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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.

Recent advances in the development of ultra-compact semiconductor lasers and technology of printed flexible hybrid electronics have opened broad perspectives for the design of new pulse oximetry and photoplethysmography devices. Conceptual design of optical diagnostic devices requires careful selection of various technical parameters, including spectral range; polarization and intensity of incident light; actual size, geometry, and sensitivity of the detector; and mutual position of the source and detector on the surface of skin. In the current study utilizing a unified Monte Carlo computational tool, we explore the variations in diagnostic volume due to arterial blood pulsation for typical transmitted and back-scattered probing configurations in a human finger. The results of computational studies show that the variations in diagnostic volumes due to arterial pulse wave are notably (up to 45%) different in visible and near-infrared spectral ranges in both transmitted and back-scattered probing geometries. While these variations are acceptable for relative measurements in pulse oximetry and/or photoplethysmography, for absolute measurements, an alignment normalization of diagnostic volume is required and can be done by a computational approach utilized in the framework of the current study.

We explore the propagation of the cylindrical vector beams (CVB) in turbid tissue-like scattering medium in comparison with the conventional Gaussian laser beam. The study of propagation of CVB and Gaussian laser beams in the medium is performed utilizing the unified electric field Monte Carlo model. The implemented Monte Carlo model is a part of a generalized on-line computational tool and utilizes parallel computing, executed on the NVIDIA Graphics Processing Units (GPUs) supporting Compute Unified Device Architecture (CUDA). Using extensive computational studies, we demonstrate that after propagation through the turbid tissue-like scattering medium, the degree of fringe contrast for CVB becomes at least twice higher in comparison to the conventional linearly polarized Gaussian beam. The results of simulations agree with the results of experimental studies. Both experimental and theoretical results suggest that there is a high potential of the application of CVB in the diagnosis of biological tissues.

Path tracing is a well-established technique for photo-realistic rendering to simulate light path transport. This method has been widely adopted in visual effects industries to generate high quality synthetic images requiring a large number of samples and a long computation time. Due to the high cost to produce the final output, intermediate previsualization of path tracing is in high demand from production artists to detect errors in the early stage of rendering. But visualizing intermediate results of path tracing is also challenging since the synthesized image with limited samples or improper sampling usually suffers from distracting noise. The ideal solution would be to provide a highly plausible intermediate result in the early stages of rendering, using a small fraction of samples, and apply a posteriori manner to approximate the ground truth. In this thesis, this issue is addressed by providing several efficient posteriori reconstructions and denoising technique for previsualization of pa-th tracing. Firstly, we address the problem for the recovery of the missing values to construct low rank matrices for incomplete images including missing pixel, missing sub-pixel, and multi-frame scenarios. A novel approach utilizing a convolutional neural network which provides fast precompletion for initializing missing values, and subsequent weighted nuclear norm minimization with a parameter adjustment strategy efficiently recovers missing values even in high frequency details. The result shows better visual quality compared to the recent methods including compressed sensing based reconstruction. Furthermore, to mitigate the computation budgets of our new approac-h, we extend our method by applying a block Toeplitz structure forming a low-rank matrix for pixel recovery, and tensor structure for multi-frame recovery. In this manner, the reconstruction time can be significantly reduced. Besides that, by exploiting temporal coherence of multi-frame with a tensor structure

We introduce a noninvasive diagnostic approach for functional monitoring of blood microflows in capillaries and thermoregulatory vessels within the skin. The measuring system is based on the combined use of laser Doppler flowmetry and skin contact thermometry. The obtained results suggest that monitoring of blood microcirculation during the occlusion, performed in conjunction with the skin temperature measurements in the thermally stabilized medium, has a great potential for quantitative assessment of angiospatic dysfunctions of the peripheral blood vessels. The indices of blood flow reserve and temperature response were measured and used as the primarily parameters of the functional diagnostics of the peripheral vessels of skin. Utilizing these parameters, a simple phenomenological model has been suggested to identify patients with angiospastic violations in the vascular system.