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).
-