Fluorescence molecular tomography (FMT) can visualize biological activities at cellular and molecular levels in vivo, and has been extensively used in drug delivery and tumor detection research of small animals. The ill-posedness of the FMT inverse problem makes it difficult to reconstruct and resolve multiple adjacent fluorescent targets that have different functional features but are labeled with the same fluorochrome. An algorithm based on independent component analysis (ICA) for multispectral excited FMT is proposed to resolve multiple fluorescent targets in this study. Fluorescent targets are excited by multispectral excitation, and the three-dimensional distribution of fluorescent yields under the excitation spectrum is reconstructed by an iterative Tikhonov regularization algorithm. Subsequently, multiple fluorescent targets are resolved from mixed fluorescence signals by employing ICA. Simulations were performed and the results demonstrate that multiple adjacent fluorescent targets can be resolved if the number of excitation wavelengths is not smaller than that of fluorescent targets with different concentrations. The algorithm obtains both independent components that provide spatial information of different fluorescent targets and spectral courses that reflect variation trends of fluorescent yields along with the excitation spectrum. By using this method, it is possible to visualize the metabolism status of drugs in different structure organs, and quantitatively depict the variation trends of fluorescent yields of each functional organ under the excitation spectrum. This method may provide a pattern for tumor detection, drug delivery and treatment monitoring in vivo.
Yuan Zhou, Huizhi Guang, Huangsheng Pu, Jiulou Zhang, Jing Bai, and Jianwen Luo, "Multispectral excitation based multiple fluorescent targets resolving in fluorescence molecular tomography," Proc. SPIE 9711, Imaging, Manipulation, and Analysis of Biomolecules, Cells, and Tissues IX, 97111O (Presented at SPIE BiOS: February 17, 2016; Published: 6 April 2016); https://doi.org/10.1117/12.2211337.
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