Wavelength-modulated photoacoustic spectroscopic instrumentation system for multiple greenhouse gas detection and in-field application in the Qinling mountainous region of China.

We present a sensitive and compact quantum cascade laser-based photoacoustic greenhouse gas sensor for the detection of CO2, CH4 and CO and discuss its applicability toward on-line real-time trace greenhouse gas analysis. Differential photoacoustic resonators with different dimensions were used and optimized to balance sensitivity with signal saturation. The effects of ambient parameters, gas flow rate, pressure and humidity on the photoacoustic signal and the spectral cross-interference were investigated. Thanks to the combined operation of in-house designed laser control and lock-in amplifier, the gas detection sensitivities achieved were 5.6 ppb for CH4, 0.8 ppb for CO and 17.2 ppb for CO2, signal averaging time 1 s and an excellent dynamic range beyond 6 orders of magnitude. A continuous outdoor five-day test was performed in an observation station in China's Qinling National Botanical Garden (E longitude 108°29', N latitude 33°43') which demonstrated the stability and reliability of the greenhouse gas sensor.

BLSTM convolution and self-attention network enabled recursive and direct prediction for optical chaos.

Chaotic time series prediction has attracted much attention in recent years because of its important applications, such as security analysis for random number generators and chaos synchronization in private communications. Herein, we propose a BLSTM convolution and self-attention network model to predict the optical chaos. We validate the model's capability for direct and recursive prediction, and the model dramatically reduces the accumulation of errors. Moreover, the time duration prediction of optical chaos is increased with comparative accuracy where the predicted sequence length reaches 4 ns with normalized mean squared error (NMSE) of less than 0.01.

Snapshot dual-wavelength digital holography with LED and laser hybrid illumination.

To address the problem of the time-sharing recording of dual-wavelength low-coherence holograms while avoiding the use of customized achromatic optical elements, a snapshot dual-wavelength digital holography with LED and laser hybrid illumination is proposed. In this method, the parallel phase-shifting method is firstly employed to suppress zero-order and twin-image noise, and to record a LED hologram with low speckle noise and full field of view. Secondly, another laser hologram with a different center wavelength affected by speckle noise is recorded simultaneously using the spatial multiplexing technique. Finally, dual-wavelength wrapped phase images are reconstructed from a spatial multiplexing hologram, and then are combined to achieve low-noise phase unwrapping utilizing the iterative algorithm. Simulation and optical experiments on a reflective step with a depth of 1.38µm demonstrate that the proposed method can achieve single-shot and large-range height measurements while maintaining low-noise and full-field imaging.

DDLA: a double deep latent autoencoder for diabetic retinopathy diagnose based on continuous glucose sensors.

The current diagnosis of diabetic retinopathy is based on fundus images and clinical experience. However, considering the ineffectiveness and non-portability of medical devices, we aimed to develop a diagnostic model for diabetic retinopathy based on glucose series data from the wearable continuous glucose monitoring system. Therefore, this study developed a novel method, i.e., double deep latent autoencoder, for exploring glycemic variability influence from multi-day glucose data for diabetic retinopathy. Specifically, the model proposed in this research could encode continuous glucose sensor data with non-continuous and variable length via the integration of a data reorganization module and a novel encoding module with fragmented-missing-wise objective function. Additionally, the model implements a double deep autoencoder, which integrated convolutional neural network, long short-term memory, to jointly capturing the inter-day and intra-day glucose latent features from glucose series. The effectiveness of the proposed model is evaluated through a cross-validation method to clinical datasets of 765 type 2 diabetes patients. The proposed method achieves the highest accuracy value (0.89), precision value (0.88), and F1 score (0.73). The results suggest that our model can be used to remotely diagnose and screen for diabetic retinopathy by learning potential features of glucose series data collected by wearable continuous glucose monitoring systems.

Fly-scan high-throughput coded ptychographic microscopy via active micro-vibration and rolling-shutter distortion correction.

