nabu.reconstruction

Classes

Reconstructor — Abstract base class for reconstructors.
MunchDeringer — Initialize a "Munch Et Al" sinogram deringer. See References for more information.
SinoBuilder — A class to build sinograms.
SinoNormalization — A class for sinogram normalization utilities.

Functions

convert_halftomo — Converts a sinogram into a sinogram with extended FOV with the "half tomography" setting.

source class Reconstructor(shape, indices_range, axis='z', vol_type='sinograms', slices_roi=None)

Abstract base class for reconstructors.

A Reconstructor is a helper to reconstruct slices in arbitrary directions (not only usual "horizontal slices") in parallel-beam tomography.

Initialize a reconstructor.

Current limitations

Limitation to the three main axes
One instance of Reconstructor can only reconstruct successive slices

Typical scenarios examples

"I want to reconstruct several slices along 'z'", where z is the vertical axis. In this case, we reconstruct "horizontal slices" in planes perpendicular to the rotation axis.
"I want to reconstruct slices along 'y'". Here y is an axis perpendicular to z, i.e we reconstruct "vertical slices".

Parameters

shape : tuple — Shape of the stack of sinograms or projections.
indices_range : tuple — Range of indices to reconstruct, in the form (start, end). As the standard Python behavior, the upper bound is not included. For example, to reconstruct 100 slices (numbered from 0 to 99), then you can provide (0, 100) or (0, None). Providing (0, 99) or (0, -1) will omit the last slice.
axis : str — Axis along which the slices are reconstructed. This axis is orthogonal to the slices planes. This parameter can be either "x", "y", or "z". Default is "z" (reconstruct slices perpendicular to the rotation axis).
vol_type : str, optional — Whether the parameter shape describes a volume of sinograms or projections. The two are the same except that axes 0 and 1 are swapped. Can be "sinograms" (default) or "projections".
slices_roi : tuple, optional — Define a Region Of Interest to reconstruct a part of each slice. By default, the whole slice is reconstructed for each slice index. This parameter is in the form (start_u, end_u, start_v, end_v), where u and v are horizontal and vertical axes on the reconstructed slice respectively, regardless of its orientation. If one of the values is set to None, it will be replaced by the corresponding default value.

Examples

To reconstruct the first two horizontal slices, i.e along z: R = Reconstructor(vol_shape, [0, 1]) To reconstruct vertical slices 0-100 along the y axis: R = Reconstructor(vol_shape, (0, 100), axis="y")

A Reconstructor is tied to the set of slices to reconstruct (axis and orientation). Once defined, it cannot be changed ; i.e another class has to be instantiated to reconstruct slices in other axes/indices.

The volume geometry conventions are defined below::

                      __________
                     /         /|
                    /         / |
     z             /         /  |
     ^            /_________/   |
     |           |          |   |
     |    y      |          |   /
     |   /       |          |  /
     |  /        |          | /
     | /         |__________|/
     |/
     ---------- > x

The axis z parallel to the rotation axis. The usual parallel-beam tomography setting reconstructs slices along z, i.e in planes parallel to (x, y).

Methods

reconstruct

source method Reconstructor.reconstruct()

Raises

ValueError

source class MunchDeringer(sigma, sinos_shape, levels=None, wname='db15', padding=None, padding_mode='edge')

Initialize a "Munch Et Al" sinogram deringer. See References for more information.

Parameters

sigma : float — Standard deviation of the damping parameter. The higher value of sigma, the more important the filtering effect on the rings.
levels : int, optional — Number of wavelets decomposition levels. By default (None), the maximum number of decomposition levels is used.
wname : str, optional — Default is "db15" (Daubechies, 15 vanishing moments)
sinos_shape : tuple, optional — Shape of the sinogram (or sinograms stack).
padding : tuple of two int, optional — Horizontal padding to use for reducing the aliasing artefacts

References

B. Munch, P. Trtik, F. Marone, M. Stampanoni, Stripe and ring artifact removal with combined wavelet-Fourier filtering, Optics Express 17(10):8567-8591, 2009.

