Bayesian Approach for Recovering Piecewise Constant Viscoelasticity from MRE Data  

作　　者：Yu JIANG Shi-hui QIAN 

机构地区：[1]School of Mathematics,Shanghai University of Finance and Economics,Shanghai 200433,China

出　　处：《Acta Mathematicae Applicatae Sinica》2020年第1期223-236,共14页应用数学学报（英文版）

基　　金：supported by the National Natural Science Foundation of China(No.11971121)。

摘　　要：This paper deals with an inverse problem for recovering the piecewise constant viscoelasticity of a living body from MRE(Magnetic Resonance Elastography)data.Based on a scalar partial differential equation whose solution can approximately simulate MRE data,our inverse coefficient problem is considered as a statistical inverse problem of reconstructing the posterior distribution of unknown viscoelastic modulus.For sampling this distribution,one usually can use the Metropolis-Hastings Markov chain Monte Carlo(MHMCMC)algorithm.However,without an appropriate"proposal"distribution given artificially,the MH-MCMC algorithm is hard to draw samples efficiently.To avoid this,a so-called slice sampling algorithm is introduced in this paper and applied for solving our problem.The performance of these statistical inversion algorithms is numerically tested basing on simulated data.

关 键 词：Bayesian approach Markov chain Monte Carlo ALGORITHM SLICE sampling ALGORITHM interior measurement magnetic resonance ELASTOGRAPHY VISCOELASTICITY 

分 类 号：O212[理学—概率论与数理统计]