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
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
GPU(CUDA)-based Monte Carlo simulation toolkit for CT imaging
Mammography and PET simulators also available
Geant4-based GPU(OpenCL)-based Monte Carlo simulation toolkit for CT imaging
Can be unreliable with higher-dimensional scanners
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
Open source Monte Carlo code for simulation the passage of visible and near infrared range photons through a medium
MATLAB only
MRI simulator
Analytical CBCT simulator for Python
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
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
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
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
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
The Reconstruction Toolkit
Operator Discretization Library for Python
LivermorE AI Projector for Computed Tomography
CT reconstruction toolkit for MATLAB based on ASTRA and Spot Linear-Operator toolboxes
EIT reconstruction and simulation software
ToMoBAR: https://github.com/dkazanc/ToMoBAR
TOmographic MOdel-BAsed Reconstruction (ToMoBAR) software
Data analysis software
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
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
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
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
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
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