Improving dynamic tomography, through Maximum a Posteriori estimation

被引：6

作者：

Myers, Glenn R. ^{[1
]}

Geleta, Matthew ^{[2
]}

Kingston, Andrew M. ^{[1
]}

Recur, Benoit ^{[1
]}

Sheppard, Adrian P. ^{[1
]}

机构：

[1] Australian Natl Univ, GPO Box 4, Canberra, ACT 0200, Australia

[2] Univ Melbourne, Melbourne, Vic 3010, Australia

来源：

DEVELOPMENTS IN X-RAY TOMOGRAPHY IX | 2014年 / 9212卷

基金：

澳大利亚研究理事会;

关键词：

Computed tomography; dynamic tomography; fluid flow; 4D tomography; maximum a posteriori; Bayesian; micro computed tomography; time-resolved tomography; PROJECTION DATA; RECONSTRUCTION; IMAGES; CT;

D O I：

10.1117/12.2061604

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Direct study of pore-scale fluid displacements, and other dynamic (i.e. time-dependent) processes is not feasible with conventional X-ray micro computed tomography (pCT). We have previously verified that a priori knowledge of the underlying physics can be used to conduct high-resolution, time-resolved imaging of continuous, complex processes, at existing X-ray /XI facilities. In this paper we present a maximum a posteriori (MAP) model of the dynamic tomography problem, which allows us to easily adapt and generalise our previous dynamic /XI approach to systems with more complex underlying physics.

引用

页数：9

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