This PDF file contains the front matter associated with SPIE Proceedings Volume 12560, including the Title Page, Copyright information, Table of Contents, and Conference Committee listings.

In order to solve the technical problems of accurate measurement of corneal parameters and effective quality evaluation of ophthalmometers, The National Institute of Metrology (NIM) independently develops a series of standard model eyes with parameters of both radius of curvature and astigmatic axis by using spherical and toric surface design based on corneal surface reflection imaging, and for the first time the physical standard is provided at home and abroad. The radius measurement range is (5.5~10.0) mm and the astigmatic axis range is 0º~180ºwith measurement uncertainty of 0.002 mm and 1ºrespectively with coverage factor of 2. The standard model eyes have been widely used and promoted, supporting the measurement standard establishment for metrological quality inspection institutions in various provinces and cities, effectively solving the test and calibration of human corneal parameter measurement instruments such as the ophthalmometer, thus forming the quantity value transmission and traceability system of the ophthalmometer across the country. In 2020, NIM, as the pilot laboratory, undertakes the national measurement comparison project for the radius verification ability of ophthalmometers which is approved by the State Administration for Market Regulation. A total of 33 laboratories participate in the comparison. Normalized deviation E_n value is used to evaluate the comparison results. The absolute E_n values of 33 participated laboratories are all less than 1. The difference between the measurement results and the reference values is within reasonable expectations, and the comparison results are acceptable for each participated laboratory. The measurement comparison results prove that the consistency and effectiveness of the standard model eyes for ophthalmometers is good, and the accuracy and consistency of the measurement results issued by each participated laboratory is effectively evaluated too. Therefore, the accuracy and reliability of the measurement results of ophthalmometers can be ensured.

Tooth is of great significance to human health. With age, the characteristics of the teeth will change. At present, different detection methods have been developed to detect the characteristics of teeth. However, the existing detection methods have shortcomings. In view of the effective characterization of teeth characteristics in different age groups, this paper aims to explore spectral polarization method, namely a non-destructive and low-loss detection method, which is a useful supplement to conventional detection methods. The method for spectral polarization to effectively characterize the tooth characteristics of different ages was proposed. Tooth samples from 7 different age groups, such as 10-20 years old, 20-30 years old, 30-40 years old, 40-50 years old, 50-60 years old, 60-70 years old and over 70 years old, were selected; 4 different observation spectrum bands such as 450nm, 550nm, 670nm, 870nm were selected; the polarization parameters were selected to describe the spectral polarization characteristics of the teeth, and a polynomial correlation mathematical model was constructed. The experimental results showed that the tooth samples in the same age group showed a negative correlation between spectrum band and polarization characteristics. The polarization characteristics of tooth samples in subjects aged 50-60 years old reached the peak value for the same observation band. Construction of the model could effectively interpret the coupling correlation between tooth samples and spectral polarization characteristics in different age groups. The research content of this paper effectively expands the method of tooth characteristic detection, reveals that spectral polarization can effectively characterize tooth characteristics, and develops a novel non-destructive and lowloss polarization spectral detection technology.

Raman spectroscopy, a “fingerprint” spectrum of substances, can be used to characterize various biological and chemical samples. To allow for blood classification using single-cell Raman spectroscopy, several machine learning algorithms were implemented and compared. A single-cell laser optical tweezer Raman spectroscopy system was established to obtain the Raman spectra of red blood cells. The Boruta algorithm extracted the spectral feature frequency shift, reduced the spectral dimension, and determined the essential features that affect classification. Next, seven machine learning classification models and deep learning model without dimensionality reduction are analyzed and compared based on the classification accuracy, precision, and recall indicators. The results show that support vector machines and convolutional neural network are the two most appropriate machine learning algorithms for single-cell Raman spectrum blood classification, and the findings provide essential guidance for future research studies.

As one of the most fatal cancers, pancreatic cancer generated nearly a half million of new cases world-widely in 2021. The cure rate of pancreatic cancer is extremely low, whose five-year survival rate after surgery is less than 5%, leading to a great demand of early diagnosis. Currently, the aspiration biopsy with hematoxylin-eosin (H&E) staining is considered as one golden standard for clinical cancer diagnosis. However, the accuracy of the identification of the biopsy is unsatisfied, which is highly affected by the experience of doctors. Here, we have used fluorescence lifetime imaging microscopy (FLIM) method to analyze H&E stained sections, providing quantitative data for further identification. Mice were randomly selected, divided into the experimental group injected with pancreatic cancer cells and the control group. Then the pancreatic tissues of both groups were obtained and stained with H&E dye solution. Next, the sections were imaged with FLIM system, providing fluorescence lifetime data for analysis. The results showed that the average fluorescence lifetime value of normal tissues was around 30.5% less than that of cancerous tissues. Moreover, phasor plot software was applied to distinguish certain regions (such as desmoplasia), which were not identified in either the bright-field-image mode nor the fluorescence lifetime mode. In conclusion, FLIM technique on H&E stained sections has generated quantitative information to identify cancerous tissues as well as desmoplasia, leading to an improved diagnostic accuracy. This FLIM-based method in analyzing H&E stained sections has a high potential in further quantitative diagnosis of different types of cancers.

