FBP

This is a CPU implementation of the Filtered Backprojection (FBP) algorithm for 2D data sets. It takes a projector, projection data and an initial reconstruction as input, and returns the reconstruction.

Supported geometries: parallel.

Configuration options

name	type	description
cfg.ProjectionDataId	required	The astra_mex_data2d ID of the projection data
cfg.ReconstructionDataId	required	The astra_mex_data2d ID of the reconstruction data. The content of this is overwritten.
cfg.FilterType	optional	Type of projection filter. Options: * ‘none’ * ‘ram-lak’ (default) * ‘shepp-logan’ * ‘cosine’ * ‘hamming’ * ‘hann’ * ‘tukey’ * ‘lanczos’ * ‘triangular’ * ‘gaussian’ * ‘barlett-hann’ * ‘blackman’ * ‘nuttall’ * ‘blackman-harris’ * ‘blackman-nuttall’ * ‘flat-top’ * ‘kaiser’ * ‘parzen’ * ‘projection’ (Fourier space filter, all projection directions share one filter) * ‘sinogram’ (Fourier space filter, every projection direction has its own filter) * ‘rprojection’ (real space filter, all projection directions share one filter) * ‘rsinogram’ (real space filter, every projection direction has its own filter)
cfg.FilterSinogramId	optional	The astra_mex_data2d ID of the filter data for ‘projection’, ‘sinogram’, ‘rprojection’ and ‘rsinogram’ filter types.
cfg.FilterParameter	optional	Parameter value for the ‘tukey’, ‘gaussian’, ‘blackman’ and ‘kaiser’ filter types.
cfg.FilterD	optional	“D” parameter value for ‘shepp-logan’, ‘cosine’, ‘hamming’ and ‘hann’ filter types.

Example

import astra
import matplotlib.pyplot as plt
import numpy

# create geometries and projector
proj_geom = astra.create_proj_geom('parallel', 1.0, 256, numpy.linspace(0, numpy.pi, 180, endpoint=False))
vol_geom = astra.create_vol_geom(256,256)
proj_id = astra.create_projector('linear', proj_geom, vol_geom)

# generate phantom image
V_exact_id, V_exact = astra.data2d.shepp_logan(vol_geom)

# create forward projection
sinogram_id, sinogram = astra.create_sino(V_exact, proj_id)

# reconstruct
recon_id = astra.data2d.create('-vol', vol_geom, 0)
cfg = astra.astra_dict('FBP')
cfg['ProjectorId'] = proj_id
cfg['ProjectionDataId'] = sinogram_id
cfg['ReconstructionDataId'] = recon_id
fbp_id = astra.algorithm.create(cfg)
astra.algorithm.run(fbp_id)
V = astra.data2d.get(recon_id)
plt.gray()
plt.imshow(V)
plt.show()

# garbage disposal
astra.data2d.delete([sinogram_id, recon_id, V_exact_id])
astra.projector.delete(proj_id)
astra.algorithm.delete(fbp_id)

%% create phantom
V_exact = phantom(256);

%% create geometries and projector
proj_geom = astra_create_proj_geom('parallel', 1.0, 256, linspace2(0,pi,180));
vol_geom = astra_create_vol_geom(256,256);
proj_id = astra_create_projector('linear', proj_geom, vol_geom);

%% create forward projection
[sinogram_id, sinogram] = astra_create_sino(V_exact, proj_id);

%% reconstruct
recon_id = astra_mex_data2d('create', '-vol', vol_geom, 0);
cfg = astra_struct('FBP');
cfg.ProjectorId = proj_id;
cfg.ProjectionDataId = sinogram_id;
cfg.ReconstructionDataId = recon_id;
fbp_id = astra_mex_algorithm('create', cfg);
astra_mex_algorithm('run', fbp_id);
V = astra_mex_data2d('get', recon_id);
imshow(V, []);

%% garbage disposal
astra_mex_data2d('delete', sinogram_id, recon_id);
astra_mex_projector('delete', proj_id);
astra_mex_algorithm('delete', fbp_id);