Name
Title | ||
|---|---|---|
Bayesian image reconstruction for improving detection performance of muon tomography. |
Abstract | ||
|---|---|---|
Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography. |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1109/TIP.2009.2014423 | IEEE Transactions on Image Processing |
Keywords | Field | DocType |
scattering density image,detection performance,muon measurement,maximum likelihood method,muon reconstruction problem,maximum likelihood estimation,bayesian image reconstruction,unregularized maximum likelihood update,inverse quadratic shrinkage function,inverse cubic shrinkage function,muon tomography,iterative shrinkage algorithm,monte carlo method,bayes theorem,maximum likelihood estimate,tungsten,algorithms,electromagnetic fields,scattering,image reconstruction,computer simulation,mesons,image quality,bayesian methods,receiver operator characteristic,roc analysis,posterior distribution,iron,normal distribution,iterative methods,maximum likelihood,prior distribution,roc curve,bayesian estimation,expectation maximization,tomography | Iterative reconstruction,Muon tomography,Pattern recognition,Expectation–maximization algorithm,Image processing,Posterior probability,Artificial intelligence,Maximum a posteriori estimation,Prior probability,Bayes estimator,Mathematics | Journal |
Volume | Issue | ISSN |
18 | 5 | 1057-7149 |
Citations | PageRank | References |
0 | 0.34 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Guobao Wang | 1 | 86 | 12.68 |
| Larry J Schultz | 2 | 0 | 0.34 |
| Jinyi Qi | 3 | 284 | 35.82 |