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