Microscopic Imaging System Research Articles

Burning structures and propagation mechanisms of nanothermites

Nanothermites demonstrate attractive combustion characteristics such as tunable reactivity and high energy density. There is however a lack of fundamental understanding on their burning structures and reaction mechanisms due to the multi-scale complexity associated with the material and reaction heterogeneities. This gap in turn hinders the optimization of nanothermite design with desirable microstructures and controllable burning properties. In this work, a high-speed microscopy imaging system was used to reveal the burning structure of Al/CuO nanothermites and to investigate the propagation mechanism of its flame front at micron and sub-millimeter scales which have not been studied. An Al/CuO nanothermite film was fabricated as a model structure. First, the previously proposed reactive sintering was confirmed as a micron-scale burning characteristic. Then, at the sub-millimeter scale, it was demonstrated that the non-uniform burning propagation of nanothermite films is featured with distinguishable roles of the active burning sites and the pre-ignition sites. The active burning sites are clusters of reactive sintering particles and the pre-ignition sites appear in the preheating regions where Al and CuO particles have not yet participated in the reaction due to insufficient ignition energy. These pre-ignition sites form randomly and are subsequently ignited by heat transferred from the adjacent active burning sites, resulting in an active burning propagation tangentially along the propagation front. At the same time, as the thermite reaction of nanoparticles in the unburnt region is initiated, the propagation front advances in the normal direction. This experimental work reveals that the burning propagation mechanism of nanothermite films is governed by active burning propagation in both tangential and normal directions of the propagation front. Although the rates of these two modes are on the same order of magnitude, the tangential propagation of active burning is slightly faster, implying that pre-ignition sites are readily ignited with lower ignition energy.

Low Cycle Fatigue Crack Damage Behavior of TC21 Titanium Alloy with Basketweave Microstructure

Low cycle fatigue (LCF) crack initiation, propagation and damage behaviors of TC21 alloy with basketweave microstructure were investigated. The process of LCF damage was observed by a long-focus optical microscopic imaging system, and fatigue crack propagation was analyzed through in-situ SEM fatigue. The results indicated that LCF crack damage displayed different sensitivity to cyclic stress. LCF microcracks initiated from slip bands and propagated through the microcrack coalescences at high stress, while LCF cracks tended to initiate at the αL/β interface and connect with these interface microcracks. Furthermore, the LCF damage model was established on the basis of Lemaitre damage theory. When the maximum stress exceeded yield stress, LCF damage increased sharply and fatigue life decreased significantly, which agreed with experiment data.

Antarctic krill peptides improve scopolamine-induced memory impairment in mice

The study aims to investigate the repair effects of Ser-Ser-Asp-Ala-Phe-Phe-Pro-Phe-Arg (SSDAFFPFR) and Ser-Asn-Val-Phe-Asp-Met-Phe (SNVFDMF) peptides on scopolamine-caused memory impairment in mice. Behavioral experiments have revealed that Antarctic krill peptides can ameliorate scopolamine caused memory impairment by changing the behavior of mice. In comparison with the scopolamine group, the two peptides at a dose of 40 mg/kg could improve memory impairment. The serum SOD activity (82.82 ± 0.19 vs 79.47 ± 2.42 U/mg prot) and hippocampal ACh level (101.46 ± 3.23 vs 99.85 ± 7.13 μg/mg prot) of SSDAFFPFR were higher than those of SNVFDMF. Hippocampal AChE activity (0.20 ± 0.03 vs 0.53 ± 0.02 U/mg prot), hippocampal MDA level (1.56 ± 0.01 vs 1.63 ± 0.05 nmol/mg prot) and the serum MDA level (3.38 ± 0.24 vs 3.88 ± 0.21 nmol/mg prot) was lower than that of SNVFDMF. The state of mouse hippocampal cells was further observed by a microscopic imaging system. In addition, western blot analysis showed that SSDAFFPFR could significantly inhibit the expression of Bax, caspase-3, and p53, and promote the expression of BCL-XL, CREB, and BDNF, thus protecting hippocampal neurons in mice. In conclusion, the Antarctic krill peptide can repair scopolamine-induced memory impairment in mice.