Recent advancements in ptychography have demonstrated the potential of coded ptychography (CP) for high-resolution optical imaging in a lensless configuration. However, CP suffers imaging throughput limitations due to scanning inefficiencies. To address this, we propose what we believe is a novel 'fly-scan' scanning strategy utilizing two eccentric rotating mass (ERM) vibration motors for high-throughput coded ptychographic microscopy. The intrinsic continuity of the 'fly-scan' technique effectively eliminates the scanning overhead typically encountered during data acquisition. Additionally, its randomized scanning trajectory considerably reduces periodic artifacts in image reconstruction. We also developed what we believe to be a novel rolling-shutter distortion correction algorithm to fix the rolling-shutter effects. We built up a low-cost, DIY-made prototype platform and validated our approach with various samples including a resolution target, a quantitative phase target, a thick potato sample and biospecimens. The reported platform may offer a cost-effective and turnkey solution for high-throughput bio-imaging.

Circular polarizers and their effect on partial coherence.

We examine the action of a circular polarizer on an incident beam that is spatially partially coherent and partially polarized. It is found that the beam's coherence area can be significantly increased or decreased by the polarizer. Furthermore, an expression for the transmission efficiency is derived.

Clinically relevant stratification of patients with type 2 diabetes by using continuous glucose monitoring data.

AIM: The wealth of data generated by continuous glucose monitoring (CGM) provides new opportunities for revealing heterogeneities in patients with type 2 diabetes mellitus (T2DM). We aimed to develop a method using CGM data to discover T2DM subtypes and investigate their relationship with clinical phenotypes and microvascular complications. METHODS: The data from 3119 patients with T2DM who wore blinded CGM at an academic medical centre was collected, and a glucose symbolic pattern (GSP) metric was created that combined knowledge-based temporal abstraction with numerical vectorization. The k-means clustering was applied to GSP to obtain subgroups of patients with T2DM. Clinical characteristics and the presence of diabetic retinopathy and albuminuria were compared among the subgroups. The findings were validated in an independent population comprising 773 patients with T2DM. RESULTS: By using GSP, four subgroups were identified with distinct features in CGM profiles and parameters. Moreover, the clustered subgroups differed significantly in clinical phenotypes, including indices of pancreatic ß-cell function and insulin resistance (all p < .001). After adjusting for confounders, group C (the most insulin resistant) had a significantly higher risk of albuminuria (odds ratio = 1.24, 95% confidence interval: 1.03-1.39) relative to group D, which had the best glucose control. These findings were confirmed in the validation set. CONCLUSION: Subtyping patients with T2DM using CGM data may help identify high-risk patients for microvascular complications and provide insights into the underlying pathophysiology. This method may help refine clinically meaningful stratification of patients with T2DM and inform personalized diabetes care.

Structured modulation multi-height microscopy for high-resolution imaging.

Conventional multi-height microscopy techniques introduce different object-to-detector distances to obtain multiple measurements for phase retrieval. However, surpassing the diffraction limit imposed by the numerical aperture (NA) of the objective lens remains a challenging task. Here, we report a novel structured modulation multi-height microscopy technique for quantitative high-resolution imaging. In our platform, a thin diffuser is placed in between the sample and the objective lens. By translating the diffuser to different axial positions, a sequence of modulated intensity images is captured for reconstruction. The otherwise inaccessible high-resolution object information can thus be encoded into the optical system for detection. In the construction process, we report a ptychographic phase retrieval algorithm to recover the existing wavefront of the complex object. We validate our approach using a resolution target, a phase target, and various biological samples. We demonstrate a ∼4-fold resolution gain over the diffraction limit. We also demonstrate our approach to achieve a 6.5 mm by 4.3 mm field of view and a half-pitch resolution of 1.2 µm. The reported methodology provides a portable, turnkey solution for quantitative high-resolution imaging with potential applications in disease diagnosis, sample screening, and other fields.

Low-cost and simple optical system based on wavefront coding and deep learning.

