As a vectorial property, polarization encodes high-dimensional information of light.^{1 – 3} Polarimetry can provide abundant optical and structural information of tissue; thus it has shown great potential in biomedical and clinical applications.^{4 – 10} After interacting with tissue, the polarization state of light can be altered by different structures.¹¹ By measuring the polarization state changes of output light from tissue, several properties, such as birefringence, dichroism, and depolarization, can be quantified.¹² For microscopic polarization imaging of thin tissue slices, linear birefringence is a valuable and prevalently used metric for anisotropic structures characterization.^{13 – 15} For instance, Wood et al.¹⁶ demonstrated that linear birefringence can be adopted for in vivo tissue fiber characterization. Furthermore, Pierangelo et al.¹⁷ showed that the reducing of linear birefringence resulting from the breaking down of well-ordered fibrous structures can be used for cervical cancer identification.

The characterization and evaluation of skin tissue structures are crucial for dermatological applications. Recently, Mueller matrix polarimetry and second harmonic generation microscopy have been widely used in skin tissue imaging due to their unique advantages. However, the features of layered skin tissue structures are too complicated to use a single imaging modality for achieving a comprehensive evaluation. In this study, we propose a dual-modality imaging method combining Mueller matrix polarimetry and second harmonic generation microscopy for quantitative characterization of skin tissue structures. It is demonstrated that the dual-modality method can well divide the mouse tail skin tissue specimens’ images into three layers of stratum corneum, epidermis, and dermis. Then, to quantitatively analyze the structural features of different skin layers, the gray level co-occurrence matrix is adopted to provide various evaluating parameters after the image segmentations. Finally, to quantitatively measure the structural differences between damaged and normal skin areas, an index named Q-Health is defined based on cosine similarity and the gray-level co-occurrence matrix parameters of imaging results. The experiments confirm the effectiveness of the dual-modality imaging parameters for skin tissue structure discrimination and assessment. It shows the potential of the proposed method for dermatological practices and lays the foundation for further, in-depth evaluation of the health status of human skin.

Mueller matrix polarimetry is widely used in biomedical studies and applications, for it can provide abundant microstructural information about tissues. Recently, several methods have been proposed to decompose the Mueller matrix into groups of parameters related to specific optical properties which can be used to reveal the microstructural information of tissue samples more clearly and quantitatively. In this study, we thoroughly compare the differences among the parameters derived from the Mueller matrix polar decomposition (MMPD) and Mueller matrix transformation (MMT), which are two popular methods in tissue polarimetry studies and applications, while applying them on different tissue samples for both backscattering and transmission imaging. Based on the Mueller matrix data obtained using the setups, we carry out a comparative analysis of the parameters derived from both methods representing the same polarization properties, namely depolarization, linear retardance, fast axis orientation and diattenuation. IN particular, we propose several modified MMT parameters, whose abilities are also analyzed for revealing the information about the specific type of tissue samples. The results presented in this study evaluate the applicability of the original and modified MMT parameters, then give the suggestions for appropriate parameter selection in tissue polarimetry, which can be helpful for future biomedical and clinical applications.

Mueller matrix polarimetry is recently attracting more and more attention for its diagnostic potentials. However, for prevalently used division of time Mueller matrix polarimeter based on dual-rotating retarder scheme, beam drift induced by rotating polarizers and waveplates introduces spatial misalignment and pseudo-edge artifacts in imaging results, hindering following accurate microstructural features characterization. In this paper, we quantitatively analyze the beam drift phenomenon in dual-rotating retarder Mueller matrix microscopy and its impact on linear retardance measurement, which is frequently used to reflect tissue fiber arrangement. It is demonstrated that polarizer rotation induces larger beam drift than waveplate rotation due to surface non-uniformity and stress deformation. Furthermore, for waveplates rotated constantly in dual-rotating retarder scheme, their tilt within polarization state analyzer can result in more drift and throughput loss than those within polarization state generator. Finally, phantom and tissue experiments confirm that beam drift, rather than inherent optical path changes, dominates the systematic overestimation of linear retardance in boundary image regions. The findings highlight beam drift as a dominant error source for quantifying linear retardance, necessitating careful optical design alignment and a reliable registration algorithm to obtain highly accurate polarization data for training machine learning models of pathological diagnosis using Mueller matrix microscopy.

Extracellular matrix (ECM) constitutes a key basement structure to human organisms by acting as a complex network of large proteins and carbohydrates that provide structural support to surrounding cells. Remodeling in the ECM’s structural fibers leads to insight into the development of diseases such as cancer, fibrosis, and carcinoma. Although standard tissue visualization in the ECM involves multiple lengthy histopathological staining protocols, Mueller-matrix-based polarimetry provides label-free tissue slices’ microstructural information and optical properties. We aim to identify three types of fiber tissues commonly found in the ECM of gastrointestinal tissue specimens by analyzing their polarization properties. To address decomposition methods’ reliance on restrictive hypotheses and inability with an individual polarization-based parameter to determine the nature of a given biological tissue, we employ the uniform manifold approximation and projection method to offer greater discriminative power and flexibility. Subsequently, polarization-based features will be extracted and compared among fiber regions statistically to discern potential diagnostic differences. By providing colorized images, we aim to demonstrate the feasibility of distinguishing different fibers with a polarization approach, offering insights for future clinical development while complementing existing staining methods for pathological tissue specimens.