TY - GEN
T1 - SIRF
T2 - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017
AU - Ovtchinnikov, Evgueni
AU - Atkinson, David
AU - Kolbitsch, Christoph
AU - Thomas, Benjamin A.
AU - Bertolli, Ottavia
AU - Da Costa-Luis, Casper O.
AU - Efthimiou, Nikolaos
AU - Fowler, Ronald
AU - Pasca, Edoardo
AU - Wadhwa, Palak
AU - Emond, Elise
AU - Matthews, Julian
AU - Prieto, Claudia
AU - Reader, Andrew J.
AU - Tsoumpas, Charalampos
AU - Turner, Martin
AU - Thielemans, Kris
N1 - Funding Information:
Manuscript received November 17, 2017. This work was supported by UK EPSRC under Grant EP/M022587/1. E. Ovtchinnikov is with the Visual Analytics and Imaging Systems Group, Rutherford-Appleton Laboratory, Science and Technology Facilities Council, UK (telephone: +44 1235 446668, e-mail: evgueni.ovtchinnikov@stfc.ac.uk). D. Atkinson is with the Centre for Medical Imaging, University College London, UK (telephone: +44 20 3549 5660, e-mail: d.atkinson@ucl.ac.uk). C. Kolbitsch is with the Physikalisch-Technische Bundesanstalt (PTB), Braunschweig and Berlin, Germany (e-mail: christoph.kolbitsch@ptb.de). B. A. Thomas is with the Institute of Nuclear Medicine, University College London, UK (e-mail: b.a.thomas@ucl.ac.uk). O. Bertolli is with the Institute of Nuclear Medicine, University College London, UK (e-mail: ottavia.bertolli.13@ucl.ac.uk). C. da Costa-Luis is with the School of Biomedical Engineering & Imaging Sciences, King’s College London, UK (e-mail: casper.dcl@kcl.ac.uk). N. Efthimiou is with the Institute of Nuclear Medicine, University College London and School of Biological, Biomedical and Environmental Sciences, University of Hull, UK (e-mail: N.Efthymiou@hull.ac.uk). R. Fowler is with the Visual Analytics and Imaging Systems Group, Rutherford-Appleton Laboratory, Science and Technology Facilities Council, UK (telephone: +44 1235 445243, e-mail: ronald.fowler@stfc.ac.uk). E. Pasca is with the Visual Analytics and Imaging Systems Group, Rutherford-Appleton Laboratory, Science and Technology Facilities Council, UK (telephone: +44 1235 445660, e-mail: edoardo.pasca@stfc.ac.uk). P. Wadhwa is with the Division of Biomedical Imaging, University of Leeds and Imanova Ltd, UK (e-mail: p.wadhwa@leeds.ac.uk). E. Emond is with the Institute of Nuclear Medicine, University College London, UK (e-mail: elise.emond.16@ucl.ac.uk). J. Matthews is with the Division of Informatics, Imaging and Data Sciences, MAHSC University of Manchester, UK (telephone: +44 161 275 0024, e-mail: Julian.Matthews@manchester.ac.uk). C. Prieto is with the Department of Biomedical Engineering, King’s College London, UK (e-mail: claudia.prieto@kcl.ac.uk). A. J. Reader is with the School of Biomedical Engineering & Imaging Sciences , King’s College London, UK (e-mail: andrew.reader@kcl.ac.uk). C. Tsoumpas is with the Division of Biomedical Imaging, University of Leeds and Imanova Ltd, UK (telephone: +44 113 343 8312, e-mail: c.tsoumpas@leeds.ac.uk). M. Turner is with the Visual Analytics and Imaging Systems Group, Rutherford-Appleton Laboratory, Science and Technology Facilities Council, UK (e-mail: martin.turner@stfc.ac.uk). K. Thielemans (corresponding author) is with the Institute of Nuclear Medicine, University College London, UK (e-mail: k.thielemans@ucl.ac.uk).
Publisher Copyright:
© 2017 IEEE.
PY - 2018/11/12
Y1 - 2018/11/12
N2 - 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, andthe search for ways to improve accuracy of the tomographicreconstruction via synergy of the two imaging techniques is an active areaof 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 dataformat exchange is being negotiated with the manufacturers.
AB - 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, andthe search for ways to improve accuracy of the tomographicreconstruction via synergy of the two imaging techniques is an active areaof 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 dataformat exchange is being negotiated with the manufacturers.
KW - Magnetic Resonance Imaging
KW - Positron Emission Tomography
KW - Research Software Engineering
KW - Scientific Programming
U2 - 10.1109/NSSMIC.2017.8532815
DO - 10.1109/NSSMIC.2017.8532815
M3 - Conference contribution
AN - SCOPUS:85058493508
BT - 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 21 October 2017 through 28 October 2017
ER -