A numerical algorithm based on a small-angle approximation of the radiative transfer equation (RTE) is developed to reconstruct scattering characteristics of biological tissues from optical coherence tomography (OCT) images. According to the algorithm, biological tissue is considered to be a layered random medium with a set of scattering parameters in each layer: total scattering coefficient, variance of a small-angle scattering phase function, and probability of backscattering, which fully describe the OCT signal behavior versus probing depth. The reconstruction of the scattering parameters is performed by their variation to fit the experimental OCT signal by the theoretical one using a time-saving genetic algorithm. The proposed reconstruction procedure is tested on model media with known scattering parameters. The possibility to estimate scattering parameters from OCT images is studied for various regimes of OCT signal decay. The developed algorithm is applied to reconstruct optical characteristics of epithelium and stroma for normal cervical tissue and its pathologies, and the potential to distinguish between the types of pathological changes in epithelial tissue by its OCT images is demonstrated.

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We investigate the possibility of using the water-backscattered radiation from a bottom sounding airborne imaging light detection and ranging (lidar) system to determine the surface slope at the point where the laser beam intersects the surface. We show that the refraction angle of the beam can be determined using receivers whose sensitivities vary linearly over their field of view. Equations are derived to estimate the statistical mean and variance values of this refracted angle. We demonstrate that the proposed algorithm improves lidar imaging. Numerical examples with reference to typical marine conditions are given.

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