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Proceedings Paper

Localizing source distribution based on the adaptive finite element methods for bioluminescence tomography
Author(s): Yujie Lv; Jie Tian; Jie Luo; Hui Li; Wenxiang Cong; Ge Wang; Wei Yang
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Paper Abstract

In small-animal molecular imaging, bioluminescence tomography (BLT) is used to reconstruct the internal bioluminescent source which can reveal the molecular and cellular information. Based on the general finite element tomographic method, the spatial resolution of source distribution need compromise between a priori fixed discretization degree to the given geometry domain and the computational cost of the reconstruction algorithm. In this contribution, an adaptive finite element methods based tomographic algorithm is represented and used to localize bioluminescent source. In the proposed algorithm, an initial coarse volumetric finite element mesh is provided and a priori knowledge is employed to determine the permissible source region. Furthermore, the local mesh refinement is performed to adaptively reduce the element size of the mesh by virtue of error estimation techniques. The above strategies reduce the ill-posedness of the BLT problem significantly and improve the numerical stability effectively. Numerical simulations with the homogeneous and heterogeneous phantoms, where the synthetic data is obtained through the adaptive finite element solver and Monte Carlo methods, show the effectiveness of the tomographic algorithm.

Paper Details

Date Published: 7 September 2006
PDF: 9 pages
Proc. SPIE 6318, Developments in X-Ray Tomography V, 63181L (7 September 2006); doi: 10.1117/12.678268
Show Author Affiliations
Yujie Lv, Institute of Automation (China)
Jie Tian, Institute of Automation (China)
Jie Luo, Institute of Automation (China)
Hui Li, Institute of Automation (China)
Capital Normal Univ. (China)
Wenxiang Cong, Univ. of Iowa (United States)
Ge Wang, Univ. of Iowa (United States)
Wei Yang, Institute of Automation (China)


Published in SPIE Proceedings Vol. 6318:
Developments in X-Ray Tomography V
Ulrich Bonse, Editor(s)

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