In this study, we combine a generalized Tikhonov regularization method with a priori anatomical information
to reconstruct the concentration of fluorophores in mouse with Chronic Obstructive Pulmonary disease (COPD)
from in vivo optical and Magnetic Resonance (MR) measurements. Generalized Tikhonov regularization incorporates
a penalty term in the optimization formulation of the fluorescence molecular tomography (FMT) inverse
problem. Our design involves two penalty terms to make use of a priori anatomical structural information from
segmented MR images. The choice of the penalty terms guide the fluorophores in reconstructed image concentrates
in the region where it is supposed to be and assure smooth flourophore distribution within tissue of same
type and enhances the discontinuities between different tissue types. We compare our results with traditional
Tikhanov regularization techniques in extensive simulations and demonstrate the performance our approach in
vivo mouse data. The results show that the increased fluorophore concentration in the mouse lungs is consistent
with an increased inflammatory response expected from the corresponding animal disease model.
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