Session Index

To find out how neurons in Suprachiamatic nucleus, a small nucleus at the bottom of the hypothalamus that acts as the principal circadian clock of brains, generate a coherence daily rhythm, the computed neuronal network at SCN is necessary to be clarified. Among genetically encoded voltage indicators, ASAP-family are currently the only ones to reflect single-spike signals and to optically characterize individual neuron coding dynamics. We report a 1.5-kilohertz-frame-rate microendoscopy system with GRIN lens which enables high-speed two-photon voltage imaging to observe the quick response of action potential in deep mice brain, and thus help identify the millisecond-level neuronal activity.

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Harmonic generation microscopy (HGM) is a non-invasive in-vivo label-free 3D imaging technique. In recent years, HGM shows great potential in improving quality and efficiency in medical treatment. However, the image modality of HGM is different from widely-used H&E-staining approach which pathologists are familiar with. This paper proposes a new image translation from HGM images to H&E-stained images. Specifically, this paper presents an unsupervised deep-learning based methodology to effectively synthesize H&E-stained image with given HGM image. Result indicates that the proposed methodology is promising in medical image translation and hopefully will facilitate adopting HGM in clinical workflows in the near future.

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The temporal focusing multiphoton microscopy can rapidly provide 3D imaging, but strong scattering through biotissue will degrade the image quality and reduce the penetration depth. In the study, we present a prediction learning model with depth information to overcome. A 3D U-Net network with digital propagation matrix has been developed to predict and improve different layer images under cross-modality training. Furthermore, a long short-term memory-based network, which is designed to forecast the deeper information according to previous 3D information, is introduced for the prediction of depth information.

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This study explores and implements the use of U-curve method to determine the regularization parameter to reconstruct diffuse optical images and use some simulated measurement data to observe the image reconstruction. Some synthesized case examples and experimental ones as well are conducted to verify the performance. uses some simulated measurement data to observe the image reconstruction.

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Isotropic Quantitative Differential Phase Contrast Microscopy (iDPC) is a novel
phase imaging method. We can accurately quantify structural information in living cells under
label-free conditions. Here, we present a U-net model that implements the transformation from
intensity to phase images and obtain the quantitative phase information. Compared to use of
Tikhonov regularization, this deep learning model not only replaces complex calculation and
parameter setting but also achieves isotropic results with only half the number of images, and
incresese the imaging efficiency two times. The results facilitate time-lapse observation for
recording dynamic cellular information.

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We present a label-free approach to achieve three-dimensional measurement and quantitative analysis in tens of seconds for cell death using holographic tomography. In the experimental results, the morphological changes and internal structures of neuroblastoma cell in autophagy and apoptosis are demonstrated with three-dimensional tomographic images.

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This study aimed to develop a versatile OCT ophthalmic detection platform, including structural imaging, angiography, and stimulus-evoked Intrinsic Optical Signal (IOS). We obtain cross-sectional images of the retinal structures of BALB/c mice under optical stimulation by OCT scanning. In addition, IOS assessments were performed for the cross-sectional images of retinal structures, providing a non-invasive, non-contact, and relatively simple method for evaluating eye function.

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PS-OCT is a non-destructive and three-dimensional imaging technique that can provide polarization property, e.g., phase retardation and optical axis, as well as the architectural information similar to conventional OCT from the sample. In this study, we have developed a high-speed PS-OCT imaging engine by using a novel wavelength-swept laser light source based on HCG-VCSEL. Example PS-OCT imaging including the human fingernail junction, 3D plastic printing material and the chicken breast tissue demonstrated the depth resolved measurement of the multifunctional information of the sample with PS-OCT and HCG-VCSEL light source at an A-scan rate of 250 kHz.

