Maximum a posteriori reconstruction of the Patlak parametric image from sinograms in dynamic PET

Physics in Medicine and Biology
Guobao WangJinyi Qi

Abstract

Parametric imaging using the Patlak graphical method has been widely used to analyze dynamic PET data. Conventionally a Patlak parametric image is generated by reconstructing a sequence of dynamic images first and then performing Patlak graphical analysis on the time-activity curves pixel-by-pixel. However, because it is rather difficult to model the noise distribution in reconstructed images, the spatially variant noise correlation is simply ignored in the Patlak analysis, which leads to sub-optimal results. In this paper we present a Bayesian method for reconstructing Patlak parametric images directly from raw sinogram data by incorporating the Patlak plot model into the image reconstruction procedure. A preconditioned conjugate gradient algorithm is used to find the maximum a posteriori solution. The proposed direct method is statistically more efficient than the conventional indirect approach because the Poisson noise distribution in PET data can be accurately modeled in the direct reconstruction. The computation cost of the direct method is similar to reconstruction time of two dynamic frames. Therefore, when more than two dynamic frames are used in the Patlak analysis, the direct method is faster than the conventional ind...Continue Reading

References

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Citations

Jul 22, 2010·Physics in Medicine and Biology·Jing TangArman Rahmim
Sep 23, 2010·Physics in Medicine and Biology·Grant T GullbergThomas F Budinger
Feb 17, 2010·Physics in Medicine and Biology·Guobao Wang, Jinyi Qi
Mar 29, 2011·Physics in Medicine and Biology·S TongP Shi
Jul 19, 2012·Physics in Medicine and Biology·Lijun LuArman Rahmim
Jan 8, 2014·Theranostics·Guobao Wang, Jinyi Qi
Oct 10, 2008·Medical Physics·Charalampos TsoumpasKris Thielemans
May 22, 2010·Journal of Nuclear Medicine : Official Publication, Society of Nuclear Medicine·Robert A de KempErik L Ritman
Feb 8, 2011·Computerized Medical Imaging and Graphics : the Official Journal of the Computerized Medical Imaging Society·Georgios I AngelisCharalampos Tsoumpas
Feb 24, 2015·IEEE Transactions on Medical Imaging· Xiaoyin Cheng Kuangyu Shi
Mar 7, 2014·IEEE Transactions on Medical Imaging·Mustafa E KamasakEvan D Morris
Apr 9, 2014·IEEE Transactions on Medical Imaging·Wentao ZhuRichard M Leahy
Aug 30, 2012·IEEE Transactions on Medical Imaging·Jianhua YanRichard E Carson
May 19, 2009·IEEE Transactions on Medical Imaging·Guobao Wang, Jinyi Qi
Aug 16, 2012·IEEE Transactions on Medical Imaging·Guobao Wang, Jinyi Qi
May 3, 2015·IEEE Transactions on Medical Imaging·Rebekka LoebSibylle I Ziegler
Jun 25, 2016·Journal of X-ray Science and Technology·Yuanyuan GaoWufan Chen
Apr 5, 2018·Physics in Medicine and Biology·George P RalliJohn D Fenwick
Jan 15, 2011·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Torsten A Ensslin, Cornelius Weig
Oct 2, 2013·Physics in Medicine and Biology·Nicolas A KarakatsanisArman Rahmim
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Aug 4, 2018·Journal of Healthcare Engineering·Michele ScipioniMaria Filomena Santarelli
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Feb 13, 2015·Physics in Medicine and Biology·Kyungsang KimJong Chul Ye
May 27, 2016·Physics in Medicine and Biology·Philip Novosad, Andrew J Reader
Nov 22, 2020·PET Clinics·Jinyi QiXuezhu Zhang
Jun 5, 2021·Biomedical Physics & Engineering Express·Xin MaoNa Zhang
Aug 26, 2021·Physics in Medicine and Biology·Zacharias ChalampalakisClaude Comtat

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