This PDF file contains the front matter associated with SPIE Proceedings Volume 6855, including the Title Page, Copyright information, Table of Contents, Introduction, and the Conference Committee listing.

The ultimate objective of laser speckle flowmetry (and a host of specific implementations such as Laser Speckle Contrast Analysis-LASCA or LSCA, Laser Speckle Spatial Contrast Analysis-LSSCA, Laser Speckle Temporal Contrast Analysis-LSTCA, etc.) is to infer flow velocity from the observed speckle contrast. A proper inversion of this association depends critically on the correct model for the statistical relationship between motion of the scatterers and the resulting spatial and temporal speckle contrast. Many researchers use the Lorentzian model for such a relationship. In fact, the Lorentzian is a homogeneous line profile appropriate only for Brownian motion. In such a case, the dynamics of a single particle are representative of the ensemble. The other extreme is an inhomogeneous (Gaussian) profile which corresponds to a process in which the dynamics are particular to the individual scatterers. The proper model for complex motion such as blood flow is undoubtedly intermediate between these two extremes. One such model for the net effect of these two stochastically independent processes is a Voigt profile. In this paper we explore the quantitative relationship between the statistics of speckle contrast and ordered flow. The study addresses the effects of speckle size relative to that of the pixel, temporal integration time relative to the decorrelation times associated with ordered and un-ordered motion, and the spatio-temporal processing schemes used to quantify speckle contrast.

Noninvasive assessments of optical clearing and permeability coefficients of tissues pose great possibilities in advanced diagnostics and medical applications. In order for both of these to become utilized in common practice, a greater understanding of molecular diffusivity in multi-layered tissues is required. In biological tissues, the different layers are comprised of differentiated cells and/or collagen fibrils which come together to form that specific layer. Therefore, a patchwork of layers is created each with its own set of properties. In our current study we analyze and describe the dynamics of matter diffusion and its underlying non-linear character in various epithelial tissues. For instance, the permeability coefficient (PC) of 20% concentrated mannitol in the rabbit eye sclera showed an increasing trend as it was measured deeper into the tissue. The PC was found to be 2.18 × 10^-6 cm/sec at 50 μm away from the epithelial layer. It increased to about 7.33 × 10^-6 cm/sec when it was computed at 210 μm from the epithelial layer. Different layers in the sclera showed different clearing response to glucose solution as well. The first 100 μm region from the epithelial layer cleared about 10% whereas the next 100 μm cleared about 17-22%. The importance of this study is that it may offer a novel explanation to how a layer's composition affects optical clearing and the permeability coefficient of analytes and solutions.

The speckle phenomenon is observed in any coherent imaging modality such as synthetic aperture radar, optical coherence tomography, ultrasound, or any number of measurement schemes involving laser illumination. Quantitative interpretation of the data from such measurement schemes (whether imaging or non-imaging) often hinges on accurate knowledge of the statistical behavior of the speckle phenomenon. To complement experimental measurements, researchers often turn to computer simulation of the phenomenon of interest. Over the years we have developed a variety of algorithms for simulating objective and subjective speckle for static and dynamic object fields. In this paper we detail the implementation of these algorithms and illustrate their use in a range of applications that include Electronic Speckle Pattern Interferometry (ESPI), Laser Speckle Imaging (LSI), Optical Coherence Tomography (OCT), etc.

Near infrared spectroscopy (NIRS) of tissue offers remarkable advantages over other imaging modalities. These are not only the low cost of equipment and high temporal resolution, but also a possibility to create very light and mobile devices, which can be used virtually at any conditions.

Our integrated computer-aided detection (CAD) scheme includes three basic modules. The first module detects whether a microscopic digital image depicts a metaphase chromosome cell. If a cell is detected, the scheme will justify whether it is analyzable with a decision tree. Once an analyzable cell is detected, the second module is applied to segment individual chromosomes and to compute two important features. Specifically, the scheme utilizes a modified thinning algorithm to identify the medial axis of a chromosome. By tracking perpendicular lines along the medial axis, the scheme computes four feature profiles, identifies centromeres, and assigns polarities of chromosomes based on a set of pre-optimized rules. The third module is followed to classify chromosomes into 24 types. In this module, each chromosome is initially represented by a vector of 31 features. A two-layer classifier with 8 artificial neural networks (ANN) is optimized by a genetic algorithm. A testing chromosome is first classified into one of the seven groups by the ANN in the first layer. Another ANN is then automatically selected from the seven ANNs in the second layer (one for each group) to further classify this chromosome into one of 24 types. To test the performance and robustness of this CAD scheme, we randomly selected and assembled an independent testing dataset. The dataset contains 100 microscopic digital images including 50 analyzable and 50 un-analyzable metphase cells identified by the experts. The centromere location, the corresponding polarity, and karyotype for each individual chromosome were recorded in the "truth" file. The performance of the CAD scheme applied to this image dataset is analyzed and compared with the results in the true file. The assessment accuracies are 93% for the first module, 90.8% for centromere identification and 93.2% for polarity assignment in the second module, over 96% for six chromosome groups and 81.8% for one group in the third module, respectively. These accuracy levels are very comparable with those achieved during our previous studies to develop and optimize these CAD modules. Hence, the study demonstrates that our automated scheme can achieve high and robust performance in identification and classification of metaphase chromosomes.

