def image_gradient(in_file, compute_abs=True, out_file=None):
"""Computes the magnitude gradient of an image using numpy"""
import os.path as op
import numpy as np
import nibabel as nb
from scipy.ndimage import gaussian_gradient_magnitude as gradient
if out_file is None:
fname, ext = op.splitext(op.basename(in_file))
if ext == '.gz':
fname, ext2 = op.splitext(fname)
ext = ext2 + ext
out_file = op.abspath('%s_grad%s' % (fname, ext))
imnii = nb.load(in_file)
data = imnii.get_data().astype(np.float32) # pylint: disable=no-member
range_max = np.percentile(data.reshape(-1), 90.)
data *= (100 / range_max)
sigma = 1e-4 * data[data > 0].std(ddof=1) # pylint: disable=no-member
grad = gradient(data, sigma)
while grad.sum() < 1.e4:
sigma *= 1.5
grad = gradient(data, sigma)
if compute_abs:
grad = np.abs(grad)
nb.Nifti1Image(grad, imnii.get_affine(),
imnii.get_header()).to_filename(out_file)
return out_file
def image_gradient(in_file, compute_abs=True, out_file=None):
"""Computes the magnitude gradient of an image using numpy"""
import os.path as op
import numpy as np
import nibabel as nb
from scipy.ndimage import gaussian_gradient_magnitude as gradient
if out_file is None:
fname, ext = op.splitext(op.basename(in_file))
if ext == '.gz':
fname, ext2 = op.splitext(fname)
ext = ext2 + ext
out_file = op.abspath('%s_grad%s' % (fname, ext))
imnii = nb.load(in_file)
data = imnii.get_data().astype(np.float32) # pylint: disable=no-member
range_max = np.percentile(data.reshape(-1), 90.)
data *= (100/range_max)
sigma = 1e-4 * data[data > 0].std(ddof=1) # pylint: disable=no-member
grad = gradient(data, sigma)
while grad.sum() < 1.e4:
sigma *= 1.5
grad = gradient(data, sigma)
if compute_abs:
grad = np.abs(grad)
nb.Nifti1Image(grad, imnii.get_affine(), imnii.get_header()).to_filename(out_file)
return out_file
def image_gradient(in_file, snr, out_file=None):
"""Computes the magnitude gradient of an image using numpy"""
import os.path as op
import numpy as np
import nibabel as nb
from scipy.ndimage import gaussian_gradient_magnitude as gradient
if out_file is None:
fname, ext = op.splitext(op.basename(in_file))
if ext == '.gz':
fname, ext2 = op.splitext(fname)
ext = ext2 + ext
out_file = op.abspath('{}_grad{}'.format(fname, ext))
imnii = nb.load(in_file)
data = imnii.get_data().astype(np.float32) # pylint: disable=no-member
datamax = np.percentile(data.reshape(-1), 99.5)
data *= 100 / datamax
grad = gradient(data, 3.0)
gradmax = np.percentile(grad.reshape(-1), 99.5)
grad *= 100.
grad /= gradmax
nb.Nifti1Image(grad, imnii.get_affine(),
imnii.get_header()).to_filename(out_file)
return out_file
def image_gradient(in_file, snr, out_file=None):
"""Computes the magnitude gradient of an image using numpy"""
import os.path as op
import numpy as np
import nibabel as nb
from scipy.ndimage import gaussian_gradient_magnitude as gradient
if out_file is None:
fname, ext = op.splitext(op.basename(in_file))
if ext == '.gz':
fname, ext2 = op.splitext(fname)
ext = ext2 + ext
out_file = op.abspath('{}_grad{}'.format(fname, ext))
imnii = nb.load(in_file)
data = imnii.get_data().astype(np.float32) # pylint: disable=no-member
datamax = np.percentile(data.reshape(-1), 99.5)
data *= 100 / datamax
grad = gradient(data, 3.0)
gradmax = np.percentile(grad.reshape(-1), 99.5)
grad *= 100.
grad /= gradmax
nb.Nifti1Image(grad, imnii.get_affine(), imnii.get_header()).to_filename(out_file)
return out_file
