CGLS_CUDA ========= This is a GPU 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 iterations. The internal state of the CGLS algorithm is reset every time astra_mex_algorithm('iterate') is called. This implies that running CGLS for N iterations and then running it for another N iterations may yield different results from running it 2N iterations at once. Supported geometries: parallel, 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 CGLS 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.GPUindex optional Specifies which GPU to use. Default = 0. cfg.option.DetectorSuperSampling optional For the forward projection, DetectorSuperSampling rays will be used. This should only be used if your detector pixels are larger than the voxels in the reconstruction volume. Defaults to 1. cfg.option.PixelSuperSampling optional For the backward projection, PixelSuperSampling^2 rays will be used. This should only be used if your voxels in the reconstruction volume are larger than the detector pixels. Defaults to 1. ================================ ======== ==== 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, 0); cfg = astra_struct('CGLS_CUDA'); cfg.ProjectionDataId = sinogram_id; cfg.ReconstructionDataId = recon_id; cgls_id = astra_mex_algorithm('create', cfg); astra_mex_algorithm('iterate', cgls_id, 100); V = astra_mex_data2d('get', recon_id); imshow(V, []); %% garbage disposal astra_mex_data2d('delete', sinogram_id, recon_id); astra_mex_algorithm('delete', cgls_id);