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Diffuse spectroscopy, a variant of diverse spectroscopic methods, has been used for investigating tissue properties for decades. This technique can work with proper models to noninvasively quantify chromophore concentrations of bulk tissues. Models designed for deep tissue interrogation have been established to enable the application of diffuse spectroscopy for studying the dynamics of functional parameters of deep tissues, such as stimulation-induced hemodynamics of the brain or muscle, or the variation of water and fat concentrations of breasts caused by chemotherapy. On the other hand, due to the strong stochastic nature of light propagation in turbid media near the light source, building models for superficial tissue studies have been a challenging task and thus this topic has been vastly studied in recent years. In this talk, I will discuss the attempts we have made to develop useful models that can work in conjunction with specialized diffuse reflectance spectroscopy configurations for the effective evaluation of functional parameters of superficial tissues such as skin collagen, hemoglobin, bilirubin, and glucose. It will also be illustrated how these local and systematic functional parameters are related to the monitoring or diagnosis of numerous diseases such as keloid, psoriasis, jaundice, and diabetes.

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Our previous work has achieved automatic neural canal opening (NCO) detection by deep learning model with fully connected (FC) layer connected after a convolutional neural network (CNN). Considering the lost spatial information of the FC layer and generality of the model, we replace the FC layer with the differentiable spatial to numerical transform (DSNT) layer in this work. Our model converges faster with an accuracy of 97% and an intersection over union (IoU) of 0.85, which is close to the accuracy (97%) and IOU (0.87) of previous work.

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We present an unsupervised model to enhance images in nonlinear optical microscopy. Without statistical assumptions, it can be applied to unseen samples with various hardware settings which shows significant improvement in the image-enhancement task.

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Quality of life can be improved in people living with dementia (PWD) by reducing the sleep disturbance. Studies show that the 24-hour light cycles is a key trigger affecting sleep. We developed a dynamic lighting system to generate uniform white light using 6 different colored LEDs that varies over 254 hours. The intensity at wavelength (λ)~480 nm maximizes at noon, reduces during the evening hours and is minimal at night causing a person wakeful. This system was redesigned to meet Canadian and North American safety standards.

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The aim of this paper is to demonstrate a novel architecture of deep learning that addresses the prediction of breast cancer when it pertains to diffuse optical imaging (DOI). We were able to localize structure representations in larger areas more effectively than in smaller structures using our hybrid architecture. This study is among the foremost to specifically address signal and image domains combined in diffusion reconstruction in DOT. The network connects two encoders with one decoder path, which optimally utilizes more information from signal data and raw images.

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Quantitative differential phase contrast (QDPC) microscopy plays an essential role in the biological field since it visualizes thin transparent samples. Tikhonov regularization is typically used for phase reconstruction in QDPC imaging. However, the regularization parameter needs to be tuned manually and the selection of the parameter influences reconstructed phase images. We proposed a self-supervised deep learning-based algorithm using deep image prior (DIP) to solve this issue. The algorithm can predict phase without pre-training with a dataset and ground truth images with DIP. The proposed method was simulated, and a standard phase target was used to validate the method's feasibility.

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3D optical imaging of biological tissue at high spatial resolution over a large scale bridges the observation and understanding of biological systems at cellular and tissue level. Imaging and reconstruction of physically sectioned tissue slices was perhaps the only way to perform such study. Although it is possible to achieve submicron, even super resolution by imaging thin tissue slices, the method wasn’t widely adopted due to the technical limitations and practical difficulties to implement the technique in different researches.
Expansion microscopy (ExM) is an emerging technology that enables biological samples to be imaged with nanoscale precision and resolution on ordinary, diffraction-limited microscopes. ExM generally works by physically magnifying a specimen in a uniform (isotropic) manner in three dimensions, which could easily achieve super-resolved image on the diffraction-limited microscope.
The holy grail in optical microscopy is imaging 3D biological specimen with the resolution, the same as in electron microscopy. Electron microscopy (EM) has a lot better spatial resolution but no color information and presumably limited to 2D. Instead, optical microscopy has chemical information due to fluorescent labeling with 3D fashion. Here, we are performing lightsheet microscopy combined with expansion microscopy to let optical microscopy meet electron microscopy and aim to map the orientation of the protein of interest at the intact tissue without physically sectioning.

