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