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TomoPhantom [1] is a toolbox written in C language to generate customisable 2D-4D phantoms (with a temporal capability) and their analytical projection data for various image processing and machine learning tasks (reconstruction, denoising, deblurring, classification, etc.).

Generate 2D models made of Gaussians, parabolas, ellipses, cones, rectangulars

Generate 3D models and 4D (temporal) extensions of them

Calculate analytical Radon transforms of models and also their numerical projections

Model Gaussian or Poisson noise and some typical acquisition artifacts

Perform 2D-4D reconstructions avoiding 'Inverse Crime'. Reconstruct with implemented FBP and Fourier slice method or using ASTRA-toolbox or TomoPy packages.

• Python (tested ver. 2.7/3.5); Cython OR
• MATLAB
• C compilers: GCC/MinGW/TDM-GCC/Visual Studio

• ASTRA-toolbox
• TomoPy

	conda build conda-recipe --numpy 1.12 --python 3.5
	conda install tomophantom --use-local --force

	run compile_mex_linux.m % to compile CPU modules on linux
	run compile_mex_windows.m % to compile CPU modules on Windows

• Phantom2DLibrary.dat and Phantom3DLibrary.dat are editable text files with parametrised models (2D/3D versions of Shepp-Logan, Defrise, and QRM phantoms are included). The generation of new phantoms is highly encouraged, please submit them through pull requests or via e-mail bellow.
• See MATLAB and Python demos

TomoPhantom is released under Apache License v.2. Note that some demos where 'ASTRA-toolbox' is used are of GPLv3 license and also BSD-3 license for TomoPy package.

• xdesign XDesign is an open-source Python package for generating configurable simulation phantoms for benchmarking tomographic image reconstruction.
• syris Syris (synchrotron radiation imaging simulation) is a framework for simulations of X-ray absorption and phase contrast dynamic imaging experiments, like time-resolved radiography, tomography or laminography.

[1] D. Kazantsev et al. 2018, TomoPhantom, a software package to generate 2D-4D analytical phantoms for CT image reconstruction algorithm benchmarks, Software X, Volume 7, January–June 2018, Pages 150–155

[2] D. Kazantsev, V. Pickalov "New iterative reconstruction methods for fan-beam tomography", IPSE, 2017

• Regularised FISTA-type iterative reconstruction algorithm for X-ray tomographic reconstruction with highly inaccurate measurements
• Joint image reconstruction method with correlative multi-channel prior for X-ray spectral computed tomography

Software related questions/comments please e-mail to Daniil Kazantsev at [email protected]