With the development of computational imaging, the integration of optical system design and digital algorithms has made more imaging tasks easier to perform. Wavefront coding (WFC) is a typical computational imaging technique that is used to address the constraints of optical aperture and depth of field. In this paper, we demonstrated a low-cost and simple optical system based on WFC and deep learning. We constructed an optimized encoding method for the phase plate under the framework of deep learning, which reduces the requirement for aberration correction in the full field of view. Optical coding was achieved with just a double-bonded lens and a simple cubic phase mask, and digital decoding used the deep residual UNet++ network framework. The final image obtained has good resolution, whereas the depth of field of the system expanded by a factor of 13, which is of great significance for the high-precision inspection and attaching of small parts of machine vision.

Monocular polarized three-dimensional absolute depth reconstruction technology for multi-target scenes.

The traditional polarization three-dimensional (3D) imaging technology has limited applications in the field of vision because it can only obtain the relative depth information of the target. Based on the principle of polarization stereo vision, this study combines camera calibration with a monocular ranging model to achieve high-precision recovery of the target's absolute depth information in multi-target scenes. Meanwhile, an adaptive camera intrinsic matrix prediction method is proposed to overcome changes in the camera intrinsic matrix caused by focusing on fuzzy targets outside the depth of field in multi-target scenes, thereby realizing monocular polarized 3D absolute depth reconstruction under dynamic focusing of targets at different depths. Experimental results indicate that the recovery error of monocular polarized 3D absolute depth information for the clear target is less than 10%, and the detail error is only 0.19 mm. Also, the precision of absolute depth reconstruction remains above 90% after dynamic focusing on the blurred target. The proposed monocular polarized 3D absolute depth reconstruction technology for multi-target scenes can broaden application scenarios of the polarization 3D imaging technology in the field of vision.

Multi-target distortion correction in 3D shape from polarization using a monocular camera system by deep neural networks.

The shape from polarization is a noncontact 3D imaging method that shows great potential, but its application is limited by the monocular camera system and surface integration algorithm. This Letter proposes a novel, to the best of our knowledge, method that employs deep neural networks to enhance multi-target 3D reconstruction, making a significant advancement in the field. By constructing the relationship between targets' blur, distance, and clarity, the proposed method provides accurate spatial information while mitigating inaccuracies arising from the continuous model. Experiments show that the constructed neural network can help improve the multi-target 3D reconstruction quality compared with conventional methods.

Complex amplitude field recovery of a scattering media obstructed object with multi-captured images.

An iterative-based method for recovering the complex amplitude field behind scattering media is presented in this Letter. This method compensates the random phase modulation of scattering media by using multiple captured scattered light fields. Complex amplitude reconstruction with local iterative averaging of scattered light fields, and double weighted feedback is efficiently applied. Two feasible types of system setups, with varying detector positions and wavelength, are proposed. Simulations and proof-of-concept experiments are employed to demonstrate the effectiveness of the proposed method in reconstructing complex amplitude of a hidden target.

T-type cell mediated photoacoustic spectroscopy for simultaneous detection of multi-component gases based on triple resonance modality.

Enhancing multi-gas detectability using photoacoustic spectroscopy capable of simultaneous detection, highly selectivity and less cross-interference is essential for dissolved gas sensing application. A T-type photoacoustic cell was designed and verified to be an appropriate sensor, due to the resonant frequencies of which are determined jointly by absorption and resonant cylinders. The three designated resonance modes were investigated from both simulation and experiments to present the comparable amplitude responses by introducing excitation beam position optimization. The capability of multi-gas detection was demonstrated by measuring CO, CH4 and C2H2 simultaneously using QCL, ICL and DFB lasers as excitation sources respectively. The influence of potential cross-sensitivity towards humidity have been examined in terms of multi-gas detection. The experimentally determined minimum detection limits of CO, CH4 and C2H2 were 89ppb, 80ppb and 664ppb respectively, corresponding to the normalized noise equivalent absorption coefficients of 5.75 × 10-7 cm-1 W Hz-1/2, 1.97 × 10-8 cm-1 W Hz-1/2 and 4.23 × 10-8 cm-1 W Hz-1/2.

