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SIRF: Synergistic Image Reconstruction Framework

Ovtchinnikov, E; Atkinson, D; Kolbitsch, C; Thomas, BA; Bertolli, O; Da Costa-Luis, CO; Efthimiou, N; ... Thielemans, K; + view all (2018) SIRF: Synergistic Image Reconstruction Framework. In: Proceedings of the 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE: Atlanta, GA, USA. Green open access

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Abstract

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++ (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.

Type: Proceedings paper
Title: SIRF: Synergistic Image Reconstruction Framework
Event: 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)
Location: Atlanta, GA
Dates: 21 October 2017 - 28 October 2017
ISBN-13: 978-1-5386-2282-7
Open access status: An open access version is available from UCL Discovery
DOI: 10.1109/NSSMIC.2017.8532815
Publisher version: https://doi.org/10.1109/NSSMIC.2017.8532815
Language: English
Additional information: This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions.
Keywords: Positron Emission Tomography, Magnetic Resonance Imaging, Research Software Engineering, Scientific Programming
UCL classification: UCL
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Medical Sciences > Div of Medicine > Department of Imaging
URI: https://discovery.ucl.ac.uk/id/eprint/10096582
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