Automatic pore size measurements from scanning electron microscopy images of porous scaffolds

Pore sizes and distribution are amongst the main morphological characteristics of porous scaffolds which indicate the suitability of scaffolds for many biological applications. Scaffolds usually have complex structures and are designed to have a specific range of pore sizes appropriate for target cells. Pore sizes are commonly estimated manually or based on semi-automatic techniques requiring high level of human intervention. Such methods are time consuming and subject to error, mainly due to lack of consistency in the process and subjective nature of the results following operator involvement. In this work, we present a novel image processing method for the measurement pore size distribution (the main morphological characteristics of scaffolds) independent from their complexity. We use thresholding, based on the histogram analysis, to segment pore areas from scaffold, followed by morphological filters to separate pores from each other. This algorithm provides robust detection and measurement of pore sizes and the distribution. The performance of the algorithm is assessed using standard calibration kit which is used for calibration of Scanning Electron Microscopy (SEM) imaging systems. The results showed consistent output with 1.3% average error as compared against their true size.The algorithm was applied to 3D Apatite-Wollastonite scaffolds manufactured using the Thermally Induced Phase Separation technique. The results were robust and consistent with visual evaluation of SEM images. The algorithm also provides the morphology of each pore and, subsequently, offering further comprehension of the influence of microstructures across a range of fields, such as tissue engineering processes.

Vision-Based 40-nm-Accuracy Liquid Level Detection Compliant With Micromanipulation

Recent efforts in single-cell research call for precise liquid level detection (LLD) for end-effectors to manipulate small volume of liquid samples such as nano- to pico-liter droplets. Existing LLD methods, however, are yet satisfactory for such delicate micromanipulation tasks. This article presents a vision-based contact type LLD method, which adopts the hardware settings normally used in typical micromanipulation scenarios. The detection principle is based on the generation of patterned ripples when the end-effector (e.g., glass micropipette), that is being vibrated, moves to get contact with the liquid surface. Through the microscopic imaging system in micromanipulation, the image frames of patterned ripples such as concentric circles are recorded, from which the wavelength is extracted to determine the contact moment. The vision-based LLD method was cross-validated by the electrical impedance-based method. Experiments revealed that the best detection accuracy was 40 nm, only limited by the micromanipulator's positioning resolution. Moreover, the method was robust to various micromanipulation settings, such as illumination intensity, microscopy magnification, exposure time, and focal plane. As a demonstration, this method was successful in detecting the surface of droplets with a volume as low as 450 pL for different liquids. Given its generality, this method is expected to suit many scenarios involving liquid handling tasks in micromanipulation and industry.

Fast autofocusing based on pixel difference with the Tanimoto coefficient between images.

Focusing objects accurately over short time scales is an essential and nontrivial task for a variety of microscopy applications. In this Letter, an autofocusing algorithm using pixel difference with the Tanimoto coefficient (PDTC) is described to predict the focus. Our method can robustly distinguish differences in clarity among datasets. The generated auto-focusing curves have extremely high sensitivity. A dataset of a defocused stack acquired by an Olympus microscope demonstrates the feasibility of our technique. This work can be applied in full-color microscopic imaging systems and is also valid for single-color imaging.

Segmentation and Recognition of the Pathological Features of Squamous Cell Carcinoma of the Skin Based on Multispectral Imaging.

