Single-view XLCT imaging based on fast Bayesian matching pursuit

被引：1

作者：

Hou Y.-Q. ^{[1
]}

Qu X. ^{[1
]}

Zhang H.-B. ^{[1
]}

Yi H.-J. ^{[1
]}

He X.-W. ^{[1
]}

机构：

[1] School of Information Sciences and Technology, Northwest University, Xi'an

来源：

He, Xiao-Wei (hexw@nwu.edu.cn) | 1600年 / Chinese Academy of Sciences卷 / 25期

关键词：

Bayesian matching pursuit; Iterative-shrinking permissible region; Optical molecular imaging; Single-view reconstruction; X-ray luminescence computed tomography;

D O I：

10.3788/OPE.20172505.1159

中图分类号：

学科分类号：

摘要：

To relieve the ill-posedness of single-view x-ray luminescence computed tomography (XLCT), a fast Bayesian matching pursuit (FBMP) method combined with iterative-shrinking permissible region (ISPR) strategy was put forward. In this method, Bayesian model was combined with the greedy algorithm to quickly and efficiently restore sparse signal from few observed values. To further improve the reconstruction accuracy, FBMP was combined with ISPR strategy to simplify the mesh generation and system matrix construction by self-adaptive finite element, downsizing the factor iterative-shrinking permissible region, meanwhile relieving the ill-posedness of XLCT in reverse solution. In order to verify the effectiveness of the method, a simulation and a real physical phantom experiment were performed. The simulation results show that the proposed method, while speeding up the reconstruction process, significantly improve the localization accuracy of nano luminescent target and quantitative result of luminescence yield, which are 0.73 mm and 0.79 μg respectively. The physical phantom experiment further verifies the feasibility of this method in actual XLCT. © 2017, Science Press. All right reserved.

引用

页码：1159 / 1170

页数：11

共 25 条

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