Esophageal carcinoma is a common clinical cancer and with sixth occurrence frequency in the world, has a low five-year survival rate. Among different types of esophageal carcinoma, esophageal squamous cell carcinoma (ESCC) has the highest incidence rate and has a poor prognosis after surgery. For clinical diagnosis, hematoxylin and eosin (H&E) stained sections of diseased tissues are considered as the “golden standard”. However, determination of the tumor regions is usually relied on professional experience, which is time consuming and has a high misdiagnosis rate. Currently, novel optical imaging tools such as multi-photon excitation imaging and fluorescence lifetime imaging microscopy (FLIM) have been applied in clinical diagnosis. FLIM contains advantages of accurate measurement and high sensitivity to microenvironment. In this work, we constructed mice orthotopic esophageal cancer model to investigate the characteristics of esophageal tumor cells. Then FLIM technique were used to investigate H&E stained sections from both healthy control mice and ESCC mice, providing difference between the fluorescence lifetime values of normal tissues and those of the pathological tissues. Results also revealed an alteration of the fluorescence lifetime values of esophageal stratum corneum, which might be generated through tumor extrusion. Furthermore, the fluorescence lifetime values of tumor cells are distinctly smaller than those of the surrounding stroma, indicating an accurate identification the lesion area. In conclusion, the fluorescence lifetime images obtained by FLIM could provide a quantitative method in future pathological identification.

Miniature two-photon microscopy combines the two-photon excitation principle and is more lightweight and flexible, allowing it to be applied to freely behaving animals. The piezoelectric tube (PZT) fiber scanner is the key actuated component in miniature fiber-scanning two-photon endomicroscopy (TPEM). In this paper, we use multi-physics field finite element simulation to model and analyze a reverse-fixed PZT fiber scanner for TPEM. The simulation results show that the first two resonant frequencies of the PZT fiber scanner are 163.6 Hz and 757.9 Hz, respectively. At the first two resonant points, the PZT fiber scanner scan range are 0.078 mm and 0.68 mm, respectively. Theoretical guidance for frequency selection of the reverse-fixed PZT fiber scanner is provided by these simulation results.

Stroke is a group of diseases with severe brain tissue damage, which are caused by either the sudden rupture of brain blood vessels (cerebral hemorrhage) or brain blood vessel obstruction, leading to rapid changes and high mortality. The diagnosis of stroke mainly relies on medical imaging techniques, including Computed Tomography (CT) and Magnetic Resonance Imaging (MRI), which require experienced radiologists to guarantee suitable accuracy. However, the amount of brain CT image data is extremely large, usually exceeding the technical capabilities of radiologists. Currently, artificial intelligence has been applied into CT image analysis in order to achieve high sensitivity and specific diagnosis results for clinical examinations. In this work, we obtained CT images from a database (CQ500), including epidural hemorrhage, cerebral parenchymal hemorrhage and intraventricular hemorrhage. Then, we introduced a deep-learning algorithm based on U-Net model, which was trained to generate image segmentation, providing a calculated accuracy of prediction yield. The results showed that the average intersection ratio of the final model on the test set could reach the value of 0.96. Briefly, artificial intelligence in this work can efficiently improve the analysis of brain CT images, suggesting an important development direction for future medical imaging auxiliary diagnosis.

Usually, when there is no glare light source, the light reflected by the target is received by the human eye and then imaged on its retina. The observer can clearly see the target object, and the human eye can correctly judge the movement speed and direction of the target. However, when the glare light source exists, the glare light is scattered to form a light curtain, which is superimposed on the retina. If the scattered light is not too strong, it will not cause discomfort to the human eye, but it reduces the observer's perception of the target object. The visual sense reduces the contrast between the target object and the environment in the human eye, and reduces the human visual response speed. Incoherent directional beam glare interferes with the visual function of normal eyes through instantaneous strong light stimulation, causing temporary loss or decline of visual function, as well as image retention, discomfort, and avoidance responses such as blinking, closing eyes, and turning heads. Based on the mechanism of glare effect, the influencing factors of glare were analyzed, and the influence of incoherent directional beams on human vision was studied from the aspects of light source brightness, irradiation time, flicker frequency, etc. The research results provide data support for the design and use of incoherent glare weapons, and lay the foundation for the application of incoherent directional beam glare weapons in public security fields such as border defense and denial, maritime expulsion, and anti-terrorism and stability maintenance.

