This PDF file contains the front matter associated with SPIE Proceedings Volume 11549, including the Title Page, Copyright Information, and Table of Contents.

In this paper, we present a multi-wavelength multiplexed setup and associated super-resolution reconstruction method in lensfree microscopy that generates high-resolution reconstructions from undersampled raw measurements captured at multiple wavelengths. The reconstruction result of the standard 1951 USAF achieves a half-pitch lateral resolution of 775 nm, corresponding to a numerical aperture of 1.0, across a large field of view (∼ 29.85 mm²). Compared with other super-resolution methods such as lateral or axial shift-based device and illumination source rotation design, wavelength multiplexed avoids the need for shifting/rotating mechanical components. This multi-wavelength multiplexed super-resolution method would benefit the research and development of a more stable lensfree microscopy system.

The key to improve the capability of photoelectric detection and countermeasure system is to improve the detection ability of the system. System resolution, detection distance, detection range, response time, system signal-to-noise ratio are important criteria, and system optics is the core of its engineering implementation. From the global perspective, the adaptive algorithm establishes a new theory which superior to the traditional method, and solves the problem of freely determining the core optical solution, and opens up a new field for the development of accurate detection system.

As one of the most well-known phase retrieval approaches, the transport of intensity equation (TIE) provides a new non-interferometric way to access quantitative phase information through intensity only measurement. In this talk, we provide an overview of the basic principle, research fields, and representative applications of TIE, focusing particularly on optical imaging, metrology, and microscopy. These results highlight a new era in which strict coherence and interferometry are no longer prerequisites for quantitative phase imaging and diffraction tomography, paving the way toward new generation label-free three-dimensional microscopy.

The spatial, temporal, and spectral information in optical imaging play a crucial role in exploring the unknown world and unencrypting natural mysteries. However, the existing optical imaging techniques can only acquire the spatiotemporal or spatiospectral information of the object with the single-shot method. In this talk, I’d like to introduce a hyperspectrally compressed ultrafast photography (HCUP) that can simultaneously record the spatial, temporal, and spectral information of the object. In our HCUP, the dynamical spatial resolution is 1.26 lp/mm in the horizontal direction and 1.41 lp/mm in the vertical direction, the temporal frame interval is 2 ps, and the spectral frame interval is 1.72 nm. Based on our HCUP, we realized the spatiotemporal-spatiospectral four-dimensional optical imaging of the chirped picosecond laser pulse and the photoluminescence dynamics. It can be expected that HCUP is flexible to couple to a variety of imaging modalities, including microscopes and telescopes, which enable recording the object at the spatial scales from cellular organelles to galaxies. Considering the powerful function of HCUP in optical imaging, it will open a new route in related application areas.

We propose label-free and motion-free resolution-enhanced intensity diffraction tomography recovering the 3D complex refractive index distribution of an object. By combining an annular illumination strategy with a high numerical aperture (NA) condenser, we achieve near diffraction-limited lateral resolution of 346 nm and axial resolution of 1.2 µm over 130 130 8 µm³ volume. Our annular pattern matches the system’s maximum NA to reduce the data requirement to 48 intensity frames. The small data requirement and high resolution enable fast 3D quantitative refractive index imaging of biological cells across hundreds of nanometers scales. The reIDT system is directly built on a standard commercial microscope with a simple LED array source and condenser lens adds-on, and promises broad applications for natural biological imaging with minimal hardware modifications. To test the capabilities of our technique, we present the 3D complex refractive index reconstructions on the Henrietta Lacks (HeLa) and HT29 human cancer cells. Our work provides an important step in intensity-based diffraction tomography towards high resolution imaging applications.

We present an annular illumination pattern optimization scheme for Fourier ptychographic microscopy (FPM) based on spectrum aliasing minimization. It has been found that an annular illumination light source could provide the highest phase retrieval accuracy while the oblique illumination angles matching the objective NA precisely. However, this conclusion is no longer valid when the Nyquist sampling criterion is not satisfied under the incoherent illumination case. In this paper, we investigate the spectrum aliasing characteristic with different spatial sampling rates. Then, an objective cost function related to the spectrum aliasing percentage and reconstruction error is established to bring about an annular illumination pattern optimization scheme. The reconstruction accuracy improvement of the proposed approach is demonstrated by achieving a full-pitch resolution of 548 nm across a wide FOV of 1.772 mm² while the incoherent spatial sampling criterion is not satisfied.

