Three-dimensional source reconstruction for bioluminescence tomography using the LSQR method with preconditioning

Jingjing Yu; Fang Liu; Licheng Jiao; Xiaowei He

doi:10.1117/12.832906

30 October 2009 Three-dimensional source reconstruction for bioluminescence tomography using the LSQR method with preconditioning

Jingjing Yu, Fang Liu, Licheng Jiao, Xiaowei He

Author Affiliations +

Proceedings Volume 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques; 74971N (2009) https://doi.org/10.1117/12.832906
Event: Sixth International Symposium on Multispectral Image Processing and Pattern Recognition, 2009, Yichang, China

Abstract

As a novel optical molecular imaging modality, Bioluminescence Tomography (BLT) aims at quantitative reconstruction of the bioluminescent source distribution inside the biological tissue from the optical signals measured on the living animal surface, which is a highly ill-posed inverse problem. In this paper, with the finite element method solving the diffusion equation, an iterative regularization algorithm, referred to as least square QR-factorization (LSQR), is applied to the inverse problem in BLT. The affect of the preconditioning strategy on the LSQR method (PLSQR) for BLT is also investigated. The Simulations with a heterogeneous mouse chest phantom demonstrate that by incorporating a priori knowledge of the permissible source region, the LSQR method can reconstruct the source accurately and stably. Moreover, by employing preconditioning strategy, PLSQR outperforms LSQR in terms of source power density and convergence speed.

Citation Download Citation

Jingjing Yu, Fang Liu, Licheng Jiao, and Xiaowei He "Three-dimensional source reconstruction for bioluminescence tomography using the LSQR method with preconditioning", Proc. SPIE 7497, MIPPR 2009: Medical Imaging, Parallel Processing of Images, and Optimization Techniques, 74971N (30 October 2009); https://doi.org/10.1117/12.832906

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