In this paper, we explore the use of anatomical information as a guide in the image formation
process of fluorescence molecular tomography (FMT). Namely, anatomical knowledge obtained
from high resolution computed tomography (micro-CT) is used to construct a model for the
diffusion of light and to constrain the reconstruction to areas candidate to contain fluorescent
volumes. Moreover, a sparse regularization term is added to the state-of-the-art least square
solution to contribute to the sparsity of the localization. We present results showing the increase
in accuracy of the combined system over conventional FMT, for a simulated experiment of lung
cancer detection in mice.
Analytically predicting photon paths in real-high
scattering-anisotropic tissues is extremely complex, due to
the significant random scattering events that photons suffer as they traverse the tissue, especially at
boundaries between areas with different optical properties. An statistically correct optical and anatomical
model of photon trajectories inside laboratory animals will therefore improve considerably our understanding
about how light diffuses within the animals, and therefore help us designing efficient experimental setups and
reconstruction algorithms for fluorescence mediated tomography (FMT). Here, we present new simulations of
photon propagation and fluorescence emission in anisotropic media using realistic models of laboratory
animals and a Monte Carlo (MC) based approach. We compare the MC simulation results with an
approximation of the solution of the diffusion equation using finite differences and discuss the different
behaviour of the two methods.
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