Reconstruction of fluorophore concentration distribution in diffuse fluorescence tomography based on Tikhonov regularisation and nonnegativity condition
Abstract:
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.
Keywords:diffuse fluorescence tomography, Tikhonov regularisation, nonnegativity condition for the solution vector, fluorescence molecular imaging.