Modeling bioluminescent photon transport in tissue based on Radiosity-diffusion model

Li Sun; Pu Wang; Jie Tian; Bo Zhang; Dong Han; Xin Yang

doi:10.1117/12.843931

9 March 2010 Modeling bioluminescent photon transport in tissue based on Radiosity-diffusion model

Li Sun, Pu Wang, Jie Tian, Bo Zhang, Dong Han, Xin Yang

Proceedings Volume 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging; 76260S (2010) https://doi.org/10.1117/12.843931
Event: SPIE Medical Imaging, 2010, San Diego, California, United States

Abstract

Bioluminescence tomography (BLT) is one of the most important non-invasive optical molecular imaging modalities. The model for the bioluminescent photon propagation plays a significant role in the bioluminescence tomography study. Due to the high computational efficiency, diffusion approximation (DA) is generally applied in the bioluminescence tomography. But the diffusion equation is valid only in highly scattering and weakly absorbing regions and fails in non-scattering or low-scattering tissues, such as a cyst in the breast, the cerebrospinal fluid (CSF) layer of the brain and synovial fluid layer in the joints. A hybrid Radiosity-diffusion model is proposed for dealing with the non-scattering regions within diffusing domains in this paper. This hybrid method incorporates a priori information of the geometry of non-scattering regions, which can be acquired by magnetic resonance imaging (MRI) or x-ray computed tomography (CT). Then the model is implemented using a finite element method (FEM) to ensure the high computational efficiency. Finally, we demonstrate that the method is comparable with Mont Carlo (MC) method which is regarded as a 'gold standard' for photon transportation simulation.

Citation Download Citation

Li Sun, Pu Wang, Jie Tian, Bo Zhang, Dong Han, and Xin Yang "Modeling bioluminescent photon transport in tissue based on Radiosity-diffusion model", Proc. SPIE 7626, Medical Imaging 2010: Biomedical Applications in Molecular, Structural, and Functional Imaging, 76260S (9 March 2010); https://doi.org/10.1117/12.843931

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