Fourier ptychographic microscopy is a newly developed method to extend the resolution beyond the conventional limit defined by a microscope optics. The positions of the LED sources strongly determine the quality of the reconstructed result. In this paper, we propose a new positional misalignment correction method, which is based on the distribution of the incident LED intensity. When the LED matrix panel has displacements along x-axis, or y-axis, the incident LED intensity distribution which propagates to the sample plane will be changed. An optimization method to correct positional misalignment is introduced, as well as the light intensity correction. Simulation has been performed to verify the effectiveness of the proposed method, which demonstrates that the reconstructed result shows a better quality.

Fourier ptychographic microscopy has the advantages of large field of view, high resolution and quantitative phase imaging, which magically compromises contradiction between the resolution and the field of view. In the traditional reconstruction process, the spectrum is always updated partly step by step, which would result in error accumulation. In order to improve the reconstruction precision, based on its working principle, the paper proposes a global iterative optimization method, which updates the spectrum holistically. And experimental results demonstrate its better performance and effectiveness.

In this paper, we improve image reconstruction in a single-pixel scanning system by selecting an detector optimal field of view. Image reconstruction is based on compressed sensing and image quality is compared to interpolated staring arrays. The image quality comparisons use a dead leaves" data set, Bayesian estimation and the Peak- Signal-to-Noise Ratio (PSNR) measure. Compressed sensing is explored as an interpolation algorithm and shows with high probability an improved performance compared to Lanczos interpolation. Furthermore, multi-level sampling in a single-pixel scanning system is simulated by dynamically altering the detector field of view. It was shown that multi-level sampling improves the distribution of the Peak-Signal-to-Noise Ratio. We further explore the expected sampling level distributions and PSNR distributions for multi-level sampling. The PSNR distribution indicates that there is a small set of levels which will improve image quality over interpolated staring arrays. We further conclude that multi-level sampling will outperform single-level uniform random sampling on average.

The emergence of super-resolution (SR) fluorescence microscopy has rejuvenated the search for new cellular sub-structures. However, SR fluorescence microscopy achieves high contrast at the cost of the lack of a holistic view of their interacting partners and surrounding environment. Thus we develop SR fluorescence-assisted diffraction computational tomography (SR-FACT), which combines label-free three-dimensional optical diffraction tomography (ODT) with two-dimensional fluorescence Hessian structured illumination microscopy. The ODT module is capable of resolving mitochondria, lipid droplets, the nuclear membrane, chromosomes, the tubular endoplasmic reticulum and lysosomes. Using dual-mode correlated live cell imaging for prolonged period of time, we observe the dynamics of a novel subcellular structure named dark-vacuole bodies. These works demonstrate the unique capabilities of SR-FACT, which suggest its wide applicability in cell biology in general.

Edge enhancement is fundamental in image processing for recognizing or highlighting image features. Existing methods can only function in free space or transparent media. It remains challenging to achieve edge enhancement in the presence of multiple scattering. In this work, we present an implementation of digital optical phase conjugation to achieve effective edge enhancement through scattering media. The hypothesis is verified through experiments; the performance is promising and can be tuned by adjusting the beam ratio. The method may potentially enrich the interpretation of images obtained from complex environments.

The main challenge in multimode fiber imaging is modal scrambling caused by environmental fluctuation. How to get high contrast and high stable imaging is the main question. In this presentation, we propose some methods to increase the contrast-to-noise ratio and stability of multimode fiber imaging. Wavelength modulation is introduced to suppress the background. Exhaustive bending effect was used to improve the imaging stability. Wavelength modulation is introduced to enhance the CNR four fold in a 200 μm field-of-view imaging. We show a near diffraction limited focusing capability at imaging depths of up to 150 µm with near constant lateral resolutions of 2.1 µm. The imaging of small fluorescent beads embedded in a 3D matrix was demonstrated.

Diffuse optical tomography (DOT) is a noninvasive biomedical imaging method to reconstruct optical property distribution. Since the underdetermined characteristic of reconstruction process, a priori information such as the structure provided by multimodal images are beneficial for imaging quality. We introduce a deep convolutional neural network-based method to rapidly calculate the heterogenous region by the diffusive intensity distribution measured by the same device used for DOT imaging. The process is based on a convolutional forward model which can accurately calculate the diffusive light intensity distribution with known structure and corresponding optical properties. The heterogeneous region imaging network is the inverse of the forward model and trained with Monte Carlo simulation results. The trained inverse network achieves the imaging sensitivity and specificity of 0.91 and 0.89 for validation data-set and the reconstruction speed is under 0.1s peer image.

