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TIGRE is an open-source toolbox for fast and accurate 3D tomographicreconstruction for any geometry. Its focus is on iterative algorithmsfor improved image quality that have all been optimized to run on GPUs(including multi-GPUs) for improved speed. It combines the higher levelabstraction of MATLAB or Python with the performance of CUDA at a lower level in order to makeit both fast and easy to use.

TIGRE is free to download and distribute: use it, modify it, add to it,share it. Our aim is to provide a wide range of easy-to-use algorithmsfor the tomographic community "off the shelf". We would like to build astronger bridge between algorithm developers and imagingresearchers/clinicians by encouraging and supporting contributions fromboth sides into TIGRE.

TIGRE remains under development as we are still adding new features(e.g., motion compensation). If you have any request for a specificapplication, do not hesitate tocontact us or open adiscussion thread!

• TIGRE features

• Installation instructions

• Getting started

• FAQ

• Further reading

• Contact

• Licensing

TIGRE is a GPU-based CT reconstruction software repository that contains a wide variety of iterative algorithms.

• MATLAB andPython libraries for high-performance x-ray absorption tomographic reconstruction.

• State-of-the-art implementations of projection and backprojection operations onGPUs (includingmulti-GPUs), with a simple interface using higher level languages to facilitate the development of new methods.

• Flexible CT geometry: Cone Beam, Parallel Beam, Digital Tomosynthesis, C-arm CT, and any other geometry. Geometric parameters are defined per projection, not per scan.

• A wide range of reconstruction algorithms for CT.

  • Filtered backprojection (FBP,FDK) and variations (different filters, Parker weights, ...)

  • Iterative algorithms

    • Gradient-based algorithms (SART, OS-SART, SIRT, ASD-POCS, OS-ASD-POCS, B-ASD-POCS-β, PCSD, AwPCSD, Aw-ASD-POCS) with multiple tuning parameters (Nesterov acceleration, initialization, parameter reduction, ...)

    • Krylov subspace algorithms (CGLS, LSQR, hybrid LSQR, LSMR, IRN-TV-CGLS, hybrid-fLSQR-TV, AB/BA-GMRES)

    • Statistical reconstruction (MLEM)

    • Variational methods (FISTA, SART-TV)

• TV denoising for 3D images.

• Basic image loading functionality.

• A variety of plotting functions.

• Image quality metrics.

• Nikon and Varian and Phillips (DICOM) scanner data loaders.

MATLAB and Python builds are both fully supported.

• Installation instructions and requirements for MATLAB.

• Installation instructions and requirements for Python.

Advanced, not required to run TIGRE, will change the source code. Only do if performance is critical.

• Tune TIGRE for machine. Tricks to slightly speed up the code

Once TIGRE in installed, we strongly suggest you have a look at the Demos folder for each of the languages,MATLAB orPython.

There is no documentation page for TIGRE (other than the function documentation), but all features are descrived and demonstrated with working code in the demos. They also serve as a tutorial of each feature. We strongly recommend you explore the first 4 demos for the basic TIGRE functionality, and look at the following ones for more advanced geometry or reconstruction functions.

For answers to frequently asked questionsclick here.

If you have new question not answered in the FAQ, pleasecontact us, join theSlack group or open adiscussion thread.

To see a gallery of images of different CT modalities reconstructed using TIGREclick here.

If you want more information on TIGRE and its algorithms,click here.

Contact the authors directly at:

tigre.toolbox@gmail.com orander.biguri@gmail.com

for any questions/comments or if you want to be added to the mailing list or the Slack team.

The Slack team is a good place for chatting about development and questions about TIGRE. Please send an email to the authors and you will receive an invitation.

The creation of TIGRE was supported by the University of Bath and CERN. It is released under the BSD License, meaning you can use and modify the software freely. However, youmust cite the original authors.For more information readthe license file or theBSD License Definition.

If you use TIGRE, please reference the following papers:

TIGRE: A MATLAB-GPU toolbox for CBCT image reconstructionAnder Biguri, Manjit Dosanjh, Steven Hancock and Manuchehr SoleimaniBiomedical Physics & Engineering Express, Volume 2, Number 5Read the article (open access)

And especially if you use images bigger than 512³ or multiple GPUs

Arbitrarily large iterative tomographic reconstruction on multiple GPUs using the TIGRE toolboxAnder Biguri, Reuben Lindroos, Robert Bryll, Hossein Towsyfyan, Hans Deyhle, Ibrahim El khalil Harrane, RichardBoardman, Mark Mavrogordato, Manjit Dosanjh, Steven Hancock, Thomas BlumensathJournal of Parallel and Distributed ComputingRead the article,Preprint

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