Cutaneous squamous cell carcinoma (cSCC) is one of the most common skin cancers, a definitive diagnosis of cSCC is crucial to prevent patients from missing out on treatment. The gold standard for the diagnosis of cSCC is still pathological biopsy. Currently, its diagnostic efficiency and accuracy largely depend on the experience of pathologists. Here, we present a simple, fast, and robust technique, a microscopic multispectral imaging system based on LED illumination, to diagnose cSCC qualitatively and quantitatively. The adaptive threshold segmentation method was used to segment the multispectral images into characteristic structures. There was a statistically significant difference between the average nucleocytoplasmic ratio of normal skin (4.239%) and cSCC tissues (15.607%) (p < 0.01), and the keratin pearls cSCC have well-defined qualitative features. These results show that the qualitative and quantitative features obtained from multispectral imaging can be used to comprehensively determine whether or not the tissue is cancerous. This work has significant implications for the development of a low-cost and easy-to-use device, which can not only reduce the complexity of pathological diagnosis but can also achieve the goal of convenient digital staining and access to critical histological information.

A Sperm Quality Detection System Based on Microfluidic Chip and Micro-Imaging System

Sperm quality assessment is the main method to predict the reproductive ability of livestock. The detection of sperm quality of livestock is of great significance to the application of artificial insemination and in vitro fertilization. In order to comprehensively evaluate sperm quality and improve the real-time and portability of sperm quality detection, a portable microscopic imaging system based on microfluidic chip is developed in this paper. The system can realize the comprehensive evaluation of sperm quality by detecting sperm vitality and survival rate. On the hardware side, a microfluidic chip is designed, which can automatically mix samples. A set of optical system with a magnification of 400 times was developed for microscopic observation of sperm. In the aspect of software, aiming at the comprehensive evaluation of sperm quality based on OpenCV, a set of algorithms for identifying sperm motility and survival rate is proposed. The accuracy of the system in detecting sperm survival rate is 94.0%, and the error rate is 0.6%. The evaluation results of sperm motility are consistent with those of computer-aided sperm analysis (CASA). The system's identification time is 9 s. Therefore, the system is absolutely suitable for sperm quality detection.

A Cost-Effective Nucleic Acid Detection System Using a Portable Microscopic Device.

A fluorescence microscope is one of the most important tools for biomedical research and laboratory diagnosis. However, its high cost and bulky size hinder the application of laboratory microscopes in space-limited and low-resource applications. Here, in this work, we proposed a portable and cost-effective fluorescence microscope. Assembled from a set of 3D print components and a webcam, it consists of a three-degree-of-freedom sliding platform and a microscopic imaging system. The microscope is capable of bright-field and fluorescence imaging with micron-level resolution. The resolution and field of view of the microscope were evaluated. Compared with a laboratory-grade inverted fluorescence microscope, the portable microscope shows satisfactory performance, both in the bright-field and fluorescence mode. From the configurations of local resources, the microscope costs around USD 100 to assemble. To demonstrate the capability of the portable fluorescence microscope, we proposed a quantitative polymerase chain reaction experiment for meat product authenticating applications. The portable and low-cost microscope platform demonstrates the benefits in space-constrained environments and shows high potential in telemedicine, point-of-care testing, and more.

In vivo observation of multi-phase spatiotemporal cellular dynamics of transplanted HSPCs during early engraftment.

Hematopoietic stem cell transplantation (HSCT) is commonly used to treat patients with various blood disorders, genetic and immunological diseases, and solid tumors. Several systemic complications following HSCT are critical limiting factors for achieving a successful outcome. These systemic complications are mainly due to the lack of initial engraftment after transplantation. However, the detailed underlying cellular dynamics of early engraftment have not been fully characterized yet. We performed in vivo longitudinal visualization of early engraftment characteristics of transplanted hematopoietic stem and progenitor cells (HSPCs) in the mouse calvarial bone marrow (BM). To achieve this, we utilized an in vivo laser‐scanning confocal microscopy imaging system with a cranial BM imaging window and stereotaxic device. We observed two distinct cellular behaviors of HSPCs in vivo, cluster formation and cluster dissociation, early after transplantation. Furthermore, we successfully identified three cellular phases of engraftment with distinct cellular distances which are coordinated with cell proliferation and cell migration dynamics during initial engraftment.

Automatic detection of head and neck squamous cell carcinoma on histologic slides using hyperspectral microscopic imaging.