Methods

remove_rings — Main function to performs rings artefacts removal on sinogram(s). CAUTION: this function defaults to in-place processing, meaning that the sinogram(s) you pass will be overwritten.

source method MunchDeringer.remove_rings(sinos, output=None)

Main function to performs rings artefacts removal on sinogram(s). CAUTION: this function defaults to in-place processing, meaning that the sinogram(s) you pass will be overwritten.

Parameters

sinos : numpy.ndarray — Sinogram or stack of sinograms.
output : numpy.ndarray, optional — Output array. If set to None (default), the output overwrites the input.

source class SinoBuilder(sinos_shape=None, radios_shape=None, rot_center=None, halftomo=False, angles=None, interpolate=False)

A class to build sinograms.

Initialize a SinoBuilder instance.

Parameters

sinos_shape : tuple of int — Shape of the stack of sinograms, in the form (n_z, n_angles, n_x). If not provided, it is derived from radios_shape.
radios_shape : tuple of int — Shape of the chunk of radios, in the form (n_angles, n_z, n_x). If not provided, it is derived from sinos_shape.
rot_center : int or array — Rotation axis position. A scalar indicates the same rotation axis position for all the projections.
halftomo : bool — Whether "half tomography" is enabled. Default is False.
interpolate : bool, optional — Only used if halftomo=True. Whether to re-grid the second part of sinograms to match projection k with projection k + n_a/2. This forces each pair of projection (k, k + n_a/2) to be separated by exactly 180 degrees.
angles : array, optional — Rotation angles (in radians). Used and required only when halftomo and interpolate are True.

Attributes

output_shape — Get the output sinograms shape.

Methods

set_rot_center — Set the rotation axis position for the current radios/sinos stack.
get_sino — The the sinogram at a given index.
convert_sino
get_sinos
radios_to_sinos — DEPRECATED. Use get_sinos() or get_sino() instead.

source method SinoBuilder.set_rot_center(rot_center)

Set the rotation axis position for the current radios/sinos stack.

rot_center: int or array Rotation axis position. A scalar indicates the same rotation axis position for all the projections.

Raises

ValueError

source property SinoBuilder.output_shape

Get the output sinograms shape.

source method SinoBuilder.get_sino(radios, i, output=None)

The the sinogram at a given index.

Parameters

radios : array — 3D array with shape (n_z, n_angles, n_x)
i : int — Sinogram index

Returns

sino : array — Two dimensional array with shape (n_angles2, n_x2) where the dimensions are determined by the current settings.

source method SinoBuilder.convert_sino(sino, output=None)

source method SinoBuilder.get_sinos(radios, output=None)

source method SinoBuilder.radios_to_sinos(radios, output=None, copy=False)

DEPRECATED. Use get_sinos() or get_sino() instead.

source convert_halftomo(sino, extended_width, transition_width=None)

Converts a sinogram into a sinogram with extended FOV with the "half tomography" setting.

source class SinoNormalization(kind='chebyshev', sinos_shape=None, radios_shape=None, normalization_array=None)

A class for sinogram normalization utilities.

Initialize a SinoNormalization class.

Parameters

kind : str, optional — Normalization type. They can be the following: - chebyshev: Each sinogram line is estimated by a Chebyshev polynomial of degree 2. This estimation is then subtracted from the sinogram. - subtraction: Each sinogram is subtracted with a user-provided array. The array can be 1D (angle-independent) and 2D (angle-dependent) - division: same as previously, but with a division operation. Default is "chebyshev"
sinos_shape : tuple, optional — Shape of the sinogram or sinogram stack. Either this parameter or 'radios_shape' has to be provided.
radios_shape : tuple, optional — Shape of the projections or projections stack. Either this parameter or 'sinos_shape' has to be provided.
normalization_array : numpy.ndarray, optional — Normalization array when kind='subtraction' or kind='division'.

Methods

normalize — Normalize a sinogram or stack of sinogram. The process is done in-place, meaning that the sinogram content is overwritten.

source method SinoNormalization.normalize(sino)

Normalize a sinogram or stack of sinogram. The process is done in-place, meaning that the sinogram content is overwritten.