Wadhwa, P;
Thielemans, K;
Efthimiou, N;
Bertolli, O;
Emond, E;
Thomas, BA;
Tohme, M;
... Tsoumpas, C; + view all
(2019)
Implementation of Image Reconstruction for GE SIGNA PET/MR PET Data in the STIR Library.
In:
2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC).
IEEE: Sydney, Australia.
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Abstract
Software for Tomographic Image Reconstruction (STIR: http://stir.sf.net) is an open source C++ library available for reconstruction of emission tomography data. This work aims at the incorporation of the GE SIGNA PET/MR scanner in STIR and enables PET image reconstruction with data corrections. The data extracted from the scanner after an acquisition includes a list of raw data files (emission, normalisation, geometric and well counter calibration (wcc) factors), magnetic resonance attenuation correction (MRAC) images and the scanner-based reconstructions. The listmode (LM) file stores a list of 'prompt' events and the singles per crystal per second. MRAC images from the scanner are used for attenuation correction. The modifications to STIR that allow accurate histogramming of this LM data in the same sinogram organisation as the scanner are also described. This allows reconstruction of acquisition data with all data corrections using STIR, and independent of any software supplied by the manufacturer. The implementations were validated by comparing the histogrammed data, data corrections and final reconstruction using the ordered subset expectation maximisation (OSEM) algorithm with the equivalents from the GE-toolbox, supplied by the manufacturer for the scanner. There is no difference in the histogrammed counts whereas an overall relative difference of 6.7 × 10 -8 % and from 0.01% to 0.86% is seen in the normalisation and randoms correction sinograms respectively. The STIR reconstructed images have similar resolution and quantification but have some residual differences due to wcc factors, decay and deadtime corrections, as well as the offset between PET and MR gantries that will be addressed in future work. This work will enable the use of all current and future STIR algorithms, including penalized image reconstruction, motion correction and direct parametric image estimation, on data from GE SIGNA PET/MR scanners.
| Type: | Proceedings paper |
|---|---|
| Title: | Implementation of Image Reconstruction for GE SIGNA PET/MR PET Data in the STIR Library |
| Event: | 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1109/NSSMIC.2018.8824341 |
| Publisher version: | https://doi.org/10.1109/NSSMIC.2018.8824341 |
| 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. |
| 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/10087274 |
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