Hybrid algorithm of maximum-likelihood expectation-maximization and multiplicative algebraic reconstruction technique for iterative tomographic image reconstruction

2019 ◽  
Author(s):  
Ryosuke Kasai ◽  
Yusaku Yamaguchi ◽  
Takeshi Kojima ◽  
Tetsuya Yoshinaga
Keyword(s):  
Maximum Likelihood ◽  
Image Reconstruction ◽  
Expectation Maximization ◽  
Hybrid Algorithm ◽  
Reconstruction Technique ◽  
Tomographic Image ◽  
Algebraic Reconstruction Technique ◽  
Multiplicative Algebraic Reconstruction Technique ◽  
Tomographic Image Reconstruction ◽  
Maximum Likelihood Expectation Maximization

BIFURCATION ANALYSIS OF ITERATIVE IMAGE RECONSTRUCTION METHOD FOR COMPUTED TOMOGRAPHY

2008 ◽  
Vol 18 (04) ◽  
pp. 1219-1225 ◽  
Author(s):  
TETSUYA YOSHINAGA ◽  
YOSHIHIRO IMAKURA ◽  
KEN'ICHI FUJIMOTO ◽  
TETSUSHI UETA
Keyword(s):  
Computed Tomography ◽  
Image Reconstruction ◽  
Computational Method ◽  
Reconstruction Technique ◽  
Reconstruction Method ◽  
Algebraic Reconstruction Technique ◽  
Reconstruction Algorithms ◽  
Iterative Image Reconstruction ◽  
Multiplicative Algebraic Reconstruction Technique ◽  
Algebraic Reconstruction

Of the iterative image reconstruction algorithms for computed tomography (CT), the power multiplicative algebraic reconstruction technique (PMART) is known to have good properties for speeding convergence and maximizing entropy. We analyze here bifurcations of fixed and periodic points that correspond to reconstructed images observed using PMART with an image made of multiple pixels and we investigate an extended PMART, which is a dynamical class for accelerating convergence. The convergence process for the state in the neighborhood of the true reconstructed image can be reduced to the property of a fixed point observed in the dynamical system. To investigate the speed of convergence, we present a computational method of obtaining parameter sets in which the given real or absolute values of the characteristic multiplier are equal. The advantage of the extended PMART is verified by comparing it with the standard multiplicative algebraic reconstruction technique (MART) using numerical experiments.

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