/surfdist

For calculating exact geodesic distances on cortical surface meshes

Primary LanguagePythonMIT LicenseMIT

surfdist

Build Status

Calculate the exact geodesic distance on a triangular surface mesh using the gdist package, which is based on the c++ library.

Installation

pip install surfdist

Example

Freesurfer files:

import nibabel as nib
import numpy as np
import matplotlib.pyplot as plt
import os
import surfdist as sd
from surfdist import viz, load, utils, analysis

# calculate and display distance from central sulcus at each node:
cmap = 'coolwarm'
base_dir = '/Applications/freesurfer/subjects/'
surf = nib.freesurfer.read_geometry(os.path.join(base_dir, 'bert/surf/lh.pial'))
cort = np.sort(nib.freesurfer.read_label(os.path.join(base_dir, 'bert/label/lh.cortex.label')))
sulc = nib.freesurfer.read_morph_data(os.path.join(base_dir, 'bert/surf/lh.sulc'))

# load central sulcus nodes
src  = sd.load.load_freesurfer_label(os.path.join(base_dir, 'bert/label/lh.aparc.a2009s.annot'), 'S_central', cort)

# calculate distance
dist = sd.analysis.dist_calc(surf, cort, src)

# visualize
plot_med = sd.viz.viz(surf[0], surf[1], dist, bg_map=sulc, bg_on_stat=True, cmap=cmap)
plot_lat = sd.viz.viz(surf[0], surf[1], dist, azim=180, bg_map=sulc, bg_on_stat=True, cmap=cmap)

# Calculate distances on native surface and display on fsaverage
fsa4 = nib.freesurfer.read_geometry(os.path.join(base_dir,'fsaverage4/surf/lh.sphere.reg'))[0]
fsa4_sulc=nib.freesurfer.read_morph_data(os.path.join(base_dir, 'fsaverage4/surf/lh.sulc'))
native = nib.freesurfer.read_geometry(os.path.join(base_dir, 'bert/surf/lh.sphere.reg'))[0]
idx_fsa4_to_native = sd.utils.find_node_match(fsa4, native)[0]

surf_fsa4 = nib.freesurfer.read_geometry(os.path.join(base_dir, 'fsaverage4/surf/lh.pial'))
plot_fsa4_med = sd.viz.viz(surf_fsa4[0], surf_fsa4[1], dist[idx_fsa4_to_native], bg_map=fsa4_sulc, bg_on_stat=True, cmap=cmap)
plot_fsa4_lat = sd.viz.viz(surf_fsa4[0], surf_fsa4[1], dist[idx_fsa4_to_native], azim=180, bg_map=fsa4_sulc, bg_on_stat=True, cmap=cmap)

plt.show()

Gifti files:

import surfdist as sd
from surfdist import viz, load, utils, analysis

surf_labels = nib.load("fsLR.32k.L.label.gii")
# pick only the vertices of the cortex, excluding the medial wall
cortex = np.where(surf_labels.darrays[0].data != 0)[0]

surfL = nib.load("sub-1_hemi-L_inflated.32k_fs_LR.surf.gii")
nodes = surfL.agg_data('NIFTI_INTENT_POINTSET')
triangles = surfL.agg_data('NIFTI_INTENT_TRIANGLE')
surf = (nodes, triangles)

destrieux = nib.load("destrieux-labels_den-32k_hemi-L.label.gii").darrays[0].data

# pick only the vertices of A1 and angular gyrus.
a1_vrtx = np.where(destrieux == 32)[0]
angG_vrtx = np.where(destrieux == 24)[0]

# calculate distances from A1 to the rest of the vertices
all_dist = analysis.dist_calc(surf, cortex, a1_vrtx)
# calculate the shortest distance from A1 to angular gyrus
dist_min = anaysis.dist_calc(surf, cortex, a1_vrtx, angG_vrtx)