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Hybrid reconstruction method for multispectral bioluminescence tomography with log-sum regularization.

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    Journal of the Optical Society of America. A, Optics, Image Science, and Vision
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    Bioluminescence tomography (BLT) reconstruction is challenging. A novel hybrid optimization algorithm (HONOR) improves stable and efficient source recovery for preclinical studies.

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    Area of Science:

    • Biomedical Imaging
    • Medical Physics
    • Optical Imaging

    Background:

    • Bioluminescence tomography (BLT) is crucial for preclinical in vivo visualization of pathological processes.
    • BLT reconstruction is an ill-posed problem, requiring advanced algorithms for accurate source localization.

    Purpose of the Study:

    • To develop a stable and efficient method for bioluminescence source reconstruction in BLT.
    • To address the ill-posed nature of BLT reconstruction using a novel regularization and optimization approach.

    Main Methods:

    • Utilized a log-sum regularization term within the objective function.
    • Implemented a hybrid optimization algorithm (HONOR) combining quasi-Newton (QN) and gradient descent steps.
    • Employed the limited-memory Broyden-Fletcher-Goldfarb-Shanno (L-BFGS) algorithm for QN steps to incorporate second-order information.

    Main Results:

    • Demonstrated remarkable performance in sparse reconstruction of BLT.
    • Validated the method through simulations and in vivo multispectral experiments.
    • Achieved stable and efficient recovery of bioluminescence sources.

    Conclusions:

    • The proposed HONOR hybrid optimization method significantly enhances BLT reconstruction accuracy.
    • This approach offers a robust solution for in vivo preclinical imaging applications.
    • The integration of first- and second-order information improves the ill-posed problem of BLT reconstruction.