SIRF 3.4.0 released

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SIRF 3.4.0 released

May 24, 2023

Dear All,

We are delighted to announce the release of our Synergistic Image Reconstruction Framework (SIRF) and associated projects Version 3.4.0.

New features in SIRF include:

  • MR:
    • Support for spiral trajectories that are pre-computed by the user.
    • Support for Gadgetron master of November 2022.
    • DICOM output for images.
    • Image processing Gadgetron chains.
    • C++17.
    • Support for STIR 5.1.
    • Support for Pinhole SPECT via the PinholeSPECTUBMatrix acquisition model if STIR 5.1 is used.
    • Extra optional argument tof_mash_factor for AcquisitionData constructor from scanner data if STIR version used supports TOF.
    • C++: PETAcquisitionData and derived classes renamed to STIRAcquisitionData* as STIR now supports SPECT in addition to PET modality.
  • Python:
    • Switched to pytest for testing.
  • Other:
    • Extraction of subsets of STIR and Gadgetron acquisition data implemented.
  • The SIRF-SuperBuild has been updated to use more recent versions of many packages, including ISMRMRD, STIR and CIL. The docker builds and VM now use Ubuntu 22.04 and Jupyterlab.

    We have also performed various small updates to the SIRF-Exercises, including compatibility with Jupyterlab.

    A more complete list of changes can be found at, and For further information and links, including links to the VM and Docker builds, please visit

    Please note that as we changed the VM to use Ubuntu 22.04, upgrading an existing VM via the usual procedure will likely fail. The following untested procedure might work: upgrade the OS on your VM to 22.04 first, and then do
    rm -rf ~/devel/buildVM -s

    For those who want to build the software natively, we supply a CMake SuperBuild which should work on Linux and Mac (native installation on Windows works now for many but not everyone yet unfortunately).

    Please try this new SIRF version out and let us know, by mailing to CCP-SYNERBI-USERS@JISCMAIL.AC.UK , whether it worked for you and provide feedback.

    We’re taking the opportunity to thank our many contributors for continuing to improve SIRF and its dependencies. In particular many thanks to Matthew Strugari for adding the pinhole SPECT support to STIR and SIRF via one of our funded exchange visits. Do join us for our next steps forward!

    Our Best Regards,

    On behalf of the CCP SyneRBI Developers

    Evgueni Ovtchinnikov
    CCP SyneRBI Project Manager