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5 June 2012 Comparisons of hybrid radiosity-diffusion model and diffusion equation for bioluminescence tomography in cavity cancer detection
Xueli Chen, Defu Yang, Xiaochao Qu, Jimin Liang, Jie Tian, Hao Hu, Xinbo Gao
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Journal of Biomedical Optics, Vol. 17, Issue 6, 066015 (June 2012). https://doi.org/10.1117/1.JBO.17.6.066015
Abstract
Bioluminescence tomography (BLT) has been successfully applied to the detection and therapeutic evaluation of solid cancers. However, the existing BLT reconstruction algorithms are not accurate enough for cavity cancer detection because of neglecting the void problem. Motivated by the ability of the hybrid radiosity-diffusion model (HRDM) in describing the light propagation in cavity organs, an HRDM-based BLT reconstruction algorithm was provided for the specific problem of cavity cancer detection. HRDM has been applied to optical tomography but is limited to simple and regular geometries because of the complexity in coupling the boundary between the scattering and void region. In the provided algorithm, HRDM was first applied to three-dimensional complicated and irregular geometries and then employed as the forward light transport model to describe the bioluminescent light propagation in tissues. Combining HRDM with the sparse reconstruction strategy, the cavity cancer cells labeled with bioluminescent probes can be more accurately reconstructed. Compared with the diffusion equation based reconstruction algorithm, the essentiality and superiority of the HRDM-based algorithm were demonstrated with simulation, phantom and animal studies. An in vivo gastric cancer-bearing nude mouse experiment was conducted, whose results revealed the ability and feasibility of the HRDM-based algorithm in the biomedical application of gastric cancer detection.
© 2012 Society of Photo-Optical Instrumentation Engineers (SPIE) 0091-3286/2012/$25.00 © 2012 SPIE
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Xueli Chen, Defu Yang, Xiaochao Qu, Jimin Liang, Jie Tian, Hao Hu, and Xinbo Gao "Comparisons of hybrid radiosity-diffusion model and diffusion equation for bioluminescence tomography in cavity cancer detection," Journal of Biomedical Optics 17(6), 066015 (5 June 2012). https://doi.org/10.1117/1.JBO.17.6.066015
Published: 5 June 2012
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Cited by 16 scholarly publications.
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KEYWORDS
Reconstruction algorithms
Cancer
Tumor growth modeling
3D modeling
Computer simulations
Diffusion
Model-based design
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