Identification of serous ovarian tumors based on polarization imaging and correlation analysis with clinicopathological features

Ovarian cancer is one of the most aggressive and heterogeneous female tumors in the world,and serous ovarian cancer(SOC)is of particular concern for being the leading cause of ovarian cancer death.Due to its clinical and biological complexities,ovarian cancer is still considered one of the most di±cult tumors to diagnose and manage.In this study,three datasets were assembled,including 30 cases of serous cystadenoma(SCA),30 cases of serous borderline tumor(SBT),and 45 cases of serous adenocarcinoma(SAC).Mueller matrix microscopy is used to obtain the polarimetry basis parameters(PBPs)of each case,combined with a machine learning(ML)model to derive the polarimetry feature parameters(PFPs)for distinguishing serous ovarian tumor(SOT).The correlation between the mean values of PBPs and the clinicopathological features of serous ovarian cancer was analyzed.The accuracies of PFPs obtained from three types of SOT for identifying dichotomous groups(SCA versus SAC,SCA versus SBT,and SBT versus SAC)were 0.91,0.92,and 0.8,respectively.The accuracy of PFP for identifying triadic groups(SCA versus SBT versus SAC)was 0.75.Correlation analysis between PBPs and the clinicopathological features of SOC was performed.There were correlations between some PBPs(δ,β,q_(L),E_(2),rqcross,P_(2),P_(3),P_(4),and P_(5))and clinicopathological features,including the International Federation of Gynecology and Obstetrics(FIGO)stage,pathological grading,preoperative ascites,malignant ascites,and peritoneal implantation.The research showed that PFPs extracted from polarization images have potential applications in quantitatively differentiating the SOTs.These polarimetry basis parameters related to the clinicopathological features of SOC can be used as prognostic factors.

Optical polarization imaging for underwater target detection with non-scatter background

For conventional optical polarization imaging of underwater target,the polarization degree of backscatter should be pre-measured by averaging the pixel intensities in the no target region of the polarization images,and the polarization property of the target is assumed to be completely depolarized.When the scattering background is unseen in the field of view or the target is polarized,conventional method is helpless in detecting the target.An improvement is to use lots of co-polarization and cross polarization detection components.We propose a polarization subtraction method to estimate depolarization property of the scattering noise and target signal.And experiment in a quartz cuvette container is performed to demonstrate the effectiveness of the proposed method.The results show that the proposed method can work without scattering background reference,and further recover the target along with smooth surface for polarization preserving response.This study promotes the development of optical polarization imaging systems in underwater environments.

A STUDY ON PENETRATION DEPTH OF POLARIZATION IMAGING

Optical clearing improves the penetration depth of optical measurements in turbid tissues.Polarization imaging has been demonstrated as a potentially promising tool for detecting cancers in superficial tissues,but its limited depth of detection is a major obstacle to the effective application in clinical diagnosis.In the present paper,detection depths of two polarization imaging methods,i.e.,rotating linear polarization imaging(RLPI)and degree of polarization imaging(DOPI),are examined quantitatively using both experiments and Monte Carlo simulations.The results show that the contrast curves of RLPI and DOPI are different.The characteristic depth of DOPI scales with transport mean free path length,and that of RLPI increases slightly with g.Both characteristic depths of RLPI and DOPI are on the order of transport mean free path length and the former is almost twice as large as the latter.It is expected that they should have different response to optical clearing process in tissues.

Influence of absorption in linear polarization imaging of melanoma tissues

The contrast mechanism of different polarization imaging techniques for melanoma in mouse skin is st udied using both experiments and Monte Carlo simulations.Total intensity,linear polariz-ation diference imaging(DPI),degree of polarization imaging(DOPI)and'rotating linearpolarization imaging(RLPl)are applied and the relative contrasts of these polarization imagingmethods between the normal and cancerous tissues are compared.A two-layer absorption-scat-tering model is proposed to explain the contrast mechanism of the polarization imaging formelanoma.By taking into account of both scattering of symmetrical and asymmetrical scat terersand absorption of inter-scatterer medium,the two-layer model reproduces the relative con trastsfor polarization images observed in experiments.The simulation results also show that,theparameters of polarization imaging change more dramatically with the variation of absorption inthe bottom layer than the top layer.

