reconstruction
: reconstruction algorithm¶
Warning
This module is known to be buggy in version 0.6: Do NOT use it without having checked it provides proper results
- class ReconstructionAlgorithm(sino_shape, slice_shape=None, axis_position=None, angles=None, ctx=None, devicetype='all', platformid=None, deviceid=None, profile=False)[source]¶
A parent class for all iterative tomographic reconstruction algorithms
- Parameters
sino_shape – shape of the sinogram. The sinogram is in the format (n_b, n_a) where n_b is the number of detector bins and n_a is the number of angles.
slice_shape – Optional, shape of the reconstructed slice. By default, it is a square slice where the dimension is the “x dimension” of the sinogram (number of bins).
axis_position – Optional, axis position. Default is (shape[1]-1)/2.0.
angles – Optional, a list of custom angles in radian.
ctx – actual working context, left to None for automatic initialization from device type or platformid/deviceid
devicetype – type of device, can be “CPU”, “GPU”, “ACC” or “ALL”
platformid – integer with the platform_identifier, as given by clinfo
deviceid – Integer with the device identifier, as given by clinfo
profile – switch on profiling to be able to profile at the kernel level, store profiling elements (makes code slightly slower)
- class SIRT(sino_shape, slice_shape=None, axis_position=None, angles=None, ctx=None, devicetype='all', platformid=None, deviceid=None, profile=False)[source]¶
A class for the SIRT algorithm
- Parameters
sino_shape – shape of the sinogram. The sinogram is in the format (n_b, n_a) where n_b is the number of detector bins and n_a is the number of angles.
slice_shape – Optional, shape of the reconstructed slice. By default, it is a square slice where the dimension is the “x dimension” of the sinogram (number of bins).
axis_position – Optional, axis position. Default is (shape[1]-1)/2.0.
angles – Optional, a list of custom angles in radian.
ctx – actual working context, left to None for automatic initialization from device type or platformid/deviceid
devicetype – type of device, can be “CPU”, “GPU”, “ACC” or “ALL”
platformid – integer with the platform_identifier, as given by clinfo
deviceid – Integer with the device identifier, as given by clinfo
profile – switch on profiling to be able to profile at the kernel level, store profiling elements (makes code slightly slower)
Warning
This is a beta version of the SIRT algorithm. Reconstruction fails for at least on CPU (Xeon E3-1245 v5) using the AMD opencl implementation.
- compute_preconditioners()[source]¶
Create a diagonal preconditioner for the projection and backprojection operator. Each term of the diagonal is the sum of the projector/backprojector along rows [1], i.e the projection/backprojection of an array of ones.
- [1] Jens Gregor and Thomas Benson,
Computational Analysis and Improvement of SIRT, IEEE transactions on medical imaging, vol. 27, no. 7, 2008
- class TV(sino_shape, slice_shape=None, axis_position=None, angles=None, ctx=None, devicetype='all', platformid=None, deviceid=None, profile=False)[source]¶
A class for reconstruction with Total Variation regularization using the Chambolle-Pock TV reconstruction algorithm.
- Parameters
sino_shape – shape of the sinogram. The sinogram is in the format (n_b, n_a) where n_b is the number of detector bins and n_a is the number of angles.
slice_shape – Optional, shape of the reconstructed slice. By default, it is a square slice where the dimension is the “x dimension” of the sinogram (number of bins).
axis_position – Optional, axis position. Default is (shape[1]-1)/2.0.
angles – Optional, a list of custom angles in radian.
ctx – actual working context, left to None for automatic initialization from device type or platformid/deviceid
devicetype – type of device, can be “CPU”, “GPU”, “ACC” or “ALL”
platformid – integer with the platform_identifier, as given by clinfo
deviceid – Integer with the device identifier, as given by clinfo
profile – switch on profiling to be able to profile at the kernel level, store profiling elements (makes code slightly slower)
Warning
This is a beta version of the Chambolle-Pock TV algorithm. Reconstruction fails for at least on CPU (Xeon E3-1245 v5) using the AMD opencl implementation.
- compute_preconditioners()[source]¶
Create a diagonal preconditioner for the projection and backprojection operator. Each term of the diagonal is the sum of the projector/backprojector along rows [2], i.e the projection/backprojection of an array of ones.
- [2] T. Pock, A. Chambolle,
Diagonal preconditioning for first order primal-dual algorithms in convex optimization, International Conference on Computer Vision, 2011