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Merge pull request #50 from josephmje/enh/skullstrip
ENH: b0 reference and skullstrip workflow
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,145 @@ | ||
| """Image tools interfaces.""" | ||
| import numpy as np | ||
| import nibabel as nb | ||
| from nipype.utils.filemanip import fname_presuffix | ||
| from nipype import logging | ||
| from nipype.interfaces.base import ( | ||
| traits, TraitedSpec, BaseInterfaceInputSpec, SimpleInterface, File | ||
| ) | ||
|
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| LOGGER = logging.getLogger('nipype.interface') | ||
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| class _ExtractB0InputSpec(BaseInterfaceInputSpec): | ||
| in_file = File(exists=True, mandatory=True, desc='dwi file') | ||
| b0_ixs = traits.List(traits.Int, mandatory=True, | ||
| desc='Index of b0s') | ||
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| class _ExtractB0OutputSpec(TraitedSpec): | ||
| out_file = File(exists=True, desc='b0 file') | ||
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| class ExtractB0(SimpleInterface): | ||
| """ | ||
| Extract all b=0 volumes from a dwi series. | ||
| Example | ||
| ------- | ||
| >>> os.chdir(tmpdir) | ||
| >>> extract_b0 = ExtractB0() | ||
| >>> extract_b0.inputs.in_file = str(data_dir / 'dwi.nii.gz') | ||
| >>> extract_b0.inputs.b0_ixs = [0, 1, 2] | ||
| >>> res = extract_b0.run() # doctest: +SKIP | ||
| """ | ||
|
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| input_spec = _ExtractB0InputSpec | ||
| output_spec = _ExtractB0OutputSpec | ||
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| def _run_interface(self, runtime): | ||
| self._results['out_file'] = extract_b0( | ||
| self.inputs.in_file, | ||
| self.inputs.b0_ixs, | ||
| newpath=runtime.cwd) | ||
| return runtime | ||
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| def extract_b0(in_file, b0_ixs, newpath=None): | ||
| """Extract the *b0* volumes from a DWI dataset.""" | ||
| out_file = fname_presuffix( | ||
| in_file, suffix='_b0', newpath=newpath) | ||
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| img = nb.load(in_file) | ||
| data = img.get_fdata(dtype='float32') | ||
|
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| b0 = data[..., b0_ixs] | ||
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| hdr = img.header.copy() | ||
| hdr.set_data_shape(b0.shape) | ||
| hdr.set_xyzt_units('mm') | ||
| hdr.set_data_dtype(np.float32) | ||
| nb.Nifti1Image(b0, img.affine, hdr).to_filename(out_file) | ||
| return out_file | ||
|
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| class _RescaleB0InputSpec(BaseInterfaceInputSpec): | ||
| in_file = File(exists=True, mandatory=True, desc='b0s file') | ||
| mask_file = File(exists=True, mandatory=True, desc='mask file') | ||
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| class _RescaleB0OutputSpec(TraitedSpec): | ||
| out_ref = File(exists=True, desc='One average b0 file') | ||
| out_b0s = File(exists=True, desc='series of rescaled b0 volumes') | ||
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| class RescaleB0(SimpleInterface): | ||
| """ | ||
| Rescale the b0 volumes to deal with average signal decay over time. | ||
| Example | ||
| ------- | ||
| >>> os.chdir(tmpdir) | ||
| >>> rescale_b0 = RescaleB0() | ||
| >>> rescale_b0.inputs.in_file = str(data_dir / 'dwi.nii.gz') | ||
| >>> rescale_b0.inputs.mask_file = str(data_dir / 'dwi_mask.nii.gz') | ||
| >>> res = rescale_b0.run() # doctest: +SKIP | ||
| """ | ||
|
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| input_spec = _RescaleB0InputSpec | ||
| output_spec = _RescaleB0OutputSpec | ||
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| def _run_interface(self, runtime): | ||
| self._results['out_b0s'] = rescale_b0( | ||
| self.inputs.in_file, | ||
| self.inputs.mask_file, | ||
| newpath=runtime.cwd | ||
| ) | ||
| self._results['out_ref'] = median( | ||
| self._results['out_b0s'], | ||
| newpath=runtime.cwd | ||
| ) | ||
| return runtime | ||
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| def rescale_b0(in_file, mask_file, newpath=None): | ||
| """Rescale the input volumes using the median signal intensity.""" | ||
| out_file = fname_presuffix( | ||
| in_file, suffix='_rescaled_b0', newpath=newpath) | ||
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| img = nb.load(in_file) | ||
| if img.dataobj.ndim == 3: | ||
| return in_file | ||
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| data = img.get_fdata(dtype='float32') | ||
| mask_img = nb.load(mask_file) | ||
| mask_data = mask_img.get_fdata(dtype='float32') | ||
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| median_signal = np.median(data[mask_data > 0, ...], axis=0) | ||
| rescaled_data = 1000 * data / median_signal | ||
| hdr = img.header.copy() | ||
| nb.Nifti1Image(rescaled_data, img.affine, hdr).to_filename(out_file) | ||
| return out_file | ||
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| def median(in_file, newpath=None): | ||
| """Average a 4D dataset across the last dimension using median.""" | ||
| out_file = fname_presuffix( | ||
| in_file, suffix='_b0ref', newpath=newpath) | ||
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| img = nb.load(in_file) | ||
| if img.dataobj.ndim == 3: | ||
| return in_file | ||
| if img.shape[-1] == 1: | ||
| nb.squeeze_image(img).to_filename(out_file) | ||
| return out_file | ||
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| median_data = np.median(img.get_fdata(dtype='float32'), | ||
| axis=-1) | ||
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| hdr = img.header.copy() | ||
| hdr.set_xyzt_units('mm') | ||
| hdr.set_data_dtype(np.float32) | ||
| nb.Nifti1Image(median_data, img.affine, hdr).to_filename(out_file) | ||
| return out_file |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,9 @@ | ||
| """Pre-processing dMRI workflows.""" | ||
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| from .base import init_dwi_preproc_wf | ||
| from .util import init_dwi_reference_wf | ||
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| __all__ = [ | ||
| 'init_dwi_preproc_wf', | ||
| 'init_dwi_reference_wf', | ||
| ] |
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