POLARIZATION IMAGING AND SCATTERING MODEL OF CANCEROUS LIVER TISSUES

We apply diferent polarization imaging techniques for cancerous liver tissues,and compare the relative contrasts for difference polarization imaging(DPI),degree of polarization imaging(DOPI)and rotating linear polarization imaging(RLPI).Experimental results show that a number of polarization imaging parameters are capable of differentiating cancerous cells in isotropic liver tisues.To analyze the contrast mechanism of the cancer:-sensitive polarization imaging parameters,we propose a scattering model cont aining two types of spherical scatterers and carry on Monte Carlo simula tions based on this bi-component model.Both the experimental and Monte Carlo simulated results show that the RLPI technique can provide a good imaging contrast of cancerous tissues.The bi-component scattering model provides a useful tool to ana-lyze the contrast mechanism of polarization imaging of cancerous tissues.

Comparative study of differential polarization imaging using linear and circular polarization in different scattering medium

Differential polarization imaging has been widely used to selectively probe the target embedded in turbid medium.A thorough understanding of image quality involved in differential polarization imaging is essential for practical use.Using polarized light Monte Carlo simulations,it has been investigated how the state of polarization of incident light and the optical properties of scattering medium affect the image contrast.The contrast for linear polarization is similar to that for circular polarization in the isotropic medium comprising small-particles.The image quality is more pronounced for circular polarization in the isotropic medium containing large-particles and the birefringent medium.Furthermore,differential polarization imaging provides better image quality for the birefringent medium compared with isotropic medium.The effect of particle-size and birefringence on the polarization characteristics of target light and backscattered light is investigated.With the help of numerical results,the polarization characteristics of target light and backscattered light,the image quality is well explained in the turbid medium mentioned above.

Multi-foci metalens for spectra and polarization ellipticity recognition and reconstruction

Multispectral and polarized focusing and imaging are key functions that are vitally important for a broad range of optical applications.Conventional techniques generally require multiple shots to unveil desired optical information and are implemented via bulky multi-pass systems or mechanically moving parts that are difficult to integrate into compact and integrated optical systems.Here,a design of ultra-compact transversely dispersive metalens capable of both spectrum and polarization ellipticity recognition and reconstruction in just a single shot is demonstrated with both coherent and incoherent light.Our design is well suited for integrated and high-speed optical information analysis and can significantly reduce the size and weight of conventional devices while simplifying the process of collecting optical information,thereby promising for various applications,including machine vision,minimized spectrometers,material characterization,remote sensing,and other areas which require comprehensive optical analysis.

Correlation of image textures of a polarization feature parameter and the microstructures of liver fibrosis tissues

Mueller matrix imaging is emerging for the quantitative characterization of pathological microstructures and is especially sensitive to fibrous structures.Liver fibrosis is a characteristic of many types of chronic liver diseases.The clinical diagnosis of liver fibrosis requires time-consuming multiple staining processes that specifically target on fibrous structures.The staining proficiency of technicians and the subjective visualization of pathologists may bring inconsistency to clinical diagnosis.Mueller matrix imaging can reduce the multiple staining processes and provide quantitative diagnostic indicators to characterize liver fibrosis tissues.In this study,a fibersensitive polarization feature parameter(PFP)was derived through the forward sequential feature selection(SFS)and linear discriminant analysis(LDA)to target on the identification of fibrous structures.Then,the Pearson correlation coeffcients and the statistical T-tests between the fiber-sensitive PFP image textures and the liver fibrosis tissues were calculated.The results show the gray level run length matrix(GLRLM)-based run entropy that measures the heterogeneity of the PFP image was most correlated to the changes of liver fibrosis tissues at four stages with a Pearson correlation of 0.6919.The results also indicate the highest Pearson correlation of 0.9996 was achieved through the linear regression predictions of the combination of the PFP image textures.This study demonstrates the potential of deriving a fiber-sensitive PFP to reduce the multiple staining process and provide textures-based quantitative diagnostic indicators for the staging of liver fibrosis.

Bioinspired Polarized Optical Flow Enables Turbid Underwater Target Motion Estimation

Underwater target motion estimation is a challenge for ocean military and scientific research.In this work,we propose a method based on the combination of polarization imaging and optical flow for turbid underwater target detection.Polarization imaging can reduce the influence of backscattered light and obtain high-quality images underwater.The optical flow shows the motion and structural information of the target.We use polarized optical flow to obtain the optical flow field and estimate the target motion.The experimental results of different targets under varying water turbidity levels illustrate that our method is realizable and robust.The precision is verified by comparing the results with the precise displacement data and calculating two error measures.The proposed method based on polarized optical flow can obtain accurate displacement information and a good recognition effect.Moving target segmentation based on the Otsu method further proves the superiority of the polarized optical flow under turbid water.This study is valuable for target detection and motion estimation in scattering environments.