Linear super-resolution microscopy via synthesis aperture approach permits fast acquisition owing to its wide-field implementations. However, it has been limited in resolution because a spatial-frequency band missing occurs when trying to use a shift magnitude surpassing the cutoff frequency of the detection system beyond a factor of two, which distorts the image severely. Here, we propose a method of chip-based 3D nanoscopy through a tunable spatial-frequency-shift effect capable of covering the full extent of the spatial-frequency component within a wide passband. The missing of the spatial spectrum can be effectively solved by developing a spatial-frequency-shift active tuning approach through wave vector manipulation and operation of optical modes propagating along multiple azimuthal directions on a waveguide chip. Besides, the method includes a chip-based sectioning capability, which is enabled by the saturated absorption of fluorophores.

In compressive spectral imaging, three-dimensional spatio-spectral data cubes are recovered from two-dimensional projections. The quality of the compressive-sensing-based reconstruction is dependent on the coherence of the sensing matrix, which is determined by the system projection and the sparse prior. Studies on the optimization of the system projection, which mainly deals with the coded aperture, successfully decreases the coherence of the sensing matrix and improves the reconstruction quality. However, the optimization of the sparse prior considering the relationship between the system projection and the sparse prior remains a challenge. In this paper, we propose a gradient-descent-based sparse prior optimization algorithm for the coherence minimization of the sensing matrix in compressive spectral imaging. The Frobenius norm coherence is introduced as the cost function for the optimization, and the overcomplete dictionary is chosen as the sparse prior to solve the optimal sparse representation in the reconstruction as it provides higher degree of freedom for optimization compared to common orthogonal bases. The optimized dictionary effectively decreases the coherence of the sensing matrix from 0.880 to 0.604 and significantly improves the quantitative image quality metrics of the reconstructed hyperspectral images with the corresponding peak signal-to-noise ratio (PSNR) increased by 9 dB, the structural similarity (SSIM) above 0.98, and the spectrum angular mapper (SAM) below 0.1. Furthermore, the requirement of the sampling snapshots is reduced, which is shown by similar image quality metrics between the reconstructed hyperspectral images of only 1 snapshot with the optimized dictionary and of more than 5 snapshots with the non-optimized dictionary.

Infrared (IR) spectroscopy depicts molecular structure and dynamics based on vibrational absorption of chemical bonds. Spatially resolved IR spectroscopy, i.e. IR imaging, further enabled label-free in situ chemical imaging for dynamics in complex systems. However, IR imaging suffers from low spatial resolution at a few micrometers due to diffraction limit, thus having difficulty in applications such as sub-cellular imaging. Recently, by visible light probing of the photothermal effect of vibrational absorption, mid-infrared photothermal imaging (MIP) overcomes the limitations of conventional IR microscopy and has achieved sub-micron resolution. In this work, we built an optimized MIP system to boost the spatial resolution and sensitivity, and demonstrated MIP imaging of nanometer-sized polymeric microspheres and living cells with a high spatial resolution of 200 nm.

The ability to accurately respond pressure transients is critical for biomedical photoacoustic (PA) imaging. The routinely-adopted piezoelectric transducer usually operates at limited sensitivity and bandwidth, resulting in inadequate response to PA impulses. Here, we propose surface plasmon sensing for PA wave detection. Relying on modulations to surface plasmon polaritons from temporal ultrasonic perturbations, PA pressure transients are retrieved by recording variations in the reflected light. We relalize PA detection with a broad bandwidth of approximately 190 MHz and a sensitivity of ~100 Pa. In vivo volumetric imaging is obtained label-freely by PA microscopy incorporating a surface plasmon sensor.

