ART

This is a CPU implementation of the Iterative Reconstruction Technique (ART) for 2D data sets. It takes projection data and an initial reconstruction as input, and returns the reconstruction after a specified number of ART iterations. Each iteration of ART consists of an FP and BP of one single projection ray. The order of the rays can be specified.

Supported geometries: parallel, parallel_vec, fanflat, fanflat_vec, matrix.

Configuration options

name	type	description
cfg.ProjectorId	required	The astra_mex_projector ID of the projector.
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 when starting ART is used as the initial reconstruction.
cfg.option.SinogramMaskId	optional	If specified, the astra_mex_data2d ID of a projection-data-sized volume to be used as a mask.
cfg.option.ReconstructionMaskId	optional	If specified, the astra_mex_data2d ID of a volume-data-sized volume to be used as a mask.
cfg.option.MinConstraint	optional	If specified, all values below MinConstraint will be set to MinConstraint. This can, for example, be used to enforce non-negative reconstructions.
cfg.option.MaxConstraint	optional	If specified, all values above MaxConstraint will be set to MaxConstraint.
cfg.option.RayOrder	optional	This specifies the order in which the projections are used. Possible values are: ‘sequential’ (default) and ‘custom’. If ‘custom’ is specified, the option.RayOrderList is required.
cfg.option.RayOrderList	optional	Required if option.RayOrder = ‘custom’, ignored otherwise. A matlab vector containing the custom order in which the projections are used.

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('ART')
cfg['ProjectorId'] = proj_id
cfg['ProjectionDataId'] = sinogram_id
cfg['ReconstructionDataId'] = recon_id
cfg['option'] = { }
cfg['option']['RayOrder'] =  'custom'
fullRayList = numpy.array(numpy.meshgrid(range(180), range(256))).reshape(2,-1).T
cfg['option']['RayOrderList'] = numpy.random.permutation(fullRayList).reshape(-1)

art_id = astra.algorithm.create(cfg)
astra.algorithm.run(art_id, 3*180*256)
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(art_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

[p,q] = meshgrid(0:179, 0:255);
rayOrderList = [p(:) q(:)];
rayOrderList = rayOrderList(randperm(numel(p)),:);

recon_id = astra_mex_data2d('create', '-vol', vol_geom, 0);
cfg = astra_struct('ART');
cfg.ProjectorId = proj_id;
cfg.ProjectionDataId = sinogram_id;
cfg.ReconstructionDataId = recon_id;
cfg.option.RayOrder = 'custom';
cfg.option.RayOrderList = rayOrderList;
art_id = astra_mex_algorithm('create', cfg);
astra_mex_algorithm('iterate', art_id, 3*numel(p));
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', art_id);

Further examples regarding the different projection orders can be found in example_art_order.m .