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Polarization imaging is a label-free and non-invasive technique that is sensitive to microstructure and suitable for probing the microstructure of living tissues. However, obtaining deep-layer information from tissues has been a challenge for optical techniques. In this work, we used tissue optical clearing (TOC) to increase optical penetration depth and characterize the layered structures of tissue samples. Different tissue phantoms were constructed to examine changes in the polarization features of the layered structure during the TOC process. We found that depolarization and anisotropy parameters were able to distinguish between single-layer and double-layer phantoms, reflecting microstructural information from each layer. We observed changes in polarization parameter images during the TOC process and, by analyzing different regions of the images, explained the sensitivity of these parameters to double-layer structures and analyzed the influence of oblique incident illumination. Finally, we conducted TOC experiments on living skin samples, leveraging the experience gained from phantom experiments to identify the double-layer structure of the skin and extract features related to layered structures. The results show that the combination of backscattering polarization imaging and tissue optical clearing provides a powerful tool for the characterization of layered samples. [ABSTRACT FROM AUTHOR]

Suspended particles play a vital role in aquatic environments. We propose a method to rapidly measure the scattered polarization parameters of individual suspended particles with continuously large angular range (PCLAR), from 60° to 120° in one shot. A conceptual setup is built to measure PCLAR with 20 kHz; to verify the setup, 10 μm-diameter silica microspheres suspended in water, whose PCLAR are consistent with those simulated by Mie theory, are measured. PCLAR of 6 categories of particles are measured, which enables high-accuracy classification with the help of a convolutional neural network algorithm. PCLAR of different mixtures of Cyclotella stelligera and silica microspheres are measured to successfully identify particulate components. Furthermore, classification ability comparisons of different angular-selection strategies show that PCLAR enables the best classification beyond the single angle, discrete angles and small-ranged angles. Simulated PCLAR of particles with different size, refractive index, and structure show explicit discriminations between them. Inversely, the measured PCLAR are able to estimate the effective size and refractive index of individual Cyclotella cells. Results demonstrate the method's power, which intrinsically takes the advantage of the optical polarization and the angular coverage. Future prototypes based on this concept would be a promising biosensor for particles in environmental monitoring. [ABSTRACT FROM AUTHOR]

Polarization imaging can quantitatively probe the microscopic structure of biological tissues which can be complex and consist of layered structures. In this paper, we established a fast-backscattering Mueller matrix imaging system to characterize the dynamic variation in the microstructure of single-layer and double-layer tissues as glycerin solution penetrated into the samples. The characteristic response of Mueller matrix elements, as well as polarization parameters with clearer physics meanings, show that polarization imaging can capture the dynamic variation in the layered microstructure. The experimental results are confirmed by Monte Carlo simulations. Further examination on the accuracy of Mueller matrix measurements also shows that much faster speed has to be considered when backscattering Mueller matrix imaging is applied to living samples. [ABSTRACT FROM AUTHOR]

Mueller matrix (MM) polarimetry can provide comprehensive information about the polarization properties that are closely related to the microstructural features and has demonstrated its potential in biomedical studies and clinical practices, and bright‐field microscopy is widely used in pathological diagnosis as the golden standard. In this work, we improve the throughput of MM microscopy by learning a statistical transformation between these two imaging systems based on deep learning. Using this approach, the MM microscope can generate an image that is equivalent to a bright‐field microscope image of the matching field of view. We add new transformative capability to the existing MM imaging system without requiring extra hardware. The translation model is based on conditional generative adversarial network with customized loss functions. We demonstrated the effectiveness of our approach on liver and breast tissues and evaluated the performance by four quantitative similarity assessment methods in pixel, image and distribution levels, respectively. [ABSTRACT FROM AUTHOR]

