def gen_peak_mask(anat_mask,func_activation):
import nibabel as nb
import numpy as np
from fir_utils import (binarize_peak, dilate_mask)
import sys
import os
anatmask = nb.load(anat_mask)
mask_data = np.asarray(anatmask.get_data())
mask_header = anatmask.get_header()
mask_affine = anatmask.get_affine()
func = nb.load(func_activation)
func_data = np.asarray(func.get_data())
func_header = func.get_header()
func_affine = func.get_affine()
if np.array(func_data).shape != np.array(mask_data).shape:
print np.array(func_data).shape
print np.array(mask_data).shape
sys.exit("functional and mask do not have the same 3d shape!")
masked_activation = np.zeros(func_data.shape)
masked_activation[np.nonzero(mask_data)] = func_data[np.nonzero(mask_data)]
peak_mask = binarize_peak(masked_activation)
dilated_peak_mask = dilate_mask(peak_mask)
path = '%s/%s.nii'%(os.path.abspath(os.path.curdir),'peak_mask')
out_image = nb.Nifti1Image(dilated_peak_mask,mask_affine,mask_header)
out_image.to_filename(path)
return path
def extract_segmentation_roi(func_aparc_aseg, segmentation_value):
"""binarizes the volume at locations equal to segmentation_value"""
import nibabel as nb
import numpy as np
import os
from fir_utils import (functional_binarize, dilate_mask)
import sys
segmentation = nb.load(func_aparc_aseg)
seg_data = segmentation.get_data()
header = segmentation.get_header()
affine = segmentation.get_affine()
seg_mask = functional_binarize(seg_data,lambda x: x == segmentation_value)
path = '%s/%s.nii'%(os.path.abspath(os.path.curdir),'mask_'+str(segmentation_value))
dilated_mask = dilate_mask(np.array(seg_mask))
out_image = nb.Nifti1Image(dilated_mask,affine,header)
out_image.to_filename(path)
return path