Infrared polarization image fusion based on combination of NSST and improved PCA

In view of the problem that current mainstream fusion method of infrared polarization image—Multiscale Geometry Analysis method only focuses on a certain characteristic to image representation.And spatial domain fusion method,Principal Component Analysis(PCA)method has the shortcoming of losing small target,this paper presents a new fusion method of infrared polarization images based on combination of Nonsubsampled Shearlet Transformation(NSST)and improved PCA.This method can make full use of the effectiveness to image details expressed by NSST and the characteristics that PCA can highlight the main features of images.The combination of the two methods can integrate the complementary features of themselves to retain features of targets and image details fully.Firstly,intensity and polarization images are decomposed into low frequency and high frequency components with different directions by NSST.Secondly,the low frequency components are fused with improved PCA,while the high frequency components are fused by joint decision making rule with local energy and local variance.Finally,the fused image is reconstructed with the inverse NSST to obtain the final fused image of infrared polarization.The experiment results show that the method proposed has higher advantages than other methods in terms of detail preservation and visual effect.

Study of Polarization Image Color Fusion Method Based on Color Transfer

Based on the characteristics that human eyes are sensitive to brightness and color, the lightness information of visible image and degree of linear polarization and polarization angle were fused in hue-saturation- value（HSV） space. To meet the observation of human eyes, hue adjustment based on color transfer was carried out to the fused image and hue was adjusted by polynomial fitting method. Hue adjustment method was improved considering the complicated real mapping relationship between hue gray scale of fused image and reference template image. The result shows that the color fusion method presented in this paper is superior to the traditional pseudo-color method and it is helpful to recognize the target from the environment correctly. The fusion result can reflect the difference of object＇s polarization characteristic, and get a natural fused image effect.

VEHICLE SEGMENTATION AND SHADOW HANDLER BASED ON EXTREMUM IMAGE

The shadows similar to the vehicle and the spots caused by vehicle lamps need to be accurately detected in the vehicle segmentation involved in the video-based traffic parameter measurement. Generally, the road surface is different from the vehicle surface in the gray-level architecture. An invariant gray-level architecture-the extremum image in the changing illumination environment is derived and a novel algorithm is presented for detecting shadows and spots. The gray-level structure that is not sensitive to the illumination is employed in the algorithm and the road surface mistaken as vehicles can be removed.

Polarization descattering imaging: a solution for nonuniform polarization characteristics of a target surface

This paper presents a polarization descattering imaging method for underwater detection in which the targets have nonuniform polarization characteristics. The core of this method takes the nonuniform distribution of the polarization information of the target-reflected light into account and expands the application field of underwater polarization imaging.Independent component analysis was used to separate the target light and backscattered light. Theoretical analysis and proof-of-concept experiments were employed to demonstrate the effectiveness of the proposed method in estimating target information. The proposed method showed superiority in accurately estimating the target information compared with other polarization imaging methods.

Temperature Influence on Divergence Angles of Quartz Crystal Wollaston Prism

We propose a structural angle and main refractive indices as two key factors to understand the temperature influence on the divergence angles of the Wollaston prism. The temperature influence on the divergence angles of quartz crystal Wollaston prism is studied theoretically. The results show that divergence angles decrease with increasing temperature, while the divergence angle of e-light decrease more quickly than that of o-light. The testing system is established to verify the above results, and the experimental results are in agreement well with the theoretical analysis.

Detection and localization of the hemoglobin and collagen distribution of the uterine cervix

Changes of the blood vessels and collagen are associated with the development of abnormal cervical cells.Recently,optical coberence tomography and Mueller polarization images were 1used to provide information regarding the presence of collagen fibers in the cervical tissue.However,most of these methods need a lot of time for image recording and are expensive.In addition,the general survey on the absorption and distribution characteristics of collagen and blood in the cervical is still lacking.In this study,we developed a colposcopy combining cross-polarized inage and image procssing algorithm with an fficient analytical model to map the distribution of blood and collagen in the uterine.For this system's proof of concept,we captured and processed the case of cervical ectopy and Nabothian cyst.The results show that the distribution of blood and collagen maps matched with anatomical and physiological when compared with Lugol's iodline images.This technology has some advantages,such as low cost,real time,and can replace the 11se of acetic acid or Lugol's iodine in the future.

