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In this paper, we report the significance of the double Stokes–Mueller polarimetry (DSMP) technique, to characterize a large size ($3\times 3\times 5$mm) Potassium titanyl phosphate (KTP) crystal. The crystal undergoes second harmonic generation with type II phase matching. The study of standard KTP crystal using the DSMP technique helps to validate the efficiency of this technique. We were able to extract the crystal’s double Mueller matrix, relative contribution of the susceptibility tensor components, the phase difference between the susceptibility tensor components, etc. We could determine the crystal axes orientation using this optical technique, which was not possible through a single crystal X-Ray diffraction technique for such a large size crystal for which both optic axes and crystallographic axes are the same. Axes direction determined from polarization microscope measurements and Laue diffraction measurements on KTP crystal is compared with those obtained from DSMP measurements.

We propose and conduct both the rotating linear polarization imaging (RLPI) and Mueller matrix transformation (MMT) measurements of different biological tissue samples, and testify the capability of the Mueller matrix polarimetry for the anisotropic scattering media. The independent parameters extracted from the RLPI and MMT techniques are compared and analyzed. The tissue experimental results show that the parameters are closely related to the structural characteristics of the turbid scattering media, including the sizes of the scatterers, the angular distribution and order of alignment of the fibers. The results and conclusions in this paper may provide a potential method for the detection of precancerous and early stage cancerous tissues. Also, such studies represent the Mueller matrix transformation procedure which results in a set of parameters linking up the Mueller matrix elements to the structural and optical properties of the media.

We developed a model to describe polarized photon scattering in biological tissues. In this model, tissues are simplified to a mixture of scatterers and surrounding medium. There are two types of scatterers in the model: solid spheres and infinitely long solid cylinders. Variables related to the scatterers include: the densities and sizes of the spheres and cylinders, the orientation and angular distribution of cylinders. Variables related to the surrounding medium include: the refractive index, absorption coefficient and birefringence. In this paper, as a development we introduce an optical activity effect to the model. By comparing experiments and Monte Carlo simulations, we analyze the backscattering Mueller matrix patterns of several tissue-like media, and summarize the different effects coming from anisotropic scattering and optical properties. In addition, we propose a possible method to extract the optical activity values for tissues. Both the experimental and simulated results show that, by analyzing the Mueller matrix patterns, the microstructure and optical properties of the medium can be obtained. The characteristic features of Mueller matrix patterns are potentially powerful tools for studying the contrast mechanisms of polarization imaging for medical diagnosis.

Scarring is one of the biggest areas of unmet need in the long-term success of glaucoma filtration surgery. Quantitative evaluation of the scar tissue and the post-operative structure with micron scale resolution facilitates development of anti-fibrosis techniques. However, the distinguishment of conjunctiva, sclera and the scar tissue in the surgical area still relies on pathologists’ experience. Since polarized light imaging is sensitive to anisotropic properties of the media, it is ideal for discrimination of scar in the subconjunctival and episcleral area by characterizing small differences between proportion, organization and the orientation of the fibers. In this paper, we defined the conjunctiva, sclera, and the scar tissue as three target tissues after glaucoma filtration surgery and obtained their polarization characteristics from the tissue sections by a Mueller matrix microscope. Discrimination score based on parameters derived from Mueller matrix and machine learning was calculated and tested as a diagnostic index. As a result, the discrimination score of three target tissues showed significant difference between each other ($p<0.001$). The visualization of the discrimination results showed significant contrast between target tissues. This study proved that Mueller matrix imaging is effective in ocular scar discrimination and paves the way for its application on other forms of ocular fibrosis as a substitute or supplementary for clinical practice.

Recently, Mueller matrix (MM) polarimetric imaging-assisted pathology detection methods are showing great potential in clinical diagnosis. However, since our human eyes cannot observe polarized light directly, it raises a notable challenge for interpreting the measurement results by pathologists who have limited familiarity with polarization images. One feasible approach is to combine MM polarimetric imaging with virtual staining techniques to generate standardized stained images, inheriting the advantages of information-abundant MM polarimetric imaging. In this study, we develop a model using unpaired MM polarimetric images and bright-field images for generating standard hematoxylin and eosin (H&E) stained tissue images. Compared with the existing polarization virtual staining techniques primarily based on the model training with paired images, the proposed Cycle-Consistent Generative Adversarial Networks (CycleGAN)-based model simplifies data acquisition and data preprocessing to a great extent. The outcomes demonstrate the feasibility of training CycleGAN with unpaired polarization images and their corresponding bright-field images as a viable approach, which provides an intuitive manner for pathologists for future polarization-assisted digital pathology.

Polarimetry is a powerful optical tool in the biomedical field, providing more comprehensive information on the sub-wavelength micro-physical structure of a sample than traditional light intensity measurement techniques. This review summarizes the concepts and techniques of polarization and its biomedical applications. Specifically, we first briefly describe the basic principles of polarized light and the Mueller matrix (MM) decomposition method, followed by some research progress of polarimetric measurement techniques in recent years. Finally, we introduce some studies on biological tissues and cells, and then illustrate the application value of polarization optical method.

It is of great significance in clinical diagnosis and treatment evaluation to accurately identify the lesion tissue and further extract its characteristics and depth location. In this study, we construct tissue phantoms for three lesion types: fibrosis (FT), organelle proliferation (OPT), and pigmentation (PT). These phantoms allow for the quantitative regulation of mimicked disease depth. The experimental results show that the parameter Kc, combined with MMT parameters, can effectively distinguish the presence of lesions and their abnormal types. Further, the study extracts depth-sensitive polarization feature parameters (DSPFPs) for specific lesion types. Through experiments of tissue phantoms with various depth settings, the established machine learning regression models based on DSPFPs demonstrate their depth retrieval capabilities.