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Osteoporosis is a severe health problem in an aging society, causing patients to suffer a higher risk of bone injury. As a result, early diagnosis is essential. To achieve quick, easy, low-cost, and non-invasive detection of osteoporosis, we develop an optical bone densitometer to predict bone mineral density via deep learning algorithm. The recent results are improved from our previous study, revealing the potential of OBD in BMD prediction.

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Our study aims to use non-invasive near-infrared spectroscopy (NIRS) to detect the changes in blood oxygen concentration of extracorporeal membrane oxygenation (ECMO) patients when adjusting speed. First, we apply various data processing to the measured blood oxygen value and record the patient's APACHE-II scale score. Patients are divided into two groups by scores of 24. Afterward, we combine the metric blood oxygen information with the APACHE-II scores and do binary classification. In Veno-Arterial (VA) group, we get the train and test accuracies of 83.3% and 81.8%, while in Veno-Venous (VV) group, the corresponding accuracies are 81.8% and 72.7%.

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Providing an appropriate prognosis for patients with peripheral arterial occlusive disease (PAOD) is essential. In this study, near-infrared spectroscopy (NIRS) was used to monitor the change of blood oxygenation of the lower limbs, combined with support vector machine (SVM) to build a prediction model of surgical effect. The model training and testing accuracies are 89.19 % and 80 %, respectively. In addition, the result of feature selection showed that tissue saturation index (TSI) could reflect the adjustment and stability of blood oxygenation of patients under external influence.

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Cell imaging largely relies on fluorescence-based microscopy because of the high detection sensitivity and molecular specificity achieved by labeling the sample with fluorophores. Unfortunately, resolving nanoscopic cell dynamics remains a challenge due to the photobleaching of fluorophores. In this talk, I will present scattering-based optical interference microscopy that facilitates direct visualization of nano-dynamics in living cells. The linear scattering signal is stable and indefinite, supporting sensitive and precise measurements at a high speed. Using common-path interferometry, the scattering imaging is highly sensitive, enabling direct observation of nano-sized biological objects. With proper image data analysis, organelle specific, high-resolution cell images can be obtained without any labels. Using our methods, rapid biological processes occurring in the millisecond timescale are resolved at high spatiotemporal resolution, including remodeling of chromatin and endoplasmic reticulum network. The label-free optical interference microscopy offers the opportunity to explore nanoscale cell dynamics with unprecedented details

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We demonstrated three-photon fluorescence microscopy for drosophila brain imaging based on a 24-MHz Cr:forsterite oscillator. We studied the soliton mode-locking dynamics to optimize the output pulse width and peak power by managing the intracavity dispersion. We have realized three-photon fluorescence imaging, and the imaging contrast and penetration depth are much better than the results obtained from the two-photon excitation. Moreover, we found that the signal-to-background ratio at depth is greatly improved when using shorter pulses from the laser oscillator. For functional imaging applications, we also demonstrated three-photon calcium imaging stimulated by an external electric shock.

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Early diagnosis of esophageal cancer is effective in treatment. Currently, computer aid in endoscopic image classification tasks has achieved remarkable achievements. A total of 936 endoscopic images were used for the training, which included 498 white-light images (WLI) and 438 narrow-band images (NBI). The esophageal neoplasms are classified into 3 groups: squamous cell carcinoma, dysplasia, and normal. Vision Transformer is proposed to improve prediction results. The prediction results are as follows: 93.55% of accuracy, and f1-score 92.86%, respectively.

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Glycated-hemoglobin- (HbA1c-) fraction is universally used in diagnosing diabetes and guiding therapy. Our recent efforts indicate that by analyzing the HbA1c distribution of red blood cells (RBCs), one could further unravel the much-needed information of glycemic variability. Here, we introduce spectrally-resolved third-harmonic-generation (srTHG) microscopy, which for the first time noninvasively provide the HbA1c imaging at the single-RBC level and map the HbA1c distributions clinically.

