Mueller Matrix Microscope Research Articles

Machine learning based local recurrence prediction in colorectal cancer using polarized light imaging.

Current treatment for stage III colorectal cancer (CRC) patients involves surgery that may not be sufficient in many cases, requiring additional adjuvant systemic therapy. Identification of this latter cohort that is likely to recur following surgery is key to better personalized therapy selection, but there is a lack of proper quantitative assessment tools for potential clinical adoption. The purpose of this study is to employ Mueller matrix (MM) polarized light microscopy in combination with supervised machine learning (ML) to quantitatively analyze the prognostic value of peri-tumoral collagen in CRC in relation to 5-year local recurrence (LR). A simple MM microscope setup was used to image surgical resection samples acquired from stage III CRC patients. Various potential biomarkers of LR were derived from MM elements via decomposition and transformation operations. These were used as features by different supervised ML models to distinguish samples from patients that locally recurred 5 years later from those that did not. Using the top five most prognostic polarimetric biomarkers ranked by their relevant feature importances, the best-performing XGBoost model achieved a patient-level accuracy of 86%. When the patient pool was further stratified, 96% accuracy was achieved within a tumor-stage-III sub-cohort. ML-aided polarimetric analysis of collagenous stroma may provide prognostic value toward improving the clinical management of CRC patients.

Hybrid calibration method for Mueller matrix microscopy

System calibration is a crucial step for improving the accuracy of the Mueller matrix microscope, many calibration methods have been proposed and widely used in practice. Most existing calibration methods adopt modeled or un-modeled strategy for the entire system. In this paper, we propose a hybrid calibration method to reduce systematic errors of the Mueller matrix microscope. By considering the characteristics of polarization state generator (PSG) and polarization state analyzer (PSA), we adopt modeled strategy for PSG and un-modeled strategy for PSA, therefore combines the advantages of both modeled and un-modeled calibration methods. By measuring only two reference samples to solve the error model of the PSG and then reconstructing the instrument matrix of PSA. Hybrid calibration method is validated on different Mueller matrix microscopes established in our previous studies, the results show that this method can perform satisfactorily on Mueller matrix microscope with different PSG & PSA schemes, numerical apertures, wavelengths, and optical geometries.

Design and calibration of a Mueller matrix microscope based on liquid crystal variable retarders

Polarization imaging techniques have achieved broad applications in areas such as material characterization, nano-scale measurement, and biomedical diagnosis. The Mueller matrix microscopy, as one of the polarization imaging techniques, can provide the most comprehensive polarization information of a sample, such as anisotropy and depolarization. However, the instrumentation of Mueller matrix microscopy is typically complex and the associated calibration process is usually difficult due to the presence of many polarization and imaging components. In this work, we present an easy-to-follow approach for the instrumentation of Mueller matrix microscopy, not from scratch, but by easily modifying a commercial microscope into a Mueller matrix microscope (MMM) based on liquid crystal variable retarders (LCVR). Optimal configurations have been generated by the genetic algorithm at wavelengths of 400-800 nm. An extended eigenvalue calibration method is proposed to accurately calibrate the polarization and imaging components of the modified instruments in a model-free approach. Experiments performed on standard samples at the wavelength of 532nm, such as a polarizer and a waveplate, have indicated the performances of the developed MMM with a measurement error of less than 0.01 and a mean standard deviation of around 0.0042.

Visualizing chiral structures in cellulose nanocrystal films by a Mueller matrix microscope.

Visualizing chiral structures in solid materials is crucial but difficult in chiral analysis. The three-dimensional structures in the helicoidal nano-assemblies in cellulose nanocrystal (CNC) films were visualized using a Mueller matrix microscope (MMM). Optical analysis of the assembly of CNCs through structural reconstruction by optical simulation revealed the complex structures in CNC films.

Discrimination and quantification of scar tissue by Mueller matrix imaging with machine learning

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 ([Formula: see text]). 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.

