Awesome Computed Tomography 中文 Star on GitHub

Awesome Computed Tomography

A curated list of CT reconstruction resources. Every paper link is resolved against Crossref, arXiv or the publisher’s own record, and every URL is rechecked weekly.

Papers
678
Toolkits
60
Datasets
82
Benchmarks
22
Learning
35
Updated
2026-10-30

Learning CT Reconstruction

35 books, courses, tutorials and tools for learning CT reconstruction, and this site's own guides.

ResourceTypeNotes
Guides All guides →
Sparse-View CT Reconstruction: Methods, Datasets and Where to StartGuideA practical guide to sparse-view CT reconstruction: method families compared, open datasets with raw projections, and papers with code to start from.
Low-Dose CT Denoising: Benchmarks, Datasets and ToolkitsGuideLow-dose CT denoising compared: the AAPM/Mayo and LoDoPaB-CT benchmarks, open low-dose datasets, and the toolkits used to simulate dose and reconstruct.
How to Choose a CT Reconstruction DatasetGuideHow to choose a CT reconstruction dataset: projection or image data, fan-beam or cone-beam geometry, measured or simulated scans, and licence, in one table.
Computed Tomography - From Photon Statistics to Modern Cone-Beam CTbookBuzug (2008). The best single bridge from the physics (photon statistics, polychromaticity, detector response) to the reconstruction algorithms.
Computed Tomography - Principles, Design, Artifacts, and Recent AdvancesbookHsieh (3rd ed. 2015, SPIE). Written from inside a CT vendor: system design, dose, artefact taxonomy and clinical correction strategies.
Computed Tomography: Algorithms, Insight, and Just Enough TheorybookHansen, Jørgensen & Lionheart (SIAM, 2021). A modern, hands-on introduction: the mathematics needed to understand reconstruction algorithms, with examples and exercises.
CT Principles and Algorithmsbook庄天戈. The Chinese-language introduction to CT principles and algorithms; widely used as a first course text and the natural entry point for readers who prefer Chinese. The 1992 edition has no publisher page online, so the link is a title search.
Foundations of Image SciencebookBarrett & Myers (2004). The encyclopaedic reference for imaging-system theory — Fourier crosstalk, task-based assessment, and the mathematical basis of iterative reconstruction.
Fundamentals of Computerized Tomography - Image Reconstruction from ProjectionsbookHerman (2nd ed. 2009). Very practical, with explicit algorithms, pseudocode and a careful treatment of sampling and discretisation artefacts.
Image Reconstruction: Algorithms and AnalysisbookFessler's book on statistical image reconstruction, free online chapter by chapter: system models, likelihoods, regularisation and the optimisation behind modern iterative CT.
Industrial CT Technology and Principlesbook张朝宗. The reference for industrial (non-destructive-testing) CT — geometry, sources, detectors and artefact sources on the industrial side, where the medical textbooks stop.
Introduction to the Mathematics of Medical ImagingbookEpstein (SIAM, 2nd ed., 2007). The mathematics behind CT and MRI — Fourier analysis, the Radon transform and its inversion — at an advanced-undergraduate level.
Mathematical Methods in Image ReconstructionbookNatterer & Wübbeling (SIAM, 2001). The algorithmic companion to Natterer's theory book: analytic and iterative methods, sampling and resolution, for parallel, fan and cone-beam geometries.
Medical Image Reconstruction - A Conceptual TutorialbookZeng (2010). Deliberately intuition-first: explains why FBP, iterative and analytic methods behave the way they do, with minimal notation.
Medical Imaging Systems: An Introductory GuidebookMaier, Steidl, Christlein & Hornegger (Springer, 2018). Open access (CC BY 4.0). An introduction to imaging systems, CT included, written with machine learning in mind.
Medical Tomographic Image Reconstruction Simulation Experimentsbook黄力宇. A hands-on Chinese-language lab manual: builds each reconstruction algorithm as a simulation experiment rather than presenting it as theory.