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In this study, we aim to figure out a better instruction method. We apply two instruction method, traditional didactic instruction (TDI) and interactive response system multiple assessment-assisted instructions (IRSAI) to senior high school education. To evaluate the effect on students’ cognitive function, we record the changes in cerebral oxygen concentration in the prefrontal cortex via functional near-infrared spectroscopy (fNIRS). Then, feed the proceed data into a machine learning model to classify, and get the training accuracy and testing accuracy of 85% and 80%, proving the feasibility of instruction evaluation via fNIRS.

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A swept-source optical coherence tomography (SS-OCT) is a non-invasive imaging technique with high resolution in a small area. A fiber-based auxiliary interferometer is implemented in SS-OCT to the correct spatial distance error from laser output nonlinearity. To
deliver the chip-based SS-OCT, a delayed Mach-Zehnder interferometer built with two broadband couplers on the silicon-on-insulator platform demonstrates the axial resolution of 20 mm through the zero-crossing resampling.

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A grating coupler-based spectral-domain optical coherence tomography is miniaturized through the photonic integrated circuit technology on a silicon-on-insulator platform. We present the design and technology verification of a Mach-Zehnder typed broadband coupler. The experimental results showed that the A-scan depth information after signal processing was 22.92 um and 48.5 dB for longitudinal resolution and sensitivity, respectively.


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To image living organisms, optical sectioning and high-speed image acquisition are required. Using diffractive optical elements, such as volume hologram and metalens, we designed and developed a compact diffractive light sheet fluorescence microscope (DLSFM) system and experimentally demonstrated in-vivo fluorescence imaging of Caenorhabditis elegans (C. elegans).

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We explored the cellular localization of μ-opioid (MOP) and nociceptin/orphanin FQ (NOP) receptors regulated by opioids. We overexpressed the fluorescence-tagged receptors (MOP-CFP & NOP-YFP) via transfecting HEK 293 cells transiently and then measured the variations of fluorescent signals in single-particle tracking (SPT) and fluorescence resonance energy transfer (FRET) by two-photon fluorescence microscopy. The results could be helpful in unraveling the cellular signaling after these receptors are stimulated by opioids.

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We have investigated the optical system design to realize nonlinear mesoscope for optical virtual biopsy. For simplifying the system and realizing image stitching, we generalize the relay lenses system while maintaining a satisfactory two-photon uniformity of 95% at a scanning angle ±7°. We obtain a stitched leaf image at sub-micron resolution with the field of view of 1.8×1.8mm2, without moving the sample. We also integrate the system into a portable setup, including the delivery of femtosecond pulses with manageable nonlinear spectral conversions. We will discuss the feasibility of our system for ex vivo skin observation in the presentation.

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The main goal of this study is to design two clinical experiments for examining our diffuse reflectance spectroscopy algorithm’s capability in measuring the variation of cytochrome c and cytochrome c oxidase in mitochondria that are linked to tissue vitality. Our findings suggest that our system could be used to noninvasively monitor wound healing, treatment of hair loss, and diabetic foot caring in the future.

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An Arduino based three gas stage-top incubator is designed and developed for biomedical experiment. The Arduino system is used to control three environment conditions: temperature, gas concentration, and humidity. Our system can provide detection of the gas concentration and creates a moderated environment which are useful for biomedical experiments.

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Optical activity related to molecular chirality are significant in the circular dichroism characteristics to determine the configuration of a chiral molecule. We used L-lactic acid (L-LA) and a transparent glue to produce biodegradable films. Adjusting the number of layers comprising L-LA and glue leads to different phase differences, forming L-LA films. Six layers and 0.8% L-LA solution were the optimal conditions to fabricate an film. The circular-polarization experiment showed that the change in the signal intensity was less than 2% at a specific angle of the L-LA film. In summary, circularly polarized light was successfully produced using the L-LA film.

