TY - GEN
T1 - Implementation of Image Reconstruction for GE SIGNA PET/MR PET Data in the STIR Library
AU - Wadhwa, Palak
AU - Thielemans, Kris
AU - Efthimiou, Nikos
AU - Bertolli, Ottavia
AU - Emond, Elise
AU - Thomas, Benjamin A.
AU - Tohme, Michel
AU - Wangerin, Kristen A.
AU - Delso, Gaspar
AU - Hallett, William
AU - Gunn, Roger N.
AU - Buckley, David
AU - Tsoumpas, Charalampos
N1 - Funding Information:
P. Wadhwa (email: p.wadhwa@leeds.ac.uk), D. Buckley and C. Tsoumpas are with Department of Biomedical Imaging Science, University of Leeds, UK. P. Wadhwa, W. Hallett, R. N. Gunn and C.Tsoumpas are with Invicro, UK K. Thielemans, O. Bertolli, E. Emond and B A. Thomas are with Institute of Nuclear Medicine, University College London, UK. N. Efthimiou is with PET Research Centre, Faculty of Health Sciences, University of Hull, Hull HU6 7RX, UK. M. Tohme and K A. Wangerin are with GE Healthcare, Waukesha, WI, US. G. Delso is with GE Healthcare, Cambridge. UK. P. Wadhwa is funded by the Medical Research Council (MR/M01746X/1). C. Tsoumpas is sponsored by a Royal Society Industry Fellowship (IF170011). This project has been supported by EPSRC Collaborative Computational Flagship Project (EP/M022587/1 and EP/P022200/1). We would like to thank Dr. Floris Jansen (GE Healthcare) and Nicholas Keat (Invicro) for their substantial support on progressing this project. Ethics number 17/WM/0084 with permission from a clinical study performed at Invicro.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/11
Y1 - 2018/11
N2 - 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.
AB - 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.
U2 - 10.1109/NSSMIC.2018.8824341
DO - 10.1109/NSSMIC.2018.8824341
M3 - Conference contribution
AN - SCOPUS:85073109196
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 -