itk-core

import itk import numpy as np import os # --- Setup: Create a dummy image if 'input.mha' doesn't exist --- input_file = "input.mha" output_file = "output_smoothed.mha" if not os.path.exists(input_file): print(f"{input_file} not found, creating a dummy 3D image for demonstration.") array_image = np.zeros((64, 64, 64), dtype=np.float32) # Add a simple cube to the image array_image[10:50, 10:50, 10:50] = 100.0 dummy_image = itk.image_from_array(array_image) # Set metadata (origin, spacing) which is important for ITK images dummy_image.SetSpacing([1.0, 1.0, 1.0]) dummy_image.SetOrigin([0.0, 0.0, 0.0]) itk.imwrite(dummy_image, input_file) print(f"Created {input_file}") # --- Core ITK Usage: Read, Process, Write --- # 1. Define the image type (e.g., 3D float image) ImageType = itk.Image[itk.F, 3] # itk.F for float, 3 for 3 dimensions # 2. Read an image print(f"Reading image from {input_file}...") image = itk.imread(input_file, ImageType) print(f"Original image size: {image.GetLargestPossibleRegion().GetSize()}") # 3. Apply a filter (e.g., Gaussian smoothing) print("Applying Gaussian filter...") gaussian_filter = itk.GaussianImageFilter[ImageType, ImageType].New() gaussian_filter.SetInput(image) gaussian_filter.SetSigma(2.0) # Set the standard deviation for the Gaussian kernel gaussian_filter.Update() # Execute the filter smoothed_image = gaussian_filter.GetOutput() # 4. Write the processed image print(f"Writing smoothed image to {output_file}...") itk.imwrite(smoothed_image, output_file) print(f"Smoothed image size: {smoothed_image.GetLargestPossibleRegion().GetSize()}") print("Image processing complete.")