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• W3206493503 abstract "The traditional finite element method-based fluorescence molecular tomography (FMT)/ X-ray computed tomography (XCT) imaging reconstruction suffers from complicated mesh generation and dual-modality image data fusion, which limits the application of <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>in vivo</i> imaging. To solve this problem, a novel standardized imaging space reconstruction (SISR) method for the quantitative determination of fluorescent probe distributions inside small animals was developed. In conjunction with a standardized dual-modality image data fusion technology, and novel reconstruction strategy based on Laplace regularization and L1-fused Lasso method, the <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>in vivo</i> distribution can be calculated rapidly and accurately, which enables standardized and algorithm-driven data process. We demonstrated the method’s feasibility through numerical simulations and quantitatively monitored <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>in vivo</i> programmed death ligand 1 (PD-L1) expression in mouse tumor xenografts, and the results demonstrate that our proposed SISR can increase data throughput and reproducibility, which helps to realize the dynamically and accurately <italic xmlns:mml=http://www.w3.org/1998/Math/MathML xmlns:xlink=http://www.w3.org/1999/xlink>in vivo</i> imaging." @default.
• W3206493503 created "2021-10-25" @default.
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• W3206493503 date "2022-03-01" @default.
• W3206493503 modified "2023-10-18" @default.
• W3206493503 title "A Fast and Automated FMT/XCT Reconstruction Strategy Based on Standardized Imaging Space" @default.
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• W3206493503 doi "https://doi.org/10.1109/tmi.2021.3120011" @default.
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