Comparative study of the imaging contrasts of Mueller matrix derived parameters between transmission and backscattering polarimetry

Characterizing colon cancer stages through optical polarimetry-assisted digital staining

Tissue polarimetry has been gaining importance in extracting useful diagnostic information from the structural attributes of tissues, which vary in response to the tissue health status and hence find great potential in cancer diagnosis. However, the complexities associated with cancer make it challenging to isolate the characteristic changes as the tumor progresses using polarimetry. This study attempts to experimentally characterize the polarimetric behavior in colon cancer associated with various stages of development. Bulk and unstained sections of normal and tumor colon tissue were imaged in the reflection and transmission polarimetry configurations at low and high imaging resolutions using an in-house developed Mueller polarimeter. Through this study, we observed that the information about the major contributors of scattering in colon tissue, manifesting in depolarization and retardance, can be obtained from the bulk tissue and unstained sections. These parameters aid in characterizing the polarimetric changes as the colon tumor progresses. While the unstained colon section best indicated the depolarization contrast between normal and tumor, the contrast through the retardance parameter was more pronounced in the bulk colon tissue. The results suggest that the polarimetric "digitally stained" images obtained by Mueller polarimetry are comparable with the bulk tissue counterparts, making it useful for characterizing colon cancer tissues across different stages of development.

Discrepancy of coordinate system selection in backscattering Mueller matrix polarimetry: exploring photon coordinate system transformation invariants

In biomedical studies, Mueller matrix polarimetry is gaining increasing attention because it can comprehensively characterize polarization-related vectorial properties of the sample, which are crucial for microstructural identification and evaluation. For backscattering Mueller matrix polarimetry, there are two photon coordinate selection conventions, which can affect the following Mueller matrix parameters calculation and information acquisition quantitatively. In this study, we systematically analyze the influence of photon coordinate system selection on the backscattering Mueller matrix polarimetry. We compare the Mueller matrix elements in the right-handed-nonunitary and non-right-handed-unitary coordinate systems, and specifically deduce the changes of Mueller matrix polar decomposition, Mueller matrix Cloude decomposition and Mueller matrix transformation parameters widely used in backscattering Mueller matrix imaging as the photon coordinate system varied. Based on the theoretical analysis and phantom experiments, we provide a group of photon coordinate system transformation invariants for backscattering Mueller matrix polarimetry. The findings presented in this study give a crucial criterion of parameters selection for backscattering Mueller matrix imaging under different photon coordinate systems.

Zwitterion-doped liquid crystal speckle reducers for immersive displays and vectorial imaging

Lasers possess many attractive features (e.g., high brightness, narrow linewidth, well-defined polarization) that make them the ideal illumination source for many different scientific and technological endeavors relating to imaging and the display of high-resolution information. However, their high-level of coherence can result in the formation of noise, referred to as speckle, that can corrupt and degrade images. Here, we demonstrate a new electro-optic technology for combatting laser speckle using a chiral nematic liquid crystal (LC) dispersed with zwitterionic dopants. Results are presented that demonstrate when driven at the optimum electric field conditions, the speckle noise can be reduced by >90% resulting in speckle contrast (C) values of C = 0.07, which is approaching that required to be imperceptible to the human eye. This LC technology is then showcased in an array of different display and imaging applications, including a demonstration of speckle reduction in modern vectorial laser-based imaging.

Hybrid spatial-temporal Mueller matrix imaging spectropolarimeter for high throughput plant phenotyping

Many correlations exist between spectral reflectance or transmission with various phenotypic responses from plants. Of interest to us are metabolic characteristics, namely, how the various polarimetric components of plants may correlate to underlying environmental, metabolic, and genotypic differences among different varieties within a given species, as conducted during large field experimental trials. In this paper, we overview a portable Mueller matrix imaging spectropolarimeter, optimized for field use, by combining a temporal and spatial modulation scheme. Key aspects of the design include minimizing the measurement time while maximizing the signal-to-noise ratio by mitigating systematic error. This was achieved while maintaining an imaging capability across multiple measurement wavelengths, spanning the blue to near-infrared spectral region (405-730 nm). To this end, we present our optimization procedure, simulations, and calibration methods. Validation results, which were taken in redundant and non-redundant measurement configurations, indicated that the polarimeter provides average absolute errors of (5.3±2.2)×10^-3 and (7.1±3.1)×10^-3, respectively. Finally, we provide preliminary field data (depolarization, retardance, and diattenuation) to establish baselines of barren and non-barren Zea maize hybrids (G90 variety), as captured from various leaf and canopy positions during our summer 2022 field experiments. Results indicate that subtle variations in retardance and diattenuation versus leaf canopy position may be present before they are clearly visible in the spectral transmission.

