hippomaps.utils.surface_to_volume๏ƒ

hippomaps.utils.surface_to_volume(surf_data, indensity, hippunfold_dir, sub, ses, hemi, space='*', label='hipp', save_out_name=None, method='nearest')๏ƒ
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).) โ€“

  • indensity (str) โ€“ Density of the unfolded space. One of โ€˜0p5mmโ€™, โ€˜1mmโ€™, โ€˜2mmโ€™, or โ€˜unfoldisoโ€™.

  • hippunfold_dir (str) โ€“ Directory path to the HippUnfold output.

  • sub (str) โ€“ Subject identifier.

  • ses (str) โ€“ Session identifier.

  • hemi (str) โ€“ Hemisphere. Either โ€˜Lโ€™ or โ€˜Rโ€™.

  • space (str, optional) โ€“ Default is โ€˜*โ€™.

  • label (str, optional) โ€“ Default is โ€˜hippโ€™.

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

  • method (str, optional) โ€“ Interpolation method. Options are โ€˜nearestโ€™, โ€˜linearโ€™, or โ€˜cubicโ€™. Default is โ€˜nearestโ€™.

Returns:

Labeled voxel data.

Return type:

numpy.ndarray