EM_CUDA
This is a GPU implementation of the Expectation-Maximization (EM) algorithm for 2D data sets. It takes projection data and an initial reconstruction as input, and returns the reconstruction after a specified number of iterations.
Supported geometries: parallel, parallel_vec, fanflat, fanflat_vec.
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 when starting SIRT is used as the initial reconstruction. |
cfg.option.GPUindex |
optional |
Specifies which GPU to use. Default = 0. |
cfg.option.DetectorSuperSampling |
optional |
Specifies the amount of detector supersampling, i.e. how many rays are cast per detector. |
cfg.option.PixelSuperSampling |
optional |
Specifies the amount of pixel supersampling, i.e. how many (one dimension) subpixels are generated from a single parent pixel. |
Example
%% create phantom
V_exact = phantom(256);
%% create geometries
proj_geom = astra_create_proj_geom('parallel', 1.0, 256, linspace2(0,pi,180));
vol_geom = astra_create_vol_geom(256,256);
%% create forward projection
[sinogram_id, sinogram] = astra_create_sino_cuda(V_exact, proj_geom, vol_geom);
%% reconstruct
recon_id = astra_mex_data2d('create', '-vol', vol_geom, 1.0); % initialize with
% ones to allow for multiplicative updates
cfg = astra_struct('EM_CUDA');
cfg.ProjectionDataId = sinogram_id;
cfg.ReconstructionDataId = recon_id;
em_id = astra_mex_algorithm('create', cfg);
astra_mex_algorithm('iterate', em_id, 15);
V = astra_mex_data2d('get', recon_id);
imshow(V, []);
%% garbage disposal
astra_mex_data2d('delete', sinogram_id, recon_id);
astra_mex_algorithm('delete', em_id);
Extra features
EM_CUDA supports astra_mex_algorithm(‘get_res_norm’) to get the 2-norm of the difference between the projection data and the projection of the reconstruction. (The square root of the sum of squares of differences.)