TY - GEN
T1 - Preliminary investigation of a Monte Carlo-based system matrix approach for quantitative clinical brain 123I SPECT imaging
AU - Auer, Benjamin
AU - Zeraatkar, Navid
AU - Banerjee, Soumyanil
AU - Goding, Justin C.
AU - Furenlid, Lars R.
AU - King, Michael A.
N1 - Funding Information:
ACKNOWLEDGMENT Research reported in this publication was supported by the National Institute of Biomedical Imaging and Bioengineering of the National Institutes of Health under Award Numbers EB022521 and R01 EB022092. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
Publisher Copyright:
© 2018 IEEE.
PY - 2018/11
Y1 - 2018/11
N2 - A next-generation, adaptive, dynamic multi-pinhole system, AdaptiSPECT-C, dedicated to clinical brain SPECT imaging, is currently under development as part of a collaboration between the universities of Arizona and Massachusetts. It has been shown that accurate modeling of the system matrix is a key aspect of SPECT image reconstruction as it has the potential to improve the imaging performance of any system. A straight-forward approach to modeling is based on the use of Monte Carlo simulation to pre-compute and store the system matrix. Generally, in clinical imaging, given the large sizes of detectors and volume of interests this approach faces critical memory storage issues despite the use of sparse structures to store the system matrix. The aim of this work was to investigate the feasibility of a Monte Carlo simulation pre-computed system matrix approach for 123I clinical brain SPECT imaging with the AdaptiSPECT-C system. Our efficient method was evaluated using an XCAT brain perfusion phantom. The present approach's feasibility was fully demonstrated in case of clinical 123I brain imaging.
AB - A next-generation, adaptive, dynamic multi-pinhole system, AdaptiSPECT-C, dedicated to clinical brain SPECT imaging, is currently under development as part of a collaboration between the universities of Arizona and Massachusetts. It has been shown that accurate modeling of the system matrix is a key aspect of SPECT image reconstruction as it has the potential to improve the imaging performance of any system. A straight-forward approach to modeling is based on the use of Monte Carlo simulation to pre-compute and store the system matrix. Generally, in clinical imaging, given the large sizes of detectors and volume of interests this approach faces critical memory storage issues despite the use of sparse structures to store the system matrix. The aim of this work was to investigate the feasibility of a Monte Carlo simulation pre-computed system matrix approach for 123I clinical brain SPECT imaging with the AdaptiSPECT-C system. Our efficient method was evaluated using an XCAT brain perfusion phantom. The present approach's feasibility was fully demonstrated in case of clinical 123I brain imaging.
KW - Clinical I brain imaging
KW - Monte Carlo simulation
KW - modeling of the system matrix
KW - quantitative SPECT imaging
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U2 - 10.1109/NSSMIC.2018.8824750
DO - 10.1109/NSSMIC.2018.8824750
M3 - Conference contribution
AN - SCOPUS:85073117874
T3 - 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings
BT - 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2018 - Proceedings
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 -