroke (grants UM1-NS132358, R01-NS119911, R01-NS127353).