This PDF file contains the front matter associated with SPIE Proceedings Volume 11963, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

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Precise polarisation imaging requires two key aspects – imaging resolution and vector information correctness. Errors in the state of polarisation (SOP) can disrupt these two aspects hence leading to imperfect interference at the focus, and incorrect vector states in the illumination or detection. Those issues will therefore lead to detrimental problems for high resolution polarisation sensitive optical systems, such as Stokes/Mueller confocal microscopes. The SOP errors can be introduced in different ways, which include pre-measurement processes, such as denoising, optimisation, and calibration, which are built on matrix calculation processes which would introduce an error amplification; or, other errors sources in optical systems such as focusing through stressed optical elements, due to Fresnel’s effects, or induced via polarising effects in materials or biological tissues

Here we put forward two techniques to deal with those errors, including next generation polarimetry and next generation adaptive optics techniques. We first show a new polarimetry method that has the ability to map all polarisation analyser states into a single vectorially structured light field, hence all vector components are analysed in a single-shot. We extract the vectorial state through inference from a physical model of the resulting image, providing a single-step sensing procedure. These methods in effect circumvent these method-related error amplification, accumulation and complex preprocessing steps. We then show a new adaptive optics technology that can correct both phase and polarisation aberrations within the optical systems. We validate improvements in both vector field state and the focal quality of an optical system, through correction for commonplace vectorial aberration sources.

Interaction of light with extended random and/or complex media, such as biological tissue samples, involves continuous changes in coherence and polarization of the propagating beams. Therefore, the classic Stokes-Mueller calculus based on the local (single-point) transformation on the order of intensity (not field) cannot completely and uniquely characterize such interaction. We suggest to use generalization of the Stokes-Mueller calculus to two-point field correlations in which both the Stokes vector and the Mueller matrix remain real-valued. We also envision that the proposed generalization will enable the unique solution of the inverse problems relating to soft biological sample characterization from polarimetric measurements.

Polarimetry has long been used to investigate fiber anisotropy of biological soft tissues, either independently or together with other imaging methods, as it leverages the natural birefringence of collagen. Despite widespread usage, previous studies of soft tissues contain ambiguous interpretations of data gathered from polarized light-based techniques. To date, there has not yet been a systematic assessment of how individual extracellular matrix (ECM) properties influence the polarization of light, which limits the ability to correctly interpret data from these techniques in some applications. To probe the effect of various ECM properties on polarized light, we used a tunable hydrogel system to vary the collagen density, crosslinking density, and absorber concentration. Samples were imaged using quantitative polarized light imaging (QPLI), which uses circularly polarized incident light and a division of focal plane polarimeter. QPLI was performed in both reflectance and transmission modes. The average degree of linear polarization (AVG DoLP; i.e., strength of alignment) and standard deviation of the angle of polarization (STD AoP; i.e., uniformity of alignment) were calculated for each hydrogel. Increasing collagen density resulted in the most pronounced changes, where AVG DoLP and STD AoP increased for reflectance and transmission mode, likely due to the increased concentration of birefringent material. Crosslinking only caused a modest increase on AVG DoLP in transmission mode but decrease in STD AoP in reflectance mode, likely due to the small length scale of the crosslink relative to the fibers. Alteration of transmissivity resulted in changes mainly in reflectance mode, where multiple scattering was more pronounced. Results will help improve data interpretation and experimental control when using polarized light to image biological soft tissues.

