Portable Microscopes Research Articles

FluoCount: An Efficient and Accurate Cells and Bioparticles Enumeration Mobile Application for Portable Fluorescence Microscopes

FluoCount: An Efficient and Accurate Cells and Bioparticles Enumeration Mobile Application for Portable Fluorescence Microscopes

3D Scan of Hardness Imprints for the Non-destructive In-Situ Structural Assessment of Operated Metal Components

The structural integrity of operated components can be assessed by non-destructive mechanical tests performed in-situ with portable instruments. Particularly promising in this context are small scale hardness tests supplemented by the mapping of the residual imprints left on metal surfaces. The data thus collected represent the input of inverse analysis procedures, which determine the material characteristics and their evolution over time. The reliability of these estimates depends on the accuracy of the geometry scans and on the robustness of the data filtering and interpretation methodologies. The objective of the present work is to evaluate the accuracy of the 3D reconstruction of the residual deformation produced on metals by hardness tests performed at a few hundred N load. The geometry data are acquired by portable optical microscopes with variable focal distance. The imperfections introduced by the imaging system, which may not be optimized for all ambient conditions when used in automatic mode, are analysed. Representative examples of the output produced by the scanning tool are examined, focusing attention on the experimental disturbances typical of onsite applications. Proper orthogonal decomposition and data reduction techniques are applied to the information returned by the instrumentation. The essential features of the collected datasets are extracted and the main noise is removed. The results of this investigation show that the accuracy achievable with the considered equipment and regularization procedures can support the development of reliable diagnostic analyses of metal components in existing structures and infrastructures.

A preliminary study on the method of identifying Zheng by bridges

Zheng is a Chinese traditional plucked instrument with a history of over 2,500 years, and it is regarded as one of the most important instruments in Chinese traditional music. The early “Zheng” obtained from archaeological excavations is generally assessed via the exclusion method. If the shape of an unearthed “wooden instrument” is not Zhu, Qin, nor Se, then it is certainly a Zheng. However, this method does not emphasize the characteristics of Zheng, which has certain limitations. Based on the study on the difference between Zheng and other plucked instruments, this article suggests that regularly arranged bridges are the most significant difference between Zheng and other instruments with similar shapes. Hence, the presence of regular bridge indentations on the wood panel should be the basis for identification. Accordingly, portable microscopes, three-dimensional laser scanners, and other equipment were employed to investigate modern Zheng samples. Via the analyses of the bridge arrangement, indentation depth, and other aspects, a set of methods that can be adopted to identify the plucked instrument was preliminarily established.

Rethinking low-cost microscopy workflow: Image enhancement using deep based Extended Depth of Field methods

Microscopic techniques in low-to-middle income countries are constrained by the lack of adequate equipment and trained operators. Since light microscopy delivers crucial methods for the diagnosis and screening of numerous diseases, several efforts have been made by the scientific community to develop low-cost devices such as 3D-printed portable microscopes. Nevertheless, these devices present some drawbacks that directly affect image quality: the capture of the samples is done via mobile phones; more affordable lenses are usually used, leading to poorer physical properties and images with lower depth of field; misalignments in the microscopic set-up regarding optical, mechanical, and illumination components are frequent, causing image distortions such as chromatic aberrations. This work investigates several pre-processing methods to tackle the presented issues and proposed a new workflow for low-cost microscopy. Additionally, two new deep learning models based on Convolutional Neural Networks are also proposed (EDoF-CNN-Fast and EDoF-CNN-Pairwise) to generate Extended Depth of Field (EDoF) images, and compared against state-of-the-art approaches. The models were tested using two different datasets of cytology microscopic images: public Cervix93 and a new dataset that has been made publicly available containing images captured with μSmartScope. Experimental results demonstrate that the proposed workflow can achieve state-of-the-art performance when generating EDoF images from low-cost microscopes.

