NF: volume computation function for nifti masks
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nibabel/cmdline/stats.py
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nibabel/imagestats.py
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setup.cfg
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nibabel/tests/test_imagestats.py
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| 1 | + | #!python |
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| 2 | + | # emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*- |
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| 3 | + | # vi: set ft=python sts=4 ts=4 sw=4 et: |
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| 4 | + | ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## |
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| 5 | + | # |
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| 6 | + | # See COPYING file distributed along with the NiBabel package for the |
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| 7 | + | # copyright and license terms. |
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| 8 | + | # |
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| 9 | + | ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## |
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| 10 | + | """ |
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| 11 | + | Compute image statistics |
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| 12 | + | """ |
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| 13 | + | ||
| 14 | + | import argparse |
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| 15 | + | from nibabel.loadsave import load |
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| 16 | + | from nibabel.imagestats import mask_volume, count_nonzero_voxels |
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| 17 | + | ||
| 18 | + | ||
| 19 | + | def _get_parser(): |
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| 20 | + | """Return command-line argument parser.""" |
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| 21 | + | p = argparse.ArgumentParser(description=__doc__) |
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| 22 | + | p.add_argument("infile", |
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| 23 | + | help="Neuroimaging volume to compute statistics on.") |
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| 24 | + | p.add_argument("-V", "--Volume", action="store_true", required=False, |
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| 25 | + | help="Compute mask volume of a given mask image.") |
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| 26 | + | p.add_argument("--units", default="mm3", required=False, |
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| 27 | + | choices=("mm3", "vox"), help="Preferred output units") |
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| 28 | + | return p |
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| 29 | + | ||
| 30 | + | ||
| 31 | + | def main(args=None): |
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| 32 | + | """Main program function.""" |
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| 33 | + | parser = _get_parser() |
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| 34 | + | opts = parser.parse_args(args) |
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| 35 | + | from_img = load(opts.infile) |
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| 36 | + | ||
| 37 | + | if opts.Volume: |
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| 38 | + | if opts.units == 'mm3': |
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| 39 | + | computed_volume = mask_volume(from_img) |
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| 40 | + | elif opts.units == 'vox': |
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| 41 | + | computed_volume = count_nonzero_voxels(from_img) |
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| 42 | + | else: |
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| 43 | + | raise ValueError(f'{opts.units} is not a valid unit. Choose "mm3" or "vox".') |
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| 44 | + | print(computed_volume) |
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| 45 | + | return 0 |
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| 1 | + | # emacs: -*- mode: python-mode; py-indent-offset: 4; indent-tabs-mode: nil -*- |
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| 2 | + | # vi: set ft=python sts=4 ts=4 sw=4 et: |
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| 3 | + | ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## |
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| 4 | + | # |
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| 5 | + | # See COPYING file distributed along with the NiBabel package for the |
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| 6 | + | # copyright and license terms. |
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| 7 | + | # |
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| 8 | + | ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## |
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| 9 | + | """ |
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| 10 | + | Functions for computing image statistics |
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| 11 | + | """ |
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| 12 | + | ||
| 13 | + | import numpy as np |
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| 14 | + | from nibabel.imageclasses import spatial_axes_first |
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| 15 | + | ||
| 16 | + | ||
| 17 | + | def count_nonzero_voxels(img): |
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| 18 | + | """ |
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| 19 | + | Count number of non-zero voxels |
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| 20 | + | ||
| 21 | + | Parameters |
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| 22 | + | ---------- |
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| 23 | + | img : ``SpatialImage`` |
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| 24 | + | All voxels of the mask should be of value 1, background should have value 0. |
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| 25 | + | ||
| 26 | + | Returns |
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| 27 | + | ------- |
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| 28 | + | count : int |
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| 29 | + | Number of non-zero voxels |
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| 30 | + | ||
| 31 | + | """ |
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| 32 | + | return np.count_nonzero(img.dataobj) |
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| 33 | + | ||
| 34 | + | ||
| 35 | + | def mask_volume(img): |
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| 36 | + | """ Compute volume of mask image. |
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| 37 | + | ||
| 38 | + | Equivalent to "fslstats /path/file.nii -V" |
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| 39 | + | ||
| 40 | + | Parameters |
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| 41 | + | ---------- |
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| 42 | + | img : ``SpatialImage`` |
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| 43 | + | All voxels of the mask should be of value 1, background should have value 0. |
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| 44 | + | ||
| 45 | + | ||
| 46 | + | Returns |
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| 47 | + | ------- |
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| 48 | + | volume : float |
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| 49 | + | Volume of mask expressed in mm3. |
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| 50 | + | ||
| 51 | + | Examples |
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| 52 | + | -------- |
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| 53 | + | >>> import numpy as np |
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| 54 | + | >>> import nibabel as nb |
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| 55 | + | >>> mask_data = np.zeros((20, 20, 20), dtype='u1') |
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| 56 | + | >>> mask_data[5:15, 5:15, 5:15] = 1 |
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| 57 | + | >>> nb.imagestats.mask_volume(nb.Nifti1Image(mask_data, np.eye(4))) |
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| 58 | + | 1000.0 |
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| 59 | + | """ |
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| 60 | + | if not spatial_axes_first(img): |
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| 61 | + | raise ValueError("Cannot calculate voxel volume for image with unknown spatial axes") |
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| 62 | + | voxel_volume_mm3 = np.prod(img.header.get_zooms()[:3]) |
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| 63 | + | mask_volume_vx = count_nonzero_voxels(img) |
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| 64 | + | mask_volume_mm3 = mask_volume_vx * voxel_volume_mm3 |
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| 65 | + | ||
| 66 | + | return mask_volume_mm3 |
| Files | Coverage |
|---|---|
| nibabel | 91.90% |
| Project Totals (101 files) | 91.90% |
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