Aditi Deshpande

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.

Electro-Optical Polarimetric Imaging System for Characterization of Resident Space Objects

The design, calibration, and testing of an automated polarimetric imaging system aimed at developing efficient and reliable optical polarimetric characterization techniques of resident space objects, with emphasis on satellite space materials, are introduced. The presented electrooptical imaging polarimeter system exhibits a high degree of accuracy and repeatability. The system’s accuracy is investigated using test materials of well-known optical properties. The outcome of this study indicates that the operational design principles of the optical polarimetric system may prove extremely useful in characterizing remote manmade materials commonly used in space.

Design, Calibration, and Testing of an Automated Near-Infrared Liquid-Crystal Polarimetric Imaging System for Discrimination of Lung Cancer Cells

A newly developed tissue diagnostic method, based on label-free near-infrared (NIR) polarimetric reflectance imaging for the classification of histopathological samples of lung cancer cells, is presented. The design, calibration, and testing of an automated NIR polarimetric imaging system, with emphasis on lung cancer detection, are put forward in detail. The described electro-optical imaging polarimeter system exhibits high degree of accuracy and repeatability. The outcome of this paper indicates that the operational design principles of the NIR polarimetric system may be proved extremely useful in discrimination of label-free normal and lung cancer cell samples as well as differentiation of different lung cancer cells and stages in vitro.

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.

Polarimetric backscattered Mueller matrix bidirectional reflectance distribution function (MmBRDF) for remote inspection of spacecrafts

Thermal insulation of space satellites and space probes often consists of Multi-layer insulation (MLI), composed of multiple layers of Mylar or Kapton coated on one side with a thin layer of metal, typically silver or aluminum. The purpose of this paper is to investigate the optical characteristics of several materials used as integral part in the design of spacecrafts. In this study, preliminary results on the remote interrogation of Mylar layers, using backscattered polarimetric imaging, at different aspect angles, are reported. Specifically, the Mueller matrix of the Bidirectional Reflectance Distribution function (MmBRDF) for Mylar was constructed, based on the estimation of the Mueller matrix (MM) elements, at different aspect angles of the target, under quasi-monostatic geometry. Measurements were performed using an in-house-built, auto calibrated, scalable imaging polarimetric system. The calibration results demonstrate the high quality of the acquired measurements, characterized by stability, and accuracy. The outcome of the study indicates that polarimetric backscattered Mueller matrix enhances significantly the intrinsic merit of our system to monitor, inspect and characterize materials commonly used in space.

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.

Low-order statistical analysis of 1-D diffuse reflectance signals from cancer cells using 2-D scalogram images

The novelty of this study is seen in the efficient characterization of cancer cells through representation of 1-D backscattered signals from cancer cells using statistical analysis on 2-D scalogram images. The proposed approach allows one to obtain a rapid and accurate visualization of the frequency components associated with the backscattered signals; while enlightening the understanding and the physics of the diffuse reflectance light waves interactions with the lung cells, by performing texture characterization and pattern recognition analysis directly on the scalograms.

Design parameters of nanocomposite matrices deposited on silicon substrates, in the optical domain

The purpose of the study is to optimize the design parameters of nanocomposites matrices deposited on silicon substrate, in the optical domain. Specifically, the interaction of polarized photons with several samples of nanocomposite matrices, consisting of different concentrations of gold nanoparticles dispersed into different concentrations of PVA (poly-vinyl alcohol), deposited on silicon substrates at different spin coating speeds, were studied. Backscattered photons, under co-polarized and cross-polarized transmitter-receiver geometries, were detected and the degree of linear polarization (DOLP) was estimated. The outcome of this study allow us to assess the optimal design parameters of nanocomposites in the optical domain. It is of paramount significance to determine how nanostructures can be effectively integrated into polymer matrices and what new information or enhanced optical properties can be achieved.