SIRF: Synergistic Image Reconstruction Framework

The combination of positron emission tomography (PET) with magnetic resonance (MR) imaging opens the way to more accurate diagnosis and improved patient management. At present, the data acquired by PET and MR scanners are essentially processed separately, and the search for ways to improve accuracy of the tomographic reconstruction via synergy of the two imaging techniques is an active area of research. The aim of the collaborative computational project on PET and MR (CCP-PETMR), supported by the UK engineering and physical sciences research council (EPSRC), is to accelerate research in synergistic PET-MR image reconstruction by providing an open access software platform for efficient implementation and validation of novel reconstruction algorithms. In this paper, we present the first release of the Synergistic Image Reconstruction Framework (SIRF) software suite from the CCP-PETMR. SIRF provides user-friendly Python and MATLAB interfaces to advanced PET and MR reconstruction packages written in C}$+ \quad +$textbf{{(currently this uses STIR, Software for Tomographic Image Reconstruction, for PET and Gadgetron for MR, but SIRF will be able to link to other reconstruction engines in the future as appropriate). The software is capable of reconstructing images from real scanner data. Both of the available integrated clinical PET-MR systems (Siemens and GE) are being targeted, and a suitable data format exchange is being negotiated with the manufacturers.