7.5.2. algotom.util.simulation

Module of simulation methods:

  • Methods for designing a customized 2D phantom.

  • Method for calculating a sinogram of a phantom based on the Fourier slice theorem.

  • Methods for adding artifacts to a simulated sinogram.

Functions:

make_elliptic_mask(size, center, length, angle)

Create an elliptic mask.

make_rectangular_mask(size, center, length, ...)

Create a rectangular mask.

make_triangular_mask(size, center, length, angle)

Create an isosceles triangle mask.

make_line_target(size)

Create line patterns for testing the resolution of a reconstructed image.

make_face_phantom(size)

Create a face phantom for testing reconstruction methods.

make_sinogram(mat, angles[, pad_rate, pad_mode])

Create a sinogram (series of 1D projections) from a 2D image based on the Fourier slice theorem (Ref.

add_noise(mat[, noise_ratio])

Add Gaussian noise to an image.

add_stripe_artifact(sinogram, size, position)

Add stripe artifacts to a sinogram.

convert_to_Xray_image(sinogram[, global_max])

Convert a simulated sinogram to an equivalent X-ray image.

add_background_fluctuation(sinogram[, ...])

Fluctuate the background of a sinogram image using a Gaussian profile beam.
algotom.util.simulation.make_elliptic_mask(size, center, length, angle)[source]

Create an elliptic mask.

Parameters

  • size (int) – Size of a square array.

  • center (float or tuple of float) – Ellipse center.

  • length (float or tuple of float) – Lengths of ellipse axes.

  • angle (float) – Rotation angle (Degree) of the ellipse.

Returns

array_like – Square array.

algotom.util.simulation.make_rectangular_mask(size, center, length, angle)[source]

Create a rectangular mask.

Parameters

  • size (int) – Size of a square array.

  • center (float or tuple of float) – Center of the mask.

  • length (float or tuple of float) – Lengths of the rectangular mask.

  • angle (float) – Rotation angle (Degree) of the mask.

Returns

array_like – Square array.

algotom.util.simulation.make_triangular_mask(size, center, length, angle)[source]

Create an isosceles triangle mask.

Parameters

  • size (int) – Size of a square array.

  • center (float or tuple of float) – Center of the mask.

  • length (float or tuple of float) – Lengths of the mask.

  • angle (float) – Rotation angle (Degree) of the mask.

Returns

array_like – Square array.

algotom.util.simulation.make_line_target(size)[source]

Create line patterns for testing the resolution of a reconstructed image.

Parameters

size (int) – Size of a square array.

Returns

array_like – Square array.

algotom.util.simulation.make_face_phantom(size)[source]

Create a face phantom for testing reconstruction methods.

Parameters

size (int) – Size of a square array.

Returns

array_like – Square array.

algotom.util.simulation.make_sinogram(mat, angles, pad_rate=0.5, pad_mode='edge')[source]

Create a sinogram (series of 1D projections) from a 2D image based on the Fourier slice theorem (Ref. [1]).

Parameters

  • mat (array_like) – Square array.

  • angles (array_like) – 1D array. List of angles (in radian) for projecting.

  • pad_rate (float) – To apply padding before the FFT. The padding width equals to (pad_rate * image_width).

  • pad_mode (str) – Padding method. Full list can be found at numpy_pad documentation.

References

[1] : https://doi.org/10.1071/PH560198

algotom.util.simulation.add_noise(mat, noise_ratio=0.1)[source]

Add Gaussian noise to an image.

Parameters

  • mat (array_like) – 2D array

  • noise_ratio (float) – Ratio between the noise level and the mean of the array.

Returns

array_like

algotom.util.simulation.add_stripe_artifact(sinogram, size, position, strength_ratio=0.2, stripe_type='partial')[source]

Add stripe artifacts to a sinogram.

Parameters

  • sinogram (array_like) – 2D array. Sinogram image.

  • size (int) – Size of stripe artifact.

  • position (int) – Position of the stripe.

  • strength_ratio (float) – To define the strength of the artifact. The value is in the range of [0.0, 1.0].

  • stripe_type ({“partial”, “full”, “dead”, “fluctuating”}) – Type of stripe as classified in Ref. [1].

Returns

array_like

References

[1] : https://doi.org/10.1364/OE.26.028396

algotom.util.simulation.convert_to_Xray_image(sinogram, global_max=None)[source]

Convert a simulated sinogram to an equivalent X-ray image.

Parameters

  • sinogram (array_like) – 2D array.

  • global_max (float) – Maximum value used for normalizing array values to stay in the range of [0.0, 1.0].

Returns

array_like

algotom.util.simulation.add_background_fluctuation(sinogram, strength_ratio=0.2)[source]

Fluctuate the background of a sinogram image using a Gaussian profile beam.

Parameters

  • sinogram (array_like) – 2D array. Sinogram image.

  • strength_ratio (float) – To define the strength of the variation. The value is in the range of [0.0, 1.0].

Returns

array_like