An important parameter in medical diagnostic and one of the most frequently determined analyte in the hospitals is blood glucose. Fast and accurate methods of measuring blood glucose concentrations could therefore be significant. We will in this paper investigate the feasibility of using a spatially resolved steady-state diffuse reflectance spectroscopy in the wavelength region 1000-1700nm, where glucose has two absorption peaks at around 1250nm and 1600nm, to quickly determine the concentration of glucose in tissue-like material. This method could later be transferred to estimate the amount of glucose in blood both in vivo e.g. the forearm and in vitro e.g. on blood samples. The novel spatially resolved system that is used for this study is based around a 2D InGaAs detector and a fibre probe with 10 fibres, one as a source and 9 to collect the diffuse reflected light at distances between 0.3-2.7mm from the source. An inversion method using Monte Carlo generated diffuse reflectance profiles is used to estimate the absolute absorption coefficient (μ_a) and reduced scattering coefficient (μ_s') which could be used to estimate the glucose concentration in the tissue-like phantoms. The method was investigated by performing spatially resolved measurements on turbid gelatin phantoms containing mixtures of water and D₂O as absorbers, Intralipid as a scatterer and glucose. The phantoms were made with four different glucose concentrations spanning the range of 0-5000 mg/dl.

A new noninvasive optical angiography, optical micro-angiography (OMAG), is recently developed. Three-dimensional flow image has been performed with Optical Angiography. The bulk motion artifacts caused by the bulk motion movement were eliminated by compensating phase varieties with Doppler shift due to the bulk motion. This method enhanced the quality of flow image greatly and has the capability of resolving three dimensional (3-D) distribution of dynamic blood perfusion at the capillary level within microcirculatory beds in vivo. The imaging contrast of blood perfusion is based on the endogenous light scattering from the moving blood cells biological tissue; thus no exogenous contrasting agents are necessary. In this paper, we presented the application of this method to visualize the 3D vasculature of ocular vessels for in vivo human retinal imaging. Depth-resolved volumetric views of the retina and choroid vasculatures are also obtained by 1) segmenting the retina and choroid layers from the OCT micro-structure images to produce two masks, 2) apply the resulted two masks onto the 3D flow image to result en-face projection views of the blood vessel networks in retina and choroid. We compare the results with those from Doppler OCT and optical coherence angiography, and show that OMAG delivers superior imaging performance.

Doppler Optical Coherence Tomography (DOCT) technique was applied to non-invasive monitoring of cross-sectional velocity profiles distributions within complex geometry vessels. A set of micro vessels of different diameters with T-shaped and Y-shaped bifurcation and vessels with aneurysm were built. The shape of the vessel was chosen to mimic human vessel shapes of similar characteristics. Intralipid, set in motion at constant input volume flow rate by a syringe pump, was used in the experiments. The influence of vessels geometry, including bifurcation (T- and Y- junctions) and the aneurysms, on the flow dynamics under different inlet flow rates was studied. We show that under constant input volume flow rate, the flow velocities distribution measured along a cross-sectional plane orthogonal to the inlet arm, located at 20 mm off the junction, exhibited stationary and laminar behaviour. A non-homogeneous distribution of flow velocity along a cross-sectional plane located at the junction was observed. The relation between the acquired velocity distribution and the vessel geometry is analyzed. The feasibility of DOCT for mapping the velocity profiles along the vessels junction with a spatial resolution of about 10×10×10 μm³ and a minimum detectable velocity of about 2 mm·s^-1 is presented.

Our analysis of spectral behavior of time-variant optical characteristics caused by RBC aggregation is applied to issues of non-invasive blood monitoring. Modulations of blood flow cause the change in geometry of RBC aggregates and corresponding variance of light scattering. This changes cause the variation of optical transmission, reflection, and polarization of outcoming light. The last can be translated back in absorption coefficients of various blood constituents, refractive index mismatch, etc. For instance, in case of long occlusion simultaneous measurements of both the azimuthal angle and the ellipticity of outcoming light can provide sufficient data to determine the blood glucose.

