Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF)

Richard Brown; Benjamin A. Thomas; Alaleh Rashidnasab; Kjell Erlandsson; Evgueni Ovtchinnikov; Edoardo Pasca; Andrew Reader; Julian C. Matthews; Charalampos Tsoumpas; Kris Thielemans

doi:10.1109/NSSMIC.2018.8824568

Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF)

Richard Brown, Benjamin A. Thomas, Alaleh Rashidnasab, Kjell Erlandsson, Evgueni Ovtchinnikov, Edoardo Pasca, Andrew Reader, Julian C. Matthews, Charalampos Tsoumpas, Kris Thielemans

Onderzoeksoutput › Academic › peer review

3 Citaten (Scopus)

Samenvatting

Motion correction has been added to a PET-MR reconstruction tool, SIRF, by incorporating a registration package, NiftyReg. New functionality has been demonstrated in the context of estimating kinetic parameters in the left temporal lobe, comparing direct and indirect reconstructions and evaluating the impact of using motion correction.Principal component analysis was used to detect motion and to determine time frames, while STIR's parametric-OSEM was used to perform the motion-corrected direct parametric reconstruction.It was found that the variance in the left temporal lobe decreased when motion correction was performed, and the same was true of direct reconstructions compared to indirect.With SIRF, the entirety of the demonstrated functionality can be performed from a single Matlab or Python script.

Originele taal-2	English
Titel	2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC)
Uitgeverij	Institute of Electrical and Electronics Engineers Inc.
Aantal pagina's	4
ISBN van elektronische versie	9781538684948
DOI's	https://doi.org/10.1109/NSSMIC.2018.8824568
Status	Published - nov.-2018
Extern gepubliceerd	Ja
Evenement	2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Sydney, Australia Duur: 10-nov.-2018 → 17-nov.-2018

Conference

Conference	2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018
Land/Regio	Australia
Stad	Sydney
Periode	10/11/2018 → 17/11/2018

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Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF)
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Brown, R., Thomas, B. A., Rashidnasab, A., Erlandsson, K., Ovtchinnikov, E., Pasca, E., Reader, A., Matthews, J. C., Tsoumpas, C., & Thielemans, K. (2018). Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF). In 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC) Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/NSSMIC.2018.8824568

@inproceedings{727cc7d55b9f4b27ae08529cdc86a045,

title = "Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF)",

abstract = "Motion correction has been added to a PET-MR reconstruction tool, SIRF, by incorporating a registration package, NiftyReg. New functionality has been demonstrated in the context of estimating kinetic parameters in the left temporal lobe, comparing direct and indirect reconstructions and evaluating the impact of using motion correction.Principal component analysis was used to detect motion and to determine time frames, while STIR's parametric-OSEM was used to perform the motion-corrected direct parametric reconstruction.It was found that the variance in the left temporal lobe decreased when motion correction was performed, and the same was true of direct reconstructions compared to indirect.With SIRF, the entirety of the demonstrated functionality can be performed from a single Matlab or Python script.",

author = "Richard Brown and Thomas, {Benjamin A.} and Alaleh Rashidnasab and Kjell Erlandsson and Evgueni Ovtchinnikov and Edoardo Pasca and Andrew Reader and Matthews, {Julian C.} and Charalampos Tsoumpas and Kris Thielemans",

note = "Funding Information: ACKNOWLEDGEMENT We thank Francesco Fraioli (UCLH) for the clinical data. This work was supported by UK EPSRC under Grants EP/M022587/1 and EP/P022200/1. Funding Information: We thank Francesco Fraioli (UCLH) for the clinical data. This work was supported by UK EPSRC under Grants EP/M022587/1 and EP/P022200/1. Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 ; Conference date: 10-11-2018 Through 17-11-2018",

year = "2018",

month = nov,

doi = "10.1109/NSSMIC.2018.8824568",

language = "English",

booktitle = "2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC)",

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

}

Brown, R, Thomas, BA, Rashidnasab, A, Erlandsson, K, Ovtchinnikov, E, Pasca, E, Reader, A, Matthews, JC, Tsoumpas, C & Thielemans, K 2018, Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF). in 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC). Institute of Electrical and Electronics Engineers Inc., 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018, Sydney, Australia, 10/11/2018. https://doi.org/10.1109/NSSMIC.2018.8824568

Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF). / Brown, Richard; Thomas, Benjamin A.; Rashidnasab, Alaleh et al.

2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC). Institute of Electrical and Electronics Engineers Inc., 2018.

Onderzoeksoutput › Academic › peer review

TY - GEN

T1 - Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF)

AU - Brown, Richard

AU - Thomas, Benjamin A.

AU - Rashidnasab, Alaleh

AU - Erlandsson, Kjell

AU - Ovtchinnikov, Evgueni

AU - Pasca, Edoardo

AU - Reader, Andrew

AU - Matthews, Julian C.

AU - Tsoumpas, Charalampos

AU - Thielemans, Kris

N1 - Funding Information: ACKNOWLEDGEMENT We thank Francesco Fraioli (UCLH) for the clinical data. This work was supported by UK EPSRC under Grants EP/M022587/1 and EP/P022200/1. Funding Information: We thank Francesco Fraioli (UCLH) for the clinical data. This work was supported by UK EPSRC under Grants EP/M022587/1 and EP/P022200/1. Publisher Copyright: © 2018 IEEE.

PY - 2018/11

Y1 - 2018/11

N2 - Motion correction has been added to a PET-MR reconstruction tool, SIRF, by incorporating a registration package, NiftyReg. New functionality has been demonstrated in the context of estimating kinetic parameters in the left temporal lobe, comparing direct and indirect reconstructions and evaluating the impact of using motion correction.Principal component analysis was used to detect motion and to determine time frames, while STIR's parametric-OSEM was used to perform the motion-corrected direct parametric reconstruction.It was found that the variance in the left temporal lobe decreased when motion correction was performed, and the same was true of direct reconstructions compared to indirect.With SIRF, the entirety of the demonstrated functionality can be performed from a single Matlab or Python script.

AB - Motion correction has been added to a PET-MR reconstruction tool, SIRF, by incorporating a registration package, NiftyReg. New functionality has been demonstrated in the context of estimating kinetic parameters in the left temporal lobe, comparing direct and indirect reconstructions and evaluating the impact of using motion correction.Principal component analysis was used to detect motion and to determine time frames, while STIR's parametric-OSEM was used to perform the motion-corrected direct parametric reconstruction.It was found that the variance in the left temporal lobe decreased when motion correction was performed, and the same was true of direct reconstructions compared to indirect.With SIRF, the entirety of the demonstrated functionality can be performed from a single Matlab or Python script.

U2 - 10.1109/NSSMIC.2018.8824568

DO - 10.1109/NSSMIC.2018.8824568

M3 - Conference contribution

AN - SCOPUS:85073104144

BT - 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC)

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018

Y2 - 10 November 2018 through 17 November 2018

ER -

Brown R, Thomas BA, Rashidnasab A, Erlandsson K, Ovtchinnikov E, Pasca E et al. Motion-corrected reconstruction of parametric images from dynamic PET data with the Synergistic Image Reconstruction Framework (SIRF). In 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC). Institute of Electrical and Electronics Engineers Inc. 2018 doi: 10.1109/NSSMIC.2018.8824568