Paper
7 September 2006 Localizing source distribution based on the adaptive finite element methods for bioluminescence tomography
Yujie Lv, Jie Tian, Jie Luo, Hui Li, Wenxiang Cong, Ge Wang, Wei Yang
Author Affiliations +
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.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yujie Lv, Jie Tian, Jie Luo, Hui Li, Wenxiang Cong, Ge Wang, and Wei Yang "Localizing source distribution based on the adaptive finite element methods for bioluminescence tomography", Proc. SPIE 6318, Developments in X-Ray Tomography V, 63181L (7 September 2006); https://doi.org/10.1117/12.678268
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KEYWORDS
Tomography

Bioluminescence

Finite element methods

Reconstruction algorithms

Monte Carlo methods

Chemical elements

Diffusion

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