Trace photoacoustic SO2 gas sensor in SF6 utilizing a 266†nm UV laser and an acousto-optic power stabilizer.

A sulfur dioxide (SO2) gas sensor based on the photoacoustic spectroscopy technology in a sulfur hexafluoride (SF6) gas matrix was demonstrated for SF6 decomposition components monitoring in the power system. A passive Q-switching laser diode (LD) pumped all-solid-state 266 nm deep-ultraviolet laser was exploited as the laser excitation source. The photoacoustic signal amplitude is linear related to the incident optical power, whereas, a random laser power jitter is inevitable since the immature laser manufacturing technology in UV spectral region. A compact laser power stabilization system was developed for better sensor performance by adopting a photodetector, a custom-made internal closed-loop feedback controller and a Bragg acousto-optic modulator (AOM). The out-power stability of 0.04% was achieved even though the original power stability was 0.41% for ∼ 2 hours. A differential two-resonator photoacoustic cell (PAC) was designed for weak photoacoustic signal detection. The special physical constants of SF6 buffer gas induced a high-Q factor of 85. A detection limit of 140 ppbv was obtained after the optimization, which corresponds to a normalized noise equivalent absorption coefficient of 3.2 × 10-9 cm-1WHz-1/2.

Depth-multiplexed ptychographic microscopy for high-throughput imaging of stacked bio-specimens on a chip.

Imaging a large number of bio-specimens at high speed is essential for many biomedical applications. The common strategy is to place specimens at different lateral positions and image them sequentially. Here we report a new on-chip imaging strategy, termed depth-multiplexed ptychographic microscopy (DPM), for parallel imaging and sensing at high speed. Different from the common strategy, DPM stacks multiple specimens in the axial direction and images the entire z-stack all at once. In our prototype platform, we modify a low-cost car mirror for programmable steering of the incident laser beam. A blood-coated image sensor is then placed underneath the stacked sample for acquiring the resulting diffraction patterns. With the captured images, we perform blind recovery of the incident beam angle and model different layers of the stacked sample as different coded surfaces for object reconstruction. For in vitro experiment, we demonstrate time-lapse cell culture monitoring by imaging 3 stacked microfluidic channels on the coded sensor. For high-throughput cytometric analysis, we image 5 stacked brain sections with a 205-mm2 field of view in ∼50 s. Cytometric analysis is also performed to quantify the cellular proliferation biomarkers on the slides. The DPM approach adds a new degree of freedom for data multiplexing in microscopy, enabling parallel imaging of multiple specimens using a single detector. The demonstrated 6-mm depth of field is among the longest ones in microscopy imaging. The novel depth-multiplexed configuration also complements the miniaturization provided by microfluidics devices, offering a solution for on-chip sensing and imaging with efficient sample handling.

Enhancing polarization 3D facial imaging: overcoming azimuth ambiguity without extra depth devices.

Polarization 3D imaging has been a research hotspot in the field of 3D facial reconstruction because of its biosafety, high efficiency, and simplicity. However, the application of this technology is limited by the multi-valued problem of the azimuth angle of the normal vector. Currently, the most common method to overcome this limitation is to introduce additional depth techniques at the cost of reducing its applicability. This study presents a passive 3D polarization facial imaging method that does not require additional depth-capturing devices. It addresses the issue of azimuth ambiguity based on prior information about the target image's features. Specifically, by statistically analyzing the probability distribution of real azimuth angles, it is found that their quadrant distribution is closely related to the positions of facial feature points. Therefore, through facial feature detection, the polarized normal azimuth angle of each pixel can be accurately assigned to the corresponding quadrant, thus determining a precise unique normal vector and achieving accurate 3D facial reconstruction. Finally, our azimuth angle correction method was validated by simulated polarization imaging results, and it achieved accurate correction for over 75% of the global pixels without using additional depth techniques. Experimental results further indicate that this method can achieve polarization 3D facial imaging under natural conditions without extra depth devices, and the 3D results preserve edge details and texture information.

