Useful links

Here is a collection of links to various potentially useful resources such as software or datasets. These are, mainly, open-source. This list will be, hopefully, updated over time.

Simulation software

• Geant4: https://geant4.web.cern.ch/

• Particle physics simulator

• GATE: http://www.opengatecollaboration.org/

• Geant4-based simulation toolkit for PET, SPECT, CT, optimal imaging (bioluminescence and fluorescence) and radiotherapy

• Not recommended for CBCT simulations

• SIMIND: https://simind.blogg.lu.se/

• Monte Carlo simulation toolkit for SPECT

• Easier to use than GATE but lacks more advanced features

• MCGPU: https://github.com/DIDSR/MCGPU

• GPU(CUDA)-based Monte Carlo simulation toolkit for CT imaging

• Mammography and PET simulators also available

• GGEMS: https://github.com/GGEMS/ggems

• Geant4-based GPU(OpenCL)-based Monte Carlo simulation toolkit for CT imaging

• Can be unreliable with higher-dimensional scanners

• DukeSim: https://cvit.duke.edu/resource/dukesim-v1-2/

• GPU(CUDA)-based simulator for CT

• Not open-source!

• Not Monte Carlo!

• CTSim: http://ctsim.org/

• CT simulation toolkit

• Doesn’t seem to be maintained anymore

• ValoMC: https://inverselight.github.io/ValoMC/

• Open source Monte Carlo code for simulation the passage of visible and near infrared range photons through a medium

• MATLAB only

• MRiLab: https://leoliuf.github.io/MRiLab/

• MRI simulator

• Fastcat: https://github.com/jerichooconnell/fastcat

• Analytical CBCT simulator for Python

• CTlab: https://github.com/MIPT-Oulu/CTlab

• CTlab is virtually implemented medical imaging device, which can be widely used in computed tomography training for all professionals who use radiation in their work

Reconstruction software

• OMEGA: https://github.com/villekf/OMEGA

• This software, in case someone ends up here through some other means

• Open-source multi-dimensional tomographic reconstruction software

• HELMET, High-dimensional Kalman filter toolbox: https://github.com/villekf/HELMET

• My own Kalman filter toolbox for MATLAB for linear dynamic problems, especially higher-dimensional ones

• STIR, Software for Tomographic Image Reconstruction: https://stir.sourceforge.net/

• C++-based reconstruction software for PET and SPECT

• TIGRE, Tomographic Iterative GPU-based Reconstruction Toolbox: https://github.com/CERN/TIGRE/

• MATLAB and Python based GPU (CUDA) capable reconstruction software for CT imaging

• CASToR, Customizable and Advanced Software for Tomographic Reconstruction: https://castor-project.org/

• C++-based reconstruction software for PET, SPECT and CT

• PyTomography: https://github.com/qurit/PyTomography

• Python-based tomography reconstruction toolkit for PET and SPECT

• ASTRA: https://astra-toolbox.com/

• MATLAB and Python toolbox of high-performance GPU primitives for 2D and 3D tomography

• TIRIUS: https://sourceforge.net/projects/tirius/

• Tomography reconstruction toolkit

• Doesn’t seem to be maintained anymore

• J-PET Analysis Framework: https://github.com/JPETTomography/j-pet-framework

• Reconstruction and analysis toolkit for PET

• QSPECT: http://www.qspect-project.com/index_e.html

• SPECT reconstruction toolkit

• Doesn’t seem to be maintained anymore

• MIRT, Michigan Image Reconstruction Toolkit: https://github.com/JeffFessler/mirt

• Tomographic image reconstruction toolkit, especially for medical imaging (emission, transmission, MRI)

• Julia version: https://github.com/JeffFessler/MIRT.jl

• NiftyRec: https://github.com/TomographyLab/NiftyRec

• GPU(CUDA)-based image reconstruction toolkit for tomographic imaging

• MR-Hub: https://ismrm.github.io/mrhub/

• Collection of various open-source MRI software, including reconstruction software

