SIRF: Synergistic Image Reconstruction Framework

Evgueni Ovtchinnikov; David Atkinson; Christoph Kolbitsch; Benjamin A. Thomas; Ottavia Bertolli; Casper O. da Costa-Luis; Nikolaos Efthimiou; Ronald Fowler; Edoardo Pasca; Palak Wadhwa; Elise Emond; Julian Matthews; Claudia Prieto; Andrew J. Reader; Charalampos Tsoumpas; Martin Turner; Kris Thielemans

doi:10.1109/NSSMIC.2017.8532815

SIRF: Synergistic Image Reconstruction Framework

Evgueni Ovtchinnikov, David Atkinson, Christoph Kolbitsch, Benjamin A. Thomas, Ottavia Bertolli, Casper O. da Costa-Luis, Nikolaos Efthimiou, Ronald Fowler, Edoardo Pasca, Palak Wadhwa, Elise Emond, Julian Matthews, Claudia Prieto, Andrew J. Reader, Charalampos Tsoumpas, Martin Turner, Kris Thielemans^*

^*Corresponding author for this work

Biomedical Engineering Department

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

2 Citations (Scopus)

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, 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.

Original language	English
Title of host publication	2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538622827
ISBN (Print)	9781538622834
DOIs	https://doi.org/10.1109/NSSMIC.2017.8532815
Publication status	Published - Nov 2018
Event	2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Atlanta, United States Duration: 21 Oct 2017 → 28 Oct 2017

Conference

Conference	2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017
Country/Territory	United States
City	Atlanta
Period	21/10/2017 → 28/10/2017

Keywords

Magnetic Resonance Imaging
Positron Emission Tomography
Research Software Engineering
Scientific Programming

Access to Document

10.1109/NSSMIC.2017.8532815

Cite this

Ovtchinnikov, E., Atkinson, D., Kolbitsch, C., Thomas, B. A., Bertolli, O., da Costa-Luis, C. O., Efthimiou, N., Fowler, R., Pasca, E., Wadhwa, P., Emond, E., Matthews, J., Prieto, C., Reader, A. J., Tsoumpas, C., Turner, M., & Thielemans, K. (2018). SIRF: Synergistic Image Reconstruction Framework. In 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings Article 8532815 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2017.8532815

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title = "SIRF: Synergistic Image Reconstruction Framework",

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, 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.",

keywords = "Magnetic Resonance Imaging, Positron Emission Tomography, Research Software Engineering, Scientific Programming",

author = "Evgueni Ovtchinnikov and David Atkinson and Christoph Kolbitsch and Thomas, {Benjamin A.} and Ottavia Bertolli and {da Costa-Luis}, {Casper O.} and Nikolaos Efthimiou and Ronald Fowler and Edoardo Pasca and Palak Wadhwa and Elise Emond and Julian Matthews and Claudia Prieto and Reader, {Andrew J.} and Charalampos Tsoumpas and Martin Turner and Kris Thielemans",

year = "2018",

month = nov,

doi = "10.1109/NSSMIC.2017.8532815",

language = "English",

isbn = "9781538622834",

booktitle = "2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 ; Conference date: 21-10-2017 Through 28-10-2017",

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Ovtchinnikov, E, Atkinson, D, Kolbitsch, C, Thomas, BA, Bertolli, O, da Costa-Luis, CO, Efthimiou, N, Fowler, R, Pasca, E, Wadhwa, P, Emond, E, Matthews, J, Prieto, C , Reader, AJ, Tsoumpas, C, Turner, M & Thielemans, K 2018, SIRF: Synergistic Image Reconstruction Framework. in 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings., 8532815, Institute of Electrical and Electronics Engineers Inc., 2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017, Atlanta, United States, 21/10/2017. https://doi.org/10.1109/NSSMIC.2017.8532815

SIRF: Synergistic Image Reconstruction Framework. / Ovtchinnikov, Evgueni; Atkinson, David; Kolbitsch, Christoph et al.
2017 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2017 - Conference Proceedings. Institute of Electrical and Electronics Engineers Inc., 2018. 8532815.

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-review

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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

PY - 2018/11

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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

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ER -

SIRF: Synergistic Image Reconstruction Framework

Abstract

Conference

Keywords

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2018 CCP PET-MR Bronze Award

Cite this

SIRF: Synergistic Image Reconstruction Framework

Abstract

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Prizes

2018 CCP PET-MR Bronze Award

Cite this