Fluorescence diffuse optical tomography (fDOT) is an imaging
modality that provides images of the fluorochrome distribution within
the object of study. The image reconstruction problem is ill-posed and
highly underdetermined and, therefore, regularisation techniques need to be
used. In this paper we use a nonlinear anisotropic diffusion regularisation
term that incorporates anatomical prior information. We introduce a split
operator method that reduces the nonlinear inverse problem to two simpler
problems, ...
Fluorescence diffuse optical tomography (fDOT) is an imaging
modality that provides images of the fluorochrome distribution within
the object of study. The image reconstruction problem is ill-posed and
highly underdetermined and, therefore, regularisation techniques need to be
used. In this paper we use a nonlinear anisotropic diffusion regularisation
term that incorporates anatomical prior information. We introduce a split
operator method that reduces the nonlinear inverse problem to two simpler
problems, allowing fast and efficient solution of the fDOT problem. We
tested our method using simulated, phantom and ex-vivo mouse data, and
found that it provides reconstructions with better spatial localisation and
size of fluorochrome inclusions than using the standard Tikhonov penalty
term.
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