We present an application of custom-designed Dynamic Light Scattering Imager (DLSI) in combination with conventional fluorescence intravital microscope (FIVM). The proposed technology was used for simultaneous examination of blood and lymphatic vessels in the mouse ear or tumor development. DLSI comprised a 650 nm diode laser with beam expander. Temporal fluctuations of laser interference pattern were used for rendering blood vessels anatomy and perfusion with a high spatial resolution. Concomitantly, various fluorescent contrast materials were used for labeling and visualization of lymphatic vessels or the tumor cells. The modular design of FIVM-DLSI allowed easy switching between different models of microscopes while conventional image sensors could be employed for both fluorescence and DLS imaging. We demonstrated that coupling with DLSI expands the fluorescent microscope imaging capabilities and does not compromise its ability to image with a high spatial resolution.

Both neuroscience and nonlinear science have focused attention on the dynamics of the neural network. However, litter is known concerning the electrical activity of the cultured neuronal network because of the high complexity and moment change. Instead of traditional methods, we use chaotic time series analysis and temporal coding to analyze the spontaneous firing spike train recorded from hippocampal neuronal network cultured on multi-electrode array. When analyzing interspike interval series of different firing patterns, we found when single spike and burst alternate, the largest Lyapunov exponent of interspike interval (ISI) series is positive. It suggests that chaos should exist. Furthermore, a nonlinear phenomenon of bifurcation is found in the ISI vs. number histogram. It determined that this complex firing pattern of neuron and the irregular ISI series were resulted from deterministic factors and chaos should exist in cultured term.These results suggest that chaotic time series analysis and temporal coding provide us effective methods to investigate the role played by deterministic and stochastic component in neuron information coding, but further research should be carried out because of the high complexity and remarkable noise of the electric activity.

We proposed a novel time-resolved optical tomography, optical coherence computed tomography. It married the key concepts of time-resolved diffuse optical tomography and optical coherence tomography. Both ballistic and multiple-scattered photons were measured at multiple source-detection positions by low-coherence interferometry. It measures the reemitted light with a temporal resolution of 56 femtoseconds, which is much better than the resolution of conventional time-resolved detection systems. A light-tissue interaction model was established using the time-resolved Monte Carlo method. The optical properties were then reconstructed by solving the inverse time-resolved radiative transport problem under the first Born approximation. Our initial results showed the potential of this technology to bridge the gap between diffuse optical tomography and optical coherence tomography.

Biological systems typically exhibit multimode oscillations and generate signals demonstrating a coexistence of rhythmic components. The coexistence of independent modes often leads to various forms of their interaction and entrainment. Difficulties of experimental studies of interaction phenomena are often caused by the nonstationarity of available biological data and by the resolution abilities of a numerical technique being used. Thus, time-varying methods have some limitations in resolving the modes whose frequencies are quite close. In our work we investigate opportunities of the wavelet-analysis in the study of coexisting rhythmic processes. Using chirp-signals we demonstrate how the possibility to estimate the instantaneous frequency depends on the rate of its change. Further, we show how the wavelet-based approach provide information about interaction phenomena in kidney autoregulation. We report clear distinctions in the autoregulation mechanisms for normotensive and hypertensive rats.

A new set of conversion coefficients from kerma free-in-air to absorbed dose and to effective dose for external photon exposure with incident energies between 15 keV and 10 MeV under six standard irradiation geometries have been calculated using the Visible Chinese Human (VCH) computational model, which was developed on purpose of radiation dosimetry and protection. The whole-body voxelized geometry of VCH was mirrored from the high quality cryosectional photographic color images and was representative for the average physical characteristics of Chinese population. Dose discrepancies in comparison with other datasets are mainly due to anatomical differences. Detailed results from the VCH model are able to complement current dosimetric data in the realm of Radiology. The investigation on simulative particle transport and dosimetry calculation provides quantitative references for the study of anthropomorphic models.

A new interference scheme of low-coherent interferometry was considered. This interference system does not use a special supporting beam. An object is lighted up by optical field directly from source of light. Back-scattered radiation is put to correlation analysis using Michelson scanning interferometer. Such unsupported interference system has a number of advantages, e.g. conducting experiments in vivo. A comparison of spatial sensitivity of OCT and HRT tomographs resolution was made during identification of local inhomogeneity in presence of nanoshells and nanorods in bio-phantoms and bio-tissues. Plasmon-resonant gold nanoparticles can be used as a new class of contrast agents in OCT diagnostics. The theoretical part of our study was to simulate the backscattering signal related to the process of electromagnetic wave propagation through a system of discrete scattering particles with consideration the effects of different scattering multiplicity. By using the computer Monte Carlo simulations, we calculated the spectra of collimated transmission, diffuse forward and back scattering for the systems of gold spherical particles and shells.

We show that robustness of sorting of neural spikes using the wavelet transform depends strongly on the statistics of experimental noise and the characteristic time scales of spike waveforms. Incorporating adaptive filtering of the extracellular potential into the wavelet sorting algorithm we propose a novel method, the Parametric Wavelet sorting with Advanced Filtering (PWAF), whose classification error approaches the theoretical minimum. Efficiency of the proposed technique is proved with both simulated and real electrophysiological recordings.