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journal article·2020-10-01Open access

Effective reconstruction of bioluminescence tomography based on GPU-accelerated inverse Monte Carlo method

Shenghan Ren, Lin Wang, Qi Zeng, Duofang Chen, Xueli Chen, Jimin Liang

AIP Advances· Volume 10· Issue 10
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Source abstract

Abstract

Diffusion equations (DEs) or simplified spherical harmonic equations are commonly used forward models in bioluminescence tomography (BLT), which are usually numerically calculated by the finite element method to construct the system matrix for reconstruction. However, the numerical solver is not accurate enough. The Monte Carlo (MC) method is regarded as the golden standard for modeling light propagation in biological tissue. In this paper, we proposed a GPU-accelerated inverse MC method for BLT reconstruction. The main feature is that the system matrix for BLT reconstruction is calculated by the MC method instead of the model-based numerical approximation. We evaluated the performance of the proposed method with both phantom-based simulation and animal-based in vivo experiment. The results show that, compared with the DE-based method, the proposed GPU-accelerated inverse MC method is more accurate and effective in BLT reconstruction.
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Research context

OpenAlex topics: Optical Imaging and Spectroscopy Techniques · Photoacoustic and Ultrasonic Imaging · Non-Invasive Vital Sign Monitoring

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Engineering Research Center of Molecular and Neuro Imaging of Ministry of Education 1 , Xi’an, Shaanxi 710126, China

School of Life Science and Technology, Xidian University 2 , Xi’an, Shaanxi 7101261, China

School of Information Sciences and Technology, Northwest University 3 , Xi’an, Shaanxi 710127, China

School of Electronic and Engineering, Xidian University 4 , Xi’an, Shaanxi 7101261, China

Funding

National Key R&D Program of China · National Natural Science Foundation of China · Shaanxi Science Fund for Distinguished Young Scholars · Program for the Young Top-Notch Talent of Shaanxi Province · Natural Science Basic Research Plan in Shaanxi Province of China · China Scholarship Council

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