Open AccessAn optimal permissible source region strategy for multispectral bioluminescence tomography
Author(s) -
Jinchao Feng,
Kebin Jia,
Guorui Yan,
Shouping Zhu,
Chenghu Qin,
Yujie Lv,
Jie Tian
Publication year - 2008
Publication title -
optics express
Language(s) - Uncategorized
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.16.015640
Subject(s) - multispectral image , a priori and a posteriori , inverse problem , imaging phantom , bioluminescence , computer science , monte carlo method , tomography , bioluminescence imaging , stability (learning theory) , algorithm , computer vision , optics , mathematics , physics , biology , luciferase , machine learning , ecology , statistics , mathematical analysis , philosophy , transfection , genetics , epistemology , cell culture
Multispectral bioluminescence tomography (BLT) attracts increasing more attention in the area of small animal studies because multispectral data acquisition could help in the 3D location of bioluminescent sources. Generally, BLT problem is ill-posed and a priori information is indispensable to reconstruction bioluminescent source uniquely and quantitatively. In this paper, we propose a spectrally solved bioluminescence tomography algorithm with an optimal permissible source region strategy. Being the most different from earlier studies, an optimal permissible source region strategy which is automatically selected without human intervention is developed to reduce the ill-posedness of BLT and therefore improves the reconstruction quality. Furthermore, both numerical stability and computational efficiency benefit from the strategy. In the numerical experiments, a heterogeneous phantom is used to evaluate the proposed algorithm and the synthetic data is produced by Monte Carlo method for avoiding the inverse crime. The results demonstrate the feasibility and potential of our methodology for reconstructing the distribution of bioluminescent sources.