TY - GEN
T1 - Kernel-Based Reconstruction of Cardiac PET Images Using MR Information
AU - Ashouri, Zahra
AU - Hunter, Chad R.
AU - Spencer, Benjamin A.
AU - Wang, Guobao
AU - Dansereau, Richard M.
AU - de Kemp, Robert A.
N1 - Funding Information:
Manuscript received December 10th, 2020. Research supported by Natural Sciences and Engineering Research Council (NSERC) of Canada. Zahra Ashouri is at Ottawa Heart Institute and Carleton University. e-mail: zashouri@ottawaheart.ca). Chad Hunter is at Ottawa Heart Institute. Benjamin
Publisher Copyright:
© 2020 IEEE
PY - 2020
Y1 - 2020
N2 - Positron emission tomography (PET) is used to observe processes within the human body using radioactive tracers. Quality of PET images is compromised by statistical noise, especially in the heart where cardiac and respiratory motion occur. Image prior information is generally useful for improving PET image quality. Sources of prior anatomic information include computed tomography (CT) or magnetic resonance imaging (MRI). In this work, we used MR information in the kernel framework to help reconstruct cardiac PET images and compared it with the kernel reconstruction from PET data only. The kernel-based reconstruction method [1], incorporates prior information in the reconstruction algorithm with the use of kernels. Our results show kernel-based image reconstruction using MR prior anatomic information gives numerically equivalent results to the original kernel method that uses composite frames to reconstruct dynamic PET images.
AB - Positron emission tomography (PET) is used to observe processes within the human body using radioactive tracers. Quality of PET images is compromised by statistical noise, especially in the heart where cardiac and respiratory motion occur. Image prior information is generally useful for improving PET image quality. Sources of prior anatomic information include computed tomography (CT) or magnetic resonance imaging (MRI). In this work, we used MR information in the kernel framework to help reconstruct cardiac PET images and compared it with the kernel reconstruction from PET data only. The kernel-based reconstruction method [1], incorporates prior information in the reconstruction algorithm with the use of kernels. Our results show kernel-based image reconstruction using MR prior anatomic information gives numerically equivalent results to the original kernel method that uses composite frames to reconstruct dynamic PET images.
KW - Kernel method
KW - MRI
KW - PET image reconstruction
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U2 - 10.1109/NSS/MIC42677.2020.9507993
DO - 10.1109/NSS/MIC42677.2020.9507993
M3 - Conference contribution
AN - SCOPUS:85124702177
T3 - 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020
BT - 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2020
Y2 - 31 October 2020 through 7 November 2020
ER -