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In this study, the nondestructive blood glucose concentration evaluation of human using near infrared (NIR) spectroscopy measurement is performed. To perform a quantitative analysis, the high power IR LEDs with wavelengths of 850 and 940 nm are used in NIR reflection spectroscopy measurement. Then the calibration model is investigated to predict the blood glucose concentration of the participants from the NIR reflection measurements alone.

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Jaundice is a phenomenon of high serum bilirubin concentration. The prevalence of neonatal jaundice can reach 80% and 21%. The gold standard is still the concentration of bilirubin in blood samples. However, this method cannot be used for continuous bilirubin level monitoring. Also, drawing blood from newborns can be difficult. Traditional bilirubin meters are too expensive and are affected by skin tone. Our team has developed a handheld DRS device for non-invasive screening and monitoring of neonatal bilirubin.

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In the research, molybdenum disulfide is grown on the light-absorbing layer of the silicon-based solar element, combined with the self-designed Serrated Interdigitated Elec-trode. The photoelectric flow measurement was performed on pleural effusion with three different types of lung cancer cell clinical samples through the photo-generated charge carrier transport mechanism

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Currently, optical coherence tomography (OCT) system requires a high-performance desktop which increases the system cost and complexity. In this study, we proposed an OCT system based on a field programmable gate array (FPGA) to replace the high-performance desktop in conventional OCT systems. As a preliminary study, we used an evaluation FPGA board to validate its feasibility to be implemented in the processing framework we have developed using the spectral-domain OCT system. The preliminary results including system framework and comparison of the processing performance with respect to conventional OCT system will be provided as well.

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We present on using polarization-resolved second harmonic generation (P-SHG) microscopy to study changes in the molecular structure of starch granules modified by gamma irradiation. With the characteristic of SHG polarization anisotropy, we extracted the second-order susceptibility, χ(2), tensor of amylopectin, which reflects the underlying molecular details. Then P-SHG microscopy in conjunction with SHG-circular dichroism (CD) were used to identify the inherent chirality of starches and their reaction to different dosages of gamma irradiation. For the first time, the relationship between starch achirality (χ21/χ16 and χ22/χ16) and chirality (χ14/χ16) determining susceptibility tensor ratios have been elucidated.

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Multiphoton excited fluorescence microscopy provides a great spatial excitation resolution for 3D image reconstruction in sub-micron resolution, and is suitable for biological imaging in vivo. We demonstrate a self-built scanning-based MPEFM system. The system lateral resolution is around 0.7 μm and axial resolution is 2.2 μm respectively. We have shown the large scale imaging ability by synchronization with the 3-axis mechanical stage, laser scanning, and fluorescence signal acquisition. The full size of mouse pulmonary fibrosis tissue is successfully reconstructed in high contrast. The experiment result shows the proposed MPEFM system yields a great feasibility for noninvasive biological imaging and analysis.

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As early as mid-19th century, artificial mechanics was proved to change cellular morphology and gene expression. Recent research shows that telogen elongation of mice skin under appropriate tension can stimulate the regeneration of hair follicle. To measure the skin tension required for regeneration, in this study, we used Mueller Matrix polarimetry to record the mouse skin image, while the mouse skin was gradually stretched in eight days. Combining the traditional skin tension measurement via spring and neural network model, the relationship between skin polarization properties and tension was found out. That provides a non-contacting method to measure the skin tension.

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Spruce is the commonly-used tonewood for violin-family instruments. It’s been shown chemical treatment and aging can cause property changes of wood and affect the acoustic properties of instruments. To reveal the spectral and spatial properties of woods, which abundantly contain lignin and cellulose, two-photon hyperspectral microscopy has been introduced. Through the hyperspectral data containing two-photon fluorescence and second-harmonic generation (SHG) information, the spatial content variations of different lignin fluorescent bases and SHG can be obtained microscopically. Comparing woods without process and with aging, heating, and chemical treatments, the effects of different processes have been reveal through the spectral variations.

