Share Email Print
cover

Proceedings Paper

Limited-memory-BFGS-based iterative algorithm for multispectral bioluminescence tomography with Huber regularization
Author(s): Jinchao Feng; Kebin Jia; Jie Tian; Chenghu Qin; Shouping Zhu
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

Multispectral bioluminescence tomography is becoming a promising tool because it can resolve the biodistibution of bioluminescent reporters associated with cellular and subcellular function through several millimeters with to centimeters of tissues in vivo. Generally, to recover the bioluminescent sources, the source reconstruction problem is formulated as a nonlinear least-squares-type bounds constrained optimization problem. However, bioluminescence tomography (BLT) is an ill-posed problem. For the sake of stability and uniqueness of BLT, many algorithms have been proposed to regularize the problem, such as L2 norm and L1 norm. Here, we proposed a new regularization method with Huber function to regularize BLT problem to obtain robustness like L1 and rapid convergence of L2. Furthermore, the computational burden is largely increased with the use of spectral data. Therefore, there is a critical need to develop a fast reconstruction algorithm for solving multispectral bioluminescence tomography. In the paper, a limited memory quasi-Newton algorithm for solving the large-scale optimization problem is proposed to fast localize the bioluminescent source. In the numerical simulation, a heterogeneous phantom was used to evaluate the performance of the proposed algorithm with the Monte Carlo based synthetic data. Additionally, the real mouse experiments were conducted to further evaluate the proposed algorithm. The results demonstrate the potential and merits of the proposed algorithm.

Paper Details

Date Published: 9 March 2010
PDF: 8 pages
Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 762619 (9 March 2010); doi: 10.1117/12.844604
Show Author Affiliations
Jinchao Feng, Beijing Univ. of Technology (China)
Kebin Jia, Beijing Univ. of Technology (China)
Jie Tian, Institute of Automation (China)
Xidian Univ. (China)
Chenghu Qin, Institute of Automation (China)
Shouping Zhu, Institute of Automation (China)


Published in SPIE Proceedings Vol. 7626:
Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging
Robert C. Molthen; John B. Weaver, Editor(s)

© SPIE. Terms of Use
Back to Top