Applications of Mueller Matrix Polarimetry to Biological and Agricultural Diagnostics: A Review

The review contains a systematization of the main approaches to the practical implementation of Mueller matrix polarimetry and the prospects for its application in biology and agriculture. The most typical optical layouts for measuring the Mueller matrix of various objects, such as disperse systems, tissues and surface structures, are discussed. Mueller matrix measurements, being integrated into standard schemes of conventional optical methods, such as scatterometry, optical coherence tomography, fluorimetry, spectrophotometry and reflectometry, can significantly expand their capabilities in the characterization of biological systems and bioorganic materials. Additionally, microwave Mueller matrix polarimetry can be used for monitoring soil conditions and crop growth. The proposed systematization is aimed at outlining the conceptual directions for the development of non-invasive diagnostic tools based on measuring the Mueller matrix, primarily with a focus on biological research and agricultural practice.

Deep learning Mueller matrix feature retrieval from a snapshot Stokes image

A Mueller matrix (MM) provides a comprehensive representation of the polarization properties of a complex medium and encodes very rich information on the macro- and microstructural features. Histopathological features can be characterized by polarization parameters derived from MM. However, a MM must be derived from at least four Stokes vectors corresponding to four different incident polarization states, which makes the qualities of MM very sensitive to small changes in the imaging system or the sample during the exposures, such as fluctuations in illumination light and co-registration of polarization component images. In this work, we use a deep learning approach to retrieve MM-based specific polarimetry basis parameters (PBPs) from a snapshot Stokes vector. This data post-processing method is capable of eliminating errors introduced by multi-exposure, as well as reducing the imaging time and hardware complexity. It shows the potential for accurate MM imaging on dynamic samples or in unstable environments. The translation model is designed based on generative adversarial network with customized loss functions. The effectiveness of the approach was demonstrated on liver and breast tissue slices and blood smears. Finally, we evaluated the performance by quantitative similarity assessment methods in both pixel and image levels.

Mueller matrix imaging microscope using dual continuously rotating anisotropic mirrors

We demonstrate calibration and operation of a Mueller matrix imaging microscope using dual continuously rotating anisotropic mirrors for polarization state generation and analysis. The mirrors contain highly spatially coherent nanostructure slanted columnar titanium thin films deposited onto optically thick titanium layers on quartz substrates. The first mirror acts as polarization state image generator and the second mirror acts as polarization state image detector. The instrument is calibrated using samples consisting of laterally homogeneous properties such as straight-through-air, a clear aperture linear polarizer, and a clear aperture linear retarder waveplate. Mueller matrix images are determined for spatially varying anisotropic samples consisting of a commercially available (Thorlabs) birefringent resolution target and a spatially patterned titanium slanted columnar thin film deposited onto a glass substrate. Calibration and operation are demonstrated at a single wavelength (530 nm) only, while, in principle, the instrument can operate regardless of wavelength. We refer to this imaging ellipsometry configuration as rotating-anisotropic-mirror-sample-rotating-anisotropic-mirror ellipsometry (RAM-S-RAM-E).

MuellerNet: a hybrid 3D-2D CNN for cell classification with Mueller matrix images

Different from conventional microimaging techniques, polarization imaging can generate multiple polarization images in a single perspective by changing the polarization angle. However, how to efficiently fuse the information in these multiple polarization images by a convolutional neural network (CNN) is still a challenging problem. In this paper, we propose a hybrid 3D-2D convolutional neural network called MuellerNet, to classify biological cells with Mueller matrix images (MMIs). The MuellerNet includes a normal stream and a polarimetric stream, in which the first Mueller matrix image is taken as the input of normal stream, and the rest MMIs are stacked to form the input of a polarimetric stream. The normal stream is mainly constructed with a backbone network and, in the polarimetric stream, the attention mechanism is used to adaptively assign weights to different convolutional maps. To improve the network's discrimination, a loss function is introduced to simultaneously optimize parameters of the two streams. Two Mueller matrix image datasets are built, which include four types of breast cancer cells and three types of algal cells, respectively. Experiments are conducted on these two datasets with many well-known and recent networks. Results show that the proposed network efficiently improves the classification accuracy and helps to find discriminative features in MMIs.

