  Optical molecular tomographic imaging is to reconstruct the concentration
distribution of photon-molecular probes in a small animal from measured photon
fluence rates. The localization and quantification of molecular probes is
related to tissue optical properties. The optical parameters can be
reconstructed by the optimization method, in which the objective function is
not convex, and there are multiple local optimal solutions. The gradient-based
optimization algorithm could converge prematurely to an inaccurate solution if
the initial guess is not close enough to the true solution. In this paper, we
develop a hybrid algorithm combined global optimization and gradient-based
optimization methods to reconstruct optical parameters. Differential evolution
is an effective global optimizer, and could yield an estimated solution near
the global optimal region to eliminate the need of initial guess of the optical
parameters. The gradient-based optimization method is further performed with
initial values obtained from DE to obtain local optimal solution for more
accurate reconstruction of optical parameters. This proposed reconstruction
method is evaluated by comprehensive numerical simulation experiments. The
results show that the proposed method is stable and accurate for the
reconstruction of optical parameters.
