Optical coherence tomography (OCT) is a promising tool for detecting micro channels, metal prints, defects and delaminations embedded in alumina and zirconia ceramic layers at hundreds of micrometers beneath surfaces. The effect of surface roughness and scattering of probing radiation within sample on OCT inspection is analyzed from the experimental and simulated OCT images of the ceramic samples with varying surface roughnesses and operating wavelengths. By Monte Carlo simulations of the OCT images in the mid-IR the optimal operating wavelength is found to be 4 µm for the alumina samples and 2 µm for the zirconia samples for achieving sufficient probing depth of about 1 mm. The effects of rough surfaces and dispersion on the detection of the embedded boundaries are discussed. Two types of image artefacts are found in OCT images due to multiple reflections between neighboring boundaries and inhomogeneity of refractive index.

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 micro-optic 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.

Monte Carlo method is applied for simulation of 2D optical coherence tomography (OCT) images of skin-like model. Layer boundaries in skin model feature curved shape which agrees with physiological structure of human skin. The effect of coherence properties of probing radiation on OCT image formation and speckles in the detected OCT signal is considered. The developed model is employed for image simulation both for conventional and polarization dependent time-domain OCT modalities. Simulation of polarized OCT signal is performed using vector approach developed previously for modeling of electromagnetic field transfer in turbid media.

The effect of silica/gold nanoshells and titanium dioxide nanoparticles on the optical properties of skin is studied. By implementing in vivo measurements and Monte Carlo simulations, we analyze the efficiency of using these nanoparticles as contrasting agents for optical coherence tomography (OCT) imaging of skin. In vivo measurements are performed on pig skin, where nanoparticle suspension drops have been applied. The identification of skin layers is performed by comparison with corresponding histology images. Experimental results exhibit an increase in contrast of the obtained OCT images after a single nanoparticles application. Multiple applications do not lead to increase in the obtained contrast. To interpret the obtained experimental OCT images of skin and understand the mechanisms of contrasting, a set of Monte Carlo calculations is performed. The results of the simulations exhibit good qualitative agreement with the experimental images, and prove that the contrasting originates from the nanoparticles added, while the contrast of inclusion originates from the absence of nanoparticles within it and their presence in the surrounding area.

The speckle pattern of an optical coherence tomography (OCT) image carries potentially useful sample information that may assist in tissue characterization. Recent biomedical results in vivo indicate that the distribution of signal intensities within an OCT tissue image is well described by a log-normal-like (Gamma) function. To fully understand and exploit this finding, an OCT Monte Carlo model that accounts for speckle effects was developed. The resultant Monte Carlo speckle statistics predictions agree well with experimental OCT results from a series of control phantoms with variable scattering properties; the Gamma distribution provides a good fit to the theoretical and experimental results. The ability to quantify subresolution tissue features via OCT speckle analysis may prove useful in diagnostic photomedicine.

Quantitative image analysis and parameter extraction using a specific implementation of polarization-sensitive optical coherence tomography (OCT) provides differential diagnosis of mucosal pathologies in in-vivo human bladders. We introduce a cross-polarization (CP) OCT image metric called Integral Depolarization Factor (IDF) to enable automatic diagnosis of bladder conditions (assessment the functional state of collagen fibers). IDF-based diagnostic accuracy of identification of the severe fibrosis of normal bladder mucosa is 79%; recurrence of carcinoma on the post-operative scar is 97%; and differentiation between neoplasia and acute inflammation is 75%. The promising potential of CP OCT combined with image analysis in human urology is thus demonstrated in vivo.