Abstract
PET image reconstruction using regularisation algorithms can provide good image quality and ensure convergence with suitable parameter selections, however they usually require many iterations to do so. A list-mode form of the BSREM regularised algorithm for PET image reconstruction is presented, with an acceleration technique whereby the number of list-mode events used in each subset is increased with increasing iteration number. This allows for quick convergence in early iterations, and avoids noise propagation from "small" subsets as well as limit cycles in later iterations.
Original language | English |
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Title of host publication | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 |
Publisher | Institute of Electrical and Electronics Engineers Inc. |
ISBN (Electronic) | 9781728141640 |
DOIs | |
State | Published - Oct 2019 |
Externally published | Yes |
Event | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 - Manchester, United Kingdom Duration: Oct 26 2019 → Nov 2 2019 |
Publication series
Name | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 |
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Conference
Conference | 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2019 |
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Country/Territory | United Kingdom |
City | Manchester |
Period | 10/26/19 → 11/2/19 |
Funding
Manuscript received on 13 December 2019. This work was supported by a fellowship from GE Healthcare.