Optical phase microscopy is widely adopted for quantitative imaging of optical density in transparent cells and tissues, yet lacks the chemical selectivity. To address this challenge, a bond-selective transient phase imaging (BTSP) technique was developed, in which a transient change in phase induced by infrared excitation of molecular vibrations was detected by a diffraction phase microscope. BTSP achieved chemically selective phase imaging of live cells. We further demonstrated an IR-pump visible-probe phase microscopy based on second harmonic generation after the sample, enabled by deep learning. The phase-sensitive information is encoded into the second harmonic signal, which is decoded using a deep learning algorithm. It presents a label-free technique featured by high phase sensitivity and high robustness against noises, which has promising applications in biological and medical imaging and remote sensing.

The problem of lithium (Li) dendrite has been one major obstacle to further improvements of the performance of Li metal batteries. Seeking for possible solutions to the problem demands thorough observations on the dendrite growth process. Despite various imaging techniques implemented hitherto, challenges still exist in direct imaging of Li dendrites with considerable contrast and both high spatial and temporal resolutions, because low electron density of Li element makes Li bulks almost invisible to electrons and X-rays. The very first implementation of photoacoustic (PA) imaging to realize high-contrast direct imaging of three-dimensional (3D) structures of Li electrodepositions inside Li batteries within minutes has been reported by our group previously. In this work, we further utilize PA imaging on top surfaces of electrodes to achieve quantitative studies of Li electrodepositions. Attenuation to PA signal amplitudes by a Celgard separator was calibrated to be less than 50% and thus the feasibility of this approach to observe entire deposited Li within and below the separator was verified. We also computed total mass of deposited Li on the cathode after the battery was discharged with different areal capacities. The results show an overall positive correlation between the computed mass and the applied discharging areal capacity, which conforms with the underlying electrochemical (EC) principles. We notice a discrepancy between the calculated mass by our PA method and by the EC curves. Possible causes of the discrepancy are discussed to provide guidelines on future development of reliable methods for quantifying Li electrodepositions based on PA imaging.

Photoacoustic microscopy is becoming an important tool for the biomedical research. It has been widely used in biological researches, such as structural imaging of vasculature, brain structural and functional imaging, and tumor detection. The conventional optical-resolution photoacoustic microscopy (OR- PAM) employs focused gaussian beam to achieve high lateral resolution by a microscope objective with high numerical apertures. Since the focused gaussian beam only has narrow depth range in focus, little detail in depth direction can be revealed. Here, we developed a synthetic multi-focus optical-resolution photoacoustic microscope using multi-scale weighted gradient-based fusion. Based on the saliency of the image structure, a gradient-based multi-focus image fusion method is used, and a multiscale method is used to determine the gradient weights. We pay special attention to a dual-scale scheme, which effectively solves the fusion problem caused by anisotropic blur and registration error. First, the structure-based largescale focus measurement method is used to reduce the effect of anisotropic blur and registration error on the detection of the focus area, and then the gradient weights near the edge wave are used by applying the small-scale focus measure. Simulation was performed to test the performance of our method, different focused images were used to verify the feasibility of the method. Performance of our method was analyzed by calculating Entropy, Mean Square Error (MSE) and Edge strength. The result of simulation shown that this method can extend the depth of field of PAM two times without the sacrifice of lateral resolution. And the in vivo imaging of the zebra fish further demonstrates the feasibility of our method.

Publisher’s Note: This paper, originally published on 10 October 2020, was withdrawn on 28 October 2020 per author request.

Here, we propose and investigate a graphene-based opt-thermoelectric nanotweezers, which replace the nano-metallic films in common opt-thermoelectric tweezers by graphene, and show advantages of single-layer graphene structure, broad working wavelength range from visible to infrared, and less toxicity for biological samples. We theoretically study the properties of thermoelectric force and optical force in trapping particles, and then experimentally verify the influence of different parameters on the trapping stiffness, including different polarization states of light, particle sizes, and incident laser energies. An enhanced particle manipulation accuracy within 50 nm has been achieved in experiment.

Surface plasmon polariton (SPP) can break though the traditional optical diffraction limit, and thus provides an important platform for the design of various nanophotonic devices. However, it is still a big challenge to achieve manipulation of SPP in both spatially nanoscale and temporally ultrafast conditions. Here, we propose a method of spatiotemporal manipulation of femtosecond SPP pulses, and achieve the functions including dynamically controlled wavefront rotation and redirection of SPP propagation. This work has great potential in applications such as ultrafast on-chip photonic information processing, ultrafast beam shaping and attosecond pulse generation.

