Journal of Innovative Optical Health Sciences, Volume. 10, Issue 3, 1750005(2017)

Performance evaluation of the simplified spherical harmonics approximation for cone-beam X-ray luminescence computed tomography imaging

Haibo Zhang1, Guohua Geng1、*, Yanrong Chen1, Fengjun Zhao1, Yuqing Hou1, Huangjian Yi1, Shunli Zhang1, Jingjing Yu2, and Xiaowei He1
Author Affiliations
  • 1School of Information Sciences and Technology, Northwest University, Xi'an, Shannxi 710027, P. R. China
  • 2School of Physics and Information Technology, Shaanxi Normal University, Xi'an, Shannxi 710062, P. R. China
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    As an emerging molecular imaging modality, cone-beam X-ray luminescence computed tomography (CB-XLCT) uses X-ray-excitable probes to produce near-infrared (NIR) luminescence and then reconstructs three-dimensional (3D) distribution of the probes from surface measurements. A proper photon-transportation model is critical to accuracy of XLCT. Here, we presented a systematic comparison between the common-used Monte Carlo model and simplified spherical harmonics (SPN). The performance of the two methods was evaluated over several main spectrums using a known XLCT material. We designed both a global measurement based on the cosine similarity and a locally-averaged relative error, to quantitatively assess these methods. The results show that the SP3 could reach a good balance between the modeling accuracy and computational e±ciency for all of the tested emission spectrums. Besides, the SP1 (which is equivalent to the diffusion equation (DE)) can be a reasonable alternative model for emission wavelength over 692 nm. In vivo experiment further demonstrates the reconstruction performance of the SP3 and DE. This study would provide a valuable guidance for modeling the photon-transportation in CB-XLCT.

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    Haibo Zhang, Guohua Geng, Yanrong Chen, Fengjun Zhao, Yuqing Hou, Huangjian Yi, Shunli Zhang, Jingjing Yu, Xiaowei He. Performance evaluation of the simplified spherical harmonics approximation for cone-beam X-ray luminescence computed tomography imaging[J]. Journal of Innovative Optical Health Sciences, 2017, 10(3): 1750005

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    Paper Information

    Received: Sep. 23, 2016

    Accepted: Dec. 14, 2016

    Published Online: Dec. 27, 2018

    The Author Email: Geng Guohua (ghgeng@nwu.edu.cn)

    DOI:10.1142/s1793545817500055

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