.SignificanceAutomatic, fast, and accurate identification of cancer on histologic slides has many applications in oncologic pathology.AimThe purpose of this study is to investigate hyperspectral imaging (HSI) for automatic detection of head and neck cancer nuclei in histologic slides, as well as cancer region identification based on nuclei detection.ApproachA customized hyperspectral microscopic imaging system was developed and used to scan histologic slides from 20 patients with squamous cell carcinoma (SCC). Hyperspectral images and red, green, and blue (RGB) images of the histologic slides with the same field of view were obtained and registered. A principal component analysis-based nuclei segmentation method was developed to extract nuclei patches from the hyperspectral images and the coregistered RGB images. Spectra-based support vector machine and patch-based convolutional neural networks (CNNs) were implemented for nuclei classification. The CNNs were trained with RGB patches (RGB-CNN) and hyperspectral patches (HSI-CNN) of the segmented nuclei and the utility of the extra spectral information provided by HSI was evaluated. Furthermore, cancer region identification was implemented by image-wise classification based on the percentage of cancerous nuclei detected in each image.ResultsRGB-CNN, which mainly used the spatial information of nuclei, resulted in a 0.81 validation accuracy and 0.74 testing accuracy. HSI-CNN, which utilized the spatial and spectral features of the nuclei, showed significant improvement in classification performance and achieved 0.89 validation accuracy as well as 0.82 testing accuracy. Furthermore, the image-wise cancer region identification based on nuclei detection could generally improve the cancer detection rate.ConclusionsWe demonstrated that the morphological and spectral information contribute to SCC nuclei differentiation and that the spectral information within hyperspectral images could improve classification performance.

Real-time reconstruction using electro-optics modulator-based structured illumination microscopy.

Structured illumination microscopy (SIM), a super-resolution technology, has a wide range of applications in life sciences. In this study, we present an electro-optic high-speed phase-shift super-resolution microscopy imaging system including 2D SIM, total internal reflection fluorescence-SIM, and 3D SIM modes. This system uses galvanometers and an electro-optic modulator to flexibly and quickly control the phase and direction of structured illumination patterns. Moreover, its design consists of precise timing for improved acquisition speed and software architecture for real-time reconstruction. The highest acquisition rate achieved was 151 frames/s, while the highest real-time super-resolution reconstruction frame rate achieved was over 25 frames/s.

A novel 3D convolutional neural network model with supervised spectral regression for recognition of hyperspectral images of colored wool fiber

AbstractPrior knowledge of textile fiber colors in blends is useful for color recipe assessment. There have been various methods to improve the accuracy of color recognition from the dataset of colored textile fibers in recent years. However, numerical assessments based on spectral feature and color difference is insufficient, in which the accuracy of color recognition can be affected by morphology and the uneven coloration on a single fiber. This paper proposes a novel 3D convolutional neural network model (3D‐CNN) with supervised spectral regression for the color recognition of hyperspectral images (HSI) of colored textile fiber. The proposed method obtained spatial‐spectral features based on 3D‐CNN, and the true spectrum of each class was used for supervised spectral regression to improve the accuracy. The loss function used was the sum of the supervised classification loss function and the spectral regression loss function model are optimized by mini‐batch‐based backpropagation. The proposed method was trained and tested on the HSI dataset composed of 100 colors of wool fibers acquired through a microscopic hyperspectral imaging system at a ×3.375 optical magnification. The experimental results showed that the proposed method exhibited better performance compared to numerical assessments and other deep learning models, except for efficiency. Specifically, it achieved better recognition performance on sub‐datasets of similar colored and light‐colored wool fiber where subtle inter‐class and large intra‐class variance existed.

