AGILE: GPU Image Reconstruction Library

AGILE: GPU Image Reconstruction Library

Florian Knoll

AGILE (Environment for Linear and non-linear Image reconstruction using GPU Acceleration) is an open source library for GPU accelerated reconstruction problems in medical imaging. It originally included reconstruction code for both MRI (Figure 1) and Fluorescence Tomography, as well as general purpose linear algebra routines. The current version that is made available for download here only includes the MR reconstruction part to facilitate easier installation. If you are interested in the complete version of the library, just contact us. (We have also made a MATLAB version available for download.)

Figure 1: Reconstruction of undersampled radial data from 48, and 32 radial spokes (256x256 matrix). Conventional regridding reconstruction (Left column) and AGILE iterative TGV image reconstruction (right column). The corresponding reconstruction times on an NVIDIA GTX 480 were 8.76s (48 spokes) and 6.36s (32 spokes).

Contributors (sorted alphabetically):

  • Kristian Bredies (University of Graz)
  • Gerald Buchgraber (Graz University of Technology, now at Datenkraft IT-Consulting)
  • Manuel Freiberger (Graz University of Technology, now at Anton Paar)
  • Andreas Huber (Graz University of Technology)
  • Florian Knoll

Version History:

1.2 (14.03.2013): Extracted MR reconstruction part. Changed support to CUDA 5.0 (CUDA helper functions instead of SDK functions)
1.11 (13.04.2012): Minor changes in documentation and readme.
1.1 (16.01.2012): Included CPU reference implementation for TGV.
1.0 (28.07.2011): First release of AGILE.

Related Publication:

If you use this library or the provided data in your publications, please cite:

Freiberger, M.; Knoll, F.; Bredies, K.; Scharfetter, H.; Stollberger, R.: The AGILE library for image reconstruction in biomedical sciences using graphics card hardware acceleration: Computing in science & engineering 15:34-44 (2013).

For any questions, comments or contributions, please contact Florian Knoll (


PLEASE NOTE: The software available on this page is provided free of charge and comes without any warranty. CAI²R and the NYU School of Medicine do not take any liability for problems or damage of any kind resulting from the use of the files provided. Operation of the software is solely at the user's own risk. The software developments provided are not medical products and must not be used for making diagnostic decisions.

The software is provided for non-commercial, academic use only. Usage or distribution of the software for commercial purpose is prohibited. All rights belong to the author (Florian Knoll) and the NYU School of Medicine. If you use the software for academic work, please give credit to the author in publications and cite the related publications.

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Philanthropic Support

We gratefully acknowledge generous support for radiology research at NYU Langone Health from:
• The Big George Foundation
• Bernard and Irene Schwartz

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