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Smart Toolkit for Fluorescence Tomography: Simulation, Reconstruction, and Validation.

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    A new software package, STIFT, automates fluorescence molecular tomography (FMT) reconstruction. This toolkit bridges simulation, data acquisition, and reconstruction, enhancing FMT experiments for routine biomedical research.

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    Area of Science:

    • Biomedical Imaging
    • Molecular Imaging
    • Computational Biology

    Background:

    • Fluorescence molecular tomography (FMT) offers insights into molecular distribution in vivo.
    • Existing FMT systems lack standardization for routine biomedical research.
    • Automation of FMT reconstruction is needed to improve accessibility and reproducibility.

    Purpose of the Study:

    • To develop a software package for automating the complete fluorescence molecular tomography (FMT) reconstruction procedure.
    • To create a comprehensive platform integrating simulation, data acquisition control, and experimental data reconstruction for FMT.

    Main Methods:

    • Introduction of the Smart Toolkit for Fluorescence Tomography (STIFT).
    • STIFT includes protocols for virtual FMT (simulated data), control of actual FMT data acquisition, and reconstruction of experimental FMT data.

    Main Results:

    • STIFT demonstrated robust reconstruction results in both simulation and phantom experiments.
    • Effective reconstruction was achieved for homogeneous and heterogeneous tissue-mimicking phantoms with fluorescent inclusions.

    Conclusions:

    • STIFT facilitates FMT experiments by automating the reconstruction process.
    • The toolkit aids in optimizing FMT experimental parameters, such as illumination patterns.
    • STIFT bridges the gap between FMT simulation, experimental acquisition, and data reconstruction, promoting wider adoption.