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Optical techniques have been increasingly applied to the screening and diagnosis of diseases, as well as non-invasive monitoring and surveillance of physiological states of tissue in vivo. For such sensing purposes, photons entering the tissue undergo multiple scattering events, and some of the photons not absorbed by the tissue return to the tissue surface and get detected. To accurately quantify pathological or physiological parameters from multi-dimensional data, the Monte Carlo (MC) method for solving the radiative transport problem has been developed and treated as the gold standard. However, a significant drawback of MC simulations is the high computational cost which hinders real-time processing. To address this issue, our group has adopted artificial neural networks to speed up MC simulations in several applications to quantify tissue optical properties in vivo. Examples include (1) absorption of melanin in the skin, (2) the strength of auto-fluorescence from the mucosa of the cervical uterine for detecting precancerous lesions, (3) scattering and absorption coefficients of major tissues in the human head to improve functional mapping of the brain activity and dosage quantification in transcranial brain stimulation, and (4) changes in oxygen saturation of venous blood.

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Nature photonic crystals have been attracting researchers for a long time due to their bright reflected lights. Some of them are integrated into laser devices as scattering materials to form random lasing or mirrors to reduce the threshold. Here we discovered the band-edge lasing from photonic crystals in the scales of butterflies with new chromophores of donor-acceptor-donor motifs for the first time. This breakthrough may inspire future designs of photonic circuits or laser applications.

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Neurite growth is essential for constructing the nervous system in the development process and the repair after trauma or disease. Numerous studies have shown that photobiomodulation by red or near-infrared light can stimulate neurite growth, but the detailed mechanisms are still unclear. In the present work we verified that 620 and 760 nm laser spots illuminating the soma of neuroblastoma cells (N2a) could cause neurite growth. This red light-induced neurite regrowth process is accompanied with an increase in intracellular reactive oxygen species (ROS).

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This study used functional near-infrared spectroscopy (fNIRS) to measure the changes in hemoglobin concentration in the prefrontal cortex lobe of 33 police officers during the mental arithmetic and verbal fluency tasks. We process the signals to extract physiologically meaningful features and build a model using the Copenhagen overwork scale score as a classification criterion. Finally, the results show a training accuracy rate of 88.9 % and a testing accuracy rate of 80.0 %, indicating significant potential in assessing overwork by combining fNIRS with machine learning.

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The polarimetric imaging system has been developed recently for many biological applications, such as tissue morphological characterization or cancer detection. This study applied the non-invasive nature of polarized light to evaluate at the polarization characteristics of two groups including healthy and malignant colorectal tissues. The experimental results showed that the normal tissues have more isotropic media features than malignancy. Moreover, the average intensity of almost all Mueller matrix components is much greater in malignant samples than in ones of normal samples. Overall, the proposed approach give a potential identification of colorectal malignant tissues on quantitative or semiquantitative criteria.

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The signal-to-noise ratio (SNR) or the contrasts of an image is the most important parameters in laser-scanning microscopy (LSM). With a superior image contrast/SNR, LSM can be performed faster or deeper without compromising image quality. In this work, we present a new method: using the non-fundamental modulations of nonlinear signals to improve the SNR. The second-harmonic generation (SHG) images of collagen were used as the demonstration example. The contrast was enhanced up to 2.5 times in the series of comparison experiments.

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Conventional optical microscopy requires labelling dyes to see organelles of a cell, but these dyes are detrimental to cells. Therefore, the researchers used a metamaterial array with a Fourier transform infrared microscope equipped with a focal plane array to image a cell. However, such imaging technique can only map two-dimensional images, losing resolution in the third dimension. To obtain 3-dimensional cell images, we designed a metamaterial perfect absorber with three resonance modes, where different modes have different detection depths, i.e., 251, 276 and 521 nm, thus approaching to 3D cell imaging with a z-axis resolution of 25 nm.

