A maximum likelihood expectation maximization algorithm with thresholding.
The maximum likelihood expectation maximization (MLEM) algorithm has several advantages over the conventional filtered back-projection (FBP) for image reconstruction. However, the slow convergence and the high computational cost for its practical implementation have limited its clinical applications. This study proposes the incorporation of a thresholding technique in both the MLEM and ordered subsets EM (OSEM) algorithm to accelerate convergence. The threshold is set to c*m, where m is the mean pixel value of the whole image. The reconstruction time is proportional to the total number of pixels, so a thresholding technique that nullifies the value of a pixel if it falls below a threshold, can effectively remove the non-active pixels and substantially accelerate reconstruction. Preliminary tests on simulated PET data reveal that the thresholding technique accelerates the convergence rate and reduce error in the reconstructed image. The reconstruction performance improves with the increase of the threshold level and the MSE reaches minimum for c value equals to about 1.
Chuang
Keh-Shih
KS
Department of Nuclear Science, National Tsing-Hua University, Hsinchu 30013, Taiwan. kschuang@mx.nthu.edu.tw
Jan
Meei-Ling
ML
Wu
Jay
J
Lu
Jeng-Chang
JC
Chen
Sharon
S
Hsu
Ching-Han
CH
Fu
Ying-Kai
YK
D000465:Algorithms; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods / Q000706:statistics & numerical data*; D016013:Likelihood Functions; D013624:Taiwan