Astra Recon Gpu¶

Description¶

A Plugin to run the astra reconstruction

Parameters

in_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description:
        summary: A list of the dataset(s) to process.
        verbose: A list of strings, where each string gives the name of a dataset that was either specified by a loader plugin or created as output to a previous plugin.  The length of the list is the number of input datasets requested by the plugin.  If there is only one dataset and the list is left empty it will default to that dataset.
    default: "[]"

out_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description:
        summary: A list of the dataset(s) to create.
        verbose: A list of strings, where each string is a name to be assigned to a dataset output by the plugin. If there is only one input dataset and one output dataset and the list is left empty, the output will take the name of the input dataset. The length of the list is the number of output datasets created by the plugin.
    default: "[]"

centre_of_rotation:
    visibility: basic
    dtype: "[float, str, dict{int:float}]"
    description: Centre of rotation to use for the reconstruction.
    default: "0.0"
    example: It could be a fixed value, a dictionary of (sinogram number, value) pairs for a polynomial fit of degree 1, or a dataset name.

init_vol:
    visibility: intermediate
    dtype: "[None, str]"
    description: Dataset to use as volume initialiser (does not currently work with preview)
    default: None
    example: "Type the name of the initialised dataset e.g. ['tomo']"

log:
    visibility: intermediate
    dtype: bool
    description:
        summary: Option to take the log of the data before reconstruction.
        verbose: Should be set to false if you use PaganinFilter
    default: "True"
    example: Set to True to take the log of the data before reconstruction.

preview:
    visibility: intermediate
    dtype: preview
    description: A slice list of required frames.
    default: "[]"

force_zero:
    visibility: intermediate
    dtype: "[list[float,float],list[None,None]]"
    description: Set any values in the reconstructed image outside of this range to zero.
    default: "['None', 'None']"
    example: "[0, 1]"

ratio:
    visibility: intermediate
    dtype: "[float, list[float, float]]"
    description: Ratio of the masks diameter in pixels to the smallest edge size along given axis. If a list of two floats is given, the second value is used to fill up the area outside the mask.
    default: "0.95"

log_func:
    visibility: advanced
    dtype: str
    description: Override the default log function with a numpy statement
    default: np.nan_to_num(-np.log(sino))

vol_shape:
    visibility: intermediate
    dtype: "[str, int]"
    description:
        summary: Override the size of the reconstruction volume with an integer value.
        verbose: When fixed, you get the dimension of the horizontal detector or you can specify any reconstruction size you like with an integer.
    default: fixed

n_iterations:
    visibility: basic
    dtype: int
    description: Number of iterations to perform
    default: "1"
    dependency:
        algorithm:
            SIRT_CUDA
            SART_CUDA
            CGLS_CUDA
            BP3D_CUDA
            CGLS3D_CUDA
            SIRT3D_CUDA

outer_pad:
    visibility: intermediate
    dtype: "[bool, float]"
    description: Pad the sinogram width to fill the reconstructed volume for asthetic purposes. Choose from True (defaults to sqrt(2)), False or float <= 2.1.
    warning: This will increase the size of the data and the time to compute the reconstruction. Only available for selected algorithms and will be ignored otherwise.
    default: "False"
    dependency:
        algorithm:
            FBP_CUDA
            BP_CUDA

centre_pad:
    visibility: intermediate
    dtype: "[bool, float]"
    description: Pad the sinogram to centre it in order to fill the reconstructed volume ROI for asthetic purposes.
    warning: This will significantly increase the size of the data and the time to compute the reconstruction)
    default: "False"
    dependency:
        algorithm:
            FBP_CUDA
            BP_CUDA

res_norm:
    visibility: basic
    dtype: "[int,bool]"
    description: Output the residual norm at each iteration (Error in the solution)
    default: "False"
    dependency:
        algorithm:
            SIRT_CUDA
            SART_CUDA
            CGLS_CUDA
            CGLS3D_CUDA
            SIRT3D_CUDA

algorithm:
    visibility: basic
    dtype: str
    options: "['FBP_CUDA', 'SIRT_CUDA', 'SART_CUDA', 'CGLS_CUDA', 'BP_CUDA', 'BP3D_CUDA', 'FBP3D_CUDA', 'SIRT3D_CUDA', 'CGLS3D_CUDA']"
    description:
        summary: Reconstruction type
        options:
            FBP_CUDA: Filtered Backprojection Method
            SIRT_CUDA: Simultaneous Iterative Reconstruction Technique
            SART_CUDA: Simultaneous Algebraic Reconstruction Technique
            CGLS_CUDA: Conjugate Gradient Least Squares
            BP_CUDA: Backward Projection
            BP3D_CUDA: Backward Projection 3D
            FBP3D_CUDA: Filtered Backprojection Method 3D
            SIRT3D_CUDA: Simultaneous Iterative Reconstruction Technique 3D
            CGLS3D_CUDA: Conjugate Gradient Least Squares 3D
    default: FBP_CUDA

FBP_filter:
    visibility: intermediate
    dtype: str
    options: "['none', 'ram-lak', 'shepp-logan', 'cosine', 'hamming', 'hann', 'tukey', 'lanczos', 'triangular', 'gaussian', 'barlett-hann', 'blackman', 'nuttall', 'blackman-harris', 'blackman-nuttall', 'flat-top', 'kaiser', 'parzen']"
    description:
        summary: The FBP reconstruction filter type
        options:
            none: No filtering
            ram-lak: Ram-Lak or ramp filter
            shepp-logan: Multiplies the Ram-Lak filter by a sinc function
            cosine: Multiplies the Ram-Lak filter by a cosine function
            hamming: Multiplies the Ram-Lak filter by a hamming window
            hann: Multiplies the Ram-Lak filter by a hann window
            tukey: None
            lanczos: None
            triangular: None
            gaussian: None
            barlett-hann: None
            blackman: None
            nuttall: None
            blackman-harris: None
            blackman-nuttall: None
            flat-top: None
            kaiser: None
            parzen: None
    default: ram-lak
    dependency:
        algorithm:
            FBP_CUDA

Key

visibility: The visibility level of the parameter
dtype: The type of data
description: A short explanation of the parameter
default: The default value
options: A list of permitted values
dependency: The name of the parameter and value which this parameter depends upon
range: A guide for the range of the parameter