Registration/Alignment utilities

This code contains helper methods in using Elastix to perform section to section aligment. Elastix takes in many many different parameter settings. Below are some notes regarding one particular parameter.

Notes from the manual regarding MOMENTS vs GEOMETRY:

The CenteredTransformInitializer parameter supports two modes of operation. In the first mode, the centers of the images are computed as space coordinates using the image origin, size and spacing. The center of the fixed image is assigned as the rotational center of the transform while the vector going from the fixed image center to the moving image center is passed as the initial translation of the transform. In the second mode, the image centers are not computed geometrically but by using the moments of the intensity gray levels.

Keep in mind that the scale of units in rotation and translation is quite different. For example, here we know that the first element of the parameters array corresponds to the angle that is measured in radians, while the other parameters correspond to the translations that are measured in millimeters

library.utilities.utilities_registration.align_image_to_affine(file_key)

This is the method that takes the rigid transformation and uses PIL to align the image. This method takes about 20 seconds to run as compared to scikit’s version which takes 220 seconds to run on a full scale image.

Parameters:

file_key – tuple of file input and output

Returns:

nothing

library.utilities.utilities_registration.apply_rigid_transform_opencv(file_key)

library.utilities.utilities_registration.apply_rigid_transform_skimage(file_key)

library.utilities.utilities_registration.compute_rigid_transformations(input_path)

Computes rigid transformation matrices for each image in the stack relative to a fixed reference image.

Parameters: - image_stack: List or array of 2D numpy arrays representing the images. - reference_index: Index of the reference image in the stack (default is 0).

Returns: - transformations: List of 3x3 numpy arrays representing the affine transformation matrices.

library.utilities.utilities_registration.convert_2d_transform_forms(arr)

Helper method used by rescale_transformations

Parameters:

arr – an array of data to vertically stack

Returns:

a numpy array

library.utilities.utilities_registration.create_affine_parameters(elastixImageFilter, defaultPixelValue='0.0', debug=False)

Create and return a dictionary of rigid registration parameters for elastixImageFilter. The iterations have been reduced as we are doing two alignment processes.

Parameters: - elastixImageFilter: The elastix image filter object. - defaultPixelValue: The default pixel value for the registration.

Returns: - rigid_params: A dictionary of rigid registration parameters.

library.utilities.utilities_registration.create_rigid_parameters(elastixImageFilter, defaultPixelValue='0.0', debug=False, iteration=0)

Create and return a dictionary of rigid registration parameters for elastixImageFilter. The iterations have been reduced as we are doing two alignment processes.

Parameters: - elastixImageFilter: The elastix image filter object. - defaultPixelValue: The default pixel value for the registration.

Returns: - rigid_params: A dictionary of rigid registration parameters.

library.utilities.utilities_registration.create_rigid_transformation(center, angle, tx, ty)

Applies a rigid transformation to the input image.

Parameters: - image: Input image as a NumPy array. - angle: Rotation angle in degrees (positive values rotate counter-clockwise). - tx: Translation along the x-axis. - ty: Translation along the y-axis.

Returns: - Transformed image as a NumPy array.

library.utilities.utilities_registration.find_matching_points(image1, image2)

library.utilities.utilities_registration.parameters_to_rigid_transform(rotation, xshift, yshift, center)

Takes the rotation, xshift, yshift that were created by Elastix and stored in the elastix_transformation table. Creates a matrix of the rigid transformation.

Parameters:

• rotation – a float designating the rotation in radians

• xshift – a float for showing how much the moving image shifts in the X direction.

• yshift – a float for showing how much the moving image shifts in the Y direction.

• center – tuple of floats showing the center of the image.

Returns:

the 3x3 rigid transformation

library.utilities.utilities_registration.rescale_transformations(transforms: dict, scaling_factor: float) → dict

Rescales the transformation matrices by a given scaling factor. Args: :param transforms (dict): A dictionary where keys are file names and values are 2D numpy arrays representing transformation matrices. scaling_factor (float): The factor by which to scale the transformation matrices. :return: dict: A dictionary with the same keys as the input, where each transformation matrix has been rescaled by the given scaling factor.

library.utilities.utilities_registration.rigid_transform_to_parmeters(transform, center)

convert a 2d transformation matrix (3*3) to the rotation angles, rotation center and translation This is used in the manual aligner notebook.

Args:

transform (array like): 3*3 array that stores the 2*2 transformation matrix and the 1*2 translation vector for a 2D image. the third row of the array is a place holder of values [0,0,1].

Returns:

float: x translation float: y translation float: rotation angle in arc list: lisf of x and y for rotation center

library.utilities.utilities_registration.tif_to_png(file_key)

This method creates a PNG from a TIF :param file_key: tuple of file input and output :return: nothing