Tomo Phantom Artifacts

Description

A plugin to add artifacts to real or generated synthetic data using TomoPhantom

Parameters
in_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description: Default input dataset names.
    default: "['synth_proj_data']"

out_datasets:
    visibility: datasets
    dtype: "[list[],list[str]]"
    description: Default out dataset names.
    default: "['synth_proj_data_artifacts']"

pattern:
    visibility: advanced
    dtype: str
    description: Pattern to apply this to.
    default: SINOGRAM

artifacts_noise_type:
    visibility: intermediate
    dtype: str
    description: Set the noise type, Poisson or Gaussian.
    default: Poisson

artifacts_noise_amplitude:
    visibility: intermediate
    dtype: float
    description: Define the amplitude of noise.
    default: "100000"
    dependency: artifacts_noise_type

datashifts_maxamplitude_pixel:
    visibility: advanced
    dtype: "[None,int]"
    description: Incorporate misalignment into projections (in pixels), requires PROJECTION pattern.
    default: None

datashifts_maxamplitude_subpixel:
    visibility: advanced
    dtype: "[None,float]"
    description: Incorporate misalignment into projections (in subpixel resolution), requires PROJECTION pattern.
    default: None

artifacts_zingers_percentage:
    visibility: intermediate
    dtype: "[None,float]"
    description: Add broken pixels to projections, a percent from total pixels number
    default: None

artifacts_zingers_modulus:
    visibility: advanced
    dtype: int
    description: modulus to control the amount of 4/6 pixel clusters (zingers) to be added
    default: "10"
    dependency: artifacts_zingers_percentage

artifacts_stripes_percentage:
    visibility: intermediate
    dtype: "[None,float]"
    description: The amount of stripes in the data (percent-wise), applied to SINOGRAM data.
    default: None

artifacts_stripes_maxthickness:
    visibility: advanced
    dtype: float
    description: Defines the maximal thickness of a stripe.
    default: "3.0"
    dependency: artifacts_stripes_percentage

artifacts_stripes_intensity:
    visibility: advanced
    dtype: float
    description: To incorporate the change of intensity in the stripe.
    default: "0.3"
    dependency: artifacts_stripes_percentage

artifacts_stripes_type:
    visibility: advanced
    dtype: str
    options: "['full', 'partial']"
    description: Set the stripe type to full or partial.
    default: full
    dependency: artifacts_stripes_percentage

artifacts_stripes_variability:
    visibility: advanced
    dtype: float
    description: The intensity variability of a stripe.
    default: "0.007"
    dependency: artifacts_stripes_percentage

artifacts_pve:
    visibility: advanced
    dtype: "[None,int]"
    description: the strength of partial volume effect, linked to the               limited resolution of the detector, try 1 or 3
    default: None

artifacts_fresnel_distance:
    visibility: advanced
    dtype: "[None,int]"
    description: observation distance for fresnel propagator, e.g. 20
    default: None

artifacts_fresnel_scale_factor:
    visibility: advanced
    dtype: float
    description: fresnel propagator sacaling
    default: "10"
    dependency: artifacts_fresnel_distance

artifacts_fresnel_wavelenght:
    visibility: advanced
    dtype: float
    description: fresnel propagator wavelength
    default: "0.003"
    dependency: artifacts_fresnel_distance

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
Citations

TomoPhantom, a software package to generate 2D-4D analytical phantoms for CT image reconstruction algorithm benchmarks by Kazantsev, Daniil et al.

Bibtex

@article{kazantsev2018tomophantom,
  title={TomoPhantom, a software package to generate 2D-4D analytical phantoms for CT image reconstruction algorithm benchmarks},
  author={Kazantsev, Daniil and Pickalov, Valery and Nagella, Srikanth and Pasca, Edoardo and Withers, Philip J},
  journal={SoftwareX},
  volume={7},
  pages={150--155},
  year={2018},
  publisher={Elsevier}
}

Endnote

%0 Journal Article
%T TomoPhantom, a software package to generate 2D-4D analytical phantoms for CT image reconstruction algorithm benchmarks
%A Kazantsev, Daniil
%A Pickalov, Valery
%A Nagella, Srikanth
%A Pasca, Edoardo
%A Withers, Philip J
%J SoftwareX
%V 7
%P 150-155
%@ 2352-7110
%D 2018
%I Elsevier
API
class TomoPhantomArtifacts[source]
get_max_frames()[source]
nInput_datasets()[source]

The number of datasets required as input to the plugin

Returns

Number of input datasets

nOutput_datasets()[source]

The number of datasets created by the plugin

Returns

Number of output datasets

process_frames(data)[source]

This method is called after the plugin has been created by the pipeline framework and forms the main processing step

Parameters

data (list(np.array)) – A list of numpy arrays for each input dataset.

setup()[source]

This method is first to be called after the plugin has been created. It determines input/output datasets and plugin specific dataset information such as the pattern (e.g. sinogram/projection).