Liquid crystal variable retarders (LCVRs) are computer-controlled birefringent devices that contain nanometer-sized birefringent liquid crystals (LCs). These devices impart retardance effects through a global, uniform orientation change of the LCs, which is based on a user-defined drive voltage input. In other words, the LC structural organization dictates the device functionality. The LC structural organization also produces a spectral scatter component which exhibits an inverse power law dependence. We investigate LC structural organization by measuring the voltage-dependent LC spectral scattering signature with an integrating sphere and then relate this observable to a fractal-Born model based on the Born approximation and a Von Kármán spectrum. We obtain LCVR light scattering spectra at various drive voltages (i.e., different LC orientations) and then parameterize LCVR structural organization with voltage-dependent correlation lengths. The results can aid in determining performance characteristics of systems using LCVRs and can provide insight into interpreting structural organization measurements.
The ability to measure polarization effects is important in many biological and industrial applications. Additionally, measuring spectral and scatter effects can offer greater sensitivity for applications where characterization and differentiation are important. Here we present a liquid crystal-based spectral imaging goniometric polarimeter to probe these effects. The system consists of two modules, a Stokes generator and a polarimeter, each constructed from a pair of liquid crystal variable retarders (LCVR). LCVRs are computer-controlled birefringent devices that impart retardance effects with no mechanical movement. Additionally, the Stokes generator utilizes a computer-controlled liquid crystal tunable filter (LCTF) to transmit a specific wavelength bandwidth, also with no mechanical movement. The polarimeter, enclosed in a cage system, manually rotates around the sample plane to provide angular scatter measurements. A CCD camera images the sample and provides spatially resolved estimates of the complete Mueller matrix as a function of wavelength and scatter angle. Here we describe the system and its calibration, and show quantitative measurement results for a number of samples.
The ability to detect changes in the structural organization of tissue has significant diagnostic value. A polarimeter has
the ability to detect these changes as it can probe the tissue
sub-wavelength structural organization through polarization
effects. Here we present a spectral imaging polarimeter that is based on liquid crystal technology. The system is
comprised of two modules, a Stokes generator and a polarimeter. Each module employs a pair of Liquid Crystal Variable
Retarders (LCVRs), which are computer-controlled birefringent devices. Additionally, the polarimeter utilizes a CCD
camera to image the illuminated region, thus providing spatially resolved estimates of the complete Mueller matrix for
the sample. Before the system can be employed, an overall system characterization involving all four LCVRs must be
performed. This characterization defines a relationship between polarimeter measurements and the incident Stokes
vectors. Here we briefly describe the calibration procedure and show example Mueller matrix images of biological
Changes in the structural organization of biological tissue can be indicative of disease. The ability to measure and
associate changes in structural organization with disease-related cellular architecture has significant diagnostic value.
Here we present a spectral imaging polarimeter to probe the local structural organization of tissue. The system is based
on liquid crystal technology, and is comprised of two modules, a Stokes generator and a polarimeter. The Stokes
generator uses a pair of Liquid Crystal Variable Retarders (LCVRs) to generate a set of Stokes vectors incident on a
sample, while the polarimeter utilizes a separate pair of LCVRs to analyze the scattered Stokes vectors. Characterization
of the system is in terms of a data reduction matrix that relates the polarimeter measurements to the incident Stokes
vector. Calibration of the polarimeter (calculation of the elements of this data reduction matrix) is performed by
presenting a series of known Stokes vectors to the device. The resulting over-determined system of equations is solved
using the Singular Value Decomposition. We discuss the construction and calibration of the system.
Successful development of cultured tissues is heavily influenced by cell alignment within the tissue scaffold. Proper cell
alignment leads to optimum tissue strength. It has been demonstrated that proper alignment is engendered by application
of physiologically realistic stresses during the cell proliferation process. In situ monitoring of cell alignment during
development thus can provide important feedback information in determining the optimum stresses. T-matrix
calculations suggest that cell alignment characteristics (cell aspect and orientation) can be inferred from the spectral
polarization of light scattered by the cells. Therefore, a spectral polarimetry system has been created to measure these
effects to provide feedback for proper cell alignment. In order to properly use the system, a calibration procedure was
first established. The calibration procedure entailed making mathematical predictions for the system performance based
on the system components, and then empirically validating these predictions. Upon system calibration, measurements
were made on a biologically relevant sample. We present results of experimental measurements on the sample and
discuss structural inferences made from these measurements. In addition, we compare our results with structural
information obtained from histological analysis.
The ultimate objective of laser speckle flowmetry is to infer flow velocity from observed speckle contrast. Since
introduction of this concept over 25 years ago, a variety of researchers have demonstrated such a qualitative relationship
(between speckle contrast and flow velocity), but a quantitative relationship has proven elusive. A fundamental reason
for this failure to demonstrate a convincing quantitative relationship is that the underlying mathematics describing LSCA
is identical to that of quasi-elastic light scatter (QLS). As a result, it is commonly (and erroneously) assumed that the
requirements for the data acquisition, the model linking the scatter dynamics to the speckle fluctuation, and the data
processing are the same as well.
Here we discuss some of our recent advances towards achieving quantitative velocity estimates from laser
speckle contrast measurements. This concept is free of any assumptions relating scatterer dynamics to light fluctuations
and is compatible with accepted data acquisition methods, but uses an entirely new data processing scheme. Results are
demonstrated with a murine model.
An important issue in the development of cultured tissues is the alignment of the cells within the scaffold, or on the
substrate. Proper alignment leads to optimum tissue strength and it has been demonstrated that proper alignment is
engendered by application of physiologically realistic stresses during the cell proliferation process. In situ monitoring of
cell alignment during development can provide important feedback information in determining the optimum stresses.
Numerical calculations suggest that cell aspect and orientation can be inferred from the polarization of the light scattered
by these cells. In this paper, we demonstrate that a measurement of the wavelength-dependent depolarization of the light
scattered from the cell layer reveals the alignment of these cells. We present results of experimental measurements on
human umbilical vein endothelial cells (HUVEC's) layered onto glass cover slips and of simulations using T-matrix
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.