reconstruct.rec_astra

Functions:

recon_astra_fbp(im, angles, method, filter_type)	Reconstruct the input sinogram by using the FBP implemented in ASTRA toolbox.
recon_astra_iterative(im, angles, method, ...)	Reconstruct the input sinogram by using one of the iterative algorithms implemented in ASTRA toolbox.

stp_core.reconstruct.rec_astra.recon_astra_fbp(im, angles, method, filter_type)

Reconstruct the input sinogram by using the FBP implemented in ASTRA toolbox.

Parameters:

im (array_like) – Image data (sinogram) as numpy array.

angles : double

Value in radians representing the number of angles of the sinogram.

method : string

A string with either “FBP” or “FBP_CUDA”.

filter_type : string

The available options are “ram-lak”, “shepp-logan”, “cosine”, “hamming”, “hann”, “tukey”, “lanczos”, “triangular”, “gaussian”, “barlett-hann”, “blackman”, “nuttall”, “blackman-harris”, “blackman-nuttall”, “flat-top”, “kaiser”, “parzen”.

stp_core.reconstruct.rec_astra.recon_astra_iterative(im, angles, method, iterations, zerone_mode)

Reconstruct the input sinogram by using one of the iterative algorithms implemented in ASTRA toolbox.

Parameters:

im (array_like) – Image data (sinogram) as numpy array.

angles : double

Value in radians representing the number of angles of the sinogram.

method : string

A string with e.g “SIRT” or “SIRT_CUDA” (see ASTRA documentation)

iterations : int

Number of iterations for the algebraic technique

zerone_mode : bool

True if the input sinogram has been rescaled to the [0,1] range (therefore positivity constraints are applied)