In the long-range imaging system, one of the main factors limiting the imaging resolution is the size of the imaging lens aperture, which determines the diffraction limit of the optical system. In the actual Fourier ptychography imaging system, the system errors such as the aberrations of imaging devices and the noise of the detector will be introduced in the actual imaging, which is also one of the important factors to reduce the quality of the reconstructed image. In order to improve the reconstruction accuracy of the Fourier ptychography imaging algorithm, this paper mainly discusses some optimization algorithms in the process of the Fourier ptychography imaging algorithm to improve the high-resolution details of the restored image. The adaptive step size based optimization algorithm is used to update the spectrum and aperture function of the current sub-aperture to obtain the high-resolution spectrum information of the measured target. The optimal spectrum overlap rate is discussed to reduce the number of image acquisition and calculation cost as much as possible. In the reconstruction process, the simulated annealing algorithm is used to correct the positioning error of the sub-aperture, and the optimization algorithm is used to update the sub-aperture, which greatly improves the accuracy of the reconstruction results and achieves the theoretical imaging resolution.

We demonstrate a label-free imaging system capable of generating two-photon fluorescence (TPF) and second-harmonic generation (SHG) signals simultaneously, using a wavelength-tunable mode-locked Ti:Sapphire laser. TPF and SHG images are acquired at two wavelength ranges. One is between 415 nm and 455 nm, and the other is between 495 nm and 635 nm. The capability of the imaging system is demonstrated by performing simultaneous TPF and SHG imaging of freshly excised mouse lung lobes. At 870 nm excitation, the microenvironment of pulmonary alveoli is revealed by TPF from elastin fibers and SHG from collagen fibers. Macrophages residing inside apparent alveolar lumens are also identified by autofluorescence.

Phase space optics allows the four-dimensional (4D) simultaneous visualization of both space (x) and spatial frequency (u) information. The Wigner distribution function (WDF) is commonly used to represent the phase space characterization. Compared with the coherent optical field expressed by two-dimensional (2D) complex amplitude, the 4D WDF (2D space and 2D spatial frequency) can characterize optical field with arbitrary coherent state. It is especially advantageous for the characterization of partially coherent optical fields. The WDF is real and may have negative values, which are the result of phase-space interference. In this paper, an improved phase-space retrieval method is demonstrated. First, capture three-dimensional intensity focal stack by camera sensors. Then, phase space tomography (PST) combined with a non-linear iterative algorithm is conducted to reconstruct the whole WDF. We further analyzed the effect of the imaging system, i.e., the illumination aperture and the aperture of objective lens effect.

We demonstrate a method for increasing the effective resolution of phase retrieval based on the transport of intensity equation (TIE) named speckle high-resolution synthetic spectrum (speckle-HSS), as the upgraded version of the speckle-TIE approach we proposed before based on the quantitative phase imaging camera with a weak diffuser (QPICWD). Benefit from the phase gradient transfer function (PGTF) and phase transfer function (PTF), the phase blurring caused by the underestimation of phase gradient can be compensated correctly via combining TIE and PTF-based deconvolution. This method broadens the application range, alleviating the artifacts and enhancing the contrast and resolution in more accurate value. The experimental results of live HeLa cells have been presented, showing the effectiveness of the proposed method.

Differential phase contrast (DPC) imaging is a popular spatially partially coherent imaging method, which pro- vides high-quality, speckle-free 3D reconstructions with lateral resolution up to twice the coherent diffraction limit, under the precondition that the pixel size of the imaging sensor is small enough to prevent spatial alias- ing/undersampling. However, cameras are in general designed to have a large pixel size so that the intensity information transmitted by the optical system cannot be adequately sampled or digitized. On the other hand, using an image sensor with smaller pixel size or adding a magnification camera adapter to the camera can re- solve the undersampling at the expense of a reduced field of view (FOV). To solve this tradeoff, we introduce a new variation of quantitative DPC approach, termed anti-aliased DPC (AADPC), which uses several aliased intensity images under asymmetric illuminations to recover wide-field aliasing-free phase images. AADPC starts from an initial phase estimate obtained by a DPC-like deconvolution based on the systems weak phase transfer function. Then the obtained initial phase map is further refined by the iterative de-multiplexing algorithm to overcome pixel-aliasing and improve the imaging resolution. The data redundancy requirement as well as the optimal illumination scheme of AADPC are analyzed and discussed, suggesting the spatial undersampling can be mitigated through the iterative algorithm that uses only 4 images, yielding a nearly 4-fold increase in the space-bandwidth product (SBP) compared to conventional DPC approach.