Image Spherizing-Based Three-Dimensional Displacement Measurement Technique for Microscope with Single Camera

The detection of three-dimensional displacement, caused by micro-nano scale deformation, is of great significance for the industrial production of glass or quartz optical fiber products. Considering the detection cost and practicability, an image spherizing-based three-dimensional displacement measurement method for a monocular microscopic imaging system (a microscope with a normal industrial camera) is proposed. Differential theory tells us that an arbitrary large-scale deformation can be approximatively considered as the sum of slope-shaped deformations. In this paper, an ordinary slope model is presented by the idea of image spherizing and differential theory, which reveals the mathematical relation between in-plane displacement and out-of-plane displacement in the deformed images captured by an optical microscope. After obtaining the in-plane displacement field, the out-of-plane displacement field can be extracted from the in-plane displacement field by the ordinary slope model, which indicates that the out-of-plane displacement information carried by the in-plane displacement is fully utilized. Simulation and application experiments are performed to demonstrate the effectiveness and all the absolute errors of the measurement by optical microscope with a magnification of 50× are less than 0.2 μm. Unlike conventional methods, the new method does not need a phase unwrapping process during detection and has many attractive characteristics such as low-cost, simple arrangements and good applicability. Because the measurement precision of this technique can meet the detection requirement, it has been applied to the industrial detection of glass or quartz optical fiber products.

A design of dust analyzer for future Main Belt Comet exploration mission

A Main Belt Comet exploration mission has been proposed to perform rendezvous with a Main Belt Comet in the future, and the probe will orbit the comet and carry on complete investigation. The scientific objective of the Main Belt Comet Dust Analyzer (MBCDA) instrument, part of the scientific payload onboard the Main Belt Comet mission, is to explore the ejections, orbit activity and origin of the comet, as well as dust evolution in the coma and their influence on the probe. To this aim, MBCDA is composed of different modules: a Microbalance Sensor system, to measure the dust flux from different directions and perform a thermo-gravimetric analysis, a Dust Size Sensor, to monitor the grain's diameter by optical detection, a Dust Momentum Sensor, to detect the momentum carried by the particles, and a Microscopic Imaging System, to obtain the morphological, charging properties and composition information of the comet dust. The preliminary calibration results of MBCDA demonstrate that the instrument is basically compatible with design specifications and is suitable to obtain scientific results about cometary dust.

An autofocus algorithm considering wavelength changes for large scale microscopic hyperspectral pathological imaging system.

Microscopic hyperspectral imaging technology has been widely used to acquire pathological information of tissue sections. Autofocus is one of the most important steps in microscopic hyperspectral imaging systems to capture large scale or even whole slide images of pathological slides with high quality and high speed. However, there are quite few autofocus algorithm put forward for the microscopic hyperspectral imaging system. Therefore, this article proposes a Laplace operator based autofocus algorithm for microscopic hyperspectral imaging system which takes the influence of wavelength changes into consideration. Through the proposed algorithm, the focal length for each wavelength can be adjusted automatically to ensure that each single band image can be autofocused precisely with adaptive image sharpness evaluation method. In addition, to increase the capture speed, the relationship of wavelength and focal length is derived and the focal offsets among different single band images are calculated for pre-focusing. We have employed the proposed method on our own datasets and the experimental results show that it can capture large-scale microscopic hyperspectral pathology images with high precise.

Simultaneous multiple-level magnification selective plane illumination microscopy (sMx-SPIM) imaging system

We report an optical-based microscopy imaging technology—simultaneous multiple-level magnification selective plane illumination microscopy (sMx-SPIM) imaging system—that addresses a longstanding technological challenge of obtaining images, specifically of biological specimen non-destructively, at different field of views (FOVs) and spatial resolutions (or magnification powers) simultaneously in real-time. This imaging system provides not only 3D images but also time-resolved sequential images with temporal resolution ∼ msec. Magnification powers (or FOVs) of the individual images can be controlled independently that is achieved by housing two separate detection arms, in SPIM imaging system, fitted with objective lenses of different magnification powers. This unique feature holds promises to observe and study: (a) sub-microscopic details and entire structure of biological specimen side-by-side simultaneously and (b) spatio-temporal dynamics of functional activities of biological specimen. For validation study of robustness of the proposed sMx-SPIM imaging system, experiments are conducted in various biological samples including Danio rerio (zebrafish) embryo, Drosophila melanogaster, Allium cepa root, and A549 cell line. Experimental results demonstrate that the study is of significant impacts from two aspects, viz., technological implication and biological applications.