Modern oceans contain large bathymetric highs (spreading oceanic ridges, aseismic ridges or oceanic plateaus and inactive arc ridges) that, in total, constitute more than 20–30% of the total area of the world's ocean floor. These bathymetric highs may be subducted, and such processes are commonly referred to as ridge subduction. Such ridge subduction events are not only very common and important geodynamic processes in modern oceanic plate tectonics, they also play an important role in the generation of arc magmatism, material recycling, the growth and evolution of continental crust, the deformation and modification of the overlying plates, and metallogenesis at convergent plate boundaries. Therefore, these events have attracted widespread attention. The perpendicular or high-angle subduction of mid-ocean spreading ridges is commonly characterized by the occurrence of a slab window, and the formation of a distinctive adakite-high-Mg andesite-Nb-enriched basalt-oceanic island basalt (OIB) or a mid-oceanic ridge basalt (MORB)-type rock suite, and is closely associated with Au mineralization. Aseismic ridges or oceanic plateaus are traditionally considered to be difficult to subduct, to typically collide with arcs or continents or to induce flat subduction (low angle of less than 10°) due to the thickness of their underlying normal oceanic crust (>6–7 km) and high topography. However, the subduction of aseismic ridges and oceanic plateaus occurred on both the western and eastern sides of the Pacific Ocean during the Cenozoic. On the eastern side of the Pacific Ocean, aseismic ridges or oceanic plateaus are being subducted flatly or at low angles beneath South and Central American continents, which may cause a magmatic gap. But slab melting can occur and adakites, or an adakite-high-Mg andesite-adakitic andesite-Nb-enriched basalt suite may be formed during the slab rollback or tearing. Cu-Au mineralization is commonly associated with such flat subduction events. On the western side of the Pacific Ocean, however, aseismic ridges and oceanic plateaus are subducted at relatively high angles (>30°). These subduction processes can generate large scale eruptions of basalts, basaltic andesites and andesites, which may be derived from fractional crystallization of magmas originating from the subduction zone fluid-metasomatized mantle wedge. In addition, some inactive arc ridges are subducted beneath Southwest Japan, and these subduction processes are commonly associated with the production of basalts, high-Mg andesites and adakites and Au mineralization. Besides magmatism and Cu-Au mineralization, ridge subduction may also trigger subduction erosion in subduction zones. Future frontiers of research will include characterizing the spatial and temporal patterns of ridge subduction events, clarifying the associated geodynamic mechanisms, quantifying subduction zone material recycling, establishing the associated deep crustal and mantle events that generate or influence magmatism and Cu-Au mineralization, establishing criteria to recognize pre-Cenozoic ridge subduction, the onset of modern-style plate tectonics and the growth mechanisms for Archean continental crust. [ABSTRACT FROM AUTHOR]

Mueller matrix (MM) microscopy has proven to be a powerful tool for probing microstructural characteristics of biological samples down to subwavelength scale. However, in clinical practice, doctors usually rely on bright-field microscopy images of stained tissue slides to identify characteristic features of specific diseases and make accurate diagnosis. Cross-modality translation based on polarization imaging helps to improve the efficiency and stability in analyzing sample properties from different modalities for pathologists. In this work, we propose a computational image translation technique based on deep learning to enable bright-field microscopy contrast using snapshot Stokes images of stained pathological tissue slides. Taking Stokes images as input instead of MM images allows the translated bright-field images to be unaffected by variations of light source and samples. We adopted CycleGAN as the translation model to avoid requirements on co-registered image pairs in the training. This method can generate images that are equivalent to the bright-field images with different staining styles on the same region. Pathological slices of liver and breast tissues with hematoxylin and eosin staining and lung tissues with two types of immunohistochemistry staining, i.e., thyroid transcription factor-1 and Ki-67, were used to demonstrate the effectiveness of our method. The output results were evaluated by four image quality assessment methods. By comparing the cross-modality translation performance with MM images, we found that the Stokes images, with the advantages of faster acquisition and independence from light intensity and image registration, can be well translated to bright-field images. [ABSTRACT FROM AUTHOR]

Significance: Reflection Mueller matrix imaging is suitable for characterizing the microstructure of bulk specimens and probing dynamic processes in living animals, there are always demands for speed and accuracy for such applications to avoid possible artifacts and reveal a sample's intrinsic properties. Aim: To demonstrate a design of collinear reflection Mueller matrix fast imaging microscope based on dual division of focal plane (DoFP) polarimeters (DoFPs-CRMMM) which has high measurement speed and accuracy. Approach: In DoFPs-CRMMM, to improve the measurement speed, we applied the dual DoFP polarimeters design on the collinear reflection system for the first time to achieve fast imaging in about 2 s. To improve the measurement accuracy, we improved the double-pass eigenvalue calibration method (dp-ECM) by background light correction, and explored the optimization of the set of reference samples. Results: DoFPs-CRMMM was applied to measure the standard polarization samples and monitor the tissue optical clearing process of an artificial layered bulk tissue. Results show that the system has satisfactory performance which can capture the variation of polarization properties during the dynamic process. Conclusions: We present the establishment and demo application of DoFPs-CRMMM. The measurement speed can be further accelerated for potential applications in monitoring dynamic processes or living biomedical systems. [ABSTRACT FROM AUTHOR]