CGLS
This is a CPU implementation of the Conjugate Gradient Least Squares (CGLS) algorithm for 2D data sets. It takes projection data and an initial reconstruction as input, and returns the reconstruction after a specified number of CGLS iterations.
The internal state of the CGLS algorithm is NOT reset between
astra.algorithm.run/astra_mex_algorithm('iterate') calls. Updating the
contents of the projection data and reconstruction data astra_mex_data2d objects
between these calls will produce undefined behavior.
Supported geometries: parallel, parallel_vec, fanflat, fanflat_vec, matrix.
Configuration options
Name |
Description |
|---|---|
ProjectorId |
|
ProjectionDataId |
|
ReconstructionDataId |
ID of data object to store the result. The content of this data is used as the initial reconstruction. |
option.SinogramMaskId |
If specified, data object ID of a projection-data-sized volume to be used as a mask. |
option.ReconstructionMaskId |
If specified, data object ID of a volume-data-sized volume to be used as a mask. |
Example
import astra
import matplotlib.pyplot as plt
import numpy as np
# Create geometries and projector
N = 256
N_ANGLES = 180
det_spacing = 1.0
angles = np.linspace(0, np.pi, N_ANGLES)
proj_geom = astra.create_proj_geom('parallel', det_spacing, N, angles)
vol_geom = astra.create_vol_geom(N, N)
projector_id = astra.create_projector('linear', proj_geom, vol_geom)
# Generate phantom image
phantom_id, phantom = astra.data2d.shepp_logan(vol_geom)
# Create forward projection
sinogram_id, sinogram = astra.create_sino(phantom_id, projector_id)
# Reconstruct
recon_id = astra.data2d.create('-vol', vol_geom)
cfg = astra.astra_dict('CGLS')
cfg['ProjectorId'] = projector_id
cfg['ProjectionDataId'] = sinogram_id
cfg['ReconstructionDataId'] = recon_id
algorithm_id = astra.algorithm.create(cfg)
astra.algorithm.run(algorithm_id, iterations=100)
reconstruction = astra.data2d.get(recon_id)
plt.imshow(reconstruction, cmap='gray')
# Clean up
astra.data2d.delete([sinogram_id, recon_id, phantom_id])
astra.projector.delete(projector_id)
astra.algorithm.delete(algorithm_id)
%% Create phantom
N = 256;
phantom = phantom(N);
%% Create geometries and projector
det_spacing = 1.0;
N_ANGLES = 180;
angles = linspace(0, pi, N_ANGLES);
proj_geom = astra_create_proj_geom('parallel', det_spacing, N, angles);
vol_geom = astra_create_vol_geom(N, N);
projector_id = astra_create_projector('linear', proj_geom, vol_geom);
%% Create forward projection
[sinogram_id, sinogram] = astra_create_sino(phantom, projector_id);
%% Reconstruct
recon_id = astra_mex_data2d('create', '-vol', vol_geom);
cfg = astra_struct('CGLS');
cfg.ProjectorId = projector_id;
cfg.ProjectionDataId = sinogram_id;
cfg.ReconstructionDataId = recon_id;
algorithm_id = astra_mex_algorithm('create', cfg);
astra_mex_algorithm('iterate', algorithm_id, 100);
reconstruction = astra_mex_data2d('get', recon_id);
imshow(reconstruction, []);
%% Clean up
astra_mex_data2d('delete', sinogram_id, recon_id);
astra_mex_projector('delete', projector_id);
astra_mex_algorithm('delete', algorithm_id);