High-fidelity and rapid cellular-level Mueller matrix imaging for tissue identification with unstained sections

Mueller matrix polarimetry is regarded as a promising technique in the field of biomedicine, especially for pathological diagnosis. However, the current studies on Mueller imaging of pathological sections are all at the tissue-level, and the cellular-level polarization information is difficult to obtain. To overcome this challenge, we first propose a cellular-level Mueller matrix imaging method for accurate quantitative identification of tissues in this study. Benefiting from the significant birefringent behavior of paraffin in unstained sections, the proposed method can locate the paraffin distribution areas of retardance images by involving Otsu's algorithm. Then, the real cellular-level polarization information (e.g., depolarization) is acquired. The efficiency of the proposed method was demonstrated on unstained rat tissue samples. The results showed that the obtained depolarization images are highly consistent with the stained microscopic images in terms of the morphology and arrangement of the tissues at cellular level. Finally, this method was preliminarily applied to the detection of human lung cancer tissue section, effectively realizing the quantitative differentiation of normal, inflamed, and malignant areas in unstained section. This study provides a possible approach for the rapid and accurate diagnosis of cancer.

Isolating individual polarization effects from the Mueller matrix: comparison of two non-decomposition techniques

The prevailing formalisms for isolating individual polarization effects from the experimental Mueller matrix M can be broadly divided into two categories; decomposition of M to derive the individual optical effects and directly associating the individual optical effects to specific elements of M (i.e., non-decomposition techniques). Mueller matrix transformation (MMT) and direct interpretation of Mueller matrix (DIMM) are two popular techniques of the latter category. In this study, these two non-decomposition techniques (i.e., MMT and DIMM) are compared in a detailed quantitative analysis comprising of tissues (n = 53) and phantom (n = 45) samples. In particular, two commonly investigated polarimetric variables (i.e., depolarization and retardance) were calculated from the experimentally measured M using both the non-decomposition (i.e., MMT and DIMM) techniques. The comparison carried out with scatter plots (integrated with the correlation coefficients), violin plots and Bland and Altman plots revealed better agreement of depolarization-related variables (as compared to the retardance) between the two non-decomposition techniques. The comparative analyses presented here would be beneficial for the interpretation of polarimetric variables and optical characterization of turbid media.

Histopathological correlations of bulk tissue polarimetric images: Case study

Polarimetric imaging and image analysis have gained increased interest in soft tissue analysis at the cellular level. However, polarimetric imaging has widely been tested on thin tissue sections to provide reliable information correlated with histopathological findings. Polarimetric bulk tissue analysis always offered an overall assessment of various tissue optical properties for diagnosis. In this study, the histopathological correlation of bulk tissue polarimetry images for soft tissues is discussed. The first-hand information on the use of bulk tissue Mueller polarimetry and image analysis as an alternative to tissue histopathology is presented for surgically extracted colon and breast tissues.

Evolution of raw meat polarization-based properties by means of Mueller matrix imaging

The possibilities of using Mueller matrix (MM) imaging polarimetry to assess meat quality have not yet been sufficiently explored. In the current study, the fresh porcine muscles are imaged at room temperature with a wide-field MM imaging polarimeter over 26 hours to visualize dynamics of tissue optical properties through applying Lu-Chipman decomposition. The frequency distribution histograms (FDHs) and statistical analysis of the MM elements show prominent changes over time. The wavelength spectra of both total depolarization and scalar retardance have dips at 550 nm whereas their values continuously increase with time; the former is referred to the increase of number of scattering events and decrease of myoglobin absorption in the red part of visible spectra related to meat color and freshness, while the latter is associated with the increase in birefringence and meat tenderness. The obtained results are promising to develop a novel fast noncontact optical technique for monitoring of meat quality.