Miniatura důstojníka 8. pěšího pluku rakouské armády. Nová akvizice Národního muzea od Patrizia Kettnera z roku 1836

The article explores a signed and dated portrait miniature of an officer by the painter Patrizio Kittner (1809–1900) from Brno, which was previously unknown. The aim of the text is to present Kittner’s portrait miniature through formal, stylistic and contextual analysis. The introduction focuses on the forgotten miniature painter’s personality, his artistic background, and his work for commissioners among the Moravian aristocracy and leading industrialists. It then proceeds with a formal description of the portrait miniature, its condition having been carefully assessed after the National Museum’s restorer removed the painting from its frame and disassembled the entire miniature into its individual components. This is followed by an analysis of Kittner’s painting style, which was examined using two portable microscopes: Dino-Lite type AM4115ZT for normal light images and Dino-Lite type AD4113T-12V for infrared images. Signed portrait miniatures from the Moravian Gallery in Brno served as adequate comparative ma­terial. The text then discusses the context of the work’s creation and identifies Kittner’s commissioners from the ranks of the Austrian army, evaluating the soldier’s rank and classification. The analyses indicate that Kittner’s miniature has been preserved in good technical condition. It is not substantially damaged, but it has undergone previous restoration, as indicated by the retouching on the right part of the man’s chest and in the upper right corner. This is an example of Kittner’s high-quality work, where the painter followed the Viennese portrait style of Moritz Michael Daffinger, known as the Daffinger School. In Kittner’s case, the clear influence of Viennese miniature production is demonstrated primarily through the painting style charac­terised by intersecting brushstrokes and the use of organic dye to depict skin tone. The article concludes by cautiously identifying the depicted figure as Anton Hahn, a lieutenant of the 8th Infantry Regiment of the Austrian Army.

AQAFI: a bioanalytical method for automated KPIs quantification of fluorescent images of human leukocytes and micro-nano particles.

Micro-nanoparticle and leukocyte imaging find significant applications in the areas of infectious disease diagnostics, cellular therapeutics, and biomanufacturing. Portable fluorescence microscopes have been developed for these measurements, however, quantitative assessment of the quality of images (micro-nanoparticles, and leukocytes) captured using these devices remains a challenge. Here, we present a novel method for automated quality assessment of fluorescent images (AQAFI) captured using smartphone fluorescence microscopes (SFM). AQAFI utilizes novel feature extraction methods to identify and measure multiple features of interest in leukocyte and micro-nanoparticle images. For validation of AQAFI, fluorescent particles of different diameters (8.3, 2, 1, 0.8 μm) were imaged using custom-designed SFM at a range of excitation voltages (3.8-4.5 V). Particle intensity, particle vicinity intensity, and image background noise were chosen as analytical parameters of interest and measured by the AQAFI algorithm. A control method was developed by manual calculation of these parameters using ImageJ which was subsequently used to validate the performance of the AQAFI method. For micro-nanoparticle images, correlation coefficients with R2 > 0.95 were obtained for each parameter of interest while comparing AQAFI vs. control (ImageJ). Subsequently, key performance indicators (KPIs) i.e., signal difference to noise ratio (SDNR) and contrast to noise ratio (CNR) were defined and calculated for these micro-nano particle images using both AQAFI and control methods. Finally, we tested the performance of the AQAFI method on the fluorescent images of human peripheral blood leukocytes captured using our custom SFM. Correlation coefficients of R2 = 0.99 were obtained for each parameter of interest (leukocyte intensity, vicinity intensity, background noise) calculated using AQAFI and control (ImageJ). A high correlation was also found between the CNR and SDNR values calculated using both methods. The developed AQAFI method thus presents an automated and precise way to quantify and assess the quality of fluorescent images (micro-nano particles and leukocytes) captured using portable SFMs. Similarly, this study finds broader applicability and can also be employed with benchtop microscopes for the quantitative assessment of their imaging performance.

Portable, Automated and Deep-Learning-Enabled Microscopy for Smartphone-Tethered Optical Platform Towards Remote Homecare Diagnostics: A Review.