To explore the damage range in the photothermal treatment at different temperatures, a temperature-feedback photothermal control system was developed. The system used an infrared thermal imager to noninvasively monitor the temperature .so it could avoid the damage caused by thermocouple measurement and apply the PID controller to achieve the desired temperature(1). the range of damage at the surface and the depth of internal damage were recorded at the different temperatures, which are based on the temperature-feedback photothermal control system. Finally, the recorded data are used to fit the curve by linear regression, and the damage depth was predicted according to the range of external damage at the surface. The technique could be a potential application for monitoring tumor treatment.

Interaction between plasmonic nanostructures and external light can excite coherent oscillation of electrons, thereby brings a field enhancement due to the localized surface plasmon resonance (LSPR). Due to their excellent characteristics, metallic gap nanostructures have been widely used in front research fields, such as physics, biomedical sciences, food chemistries, etc.. Intensity of the plasmonic field in metallic GAP structures can be enhanced with orders of magnitude compared to the excitation beam, which provides an effective tool to investigate nonlinear effects. The nonlinear variation of physical properties, especially for dielectric constant and polarizability of the plasmonic Bowtie structures, will introduce great influences on the field distribution. Consequently, the optical force and potential well in such gap structures show novel properties. This new characteristics will play a significant role in future developments and applications of plasmonic tweezers.

In this Letter, we propose a universal iterative compensation solution to the transport-of-intensity equation (US- TIE) with the advantages of high accuracy, convergence guarantee, applicability to arbitrarily-shaped regions, and simplified implementation and computation. With the “maximum intensity assumption”, we firstly simplified TIE as a standard Poisson equation to get an initial guess of the solution. Then the initial solution is further refined iteratively by solving the same Poisson equation, and thus, the instability associated with the division by zero/small intensity values and large intensity variations can be effectively bypassed. The convergence analysis and effectiveness of the iterative process has been given in detail. Furthermore, simulations with arbitrary phase, arbitrary aperture shapes, and nonuniform intensity distributions verify the effectiveness and universality of the proposed method.

Recently, a new technique called MINFLUX was promoted and attained ~1-nanometer precision. However, MINFLUX is incapable of discerning two molecules within the diffraction-limited region unless with the help of on-off switching scheme of SMLM which yet entails time-consuming processes. Here, we produce a novel kind of focal spot pattern, called sub-diffraction dark spot, to localize molecules within the sub-diffraction region of interest. In our proposed technique nominated as sub-diffracted dark spot localization microscopy (SDLM), multiple molecules within the diffraction-limited region could be distinguished without the requirement of fluorescent switches. We have numerically presented the SDLM modality and some impacts, like intensity, are investigated. Simulative localization framework has been implemented on randomly-distributed and specifically-structured samples. SDLM is evidenced to have high localization accuracy and stability in densely-packed fluorescent solution.

Since it was first presented in 2002, the Optical Projection Tomography(OPT) imaging system has emerged as a powerful tool for the study of a biomedical specimen on the mm to cm scale. In this paper, we present a rough and precise algorithm to further improve OPT image acquisition and tomographic reconstruction. The rough and precise algorithm combines the merits of the binarization process and the maximum correlation coefficient, and can accurately correct the displacement of the rotation axis. The tomographic images corrected by the rough and precise algorithm have higher image quality in the simulation experiments and specimen experiments. The reconstructed 3D images based on tomographic images can restore the original specimens. Thereby, the rough and precise algorithm contributes to increasing acquisition speed and quality of OPT data. More work should be performed to better understand and amend the rough and precise algorithm by abundant specimen experiments.

To realize the on-chip detection of cylindric vector beams (CVBs), we propose a method with a chiral plasmonic lens, which make the left-handed circularly polarized part of CVB form a strong plasmonic focus, and the focus position depends on the polarization order of CVB. To avoid the scanning of whole plasmonic field, we change the incident angle of CVB to keep the focus at the center where a waveguide is placed for detection. Then we only needs to measure the incident angle where the light in the waveguide reaches the peak, and the corresponding CVB order can be obtained.