The Double Stokes-Mueller polarimetry (DSMP) is an efficient imaging technique that extract the second-order nonlinear optical properties of tissues. Many errors are inevitably introduced into DSMP in medical estimating, such as intensity errors and instrument errors. In order to improve the precision in medical estimating, we optimized the optical measurement of the polarimeter through the following steps. Firstly, we introduce the principle of DSMP. The double Mueller matrix of DSMP is 4 × 9 matrix and thus the polarization state generator (PSG) generates 9 different polarization states of incident light and the polarization state analyzer (PSA) performs 4 measurement states to analyzes every state of the emergent light. Secondly, we demonstrate the 36×36 measurement matrix for obtaining the double Mueller matrix of DSMP. Condition number is used to be the evolution for the measurement matrix. Finally, we post the result of optimal azimuth angles for the measurement matrix. Minimal condition number for DSMP is 8.07. The experiment is proved that the optimal design of the measurement can well perform.

Polarimetry is an important noninvasive blood glucose measurement method and attracts extensive attention from researchers. However, one of the difficulties associated with polarimetry is the low concentration of blood glucose, which results in weak optical rotation signals. In this paper, we report a fast and accurate spatial polarization modulation system (SPMS) that can measure the low glucose concentration by analyzing a single digital image. In this system, the rotated polarizer gain mechanism (RPGM) is adopted to amplify the weak optical rotation signals. And in order to extract the optical rotation signals from the background more easily, a vortex phase difference retarder (VPDR) is employed to modulate the optical rotation signals, which is a specially designed birefringent crystal with a vortex phase difference along the azimuth angle. We have established the theoretical model of the SPMS by the Jones matrix theory, and both the simulation experiments with noise and without noise have shown that the SPMS has a resolution of 100mg/dl.

This article is based on the principle of thermal convection PCR and nucleic acid fluorescence intensity detection technology. The principle of thermal convection PCR is to form a temperature difference by separately controlling the upper temperature and the bottom temperature of the reaction tube. The lower temperature liquid at the upper part has relatively high density or specific gravity, and the upper and lower liquids will produce convection, which drives the flow of molecules in the tubular chamber. The reaction solution is formed into thermal convection in the reaction test tube and subjected to different temperatures, so as to meet the required conditions for the reaction of different enzymes, and realize the pre-denaturation, annealing and extension processes in the nucleic acid PCR amplification in a short time. Nucleic acid fluorescence intensity detection technology involves embedded system design for device control and signal analysis, optical system design for optical signal filtering and collection, and differential amplifier circuit design. The embedded system design is based on the development of precise temperature control system, motion system and signal analysis system based on Stm32 single-chip microcomputer. The temperature control system includes independent temperature control to control the heaters at the bottom of the reaction tube and the top of the reaction tube respectively; the motion system includes sample switching and switching of the light source in the imaging system. The optical system design includes 540nm FAM excitation light source, 570nm CY3 excitation light source and spherical lens focusing excitation system. This device uses a photodiode to convert the optical signal into an electrical signal, and then amplifies the collected electrical signal with a two-stage operational amplifier through a two-color light differential amplifier circuit, and then uses the signal analysis system to record and display the electrical signal changes in real time, and Make a qualitative analysis. This device not only has the advantages of low cost and high sensitivity, but also solves the key problem of the long time (more than 2 hours) of the whole process of real-time fluorescent quantitative PCR in the detection of new crown nucleic acid and cannot be screened quickly on site. The PCR time of this device is from 2 The hour is reduced to 30 minutes, which is suitable for POCT inspections, and achieves rapid screening goals for crowds of people, which isconducive to responding to acute nucleic acid detection and large-scale nucleic acid detection. This device is currently used with COVID-19 detection reagents to detect new coronaviruses, and realize the detection of 20 copies of nucleic acid sensitivity within 30 minutes. Four samples can be processed in batches at a time, and the sample size for single processing can be increased appropriately according to needs. This device provides rapid and sensitive screening methods for global epidemic prevention and control, and is of great significance to improve human health. This device can also be applied to other rapid nucleic acid detection fields. With different nucleic acid detection reagents, this device can detect different gene loci, and has a broad development space and application fields.