Globally new pandemic diseases induce urgent demands for portable diagnostic systems to prevent and control infectious diseases. Smartphone-based portable diagnostic devices are significantly efficient tools to user-friendly connect personalized health conditions and collect valuable optical information for rapid diagnosis and biomedical research through at-home screening. Deep learning algorithms for portable microscopes also help to enhance diagnostic accuracy by reducing the imaging resolution gap between benchtop and portable microscopes. This review highlighted recent progress and continued efforts in a smartphone-tethered optical platform through portable, automated, and deep-learning-enabled microscopy for personalized diagnostics and remote monitoring. In detail, the optical platforms through smartphone-based microscopes and lens-free holographic microscopy are introduced, and deep learning-based portable microscopic imaging is explained to improve the image resolution and accuracy of diagnostics. The challenges and prospects of portable optical systems with microfluidic channels and a compact microscope to screen COVID-19 in the current pandemic are also discussed. It has been believed that this review offers a novel guide for rapid diagnosis, biomedical imaging, and digital healthcare with low cost and portability.

Computational Portable Microscopes for Point-of-Care-Test and Tele-Diagnosis.

In bio-medical mobile workstations, e.g., the prevention of epidemic viruses/bacteria, outdoor field medical treatment and bio-chemical pollution monitoring, the conventional bench-top microscopic imaging equipment is limited. The comprehensive multi-mode (bright/dark field imaging, fluorescence excitation imaging, polarized light imaging, and differential interference microscopy imaging, etc.) biomedical microscopy imaging systems are generally large in size and expensive. They also require professional operation, which means high labor-cost, money-cost and time-cost. These characteristics prevent them from being applied in bio-medical mobile workstations. The bio-medical mobile workstations need microscopy systems which are inexpensive and able to handle fast, timely and large-scale deployment. The development of lightweight, low-cost and portable microscopic imaging devices can meet these demands. Presently, for the increasing needs of point-of-care-test and tele-diagnosis, high-performance computational portable microscopes are widely developed. Bluetooth modules, WLAN modules and 3G/4G/5G modules generally feature very small sizes and low prices. And industrial imaging lens, microscopy objective lens, and CMOS/CCD photoelectric image sensors are also available in small sizes and at low prices. Here we review and discuss these typical computational, portable and low-cost microscopes by refined specifications and schematics, from the aspect of optics, electronic, algorithms principle and typical bio-medical applications.

Rapid Bacterial Motility Monitoring Using Inexpensive 3D-Printed OpenFlexure Microscopy Allows Microfluidic Antibiotic Susceptibility Testing.

Antibiotic susceptibility testing is vital to tackle the emergence and spread of antimicrobial resistance. Inexpensive digital CMOS cameras can be converted into portable digital microscopes using 3D printed x-y-z stages. Microscopic examination of bacterial motility can rapidly detect the response of microbes to antibiotics to determine susceptibility. Here, we present a new simple microdevice-miniature microscope cell measurement system for multiplexed antibiotic susceptibility testing. The microdevice is made using melt-extruded plastic film strips containing ten parallel 0.2 mm diameter microcapillaries. Two different antibiotics, ceftazidime and gentamicin, were prepared in Mueller-Hinton agar (0.4%) to produce an antibiotic-loaded microdevice for simple sample addition. This combination was selected to closely match current standard methods for both antibiotic susceptibility testing and motility testing. Use of low agar concentration permits observation of motile bacteria responding to antibiotic exposure as they enter capillaries. This device fits onto the OpenFlexure 3D-printed digital microscope using a Raspberry Pi computer and v2 camera, avoiding need for expensive laboratory microscopes. This inexpensive and portable digital microscope platform had sufficient magnification to detect motile bacteria, yet wide enough field of view to monitor bacteria behavior as they entered antibiotic-loaded microcapillaries. The image quality was sufficient to detect how bacterial motility was inhibited by different concentrations of antibiotic. We conclude that a 3D-printed Raspberry Pi-based microscope combined with disposable microfluidic test strips permit rapid, easy-to-use bacterial motility detection, with potential for aiding detection of antibiotic resistance.

A review on low-cost microscopes for Open Science.

This article presents a review after an exhaustive search that yielded 23 works carried out in the last decade for the availability of optical microscopes with open hardware as a low-cost alternative to commercial systems. These works were developed with the aim of covering needs within several areas such as: Bio Sciences research in institutions with limited resources, diagnosis of diseases and health screenings in large populations in developing countries, and training in educational contexts with a need for high availability of equipment and low replacement cost. The analysis of the selected works allows us to classify the analyzed solutions into two main categories, for which their essential characteristics are enumerated: portable field microscopes and multipurpose automated microscopes. Moreover, this work includes a discussion on the degree of maturity of the solutions in terms of the adoption of practices aligned with the development of Open Science. RESEARCH HIGHLIGHTS: Concise review on low-cost microscopes for developing Open Science, exposing the role of smartphone-based microscopy. The work classifies microscopes in two main categories: (1) portable field microscopes, and (2) multipurpose automated microscopes.

