__all__ = ['iMath',
'image_math',
'multiply_images',
'iMath_get_largest_component',
'iMath_normalize',
'iMath_truncate_intensity',
'iMath_sharpen',
'iMath_pad',
'iMath_maurer_distance',
'iMath_perona_malik',
'iMath_grad',
'iMath_laplacian',
'iMath_canny',
'iMath_histogram_equalization',
'iMath_MD',
'iMath_ME',
'iMath_MO',
'iMath_MC',
'iMath_GD',
'iMath_GE',
'iMath_GO',
'iMath_GC',
'iMath_fill_holes',
'iMath_get_largest_component',
'iMath_normalize',
'iMath_truncate_intensity',
'iMath_sharpen',
'iMath_propagate_labels_through_mask']
from .process_args import _int_antsProcessArguments
from .. import utils
_iMathOps = {'FillHoles',
'GetLargestComponent',
'Normalize',
'Sharpen',
'Pad',
'D',
'MaurerDistance',
'PeronaMalik',
'Grad',
'Laplacian',
'Canny',
'HistogramEqualization',
'MD',
'ME',
'MO',
'MC',
'GD',
'GE',
'GO',
'GC',
'FillHoles',
'GetLargestComponent',
'LabelStats',
'Normalize',
'TruncateIntensity',
'Sharpen',
'PropagateLabelsThroughMask'}
[docs]def multiply_images(image1, image2):
return image1 * image2
[docs]def iMath(image, operation, *args):
"""
Perform various (often mathematical) operations on the input image/s.
Additional parameters should be specific for each operation.
See the the full iMath in ANTs, on which this function is based.
ANTsR function: `iMath`
Arguments
---------
image : ANTsImage
input object, usually antsImage
operation
a string e.g. "GetLargestComponent" ... the special case of "GetOperations"
or "GetOperationsFull" will return a list of operations and brief
description. Some operations may not be valid (WIP), but most are.
*args : non-keyword arguments
additional parameters specific to the operation
Example
-------
>>> import ants
>>> img = ants.image_read(ants.get_ants_data('r16'))
>>> img2 = ants.iMath(img, 'Canny', 1, 5, 12)
"""
if operation not in _iMathOps:
raise ValueError('Operation not recognized')
imagedim = image.dimension
outimage = image.clone()
args = [imagedim, outimage, operation, image] + [a for a in args]
processed_args = _int_antsProcessArguments(args)
libfn = utils.get_lib_fn('iMath')
libfn(processed_args)
return outimage
image_math = iMath
def iMath_ops():
return _iMathOps
[docs]def iMath_canny(image, sigma, lower, upper):
return iMath(image, 'Canny', sigma, lower, upper)
def iMath_distance_map(image, use_spacing=True):
return iMath(image, 'DistanceMap', use_spacing)
[docs]def iMath_fill_holes(image, hole_type=2):
return iMath(image, 'FillHoles', hole_type)
[docs]def iMath_GC(image, radius=1):
return iMath(image, 'GC', radius)
[docs]def iMath_GD(image, radius=1):
return iMath(image, 'GD', radius)
[docs]def iMath_GE(image, radius=1):
return iMath(image, 'GE', radius)
[docs]def iMath_GO(image, radius=1):
return iMath(image, 'GO', radius)
[docs]def iMath_get_largest_component(image, min_size=50):
return iMath(image, 'GetLargestComponent', min_size)
[docs]def iMath_grad(image, sigma=0.5, normalize=False):
return iMath(image, 'Grad', sigma, normalize)
[docs]def iMath_histogram_equalization(image, alpha, beta):
return iMath(image, 'HistogramEqualization', alpha, beta)
[docs]def iMath_laplacian(image, sigma=0.5, normalize=False):
return iMath(image, 'Laplacian', sigma, normalize)
[docs]def iMath_MC(image, radius=1, value=1, shape=1, parametric=False, lines=3, thickness=1, include_center=False):
return iMath(image, 'MC', radius, value, shape, parametric, lines, thickness, include_center)
[docs]def iMath_MD(image, radius=1, value=1, shape=1, parametric=False, lines=3, thickness=1, include_center=False):
return iMath(image, 'MD', radius, value, shape, parametric, lines, thickness, include_center)
[docs]def iMath_ME(image, radius=1, value=1, shape=1, parametric=False, lines=3, thickness=1, include_center=False):
return iMath(image, 'ME', radius, value, shape, parametric, lines, thickness, include_center)
[docs]def iMath_MO(image, radius=1, value=1, shape=1, parametric=False, lines=3, thickness=1, include_center=False):
return iMath(image, 'MO', radius, value, shape, parametric, lines, thickness, include_center)
[docs]def iMath_maurer_distance(image, foreground=1):
return iMath(image, 'MaurerDistance', foreground)
[docs]def iMath_normalize(image):
return iMath(image, 'Normalize')
[docs]def iMath_pad(image, padding):
return iMath(image, 'Pad', padding)
[docs]def iMath_perona_malik(image, conductance=0.25, n_iterations=1):
return iMath(image, 'PeronaMalik', conductance, n_iterations)
[docs]def iMath_sharpen(image):
return iMath(image, 'Sharpen')
[docs]def iMath_propagate_labels_through_mask(image, labels, stopping_value=100, propagation_method=0):
"""
>>> import ants
>>> wms = ants.image_read('~/desktop/wms.nii.gz')
>>> thal = ants.image_read('~/desktop/thal.nii.gz')
>>> img2 = ants.iMath_propagate_labels_through_mask(wms, thal, 500, 0)
"""
return iMath(image, 'PropagateLabelsThroughMask', labels, stopping_value, propagation_method)
[docs]def iMath_truncate_intensity(image, lower_q, upper_q, n_bins=64):
"""
>>> import ants
>>> img = ants.image_read(ants.get_ants_data('r16'))
>>> ants.iMath_truncate_intensity( img, 0.2, 0.8 )
"""
return iMath(image, 'TruncateIntensity', lower_q, upper_q, n_bins )