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In this study, the experiments of simultaneous multi-frequency and single-frequency wave-driven light sources were carried out on cylindrical phantoms with imitating breast optical coefficients, and compared the differences of reconstructed images driven by the two light sources. The results exhibit that the reconstructed image of the simultaneous multi-frequency measurement can detect the position of the inclusion and distinguish its size, and the reconstruction result is better than the single-frequency reconstruction result because of more optical information.

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We present a deep learning based single shot optical sectioning imaging system, which utilizes the CNN based U-net model to obtain the HiLo optical sectioning images. It can reduce the acquisition time of sectioning images.

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Concentration of bilirubin is an important indicator for healthcare professionals performing the diagnosis of hepatitis or common bile duct stone. In this study, we constructed a non-invasive spatially resolved diffuse reflectance spectroscopy (SRDRS) measurement system and the novel spectral analysis algorithm to calculate the bilirubin level of adults. We recruited 42 patients who required bilirubin tests in the internal medicine department of National Cheng Kung University Hospital. We used linear regression analysis and Bland-Altman Plot to compare hospital lab bilirubin level with optically derived bilirubin level and concluded that our system can be used to accurately determine adult bilirubin concentration.

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Electric field Monte Carlo method can be used to include the phase and polarization state information of complex light in turbid media. In this paper, based on EMC framework we investigate the propagation property of Bessel beam over the penetration depth in turbid medium for biomedical applications.

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An automatic control program and an easy-to-use GUI have been developed for the quantitative differentia phase contrast microscope (QDPC). The software has the functionality of real-time control of pupil graphics, image capture, and automatic storage of pictures. Our software is user-friendly and easy to implement with a GUI interface to speed up the imaging process. The real-time automatic image control and storage will help to improve overall imaging performance. Moreover, the system could be applied to other microscopy processes with the same benefits.

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Owing to the non-invasive nature and cost-effectiveness, photoplethysmogram (PPG) is an optical technique widely used in physiological measurement. It has widespread clinical application for evaluating cardiovascular health and detecting diseases. However, signal processing is a key step in using PPG to obtain physiological measurements. The reflective type PPG based on a conventional biosensor is investigated in this study. With the red light, IR light and photodiode in the chosen biosensor SFH7072,the reflective type PPG including its acquired waveform, representative noise, pre-filtering technology, feature extraction technology, and post-processing technology is investigated to achieve practical reflective type PPG used in wearable devices.

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We use surface plasmon resonance imaging to monitor the activity between exosome and antibody on gold-coated nanostructures. There are antigens, named EP-CAM, on the surface of exosome. When exosome begins to combine with the anti-EPCAM antibody on the gold-coated nanostructure, the peak wavelength of the spectrum changes. Therefore, we can know the activities between the exosome and antibody by the peak wavelength change of the spectrum.

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In this work, a spectral domain optical coherence tomography radial scanning endoscope is proposed, which uses a light source of 880 nm ± 70 nm. It has the characteristics of high resolution and a long detection depth. Our piezo actuated radial scanning endoscope, can enter the organs in the human body for high speed 3D image construction. It can be used in biomedical as well as industrial detection and inspection work.

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We have established an optical model for the spectral reflectance of human skin with five-layer tissues. As using the simulation programs containing the ray-tracing and the light scattering, the spectral reflectance can be accurately evaluated in a simple and quick calculation. The comparison between the simulation results and the measured data is also presented to verify the proposed optical model.

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Optical Coherence Tomography (OCT) is a non-invasive optical imaging technique.
It has been applied to many biomedical imaging problems. However, it is not every scan in
clear sample information. In this article, we use Pix2Pix Generative Adversarial Network
(GAN) to enhance OCT image quality. After using Pix2Pix GAN to train and verify a large
number of source images and clear target images, a blur OCT image can be transferred into a
clear OCT image by the trained Pix2Pix GAN model.

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