Application of multiple artificial neural networks for the determination of the optical properties of turbid media.

We determined the optical properties of turbid media from simulated spatially resolved reflectance (SRR) curves using an artificial neural network (ANN). In order to improve the performance of our method, multiple ANNs were applied for this problem. First, Monte Carlo (MC) simulations were performed using random optical properties which are relevant for biological tissue. For a better performance of the ANN in respect of SRR measurements, the exact setup geometry was taken into account for the MC simulations. Second, the performed simulations were classified into different categories according to their shape. Third, multiple ANNs which were adjusted to these categories, were used to solve the inverse problem, i.e., the determination of the optical properties from SRR curves. Finally, these ANNs were applied to determine the optical properties of simulated SRR curves out of the range 0.5 mm(-1) < μ(s)(') < 5  mm(-1) and 0.0001 mm(-1) < μ(a)<1 mm(-1). The average relative error was 2.9% and 6.1% for the reduced scattering coefficient μs' and for the absorption coefficient μ(a), respectively.