mbircone.laminography

Functions:

`recon_lamino`(sino, angles, theta[, weights, ...])	Compute MBIR reconstruction for parallel-beam laminography geometry.
`project_lamino`(image, angles, theta, ...[, ...])	Compute forward projection for parallel-beam laminography geometry.

mbircone.laminography.project_lamino(image, angles, theta, num_det_rows, num_det_channels, delta_det_channel=1.0, delta_det_row=1.0, delta_pixel_image=None, det_channel_offset=0.0, image_slice_offset=0.0, num_threads=None, verbose=1, lib_path='/home/docs/.cache/mbircone')[source]

Compute forward projection for parallel-beam laminography geometry.

Parameters:

image (float, ndarray) – 3D image to be projected, with shape (num_img_slices, num_img_rows, num_img_cols).
angles (float, ndarray) – 1D array of view angles in radians.
theta (float) – Angle in radians that source-detector line makes with the object vertical axis.
num_det_rows (int) – Number of rows in laminography sinogram data.
num_det_channels (int) – Number of channels in laminography sinogram data.
delta_det_channel (float, optional) – [Default=1.0] Detector channel spacing in \(ALU\).
delta_det_row (float, optional) – [Default=1.0] Detector row spacing in \(ALU\).
delta_pixel_image (float, optional) – [Default=None] Image pixel spacing in \(ALU\). If None, automatically set to delta_det_channel.
det_channel_offset (float, optional) – [Default=0.0] Distance in \(ALU\) from center of detector to the detector z-axis along a row. (Note: There is no det_row_offset parameter; due to the parallel beam geometry such a parameter would be redundant with image_slice_offset.)
image_slice_offset (float, optional) – [Default=0.0] Vertical offset of the image in units of \(ALU\).
num_threads (int, optional) – [Default=None] Number of compute threads requested when executed. If None, num_threads is set to the number of cores in the system.
verbose (int, optional) – [Default=1] Possible values are {0,1,2}, where 0 is quiet, 1 prints minimal reconstruction progress information, and 2 prints the full information.
lib_path (str, optional) – [Default=~/.cache/mbircone] Path to directory containing library of forward projection matrices.

Returns:

(float, ndarray) – 3D laminography sinogram with shape (num_views, num_det_rows, num_det_channels).

mbircone.laminography.recon_lamino(sino, angles, theta, weights=None, weight_type='unweighted', init_image=0.0, prox_image=None, num_image_rows=None, num_image_cols=None, num_image_slices=None, delta_det_channel=1.0, delta_det_row=1.0, delta_pixel_image=None, det_channel_offset=0.0, image_slice_offset=0.0, sigma_y=None, snr_db=40.0, sigma_x=None, sigma_p=None, p=1.2, q=2.0, T=1.0, num_neighbors=6, sharpness=0.0, positivity=True, max_resolutions=None, stop_threshold=0.2, max_iterations=100, NHICD=False, num_threads=None, verbose=1, lib_path='/home/docs/.cache/mbircone')[source]

Compute MBIR reconstruction for parallel-beam laminography geometry.

Parameters:

sino (float, ndarray) – 3D laminography sinogram data with shape (num_views, num_det_rows, num_det_channels).
angles (float, ndarray) – 1D array of view angles in radians.
theta (float) – Angle in radians that source-detector line makes with the object vertical axis.
weights (float, ndarray, optional) – [Default=None] 3D weights array with same shape as sino. If weights is not supplied, then cone3D.calc_weights is used to set weights using weight_type. weights=0.0 indicates an invalid sinogram entry in sino.
weight_type (string, optional) – [Default=’unweighted’] Type of noise model used for data.
- 'unweighted' corresponds to unweighted reconstruction;
- 'transmission' is the correct weighting for transmission CT with constant dosage;
- 'transmission_root' is commonly used with transmission CT data to improve image homogeneity;
- 'emission' is appropriate for emission CT data.
init_image (float, ndarray, optional) – [Default=0.0] Initial value of reconstruction image, specified by either a scalar value or a 3D numpy array with shape (num_img_slices, num_img_rows, num_img_cols).
prox_image (float, ndarray, optional) – [Default=None] 3D proximal map input image with shape (num_img_slices, num_img_rows, num_img_cols).
num_image_rows (int, optional) – [Default=None] Number of rows in reconstructed image. If None, automatically set by laminography.auto_image_rows_cols.
num_image_cols (int, optional) – [Default=None] Number of columns in reconstructed image. If None, automatically set by laminography.auto_image_rows_cols.
num_image_slices (int, optional) – [Default=None] Number of slices in reconstructed image. If None, automatically set by laminography.auto_image_slices.
delta_det_channel (float, optional) – [Default=1.0] Detector channel spacing in \(ALU\).
delta_det_row (float, optional) – [Default=1.0] Detector row spacing in \(ALU\).
delta_pixel_image (float, optional) – [Default=None] Image pixel spacing in \(ALU\). If None, automatically set to delta_det_channel.
det_channel_offset (float, optional) – [Default=0.0] Distance in \(ALU\) from center of detector to the detector z-axis along a row. (Note: There is no det_row_offset parameter; due to the parallel beam geometry such a parameter would be redundant with image_slice_offset.)
image_slice_offset (float, optional) – [Default=0.0] Vertical offset of the image in units of \(ALU\).
sigma_y (float, optional) – [Default=None] Forward model regularization parameter. If None, automatically set with cone3D.auto_sigma_y.
snr_db (float, optional) – [Default=40.0] Assumed signal-to-noise ratio of the data in \(dB\). Ignored if sigma_y is not None.
sigma_x (float, optional) – [Default=None] qGGMRF prior model regularization parameter. If None, automatically set with cone3D.auto_sigma_x as a function of sharpness. If prox_image is given, sigma_p is used instead of sigma_x in the reconstruction.
sigma_p (float, optional) – [Default=None] Proximal map regularization parameter. If None, automatically set with cone3D.auto_sigma_p as a function of sharpness. Ignored if prox_image is None.
p (float, optional) – [Default=1.2] Scalar value in range \([1,2]\) that specifies qGGMRF shape parameter.
q (float, optional) – [Default=2.0] Scalar value in range \([p,1]\) that specifies qGGMRF shape parameter.
T (float, optional) – [Default=1.0] Scalar value \(>0\) that specifies the qGGMRF threshold parameter.
num_neighbors (int, optional) – [Default=6] Possible values are \({26,18,6}\). Number of neighbors in the qGGMRF neighborhood. More neighbors results in a better regularization but a slower reconstruction.
sharpness (float, optional) – [Default=0.0] Sharpness of reconstruction. sharpness=0.0 is neutral; sharpness>0 increases sharpness; sharpness<0 reduces sharpness. Used to calculate sigma_x and sigma_p. Ignored if sigma_x is not None in qGGMRF mode, or if sigma_p is not None in proximal map mode.
positivity (bool, optional) – [Default=True] Determines if positivity constraint will be enforced.
max_resolutions (int, optional) – [Default=None] Integer \(\geq 0\) that specifies the maximum number of grid resolutions used to solve MBIR reconstruction problem. If None, automatically set by cone3D.auto_max_resolutions.
stop_threshold (float, optional) – [Default=0.2] Relative update stopping threshold, in percent, where relative update is given by (average value change) / (average voxel value).
max_iterations (int, optional) – [Default=100] Maximum number of iterations before stopping.
NHICD (bool, optional) – [Default=False] If True, uses non-homogeneous ICD updates.
num_threads (int, optional) – [Default=None] Number of compute threads requested when executed. If None, this is set to the number of cores in the system.
verbose (int, optional) – [Default=1] Possible values are {0,1,2}, where 0 is quiet, 1 prints minimal reconstruction progress information, and 2 prints the full information.
lib_path (str, optional) – [Default=~/.cache/mbircone] Path to directory containing library of forward projection matrices.

Returns:

(float, ndarray) – 3D laminography reconstruction image with shape (num_img_slices, num_img_rows, num_img_cols) in units of \(ALU^{-1}\).