Abstract

A finite element mesh aggregating approach is presented to reconstruct images of multiple internal bioluminescence sources. Rather than assuming independence between mesh nodes, the proposed reconstruction strategy exploits spatial structure of nodes and aggregation feature of density distribution on the finite element mesh to adaptively determine the number of sources and to improve the quality of reconstructed images. With the proposed strategy integrated in the regularization-based reconstruction process, reconstruction algorithms need no a priori knowledge of source number; even more importantly, they can automatically reconstruct multiple sources that differ greatly in density or power.

Highlights

  • Bioluminescence tomography (BLT) is a rapidly growing field of research in optical molecular imaging, which allows for the visualization of normal and abnormal cellular processes in living subjects at the molecular or genetic level [1,2,3,4]

  • Comparison is performed between the proposed multiple-source detection strategy (MSDS) and the traditional global threshold strategy (GTS)

  • It should be pointed that the main theme of this paper is to evaluate the performance of this framework for multiple-source reconstruction in BLT, rather than the comparison between specific reconstruction algorithms

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Summary

Introduction

Bioluminescence tomography (BLT) is a rapidly growing field of research in optical molecular imaging, which allows for the visualization of normal and abnormal cellular processes in living subjects at the molecular or genetic level [1,2,3,4]. Different strategies have been proposed for coping with the ill posedness of BLT inverse problems These studies obtain stable reconstruction by increasing the amount of independent measurements with spectrally resolved approaches [11,12,13], or by reducing the number of unknowns [10, 14], or with regularization techniques to incorporate some a priori information regarding the inverse source problem [15,16,17]. In most applications of BLT, for example, monitoring cancer metastasis, neither the sources number nor an appropriate global threshold is easy to determine This is mainly due to the fact that bioluminescent lights are usually weak and diffuse, and the number of potential sources is hard to estimate only by surface photon distributions. Short discussions and concluding remarks are given at the end of this paper

Multiple-Source Reconstruction Framework
H Right L B
Numerical Results and Analysis
Phantom Study
Discussions and Conclusion
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