Principles of Computerized Tomographic ImagingbookKak & Slaney (1988). Free online, chapter by chapter as PDFs. The foundation: Radon transform, Fourier-slice theorem, FBP, algebraic reconstruction, fan/cone-beam rebinning. Read chapters 1-3 first.
The Mathematics of Computerized TomographybookNatterer (1986, SIAM reissue). The rigorous inverse-problem treatment — Radon transform on Sobolev spaces, sampling theory, ill-posedness and regularisation.
Principles of Medical Imaging (MIT OCW 22.058)courseFree lecture notes and problem sets covering projection imaging, the Radon transform and reconstruction alongside MRI, ultrasound and PET.
ASTRA Toolbox documentation and tutorialstutorialThe most accessible hands-on entry point: CPU/GPU forward and back projectors, FBP, SART/SIRT, CGLS, with runnable examples for each geometry.
CIL-DemostutorialJupyter notebooks for the Core Imaging Library (CIL): from loading data and FBP to iterative, regularised and limited-data reconstruction on real datasets.
DeepInverse documentationtutorialModern PyTorch-first tutorial track: physics operators, learned denoisers, plug-and-play and diffusion samplers, all with CT examples.
ODL examplestutorialShows how to express a CT problem as operators and functionals, then solve it with proximal methods — the clearest introduction to variational CT.
Radon transform in scikit-imagetutorialTwenty lines of code from a phantom to a sinogram and back with FBP; the fastest way to build intuition before touching a real geometry.
TIGRE demostutorialRunnable GPU demos from analytical FBP through iterative, total-variation and plug-and-play reconstruction, plus a CBCT geometry-calibration walkthrough.
gVXR (gVirtualXray)toolGPU-accelerated X-ray projection simulator supporting arbitrary 3D scenes and polychromatic spectra — useful for building large synthetic projection datasets.
NIST X-Ray Mass Attenuation CoefficientstoolNIST. Authoritative tabulation of mu/rho and mu_en/rho across the periodic table. What XrayPhysics and SpekPy are internally calibrated against — useful whenever you need to sanity-check a polychromatic model.
SimpleITKtoolThe standard I/O and resampling layer for medical volumes; almost every CT dataset in this list is easiest to load through it.
SpekPytoolX-ray tube spectrum simulation (TASMIP/IPEM lineage), distributed as a Python package. Use it to generate realistic polychromatic spectra for beam-hardening experiments.
TomoPhantomtoolFast analytical 2D/3D/4D phantom generation with built-in noise and offset models; convenient for controlled reconstruction studies. Also listed among the toolkits.
X-Ray Data BooklettoolLBNL. The standard quick reference for X-ray properties of the elements — absorption edges, fluorescence yields and scattering cross-sections. The first place to look when a simulation needs a physical constant.
XDesigntoolConfigurable X-ray phantom generation, acquisition simulation and reconstruction benchmarking, built for developing and comparing new tomographic reconstruction methods; analytic solutions keep the simulations fast. Maintained by the Advanced Photon Source.
Awesome 3D Gaussian SplattinglistThe reference 3DGS list. Its tomography-adjacent entries (r2_gaussian, X-Gaussian, X2-Gaussian) are the bridge to Gaussian-splatting CT.
Awesome CT Reconstruction (LoraLinH)listThe best-known prior CT reconstruction list. Useful for cross-checking coverage of the 2020-2024 literature.
Awesome Medical ImaginglistBroader medical image analysis resources: datasets, toolkits and pretrained models that are frequently reused in CT pipelines.
Awesome NeRF and 3DGS for SLAMlistNeural-field literature in the robotics/vision community; the source of the implicit-representation techniques now being adapted to CT.
CT Denoising ReviewlistDedicated to low-dose CT denoising, with an emphasis on the SSinyu/Mayo lineage of methods.
Low-Dose CT Denoising (code collection)listA running collection of low-dose CT denoising code releases, organised by year — convenient for locating the implementation behind a given paper.