Effects of optical axis direction on optical path difference and lateral displacement of Savart polariscope

A simple method is applied to calculating the optical path difference （OPD） of a plane parallel uniaxial plate with an arbitrary optical axis direction. Then, the theoretical expressions of the OPD and lateral displacement （LD） of Savart polariscope under non-ideal conditions are obtained exactly. The variations of OPD and LD are simulated, and some important conclusions are obtained when the optical axis directions have an identical tolerance of ／pm 1^{{／circ}}. An application example is given that the tolerances of optical axis directions are gained according to the spectral resolution tolerances of the stationary polarization interference imaging spectrometer （SPIIS）. Several approximate formulae are obtained for explaining some conclusions above. The work provides a theoretical guidance for the optic design, crystal processing, installation and debugging, data analysis and spectral reconstruction of the SPIIS.

A novel particle tracking algorithm using polar coordinate system similarity

A new algorithm using polar coordinate system similarity （PCSS） for tracking particle in particle tracking velocimetry （PTV） is proposed. The essence of the algorithm is to consider simultaneously the changes of the distance and angle of surrounding particles relative to the object particle. Monte Carlo simulations of a solid body rotational flow and a parallel shearing flow are used to investigate flows measurable by PCSS and the influences of experimental parameters on the implementation of the new algorithm. The results indicate that the PCSS algorithm can be applied to flows subjected to strong rotation and is not sensitive to experimental parameters in comparison with the conventional binary image cross-correlation （BICC） algorithm. Finally, PCSS is applied to images of a real experiment.

Deep learning reconstruction enables full-Stokes single compression in polarized hyperspectral imaging

Polarized hyperspectral imaging,which has been widely studied worldwide,can obtain four-dimensional data including polarization,spectral,and spatial domains.To simplify data acquisition,compressive sensing theory is utilized in each domain.The polarization information represented by the four Stokes parameters currently requires at least two compressions.This work achieves full-Stokes single compression by introducing deep learning reconstruction.The four Stokes parameters are modulated by a quarter-wave plate(QWP)and a liquid crystal tunable filter(LCTF)and then compressed into a single light intensity detected by a complementary metal oxide semiconductor(CMOS).Data processing involves model training and polarization reconstruction.The reconstruction model is trained by feeding the known Stokes parameters and their single compressions into a deep learning framework.Unknown Stokes parameters can be reconstructed from a single compression using the trained model.Benefiting from the acquisition simplicity and reconstruction efficiency,this work well facilitates the development and application of polarized hyperspectral imaging.

Research on a multi‑dimensional image information fusion algorithm based on NSCT transform

Traditional inspection cameras determine targets and detect defects by capturing images of their light intensity,but in complex environments,the accuracy of inspection may decrease.Information based on polarization of light can characterize various features of a material,such as the roughness,texture,and refractive index,thus improving classification and recognition of targets.This paper uses a method based on noise template threshold matching to denoise and preprocess polarized images.It also reports on design of an image fusion algorithm,based on NSCT transform,to fuse light intensity images and polarized images.The results show that the fused image improves both subjective and objective evaluation indicators,relative to the source image,and can better preserve edge information and help to improve the accuracy of target recognition.This study provides a reference for the comprehensive application of multi-dimensional optical information in power inspection.

Inverse-designed Jones matrix metasurfaces for high-performance meta-polarizers

Polarizers have always been an important optical component for optical engineering and have played an indispensable part of polarization imaging systems.Metasurface polarizers provide an excellent platform to achieve miniaturization,high resolution,and low cost of polarization imaging systems.Here,we proposed freeform metasurface polarizers derived by adjoint-based inverse design of a full-Jones matrix with gradient-descent optimization.We designed multiple freeform polarizers with different filtered states of polarization(SOPs),including circular polarizers,elliptical polarizers,and linear polarizers that could cover the full Poincarésphere.Note that near-unitary polarization dichroism and the ultrahigh polarization extinction ratio(ER)reaching 50 d B were achieved for optimized circular polarizers.The multiple freeform polarizers with filtered polarization state locating at four vertices of an inscribed regular tetrahedron of the Poincarésphere are designed to form a full-Stokes parameters micropolarizer array.Our work provides a novel approach,we believe,for the design of meta-polarizers that may have potential applications in polarization imaging,polarization detection,and communication.