Computational optical system design: a global optimization method in a simplified imaging system.

An optical imaging system often has problems of high complexity and low energy transmittance to compensate for aberrations. Here we propose a method to correct aberrations by coupling an optical subsystem with a digital subsystem. Specifically, in the global optimization process, the two subsystems correct their respective, easily handled aberrations so that the final imaging aberration is minimized. We design simple lenses with this method and assess imaging quality. In addition, we conduct a tolerance analysis for the proposed method and verify the effectiveness of deconvolution using a spatially varying point spread function (SVPSF) in the actual imaging process. Simulation results show the superiority of the proposed method compared with the conventional design and the feasibility of simplifying the optical system. Experimental results prove the effectiveness of deconvolution using SVPSF.

Impact of color on polarization-based 3D imaging and countermeasures.

Diffuse polarization-based 3D imaging has flourished with the ability to obtain the 3D shapes of objects without multiple detectors, active mode lighting, or complex mechanical structures, which are major drawbacks of other methods for 3D imaging in natural scenes. However, traditional polarization-based 3D imaging technology introduces color distortion when reconstructing the surface of multi-colored targets. We propose a polarization-based 3D imaging model to recover the 3D geometry of multi-colored Lambertian objects. In particular, chromaticity-based color removal theory is used to restore the intrinsic intensity, which is modulated only by the target shape, and we apply the recovered intrinsic intensity to address the orientation uncertainty of target normals due to azimuth ambiguity. Finally, we integrate the corrected normals to reconstruct high-precision 3D shapes. Experimental results demonstrate that the proposed model has the ability to reconstruct multi-colored Lambertian objects exhibiting non-uniform reflectance from single views under natural light conditions.

Estimation and removal of backscattered light with nonuniform polarization information in underwater environments.

The nonuniform of polarization information of backscattered light has always been a neglected characteristic in polarization underwater imaging, but its accurate estimation plays an important role in the quality of imaging results. Traditional polarization imaging methods assume that the degree of polarization and angle of polarization of backscattered light are constant. In fact, the polarization information of backscattering light is gradual, this assumption makes traditional methods work only in a small area of the camera's field of view, in which the change of the polarization information of backscattered light can be ignored. In this paper, by analyzing the distribution of backscattered light, it is concluded that its polarization information has the characteristics of low-rank. Then, the degree of polarization and angle of polarization of backscattered light were estimated by low-rank and sparse matrix decomposition, and the clear scene was reconstructed. Experimental results show that the proposed method breaks through the limitation of the assumption of backscattered light in traditional polarization imaging method, and expands the detection field under the same conditions, which makes it possible to develop polarization underwater imaging method to the direction of large field of view detection.

Large field-of-view non-invasive imaging through scattering layers using fluctuating random illumination.

Non-invasive optical imaging techniques are essential diagnostic tools in many fields. Although various recent methods have been proposed to utilize and control light in multiple scattering media, non-invasive optical imaging through and inside scattering layers across a large field of view remains elusive due to the physical limits set by the optical memory effect, especially without wavefront shaping techniques. Here, we demonstrate an approach that enables non-invasive fluorescence imaging behind scattering layers with field-of-views extending well beyond the optical memory effect. The method consists in demixing the speckle patterns emitted by a fluorescent object under variable unknown random illumination, using matrix factorization and a novel fingerprint-based reconstruction. Experimental validation shows the efficiency and robustness of the method with various fluorescent samples, covering a field of view up to three times the optical memory effect range. Our non-invasive imaging technique is simple, neither requires a spatial light modulator nor a guide star, and can be generalized to a wide range of incoherent contrast mechanisms and illumination schemes.