Physical cues from cellular external environment, especially substrate stiffness, have gradually been recognized as key factors that could mediate some cell behaviors and its physiological processes. In this study, atomic force microscopy was used to investigate the influence of substrate stiffness on cellular mechanical properties, which were regarded as potential indicators for early detection of tumor. Our results showed that the viscoelasticity of breast cancer cells was significantly lower than that of breast epithelial cells in the hard substrate, while the viscoelasticity of ovarian cancer cells did not change with substrate change. It can be seen that substrate stiffness indeed plays an important role in the development of tumor, which could be attribute to its regulation of the cellular mechanical properties.

We applied a one-dense-layer model to reconstruct the input images from the intensity of the speckle patterns coupled out from a multimode fiber. We studied the singular value statistics of the complex weight matrix, an approximation to the full transmission matrix. We compared the reconstruction quality with other DL models. We observed less time consuming and better tolerance to speckle patterns blocking and downsampling compared to other DL methods. We believe this one-dense-layer model shows alternative routes to retrieve the transmission matrix with machine learning. Our statistical study of the complex weight matrix would advance the physical understanding of image reconstruction through multimode fiber with different DL models.

Imaging through thick scattering media produces a random speckle signal with wealth information, which can be restored by subsequent processing. While a moving target is hard to reconstruct by existing technology, we apply temporal Bayesian compressed sensing method to overcome this limitation. In addition, an over completed dictionary is used as a sparse base to improve the accuracy of the reconstructions. In this letter, we improve system time resolution without changing its spatial resolution and reconstruct T frame speckle images from a single temporal compressed speckle measurement.

Optical coherence tomography (OCT) is a non-invasive technique in biomedical imaging since it provides high axial and lateral resolutions. OCT requires approaching the measurement probe to the sample within the axial range of several millimeters. If there is an initial condition that the distance is unknown; as expected for automatic measurement. In a distance with longer axial range, the time-of-flight (ToF) becomes is useful. In this research, we integrated ToF with sub-millimeter axial resolution and a meter-order axial range; and OCT with micrometer-order axial resolution and a millimeter-order axial measurable range. A spectral-domain (SD-OCT) system composed of a superluminescent diode, optical fibers, and a spectrometer was implemented. ToF system holds a semiconductor laser which is sinusoidally modulated by an electric signal ranging frequency from 0.1 to 1 GHz, a Si PIN photodetector. The ToF and the SD-OCT systems share a common optical path; the phase difference of the sinusoidal signals returning from the sample and reference arms are measured. The importance of the integrated system is that the accuracy of ToF is smaller than the axial measurable range of SD-OCT. The SLD of the SD-OCT system has a central wavelength of 840 nm and a bandwidth of 80 nm. The axial measurable range was 3.7 mm which was calculated from the specifications of the grating and the LSC system. The ToF system has an experimental accuracy of 0.9 mm operating at a frequency of 0.8 GHz. It is enough for the axial resolution measurable in the range of SD-OCT.

An improved Blackman Harris apodization function is studied for rectify the shortcomings of large main lobe width of Blackman Harris apodization function in apodization processing of Fourier transform spectrometer. The basic principle of apodized interferogram is analyzed. The Chebyshev function with tunable parameters is introduced to improve Blackman Harris function. Compared with the original function through Matlab simulation, the improved apodization function shows not only the characteristics of main lobe width is enhanced, but also the side lobe attenuation can be adjusted, so the function is more flexible in engineering application.

Holographic display is widely known for aberration correction capability. In this paper, we analyze the image quality degradation when aberration is present in the holographic display system. Though built with lenses with minimal aberrations, it is inevitable from undesirable error when perceived with an usual eye. Thus, we mainly analyze holographic image quality in two cases: when eye gets defocused and rotated. In simulation, accommodation-dependent schematic eye model is utilized for precise acquisition of aberration-corrected hologram. The hologram acquired with ray tracing is assessed with the bench-top prototype of holographic near-eye display.

The non-contact temperature measurement method has been widely used in the field of temperature measurement. Based on element energy spectrum excitation and Laser induced breakdown spectroscopy (LIBS) mechanism, through the analysis of the intrinsic physical properties of the object under test, the excitation characteristic spectrum of heated internal elements in high temperature field was explored, in order to select effective detection wavelength of non-contact detection module, and designed a narrow-band filter module to compress the detection band. The accuracy of optical detection model can be improved. By preparing and analyzing samples of various elements, K and Cu were selected as external doping elements, the characteristic wavelength of K and Cu can be used as an effective detection wavelength, the CMOS camera was used to detect the burner flame under the different wavelengths and obtained the flame image. The experimental results validate the feasibility of the method.

