Computational and Mathematical Methods in Medicine
Volume 2013 (2013), Article ID 548491, 12 pages
http://dx.doi.org/10.1155/2013/548491
Research Article
Hybrid Multilevel Sparse Reconstruction for a Whole Domain Bioluminescence Tomography Using Adaptive Finite Element
1School of Physics and Information Technology, Shaanxi Normal University, Xi’an, Shanxi 710062, China
2School of Information Sciences and Technology, Northwest University, Xi’an, Shanxi 710069, China
3School of Computer Science and Technology, Xidian University, Xi’an, Shanxi 710071, China
4Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China, Xi’an, Shanxi 710071, China
Received 15 September 2012; Accepted 26 January 2013
Academic Editor: Chenghu Qin
Copyright © 2013 Jingjing Yu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract
Quantitative reconstruction of bioluminescent sources from boundary measurements is a challenging ill-posed inverse problem owing to the high degree of absorption and scattering of light through tissue. We present a hybrid multilevel reconstruction scheme by combining the ability of sparse regularization with the advantage of adaptive finite element method. In view of the characteristics of different discretization levels, two different inversion algorithms are employed on the initial coarse mesh and the succeeding ones to strike a balance between stability and efficiency. Numerical experiment results with a digital mouse model demonstrate that the proposed scheme can accurately localize and quantify source distribution while maintaining reconstruction stability and computational economy. The effectiveness of this hybrid reconstruction scheme is further confirmed with in vivo experiments.