Analyzing the Influence of Imaging Resolution on Polarization Properties of Scattering Media Obtained From Mueller Matrix

The Mueller matrix contains abundant micro- and even nanostructural information of media. Especially, it can be used as a powerful tool to characterize anisotropic structures quantitatively, such as the particle size, density, and orientation information of fibers in the sample. Compared with unpolarized microscopic imaging techniques, Mueller matrix microscopy can also obtain some essential structural information about the sample from the derived parameters images at low resolution. Here, to analyze the comprehensive effects of imaging resolution on polarization properties obtained from the Mueller matrix, we, first, measure the microscopic Mueller matrices of unstained rat dorsal skin tissue slices rich in collagen fibers using a series of magnifications or numerical aperture (NA) values of objectives. Then, the first-order moments and image texture parameters are quantified and analyzed in conjunction with the polarization parameter images. The results show that the Mueller matrix polar decomposition parameters diattenuation D, linear retardance δ, and depolarization Δ images obtained using low NA objective retain most of the structural information of the sample and can provide fast imaging speed. In addition, the scattering phase function analysis and Monte Carlo simulation based on the cylindrical scatterers reveal that the diattenuation parameter D images with different imaging resolutions are expected to be used to distinguish among the fibrous scatterers in the medium with different particle sizes. This study provides a criterion to decide which structural information can be accurately and rapidly obtained using a transmission Mueller matrix microscope with low NA objectives to assist pathological diagnosis and other applications.

Deep learning for denoising in a Mueller matrix microscope.

The Mueller matrix microscope is a powerful tool for characterizing the microstructural features of a complex biological sample. Performance of a Mueller matrix microscope usually relies on two major specifications: measurement accuracy and acquisition time, which may conflict with each other but both contribute to the complexity and expenses of the apparatus. In this paper, we report a learning-based method to improve both specifications of a Mueller matrix microscope using a rotating polarizer and a rotating waveplate polarization state generator. Low noise data from long acquisition time are used as the ground truth. A modified U-Net structured network incorporating channel attention effectively reduces the noise in lower quality Mueller matrix images obtained with much shorter acquisition time. The experimental results show that using high quality Mueller matrix data as ground truth, such a learning-based method can achieve both high measurement accuracy and short acquisition time in polarization imaging.

Development and Implementation of a multi-focal plane Mueller matrix microscope

We have developed a polarimetric imaging system to obtain full Mueller matrix images within ten-odd seconds. In this work, a specially designed diffractive grating was incorporated in the Mueller matrix imaging system that enables imaging on different focal planes within the specimen simultaneously. Nine multi-focus images of a starch granule providing full polarization characteristics were demonstrated. The approach not only provided axially-resolved ability but also measured the correlations between the polarization information and the inner structure of the starch granule.

Mueller Matrix Ellipsometric Approach on the Imaging of Sub-Wavelength Nanostructures

Conventional spectroscopic ellipsometry is a powerful tool in optical metrology. However, when it comes to the characterization of non-periodic nanostructures or structured fields that are much smaller than the illumination spot size, it is not well suited as it integrates the results over the whole illuminated area. Instead, imaging ellipsometry can be applied. Especially imaging Mueller matrix ellipsometry is highly useful in nanostructure characterization and defect inspection, as it is capable to measure the complete Mueller matrix for each pixel in a microscope image of the sample. It has been shown that these so-called Mueller matrix images can help to distinguish geometrical features of nanostructures in the sub-wavelength regime due to visible differences in off-diagonal matrix elements. To further investigate the sensitivity of imaging Mueller matrix ellipsometry for sub-wavelength sized features, we designed and fabricated a sample containing geometrical nanostructures with lateral dimensions ranging from 50 to 5,000 nm. The structures consist of square and circular shapes with varying sizes and corner rounding. For the characterization of their Mueller matrix images, we constructed an in-house Mueller matrix microscope capable of measuring the full Mueller matrix for each pixel of a CCD camera, using an imaging system and a dual-rotating compensator configuration for the ellipsometric system. The samples are illuminated at 455 nm wavelength and the measurements can be performed in both transmission and reflection. Using this setup, we systematically examine the sensitivity of Mueller matrix images to small features of the designed nanostructures. Within this contribution, the results are compared with traceable atomic force microscopy measurements and the suitability of this measurement technique in optical nanometrology is discussed. AFM measurements confirm that the fabricated samples closely match their design and are suitable for nanometrological test measurements. Mueller matrix images of the structures show close resemblance to numerical simulations and significant influence of sub-wavelength features to off-diagonal matrix elements.

