hippomaps.utils.surface_to_volume

hippomaps.utils.surface_to_volume(surf_data, indensity, hippunfold_dir, sub, ses, hemi, space='*', label='hipp', save_out_name=None, method='nearest')
Labels voxels using data on a folded/unfolded surface and native space coordinates images.

from https://github.com/khanlab/hippunfold/blob/master/hippunfold/workflow/scripts/label_subfields_from_vol_coords.py this function labels voxels using data on a folded/unfolded surface (midthickness or any), and native space coords (ap, pd) images TODO: consider trying to simplify inputs specifying the coords paths?

Parameters:

  • surf_data (Data on the folded/unfolded surface (midthickness or any).) –

  • indensity (str) – Density of the unfolded space. One of β€˜0p5mm’, β€˜1mm’, β€˜2mm’, or β€˜unfoldiso’.

  • hippunfold_dir (str) – Directory path to the HippUnfold output.

  • sub (str) – Subject identifier.

  • ses (str) – Session identifier.

  • hemi (str) – Hemisphere. Either β€˜L’ or β€˜R’.

  • space (str, optional) – Default is β€˜*’.

  • label (str, optional) – Default is β€˜hipp’.

  • save_out_name (str, optional) – Output file name to save the label image. Default is None.

  • method (str, optional) – Interpolation method. Options are β€˜nearest’, β€˜linear’, or β€˜cubic’. Default is β€˜nearest’.

Returns:

Labeled voxel data.

Return type:

numpy.ndarray