Deriving Polarimetry Feature Parameters to Characterize Microstructural Features in Histological Sections of Breast Tissues

OBJECTIVE

Mueller matrix polarimetry technique has been regarded as a powerful tool for probing the microstructural information of tissues. The multiplying of cells and remodeling of collagen fibers in breast carcinoma tissues have been reported to be related to patient survival and prognosis, and they give rise to observable patterns in hematoxylin and eosin (H&E) sections of typical breast tissues (TBTs) that the pathologist can label as three distinctive pathological features (DPFs)-cell nuclei, aligned collagen, and disorganized collagen. The aim of this paper is to propose a pixel-based extraction approach of polarimetry feature parameters (PFPs) using a linear discriminant analysis (LDA) classifier. These parameters provide quantitative characterization of the three DPFs in four types of TBTs.

METHODS

The LDA-based training method learns to find the most simplified linear combination from polarimetry basis parameters (PBPs) constrained under the accuracy remains constant to characterize the specific microstructural feature quantitatively in TBTs.

RESULTS

We present results from a cohort of 32 clinical patients with analysis of 224 regions-of-interest. The characterization accuracy for PFPs ranges from 0.82 to 0.91.

CONCLUSION

This work demonstrates the ability of PFPs to quantitatively characterize the DPFs in the H&E pathological sections of TBTs.

SIGNIFICANCE

This technique paves the way for automatic and quantitative evaluation of specific microstructural features in histopathological digitalization and computer-aided diagnosis.

Accurate reconstruction of polarization parameters for channeled spectroscopic Stokes polarimeters

In this work, we present an accurate polarization reconstruction method based on the coherence demodulation technique, which is different from the previous windowing method operating in the optical path difference domain. The proposed method uses a signal multiplier and a low-pass filter to reconstruct Stokes parameters without performing any Fourier transform. Because this method does not require a Fourier transform, the Stokes reconstruction could be finished in the spectral domain. For calibrating the waveplate phase error, coherence demodulation allows for establishing an analytical model to describe the influence of waveplate imperfections on the polarization measurement process. The phase error will result in a channel shift and Fourier broadening, both of which cause serious errors during Stokes reconstruction. With the model, a method based on a linear polarizer was proposed for calibrating the phase deviation of waveplate. After that, the accurate reconstruction of polarization parameters could be achieved. An experiment was performed to check the ability of the proposed method. The experimental result showed that it has the same excellent performance of reconstructing Stokes parameters using the traditional windowing method. Finally, a series of simulations was carried out to verify the robustness of this method, which showed that the reconstruction technique is robust to misalignment and additional noise.

Design of an endomicroscope including a resonant fiber-based microprobe dedicated to endoscopic polarimetric imaging for medical diagnosis

We report on a novel endomicroscope, to the best of our knowledge, designed for achieving full 4×4 Mueller polarimetric images of biological tissues through a fiber endoscope for medical diagnosis. The polarimetric technique is based on a previously published two-wavelength differential method (TWDM). A key component of the endomicroscope is a resonant fiber-based microprobe including a highly-selective fiber Bragg grating (FBG), free of detrimental polarimetric effects, photo written in the core of the fiber, near the output face. By means of the TWDM, and using the specially designed microprobe (diameter 2.9 mm, length 30 mm), full Mueller images of 250×250 pixels were produced at the rate of 1 image/2 s through a 2 m single mode fiber, paving the way to in vivo applications in polarimetric endomicroscopy.

Probing variations of fibrous structures during the development of breast ductal carcinoma tissues via Mueller matrix imaging

Recently, we developed a label-free method to probe the microstructural information and optical properties of unstained thin tissue slices based on microscopic Mueller matrix imaging technique. In this paper, we take the microscopic Mueller matrix images of human breast ductal carcinoma tissue samples at different pathological stages, and then calculate and analyze their retardance-related Mueller matrix-derived parameters. To reveal the microstructural features more quantitatively and precisely, we propose a new method based on first-order statistical properties of image to transform the 2D images of Mueller matrix parameters into several statistical feature vectors. We evaluate each statistical feature vector by corresponding classification characteristic value extracted from the statistical features of Mueller matrix parameters images of healthy breast duct tissue samples. The experimental results indicate that these statistical feature vectors of Mueller matrix derived parameters may become powerful tools to quantitatively characterize breast ductal carcinoma tissue samples at different pathological stages. It has the potential to facilitate automating the staging process of breast ductal carcinoma tissue, resulting in the improvement of diagnostic efficiency.