Nanoform evaluation approach using Mueller matrix microscopy and machine learning concepts

We realized an imaging Mueller matrix microscope for nanostructure characterization. For investigations on nanoform characterization via Mueller matrix images, we measured and simulated Mueller matrix images of specially designed nanostructures. As an approach towards machine learning evaluation in imaging ellipsometry, we calculated Haar-like features of the images and observed a higher sensitivity to subwavelength features in off-diagonal matrix elements compared to microscopy.

Computational image translation from Mueller matrix polarimetry to bright-field microscopy.

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.

Geometric optimization method for a polarization state generator of a Mueller matrix microscope.

We propose a geometric optimization method combined with the Coulombic energy indicator that can uniformly distribute N polarization states on the Poincaré sphere. Based on this method, we investigate the optimal frames of a rotating polarizer and rotating quarter-wave plate (RPRQ)-based polarization state generator (PSG) at different numbers of modulations. We use the PSG on a dual DoFP polarimeter-based Mueller matrix microscope to measure standard samples and pathological sections for testing the performance of an optimized RPRQ. The experimental results show that this method can effectively restrain noise and improve measurement accuracy.

Polarimetry feature parameter deriving from Mueller matrix imaging and auto-diagnostic significance to distinguish HSIL and CSCC

High-grade squamous intraepithelial lesion (HSIL) is regarded as a serious precancerous state of cervix, and it is easy to progress into cervical invasive carcinoma which highlights the importance of earlier diagnosis and treatment of cervical lesions. Pathologists examine the biopsied cervical epithelial tissue through a microscope. The pathological examination will take a long time and sometimes results in high inter- and intra-observer variability in outcomes. Polarization imaging techniques have broad application prospects for biomedical diagnosis such as breast, liver, colon, thyroid and so on. In our team, we have derived polarimetry feature parameters (PFPs) to characterize microstructural features in histological sections of breast tissues, and the accuracy for PFPs ranges from 0.82 to 0.91. Therefore, the aim of this paper is to distinguish automatically microstructural features between HSIL and cervical squamous cell carcinoma (CSCC) by means of polarization imaging techniques, and try to provide quantitative reference index for pathological diagnosis which can alleviate the workload of pathologists. Polarization images of the H&E stained histological slices were obtained by Mueller matrix microscope. The typical pathological structure area was labeled by two experienced pathologists. Calculate the polarimetry basis parameter (PBP) statistics for this region. The PBP statistics (stat_PBPs) are screened by mutual information (MI) method. The training method is based on a linear discriminant analysis (LDA) classifier which finds the most simplified linear combination from these stat_PBPs and the accuracy remains constant to characterize the specific microstructural feature quantitatively in cervical squamous epithelium. We present results from 37 clinical patients with analysis regions of cervical squamous epithelium. The accuracy of PFP for recognizing HSIL and CSCC was 83.8% and 87.5%, respectively. This work demonstrates the ability of PFP to quantitatively characterize the cervical squamous epithelial lesions in the H&E pathological sections. Significance: Polarization detection technology provides an efficient method for digital pathological diagnosis and points out a new way for automatic screening of pathological sections.

Polarization properties of mouse oocyte captured by Mueller matrix imaging

Non-invasive assessment of oocyte quality is of important basis in embryo transfer and other related fields. Until now, the oocyte quality assessment is mainly focus on the morphology observation. Oocyte quality is often reflected in varieties of its microstructure which can be provided by polarization imaging technology. The Mueller matrix is a label-free technique to characterize all polarization properties of samples. This paper used a Mueller matrix microscope for the first time for non-invasive imaging the mouse oocyte. By Mueller matrix analysis, we successfully examined the dichroism, phase delay and scattering depolarization of oocytes, furthermore used the above to compare the polarization properties of mouse oocytes at GV stage and MII stage and the polarization properties of matured fresh oocytes and postovulatory aged oocytes. In this paper changed phase delay were observed before and after oocyte maturation (and oocyte aging). It suggested that the Mueller matrix imaging may provide a potential breakthrough for oocyte quality assessment.

Fast Mueller matrix microscope based on dual DoFP polarimeters.

In this Letter, we report a dual division of focal plane (DoFP) polarimeters-based full Mueller matrix microscope (DoFPs-MMM) for fast polarization imaging. Both acquisition speed and measurement accuracy are improved compared with those of a Mueller matrix microscope based on dual rotating retarders. Then, the system is applied to probe the polarization properties of a red blood cells smear. The experimental results show that a DoFPs-MMM has the potential to be a powerful tool for probing dynamic processes in living cells in future studies.

