T. Quang

Integrative paradigms bridging defense and bioscience

The objective of the study is to present integrative paradigms highlighting their applicability of polarimetry to multidisciplinary areas such as space defense and bioscience applications. Polarimetric sensing and imaging offer unique advantages for a wide range of detection and classification problems due to the intrinsic potential for high contrast in different polarization components of the backscattered light. Indeed, polarized imaging can yield high-specificity images under high-dynamic range and extreme condition scenarios, in scattering media, or cluttered environments, offering at the same instance information related to the object material composition and its surface characteristics. In this study, a new imaging approach based on polarimetric detection principles will be introduced and the Mueller matrix formalism will be defined, and will be applied for space applications, such as detection of unresolved objects, as well as for early cancer detection. The design principles of the liquid crystal polarimetric imaging system will be introduced and related to operating conditions and system performance metrics. The depolarization, diattenuation, and retardance of the materials will be estimated using Mueller matrix decomposition for different aspect angles.

Integrated quantitative fractal polarimetric analysis of monolayer lung cancer cells

Digital diagnostic pathology has become one of the most valuable and convenient advancements in technology over the past years. It allows us to acquire, store and analyze pathological information from the images of histological and immunohistochemical glass slides which are scanned to create digital slides. In this study, efficient fractal, wavelet-based polarimetric techniques for histological analysis of monolayer lung cancer cells will be introduced and different monolayer cancer lines will be studied. The outcome of this study indicates that application of fractal, wavelet polarimetric principles towards the analysis of squamous carcinoma and adenocarcinoma cancer cell lines may be proved extremely useful in discriminating among healthy and lung cancer cells as well as differentiating among different lung cancer cells.

Bioinformatics of Lung Cancer

The objective of this study is to explore novel bioinformatics techniques, namely, the Polarimetric Exploratory Data Analysis (pEDA), for early identification and discrimination of precancerous and cancerous lung tissues. The outcome of this study indicates that the full-width-at half maximum (FWHM) and Dynamic Range (DR) extracted from histograms of inherent (label-free) near infrared (NIR) diffused-polarimetric reflectance signals provide an important metrics for the characterization of cancerous tissue. Application of pEDA on the acquired data has been proved an effective diagnostic tool aimed at discriminating optical information among normal, precancerous, and cancerous lung tissue samples. Therefore, it can eventually be proved a useful diagnostic tool in the early detection of Non-Small Cell Lung Cancer (NSCLC) as well as in classical cytopathology and histopathology.

Lung cancer pathology discrimination techniques using time series analysis

The goal of this study is to discover, analyze, compare, and interpret diffused reflectance polarimetric signatures from lung cancer cells through time series analysis techniques, by using recently invented efficient polarimetric backscattering detection techniques. Specifically, different time series analyses, relying on linear and generalized linear modeling, have been investigated, with special emphasis on the Granger test for the time series. The experimental results indicate that statistically enhanced discrimination between normal and different types of lung cancer cells and stages can be achieved based on the pairwise comparisons of the time series diffused reflectance signal intensities and depolarization properties of the cells.

An automated digital fluorescence imaging system of tumor margins using clustering-based image thresholding

An optical system for efficient fluorescence imaging of cancer margins aiming at enhanced discrimination of the tumor area from the surrounding normal tissue, is presented. Fluorescence imaging was used to acquire grayscale images of brain tumor samples of 10 μm slice thickness. The tumor cells are characterized as Gli36Δ5 cells expressing Green Fluorescent Protein (GFP). An image processing technique involving the clustering-based concept of Otsu segmentation was applied to enhance the contrast and difference between the tumor and the rest of the tissue for improved visualization of tumor margins. Edge detection was performed on these processed images to mark the boundaries of the tumor area. The fluorescence imaging results depict clear demarcation of tumor boundary and a substantial improvement of the contrast, post processing.

Label-free discrimination of lung cancer cells through mueller matrix decomposition of diffuse reflectance imaging

Abstract In this article, we explore the potential of an original label-free Near-Infrared (NIR) imaging technique, based on Mueller Matrix decomposition reflectance, for efficient detection and classification of histopathological samples of lung cancer cells. Experimental results were acquired, processed, and analyzed by means of an accurate, fully-automated, auto-calibrated liquid-crystal NIR polarimetric imaging system, developed for real-time Mueller matrix analysis and optical characterization of target media. The polarimetric Figure-of-Merits (FOMs), estimated using Mueller matrix decomposition, as well as the statistics associated with the sixteen Mueller matrix elements of each lung cell sample indicate that enhanced discrimination among the samples can be achieved. Similarly, polarimetric Exploratory Data Analysis (pEDA), based on histograms obtained from diffuse reflectance polarimetric signals, has been used to determine if aberrations and/or changes in the spread of the histogram between different stages of lung cancer can be proved effective biomarkers for its progression and also discrimination among different lung pathologies. The outcome of this study indicates that Mueller matrix formalism may be proved extremely useful in discriminating among healthy and malignant lung cells as well as differentiating among the different types of malignancies with high accuracy. As a result, it may contribute positively to the enhancement and implementation of the operational principles of the Whole Slide Imaging (WSI) field.

Fluorescence Imaging Topography Scanning System for intraoperative multimodal imaging

Fluorescence imaging is a powerful technique with diverse applications in intraoperative settings. Visualization of three dimensional (3D) structures and depth assessment of lesions, however, are oftentimes limited in planar fluorescence imaging systems. In this study, a novel Fluorescence Imaging Topography Scanning (FITS) system has been developed, which offers color reflectance imaging, fluorescence imaging and surface topography scanning capabilities. The system is compact and portable, and thus suitable for deployment in the operating room without disturbing the surgical flow. For system performance, parameters including near infrared fluorescence detection limit, contrast transfer functions and topography depth resolution were characterized. The developed system was tested in chicken tissues ex vivo with simulated tumors for intraoperative imaging. We subsequently conducted in vivo multimodal imaging of sentinel lymph nodes in mice using FITS and PET/CT. The PET/CT/optical multimodal images were co-registered and conveniently presented to users to guide surgeries. Our results show that the developed system can facilitate multimodal intraoperative imaging.

Polymer Nanostructure Materials for Space Defense Applications

The unique functional characteristics of nanostructured material are stemming mainly from a large surface-to-volume-ratio and on quantum effects; can yield numerous potential space defense applications. The objective of this study is to explore the polarimetric characterization of polymer nanomaterials, using Mueller matrix and Stokes parameters analysis. Specifically, gold nanoparticles were dispersed within a matrix of two-different polymer domains and their polarimetric response to infrared light was studied.

Bioinspired Polarization Navigation Sensor for Autonomous Munitions Systems

Small unmanned aerial vehicles UAVs (SUAVs), micro air vehicles (MAVs), Automated Target Recognition (ATR), and munitions guidance, require extreme operational agility and robustness which can be partially offset by efficient bioinspired imaging sensor designs capable to provide enhanced guidance, navigation and control capabilities (GNC). Bioinspired-based imaging technology can be proved useful either for long-distance surveillance of targets in a cluttered environment, or at close distances limited by space surroundings and obstructions. The purpose of this study is to explore the phenomenology of image formation by different insect eye architectures, which would directly benefit the areas of defense and security, on the following four distinct areas: a) fabrication of the bioinspired sensor b) optical architecture, c) topology, and d) artificial intelligence. The outcome of this study indicates that bioinspired imaging can impact the areas of defense and security significantly by dedicated designs fitting into different combat scenarios and applications.