During the last decades, the attention on the application of polarimetric methods for biological tissues inspection has been increasing. Nowadays, organic tissue recognition algorithms are of potential interest in different research areas, as for instance, in biomedical applications for the early detection of diseases or the classification of biological structures. Based on the modifications in polarization that light-matter interactions produce, an exhaustive polarimetric analysis of the sample (extraction of dichroism, retardance and depolarization) may unveil the different tissue inherent characteristics and provide a complete description of how the biological structures interact with incident polarized light. By taking advantage of such polarimetric methods tissues characterization, we propose four predictive models corresponding to the recognition of four ex-vivo chicken tissue categories: bone, muscle, tendon and myotendinous junction tissue samples. The implemented multivariant probabilistic models are based on the logistic regression fit of the experimental Mueller matrixderived polarimetric observables (measured at three different wavelengths: 625 nm, 530 nm and 470nm): polarizance P, diattenuation D, depolarization content (Indices of Polarimetric Purity P1, P2, P3 and depolarization index 𝑃Δ), retardance (global, R, and linear δ) and optical rotation Ψ. As a result, we achieve stable predictive models whose output, in terms of sensitivity and specificity indicators, are of 82.6% and 80.6% for bone recognition, 85% and 93.5% for tendon, 86% and 88.8% for muscle and 82% and 71% for myotendinous junction, respectively. Obtained results suggest that these noninvasive methods could be applied in multiple biomedical scenarios such as for early diagnosis of pathologies.

Compared to traditional optical technology, polarization imaging can obtain more abundant microstructure and anisotropy information of the sample, and Mueller matrix contains the sample’s complete polarization properties. In our previous study, we have established the Mueller matrix microscope based on dual DoFP polarimeters (DoFPs-MMM), which takes advantages of fast measurement speed and high measurement stability of DoFP polarimeters. However, compared to other polarization measurement schemes, the systematic errors of DoFPs-MMM are complex and difficult to analyze. In this paper, we propose a semi-modelled calibration method (SMCM) to achieve complete calibration of DoFPs-MMM, which only needs to establish the error model of the polarization states generator (PSG). The calibration method is based on solving the error model of PSG and then the instrument matrix of polarization states analyzer (PSA) can be directly calibrated by PSG. The performance of the calibration method is verified by measuring standard polarization samples using the multiwavelength DoFPs-MMM after calibration. The results show that the proposed calibration method has the advantages of accurate calibration, suitable for multiwavelength system, and convenient for operation.

Polarization is capable of probing microstructures and has unique sensitivity to fibrous anisotropic structure. Polarimetric imaging has demonstrated promising potential in diverse applications ranging from biomedicine, material science, and atmospheric remote sensing. The polarization properties of samples can be comprehensively described by a Mueller matrix (MM). However, the relationship between individual MM elements and properties of the sample is often not clear. There have been consistent efforts to derive polarization parameters from MM based on certain assumptions for better description of the samples, e.g., MM polar decomposition (MMPD), MM transformation (MMT) and MM differential decomposition. Usually, the MM imaging requires sequential measurements with different polarization states of incident light and the imaging process is time consuming. In addition, for movable samples, we cannot guarantee the consistency during the imaging. This may cause precision issues since the images cannot be well-registered. In this work, we built a statistical translation model to generate polarization parameters from a single Stokes vector which can be obtained by one-shot imaging. This will improve the imaging efficiency, simplify the optical system and avoid introducing errors by the image registration. In the model design, we adopted the generative adversarial network (GAN) where the generator is based on a U-net architecture. We demonstrated the effectiveness of our approach on liver tissue, blood smear and porous anodic alumina (PAA) film, and quantitatively evaluated the results by similarity assessment methods. The model can generate a parameter image within 0.1 second on a desktop computer, which shows the potential to achieve real-time performance.

Reflectance imaging gives a convolved image of superficial and deeper tissue layers. On the other hand, polarization reflectance imaging allows separation of superficial tissue from the convolved tissue image. In this report, polarized light imaging is used to investigate hydration and desiccation on superficial layers of ex vivo porcine skin tissues. A polarization camera acquired co-polarized and cross-polarized reflectance images from porcine front and back dermal surfaces. Polarized scattering is sensitive to sub-micrometer changes in tissue structure, and therefore is useful in detecting collagen density changes in tissue. The reflectance images were acquired at five different wavelengths (405, 490, 590, 660, and 700 nm) for hydrated and desiccated tissues. The back surface (dermal surface) of the skin was affected by hydration or desiccation, while the front surface (epidermal surface) was not as affected due to the stratum corneum which resists desiccation.