Because of the influence of extreme environment such as high temperature, high pressure, high speed and high impact, it is difficult to measure the transient high temperature of high temperature flame in the explosion field accurately. This kind of transient temperature measurement is often accompanied by high pressure or high speed air flow, most of which are non repeatable one-time processes. Therefore, poor measurement conditions, high technical difficulty and inaccurate temperature measurement are all problems that can not be ignored. At the same time, there are high requirements for the reliability and data acquisition rate of the system. In this paper, we use the alcohol burner to operate in the laboratory, use the infrared thermal imager to collect the temperature of the nozzle after the alcohol is fully burned, adjust the flame emissivity and collect the temperature of the flame, and export the collected flame pictures for data analysis. By using modern simulation software, combining hydrodynamics and software simulation, the turbulent k-ε model is applied to simulate the single nozzle high temperature flame through the material transfer and fluid heat transfer in the combustion process. Comparing the simulation results with the experimental data, it can be seen that the simulation results well reproduce the experimental parameters such as the velocity and pressure of the nozzle and the temperature of the exit flame, including the mass fraction of each material after combustion, which is roughly similar to the temperature field collected by the infrared thermal imager, providing an efficient and more accurate verification means for the detection and reconstruction of multiple temperature fields in the future.

Light-sheet Fluorescence microscopy (LSFM) with scanned Bessel beam draws a strong attention because it provides certain advantages. Especially, a thin light-sheet over a large field can be produced by Bessel beams. Also, as a non-diffracting beam, the Bessel beam enables deeper penetration into thick cells or tissues. Usually, the Bessel beam with high side-lobes is created by inserting an annular pupil filter in a Gaussian beam. The fluorescence background from the side lobes of the Bessel beam blurs the image and broadens the thickness of the light-sheet, which results in a lower image contrast and sacrificing the optical sectioning capability. To address this issue, in this paper, a leaky filter is designed to be inserted in the Gaussian beam to create a similar Bessel beam with lower side lobes. By optimizing the parameters of the leaky filter, the suppression of the side lobes is demonstrated.

Deep learning is a powerful technique based on neural networks, which has distinct advantages in terms of finding the relation between the input and the label, and it has shown the superior performance for image recovery in complex and strong noise environment than other methods. We employ the deep learning method for polarimetric imaging in turbid media and in strong noise environment. For underwater imaging, the proposed learning-based method can effectively remove the veiling light and outperforms other existing methods, even in dense turbid water. For image denosing, the experimental results show that the proposed learning-based method has an evident performance on the noise suppression and outperforms other existing methods. Especially for the images of the degree of polarization and the angle of polarization, which are quite sensitive to the noise, the proposed learning-based method can well reconstruct the details flooded in strong noise.

Two non-destructive detection methods for potato blight based on hyperspectral imaging were used: convolutional neural network (CNN) and support vector machine (SVM) to classify potato leaves. By comparing the classification results, the advantages and disadvantages of different methods are analyzed. In the experiment, normal potato leaves and early blight leaves were selected as research objects. Hyperspectral images of samples were obtained by hyperspectral imaging system, and then principal component images were extracted by principal component analysis method. It was found that the principal component images of normal leaves and blight leaves were significantly different, and finally two models of blight detection were established for convolutional neural network and support vector machine. The experimental results showed that the convolutional neural network was better than the support vector function in the detection of potato blight.

Optical cryptosystem based on phase-truncated-Fourier-transforms (PTFT) is one of the most interesting optical cryptographic schemes due to its unique mechanism of encryption/decryption. Conventional learning-based attack method need a large number of plaintext-ciphertext pairs to train a neural network and then predict the plaintexts from subsequent ciphertexts. In this work, we propose an alternative method of attack on PTFT-based optical asymmetric cryptosystem by using an untrained neural network. We optimize the parameters of a neural network with the help of the encryption model of PTFT-based cryptosystem, hoping to get the ability of retrieving any plaintext from the corresponding unknown ciphertext but without help of the decryption keys. The proposed untrained-neural-network-based attack approach eliminates the requirement of tens of thousands of training images and might open up a new avenue for optical cryptanalysis.