• RTK: https://github.com/RTKConsortium/RTK

• The Reconstruction Toolkit

• ODL: https://github.com/odlgroup/odl

• Operator Discretization Library for Python

• LEAP: https://github.com/LLNL/LEAP

• LivermorE AI Projector for Computed Tomography

• HelTomo: https://github.com/Diagonalizable/HelTomo

• CT reconstruction toolkit for MATLAB based on ASTRA and Spot Linear-Operator toolboxes

• OOEIT: https://github.com/PetriKuusela/OOEIT

• EIT reconstruction and simulation software

• ToMoBAR: https://github.com/dkazanc/ToMoBAR

• TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software

Data analysis software

• AEDES: https://github.com/mjnissi/aedes

• ROI analysis tool for MRI images

• Algotom: https://github.com/algotom/algotom

• Data processing algorithms for tomography

• ROOT: https://root.cern/

• CERN’s data analysis software for particle physics

• CARIMAS: https://carimas.fi/

• Data analysis tool for PET images

• Commercial software

• MR-Hub: https://ismrm.github.io/mrhub/

• Collection of various open-source MRI software, including data analysis software

• ImageJ: https://imagej.net/ij/

• Potentially useful visualization and analysis tool for medical images

• AMIDE: https://amide.sourceforge.net/

• A bit similar to ImageJ, i.e. a visualization and analysis tool for medical images

• Insight Toolkit: https://itk.org/

• Image analysis toolkit for e.g. segmentation and registration

• (X)MedCon: https://xmedcon.sourceforge.io/

• Medical image conversion tool

• 3D Slicer: https://www.slicer.org/

• 3D Slicer is a free, open source software for visualization, processing, segmentation, registration, and analysis of medical, biomedical, and other 3D images and meshes; and planning and navigating image-guided procedures.

Programming and languages

• Julia language: https://julialang.org/

• Modern, Python- and MATLAB-like, language (open-source)

• Flux.jl: https://github.com/FluxML/Flux.jl

• Julia’s machine learning library

• ZLUDA: https://github.com/vosen/ZLUDA

• Run CUDA applications on AMD GPUs

• An alternative fork, based on earlier work: https://github.com/lshqqytiger/ZLUDA

• AMD HIP: https://github.com/ROCm/HIP

• AMD’s version of CUDA

• HIP code can run on both AMD and Nvidia hardware

• Intel OneAPI: https://www.intel.com/content/www/us/en/developer/tools/oneapi/overview.html

• SYCL-based API for parallel architectures, such as GPUs

• ArrayFire: https://github.com/arrayfire/arrayfire

• General-purpose tensor library for parallel architectures

• Supports CPU, OpenCL, CUDA and OneAPI

• EasyCL: https://github.com/hughperkins/EasyCL

• Can make running OpenCL kernels easier

• Kokkos: https://github.com/kokkos/kokkos

• Implements a programming model in C++ for writing applications targeting all major HPC platforms. Supports CUDA, HIP, SYCL, HPX, OpenMP and C++.

Deep learning based denoisers

• ADL: https://github.com/mogvision/ADL

• Adversarial Distortion Learning for Denoising and Distortion Removal

• Low-dose CT denoiser: https://github.com/Ryosaeba8/Medical-Imaging-LOW-DOSE-CT-DENOISING

• Implementation of Low Dose CT Image Denoising Using a Generative Adversarial Network with Wasserstein Distance and Perceptual Loss

• CoreDiff: https://github.com/qgao21/CoreDiff

• Contextual Error-Modulated Generalized Diffusion Model for Low-Dose CT Denoising and Generalization

• DU-GAN: https://github.com/Hzzone/DU-GAN

• Generative Adversarial Networks with Dual-Domain U-Net Based Discriminators for Low-Dose CT Denoising

Datasets

• Finnish Inverse Problems Society datasets: https://zenodo.org/communities/fips/

• Datasets for, for example, CBCT, electrical impedance tomography and PET

• fastMRI dataset: https://fastmri.med.nyu.edu/

• Low dose CT grand challenge dataset: https://www.aapm.org/GrandChallenge/LowDoseCT/

• Stanford University datasets: https://aimi.stanford.edu/shared-datasets

• FAME datasets: https://fameflagship.fi/category/output/data/

• Datasets for, for example, fMRI and EIT