This work describes a wide-field imaging Mueller polarimetric system optimized for operation in the VIS and NIR ranges. It makes use of two fast switching compensators with optimal values of retardance that are oriented to a discrete set of orientations. The acquisition of 16 raw intensity images is done in a few seconds, which allows the determination of the complete Mueller matrix of a sample in the backscattering configuration at a speed compatible with in-vivo applications. Mueller matrix NIR imaging of polarization properties unveils quantitative information from deeper parts of the tissue than in systems using VIS radiation, making it an interesting and promising tool for non-invasive biomedical diagnostics.

Preterm birth (PTB) is defined as any birth prior to 37 weeks of gestation. Preterm birth contributes to 35% of 3.1 million neonatal deaths annually. There is a critical absence of clinical tools for diagnosis of preterm birth risk. We have proposed the use of Mueller Matrix Imaging (MMI) as a sensitive tool to monitor the atypical remodeling of collagen occurring in PTB. Here we expand our previous work to demonstrate that a Portable PReterm IMaging System capable of 3x4 MMI can be used at the point of care. It consists of a sheath insertable in the vaginal canal combined with a polarized imaging system. The main PPRIM body consists of a camera with integrated polarizers combined with a custom-made LED ring illuminator. The optical layout consists of a reverse telephoto lens suitable for imaging at long front working distance. Angle of incidence of the optical elements are minimized to reduce the sensitivity to misalignment and polarization aberrations. The system has a field of view of approximately 25 x 25 mm² at 20 mm working distance. PPRIM is controlled by a laptop computer and custom software. To demonstrate the feasibility of the device, imaging tests were performed on a Gynecologic Skills Trainer as well as healthy volunteers.

There are 15 million infants born prematurely each year worldwide. Of these, about 1 million will die of complications from reduced gestation (37 weeks and less) before the age of five. Cervical remodeling, which is the transformation of the cervix from a firm structure to a soft one, is essential for both term and preterm birth (PTB). Monitoring the uterine cervix remodeling and particularly the arrangement of the cervix primary structural components (elastin and collagen) is of great interest to researchers studying PTB. We have utilized a Self-validating Mueller Matrix Micro-Mesoscope (SAMMM) with convolutional neural networks (CNN) and K-nearest neighbor (K-NN) for classification of elastin and collagen fibers in the mouse cervix. In this work, we proposed that an independent polarized microscope can be used for collagen and elastin classification leveraging the previously developed classifier. The Mueller matrix and decomposition parameters of depolarization, retardance and diattenuation obtained with this system are fed to the previously developed classifier. Excised cervical tissues (50 μm thickness) were used in this study including samples obtained at different gestation days.

As an emerging new tool for characterizing microstructural features of tissues and cells, Mueller matrix polarimetry has attracted more and more attention. It has been widely used in various biomedical studies and applications, especially pathological diagnosis for its significant advantages in distinguishing tissue microstructural changes as a non-invasive, non-contact and label-free tool. Recently, several Mueller matrix analyzing methods have been proposed to derive groups of parameters with clear associations to microstructures and physical properties of tissues. In this study, for quantitative assessment of different tissue structures accurately, we compared several groups of Mueller matrix derived parameters with similar physical meanings of linear retardance, linear birefringence fast axis orientation, diattenuation, and depolarization. By performing the correlation analysis of both the transmission Mueller matrix microscopic imaging results of thin tissue slices and backscattering Mueller matrix imaging results of bulk tissue samples, we discuss the applicability of the original and modified Mueller matrix derived parameters for tissue structures assessment, then give the suggestions for appropriate parameter selection in biomedical studies and applications.