Welcome to Surface tools! a collection of tools for surface-based operations
Equivolumetric surfaces: creates equivolumetric surfaces based on the ratio of areas of the mesh surfaces, without the trouble of dealing with volumetric operations.
Equivolumetric surfaces (red) at 0.25, 0.5 and 0.75 cortical depth on the BigBrain. Euclidean surface (yellow) at mid depth. The euclidean surface samples different layers in gyri and sulci. Euclidean vs equivolumetric intensity sampling. The laminar peaks are better aligned using equivolumetric sampling than euclidean sampling.Written by Konrad Wagstyl and Alexander Huth at a Brain Hack, a version is also available in Pycortex. Casey Paquola and Richard Bethlehem were involved in piloting these scripts on CIVET and FreeSurfer respectively.
# install from git
pip install git+https://github.com/kwagstyl/surface_tools
This puts the generate_equivolumetric_surfaces
-script in the bin
-folder of the environment:
generate_equivolumetric_surfaces --help
usage: generate_equivolumetric_surfaces [-h] [--smoothing SMOOTHING]
[--software {CIVET,freesurfer}] [--subject_id SUBJECT_ID]
gray white n_surfs output
Generate equivolumetric surfaces between input surfaces
positional arguments:
gray input gray surface
white input white surface
n_surfs number of output surfaces, also returns gray and white surfaces at 0 and 1
output output surface prefix e.g., equi_left_{N}
optional arguments:
-h, --help show this help message and exit
--smoothing SMOOTHING
fwhm of surface area smoothing (default=0mm)
--software {CIVET,freesurfer}
surface software package
--subject_id SUBJECT_ID
subject name if freesurfer
The code requires either CIVET and FreeSurfer to be installed.
generate_equivolumetric_surfaces --smoothing 0 gray_left.obj white_left.obj 5 equi_left
Then you can use volume_object_evaluate to sample the intensities at the particular depth:
volume_object_evaluate volume.mnc equi_left0.5.obj equi_left_intensities0.5.txt
(we assume CIVET as default, so if using freesurfer, specify with the freesurfer flag):
generate_equivolumetric_surfaces --smoothing 0 <subj>/surf/lh.pial <subj>/surf/lh.white 5 lh.equi --software freesurfer --subject_id SUBJECT_ID
Then you can use mri_vol2surf to sample the intensities at the particular depth:
mri_vol2surf --src volume.nii --out lh.equi_intensity_0.5.mgh --hemi lh --surf <subj>/surf/lh.equi0.5.pial --out_type mgh
If you notice any typos/bugs, or have any suggestions or improvements, we would really value your input. Either send us a pull request, email us at [email protected]
This code has so far been tested on:
- python 2.7 and 3.6, freesurfer v.6 and on linux (Ubuntu 16.04) and macOS (10.12.6)
- python 2.7, CIVET 2.1, Ubuntu 12.04
The io_mesh code was copied and adapted from https://github.com/juhuntenburg/laminar_python, another great tool for doing volume-based equivolumetric laminar processing.
The equations for generating equivolumetric surfaces come from Waehnert et al 2014: "Anatomically motivated modeling of cortical laminae" https://doi.org/10.1016/j.neuroimage.2013.03.078
Code is demo-ed here on the BigBrain (Amunts et al., 2013), freely available histological atlas of the human brain https://bigbrain.loris.ca/
This work was partially supported by the Healthy Brains for Healthy Lives (HBHL) initiative and the Avrith MNI-Cambridge Neuroscience Collaboration.