We propose to solve the inverse problem of diffuse fluorescence tomography (DFT) – reconstruction of the spatial distribution of the fluorophore in biological tissues – by a method based on Tikhonov regularisation with the nonnegativity condition (TRNC) of the reconstructed components of the solution vector. Model experiments on a biotissue phantom demonstrate that the TRNC method allows for a more accurate reconstruction of the distribution of the fluorophore concentration, and is also more stable in comparison with the known algorithms used in DFT, such as ART, SMART, NNLS, etc.

中文翻译：

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基于Tikhonov正则化和非负性条件的漫射荧光层析成像荧光团浓度分布重建

我们建议解决漫射荧光断层扫描 (DFT) 的逆问题 – 重建生物组织中荧光团的空间分布 – 通过基于 Tikhonov 正则化和解向量重建分量的非负性条件 (TRNC) 的方法。在生物组织体模上的模型实验表明，TRNC 方法可以更准确地重建荧光团浓度的分布，并且与 DFT 中使用的已知算法（如 ART、SMART、NNLS 等）相比也更稳定。