Comparative study of the influence of imaging resolution on linear retardance parameters derived from the Mueller matrix

Polarization imaging techniques are emerging tools to provide quantitative information of anisotropic structures, such as the density and orientation distribution of fibers in tissue samples. Recently, it is found that when using Mueller matrix polarimetry to obtain the structural features of tissue samples, some information can be revealed by relatively low-resolution polarization parameter images. Thus, to analyze what kinds of anisotropic optical and structural information contained in high-resolution polarization images are preserved in low-resolution ones, here we carry out a comparative study of the influence of imaging resolution on the Mueller matrix derived linear retardance parameters. We measure the microscopic Mueller matrix of human healthy breast duct tissues and ductal carcinoma in situ (DCIS) tissues, which have distinct typical fibrous structures, using objectives with different numerical aperture. Then we quantitatively compare a group of image texture feature parameters of the linear retardance parameters images under high and low imaging resolutions. The results demonstrate that the fibers density information contained in the texture features of linear retardance δ parameter image are preserved well with the decline of imaging resolution. While for the azimuthal orientation parameter θ which closely related to the spatial location, we still need high imaging resolution to obtain quantitative structural information. The study provides an important criterion to decide which information of fibrous structures can be extracted accurately using transmission Mueller matrix microscope with low numerical aperture objectives.

Error Analysis and Calibration Improvement of the Imaging Section in a Mueller Matrix Microscope

Currently, there are various calibration methods available to reduce the errors caused by the polarizing section of a dual-rotating-retarder polarimeter. Although these methods have high measurement accuracy, their robustness must be improved and the influence of the imaging section needs be discussed when they are applied in Mueller matrix microscopes. In this paper, a method of error source analysis and element calibration for the Mueller matrix microscope is proposed by using error transform coefficient matrices to account for the polarizing effect of the imaging section. Using Taylor expansion, an approximate linear relationship is established between the sources of errors and the Mueller matrix elements of the measured sample. From this relationship, error magnification coefficient matrices are calculated to determine the specific parameter errors in both the polarizing and imaging sections. Furthermore, elements in the fourth row or column of the error magnification coefficient matrix are especially important for the imaging section. The measurement and simulation results for an air sample and a quarter-wave plate sample as the standard samples, as well as a Daphnia organism sample with complex internal structure, are investigated and discussed. Furthermore, the comparison results reveal the effect of the imaging section on the birefringence characteristics of the Mueller matrix. With the proposed method, the maximum error can be reduced to be less than 0.01 for all the matrix elements and for the amplitude parameter of birefringence, even when the two system parameters a 2 and a 3 of the rotating mechanical part deviate from the default.

A collinear reflection Mueller matrix microscope for backscattering Mueller matrix imaging

We developed a collinear reflection Mueller matrix microscope by adding polarization state generator (PSG) and polarization state analyzer (PSA) into the illumination and detection optical paths of a commercial metallurgical microscope. It is found that specific efforts have to be made to reduce the artifacts due to the intrinsic polarizations of the optical system, particularly the dichroism due to the 45° beam splitter. We adopt a new calibration method based on numerical reconstruction of the instrument matrix to minimize the artifacts of the beam splitter. Using a reflection mirror as the sample, maximum error in the calibrated Mueller matrix elements is smaller than 0.02. Preliminary test results using electrospinning samples show that the collinear reflection Mueller matrix microscope can effectively minimize the dependence of Mueller matrix to azimuth orientations and enhance the capability for characterizing the microstructural features of anisotropic samples.

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.

Quantitative discrimination of biological tissues by micro-elastographic measurement using an epi-illumination Mueller matrix microscope.

We propose a method for estimating the stiffness of bio-specimens by measuring their linear retardance properties under applied stress. For this purpose, we employ an epi-illumination Mueller matrix microscope and show the procedures for its calibration. We provide experimental results demonstrating how to apply Mueller matrix data to elastography, using chicken liver and chicken heart as biological samples. Finally, we show how the histograms of linear retardance images can be used to distinguish between specimens and quantify the discrimination accuracy.