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 ------- .. code-block:: matlab %% 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.)