All-dielectric concentration of electromagnetic fields at the nanoscale: the role of photonic nanojets

The photonic nanojet (PNJ) is a narrow high-energy beam that was originally found on the back side of all-dielectric spherical structures. It is a unique type of energy concentration mode. The field of PNJs has experienced rapid growth in the past decade: nonspherical and even pixelized PNJ generators based on new physics and principles along with extended photonic applications from linear optics to nonlinear optics have driven the re-evaluation of the role of PNJs in optics and photonics. In this article, we give a comprehensive review for the emerging sub-topics in the past decade with a focus on two specific areas: (1) PNJ generators based on natural materials, artificial materials and nanostructures, and even programmable systems instead of conventional dielectric geometries such as microspheres, cubes, and trihedral prisms, and (2) the emerging novel applications in both linear and nonlinear optics that are built upon the specific features of PNJs. The extraordinary features of PNJs including subwavelength concentration of electromagnetic energy, high intensity focusing spot, and lower Joule heating as compared to plasmonic resonance systems, have made PNJs attractive to diverse fields spanning from optical imaging, nanofabrication, and integrated photonics to biosensing, optical tweezers, and disease diagnosis.

Distinguishing structural features between Crohn's disease and gastrointestinal luminal tuberculosis using Mueller matrix derived parameters

Recently, the incidence of inflammatory bowel diseases, especially the Crohn's disease (CD) and gastrointestinal luminal tuberculosis (ITB), has grown rapidly worldwide. Currently there is no general gold standard to distinguish between CD and ITB tissues, which both have tuberculosis and surrounding fibrous structures. Mueller matrix imaging technique is suitable for describing the location, density and distribution behavior of such fibrous structures. In this study, we apply the Mueller matrix microscopic imaging to the CD and ITB tissue samples. The 2D Mueller matrix images of the CD and ITB tissue slices are measured using the Mueller matrix microscope developed in our previous study, then the Mueller matrix polar decomposition and Mueller matrix transformation parameters are calculated. To evaluate the distribution features of the fibrous structures surrounding the tuberculosis areas more quantitatively and precisely, we analyze the retardance related Mueller matrix derived parameters, which show clear different distribution behaviors between the CD and ITB tissues, using the Tamura image processing method. It is demonstrated that the Mueller matrix derived parameters can reveal the structural features of tuberculosis areas and be used as quantitative indicators to distinguish between CD and ITB tissues, which may be useful for the clinical diagnosis.

Minimized Laplacian residual interpolation for DoFP polarization image demosaicking

Division of focal plane (DoFP) polarization imaging sensors have the distinct advantage of acquiring temporally synchronized Stokes vector in one scene. The sensors' spatially modulated arrangement of a micropolarization array results in loss of spatial resolution and instantaneous field-of-overview errors. Polarization demosaicking (PDM) methods are often utilized to address these drawbacks and achieve the goal of recovering missing polarization information. In this paper, we propose minimized Laplacian polarization residual interpolation for PDM. The Laplacian energy is introduced to improve the interpolation accuracy. We employ interchannel correlation and a guided filter to generate precise tentative estimates and the interpolation performed in the residual domain, where the residuals are the differences between observed values and tentative estimates. Experiments demonstrate that the proposed algorithm provides superior performance in terms of mean average error and peak signal-to-noise ratio.

Quantitative Analysis of 4 × 4 Mueller Matrix Transformation Parameters for Biomedical Imaging

Mueller matrix polarimetry is a potentially powerful technique for obtaining microstructural information of biomedical specimens. Thus, it has found increasing application in both backscattering imaging of bulk tissue samples and transmission microscopic imaging of thin tissue slices. Recently, we proposed a technique to transform the 4 × 4 Mueller matrix elements into a group of parameters, which have explicit associations with specific microstructural features of samples. In this paper, we thoroughly analyze the relationships between the Mueller matrix transformation parameters and the characteristic microstructures of tissues by using experimental phantoms and Monte Carlo simulations based on different tissue mimicking models. We also adopt quantitative evaluation indicators to compare the Mueller matrix transformation parameters with the Mueller matrix polar decomposition parameters. The preliminary imaging results of bulk porcine colon tissues and thin human pathological tissue slices demonstrate the potential of Mueller matrix transformation parameters as biomedical diagnostic indicators. Also, this study provides quantitative criteria for parameter selection in biomedical Mueller matrix imaging.