Effect of height to diameter ratio on dynamic characteristics of cemented tailings backfills with fiber reinforcement through impact loading

The safety and durability of underground backfilled stopes of metalliferous mines are so crucial owing to several dynamic events such as rock bursting, loads triggered by blasting, and loading conditions under stress. Besides, the effect of height to diameter ratio on dynamic properties of fiber reinforced paste backfill has not yet been explored suitably, but this factor is vital to determine the design properties of mining with backfill. This study deals the findings of the dynamic tests done on fiber reinforced cemented tailings backfills (FRCTB) considering different height to diameter ratios under impact loading. A cement mortar mixed with polypropylene fiber with 12 mm length was made, cast in six diverse molds (H × D: 25 × 50; 30 × 50; 35 × 50; 40 × 50; 45 × 50; and 50 × 50 mm), and experimented through Split-Hopkinson pressure bar (SHPB) setup. Later, internal crack formation within FRCTB was observed by employing a computerized X-ray imaging (CT) and scanning-electron microscope (SEM) system. The results indicated that fracture number/path and failure damage of FRCTB decreases with increasing H/D ratio while their dynamic strengths drop with growing mean strain rate. Fractures arise because of the greatest micro-cracks as a function of stress application. These cracks rise with an increase in specimen size, resulting in lower strengths. Through SEM and CT observations, it is found that polypropylene fiber boosts the cementation of FRCTB and frequent hydration products are attached to fiber surface. Assessing research findings in mine backfill applications will help the better consideration of FRCTB dynamic characteristics, and the actual strength resistance and dynamic durability design of deep mining with backfilling.

Increasing a microscope's effective field of view via overlapped imaging and machine learning.

This work demonstrates a multi-lens microscopic imaging system that overlaps multiple independent fields of view on a single sensor for high-efficiency automated specimen analysis. Automatic detection, classification and counting of various morphological features of interest is now a crucial component of both biomedical research and disease diagnosis. While convolutional neural networks (CNNs) have dramatically improved the accuracy of counting cells and sub-cellular features from acquired digital image data, the overall throughput is still typically hindered by the limited space-bandwidth product (SBP) of conventional microscopes. Here, we show both in simulation and experiment that overlapped imaging and co-designed analysis software can achieve accurate detection of diagnostically-relevant features for several applications, including counting of white blood cells and the malaria parasite, leading to multi-fold increase in detection and processing throughput with minimal reduction in accuracy.

Flame stand-off effects on propagation of 3D printed 94 wt% nanosized pyrolants loading composites

Understanding the relationship between heat transport mechanisms, particularly given the new opportunities to microstructure architecture through additive manufacturing to adjust heat flux (energy release rate per area, unit W/m2), is highly desirable. In this study, we directly write free-standing iodized pyrolant sticks (94 wt% pre-assembled Ti/Ca(IO3)2 nanocomposites) with only 6 wt% binder addition. Compared to the substrate-supported pyrolant composites without using polymer (100 wt% Ti/Ca(IO3)2), we saw a > 4X reduction on the heat release rate with only 6 wt% polymer. Additionally the physically mixed case (94 wt% physically mixed Ti/Ca(IO3)2 has another 4X lower heat release rate than the above pre-assembled case. To explore heat feedback we observed the flame stand-off particularly in the samples with 6 wt% polymer via a microscopic imaging system with pyrometry. We found that with the pre-assembled and physically mixed pyrolants, the flame stand-off distances are ∼ 0.7 mm and ∼ 1.2 mm, respectively, which provides low heat feedback to the burning surface leading to partial ignition of nanocomposites on the burning surface. A simple thermal calculation was used to explain the relative role of the different modes of heat feedback and their relationship to stand-off and ignition.