def image_postprocessing(self, image):
"""
Processes input image files. Blurs, crops, pads, and normalizes according to the parameters.
:param image: The sitk image.
:return: The processed sitk image.
"""
if self.image_gaussian_blur_sigma > 0:
image = gaussian(image, [self.image_gaussian_blur_sigma, self.image_gaussian_blur_sigma])
image_float = sitk.Cast(image, sitk.sitkFloat32)
image_float = normalize_robust_sitk(image_float, (-1, 1), consideration_factors=self.normalization_consideration_factors)
return image_float
def image_preprocessing(self, image):
if self.image_gaussian_blur_sigma > 0:
image = gaussian(image, self.image_gaussian_blur_sigma)
if self.crop_image_size is not None:
image = sitk.Crop(image, self.crop_image_size,
self.crop_image_size)
image.SetOrigin([0] * image.GetDimension())
if self.pad_image:
pad_size = image.GetSize()
pad_size = [int(s / 2) for s in pad_size]
image = sitk.MirrorPad(image, pad_size, pad_size)
image_float = sitk.Cast(image, sitk.sitkFloat32)
image_float = normalize_robust_sitk(
image_float, (-1, 1),
consideration_factors=self.normalization_consideration_factors)
return image_float
def image_postprocessing(self, image):
"""
Processes input image files. Blurs, crops, pads, and normalizes according to the parameters.
:param image: The sitk image.
:return: The processed sitk image.
"""
if self.image_gaussian_blur_sigma > 0:
image = gaussian(image, [self.image_gaussian_blur_sigma, self.image_gaussian_blur_sigma])
if self.crop_image_size is not None:
image = sitk.Crop(image, self.crop_image_size, self.crop_image_size)
if self.pad_image:
pad_size = image.GetSize()
pad_size = [int(s / 2) for s in pad_size]
image = sitk.MirrorPad(image, pad_size, pad_size)
image_float = sitk.Cast(image, sitk.sitkFloat32)
image_float = normalize_robust_sitk(image_float, (-1, 1), consideration_factors=self.normalization_consideration_factors)
return image_float