TY - GEN
T1 - Penalized MLAA with spatially-encoded anatomic prior in TOF PET/MR
AU - Kim, Kyungsang
AU - Yang, Jaewon
AU - El Fakhri, Georges
AU - Seo, Youngho
AU - Li, Quanzheng
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/10/16
Y1 - 2017/10/16
N2 - PET/MR scanner has been developed for both molecular and morphological assessment with great potentials. In the PET/MR scan, the attenuation correction is still a problem. One method is the MR-based attenuation correction that generates the synthetic CT images from MR images. However, the lack of bone signal and the bias from the synthetic CT image can degrade the PET image quality. Another method is a maximum likelihood reconstruction of activity and attenuation (MLAA) using the time-of-flight (TOF) PET emission data, however, the noise component is considerably high from TOF PET data. To address this issue, we propose a penalized MLAA using a spatially-encoded anatomic MR prior, which jointly use a patch-based spatially-encoded similarity weight of MR image to improve the attenuation image quality. In addition, we propose a non-divergence criteria using a consistency condition in the iterative process. We exploit an alternating direction method of multipliers (ADMM) algorithm to optimize the cost function. In computer simulations, we demonstrate that the proposed method outperform the conventional MLAA.
AB - PET/MR scanner has been developed for both molecular and morphological assessment with great potentials. In the PET/MR scan, the attenuation correction is still a problem. One method is the MR-based attenuation correction that generates the synthetic CT images from MR images. However, the lack of bone signal and the bias from the synthetic CT image can degrade the PET image quality. Another method is a maximum likelihood reconstruction of activity and attenuation (MLAA) using the time-of-flight (TOF) PET emission data, however, the noise component is considerably high from TOF PET data. To address this issue, we propose a penalized MLAA using a spatially-encoded anatomic MR prior, which jointly use a patch-based spatially-encoded similarity weight of MR image to improve the attenuation image quality. In addition, we propose a non-divergence criteria using a consistency condition in the iterative process. We exploit an alternating direction method of multipliers (ADMM) algorithm to optimize the cost function. In computer simulations, we demonstrate that the proposed method outperform the conventional MLAA.
KW - Attenuation correction using a MR prior
KW - MLAA
UR - http://www.scopus.com/inward/record.url?scp=85041539027&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85041539027&partnerID=8YFLogxK
U2 - 10.1109/NSSMIC.2016.8069514
DO - 10.1109/NSSMIC.2016.8069514
M3 - Conference contribution
AN - SCOPUS:85041539027
T3 - 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
BT - 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2016 IEEE Nuclear Science Symposium, Medical Imaging Conference and Room-Temperature Semiconductor Detector Workshop, NSS/MIC/RTSD 2016
Y2 - 29 October 2016 through 6 November 2016
ER -