We developed a compact, hand-held hyperspectral imaging system for 2D neural network-based visualization of skin chromophores and blood oxygenation. State-of-the-art microoptic multichannel matrix sensor combined with the tunable Fabry-Perot micro interferometer enables a portable diagnostic device sensitive to the changes of the oxygen saturation as well as the variations of blood volume fraction of human skin. Generalized object-oriented Monte Carlo model is used extensively for the training of an artificial neural network utilized for the hyperspectral image processing. In addition, the results are verified and validated via actual experiments with tissue phantoms and human skin in vivo. The proposed approach enables a tool combining both the speed of an artificial neural network processing and the accuracy and flexibility of advanced Monte Carlo modeling. Finally, the results of the feasibility studies and the experimental tests on biotissue phantoms and healthy volunteers are presented.

We show, through visible-range Mueller polarimetry, as well as numerical simulations, that the depolarization in a homogeneous turbid medium consisting of submicron spherical particles follows a parabolic law with the path-length traveled by light through the medium. This result is in full agreement with the phenomenological theory of the fluctuating medium within the framework of the differential Mueller matrix formalism. We further found that the standard deviations of the fluctuating elementary polarization properties of the medium depend linearly on the concentration of particles. These findings are believed to be useful for the phenomenological interpretation of polarimetric experiments, with special emphasis on biomedical applications.

The decomposition of the Mueller matrix of blood films has been carried out using differential matrices with polarized and depolarized parts. The use of a coherent reference wave is applied and the algorithm of digital holographic reconstruction of the field of complex amplitudes is used. On this basis, the 3D Mueller-matrix diffuse tomography method—the reconstruction of distributions of fluctuations of linear and circular birefringence of depolarizing polycrystalline films of human blood is analytically justified and experimentally tested. The dynamics of the change in the magnitude of the statistical moments of the first-fourth order, which characterize layer-by-layer distributions of fluctuations in the phase anisotropy of the blood film, is examined and analyzed. The most sensitive parameters for prostate cancer are the statistical moments of the third and fourth orders, which characterize the asymmetry and kurtosis of fluctuations in the linear and circular birefringence of blood films. The excellent accuracy of differentiation obtained polycrystalline films of blood from healthy donors and patients with cancer patients was achieved.

No abstract

Doppler optical coherence tomography (OCT) is a technique to image tissue morphology and to measure flow in turbid media. In its most basic form, it is based on single (Mie) scattering. However, for highly scattering and dense media multiple and concentration dependent scattering can occur. For Intralipid solutions with varying scattering strength, the effect of multiple and dependent scattering on the OCT signal attenuation and Doppler flow is investigated. We observe a non-linear increase in the OCT signal attenuation rate and an increasingly more distorted Doppler OCT flow profile with increasing Intralipid concentration. The Doppler OCT attenuation and flow measurements are compared to Monte Carlo simulations and good agreement is observed. Based on this comparison, we determine that the single scattering attenuation coefficient µ s is 15% higher than the measured OCT signal attenuation rate. This effect and the distortion of the measured flow profile are caused by multiple scattering. The non-linear behavior of the single scattering attenuation coefficient with Intralipid concentration is attributed to concentration dependent scattering.