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@@ -1,10 +1,8 @@
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from templateflow import api
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-from scikit.ndimage import gaussian_filter
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from scipy.ndimage import gaussian_filter
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import nibabel as nb
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import numpy as np
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from skimage.morphology import ball
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-from scikit.ndimage import binary_erosion
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from scipy.ndimage import morphology as m
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path = api.get('MNI152NLin2009cAsym', desc='brain', resolution=1, suffix='mask')
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@@ -14,6 +12,8 @@ dilate1 = m.binary_dilation(data == 1, ball(1))
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dilate2 = m.binary_dilation(dilate1, ball(1))
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soft = 0.95 * dilate2
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soft[dilate1] = 1.0
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-gauss = gaussian_filter(soft, 1)
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-nb.Nifti1Image(gauss, im.affine, im.header).to_filename('gauss.nii.gz')
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+gauss = gaussian_filter(soft.astype('float32'), 1)
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+header = im.header.copy()
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+header.set_data_dtype('float32')
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+nb.Nifti1Image(gauss.astype('float32'), im.affine, header).to_filename('tpl-MNI152NLin2009cAsym_res-01_desc-brain_probseg.nii.gz')
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