Calibration and validation of the application of low-cost, lightweight, and portable paper microscopes for monitoring pollen traits as a screening tool for drought tolerance

An efficient, low-cost, lightweight, and portable paper microscope can be used to monitor real-time in vivo pollination, which is not feasible with a conventional compound microscope. The advantages of paper microscopes (foldscopes) remain unexplored for in vivo field-oriented assessment of pollination. In this study, experiments were carried out to calibrate and validate the capability of foldscopes to investigate in vitro pollen traits and to understand the feasibility of using in real-time in vivo field-level investigations. Comparison of optical images of pollen morphological traits (color, size, and shape) of diverse plant species (including crops) captured using a foldscope and a compound microscope revealed little to no differences. In addition, foldscopes were calibrated to monitor and estimate in vitro pollen viability in wheat, sorghum, sunflower, chickpea, soybean, and periwinkle and to determine in vitro pollen germination in chickpea, maize, and periwinkle. Pollen tube growth was observed by time-lapse imaging of pollen from periwinkle. The foldscope efficiently captured genotypic variation in in vitro pollen germination of twelve chickpea genotypes under drought revealing the possibility of foldscopes as a tool for field level, real-time in vivo monitoring of pollination under drought.

OPTIMIZED CONFIGURATIONS FOR MICRO-PHOTOGRAMMETRIC SURVEYING ADAPTABLE TO MACRO OPTICS AND DIGITAL MICROSCOPE

Abstract. The configuration of new survey approaches for digitizing tiny artefacts is gradually emerging in favour of the related results sharing in new modalities such as 3D printing and or Cultural Heritage open-access datasets. Unfortunately, due to the still high cost of the instrumentations and the time required for specialized operators training, both the digital documentation of small artefacts and the dissemination of 3D data are still a long way from becoming truly mainstream practices.Alternative solutions, often at low cost, could be considered, involving the use of passive sensors for image-based modelling processes, relying on a widespread technology that is now within everyone’s reach. Therefore, we intend to meet the demand for the three-dimensional representation of small objects with complex surfaces and sub-millimetre morphological characteristics by designing several custom accessories that optimize the photogrammetric workflow while maintaining very high metric rigour.In this current work, the authors will focus on researching the most suitable acquisition method and hardware setup to achieve a digital twin of a complex and detailed cuneiform tablet replica using the now widely available on the market digital portable microscopes, able to achieve high magnification. The results were compared with a reference dataset from an active sensor acquisition for the necessary procedure validations.

Functional network topography of the medial entorhinal cortex

The medial entorhinal cortex (MEC) creates a map of local space, based on the firing patterns of grid, head-direction (HD), border, and object-vector (OV) cells. How these cell types are organized anatomically is debated. In-depth analysis of this question requires collection of precise anatomical and activity data across large populations of neurons during unrestrained behavior, which neither electrophysiological nor previous imaging methods fully afford. Here, we examined the topographic arrangement of spatially modulated neurons in the superficial layers of MEC and adjacent parasubiculum using miniaturized, portable two-photon microscopes, which allow mice to roam freely in open fields. Grid cells exhibited low levels of co-occurrence with OV cells and clustered anatomically, while border, HD, and OV cells tended to intermingle. These data suggest that grid cell networks might be largely distinct from those of border, HD, and OV cells and that grid cells exhibit strong coupling among themselves but weaker links to other cell types.

From on-site to in-lab: Microscopic observation of fungal proliferation on 17th century mural paintings

The fungal community of biodeteriorated 17th century mural paintings within the nave and altar portion of the old Church of the Holy Ascension (Veliki Krcimir, Nisava District, Serbia) has been studied via an array of microscopic analyses in order to detect actively growing fungi and assess their potential damage to the painted layer and mortar. In situ microscopy, performed with portable microscopes, together with optical and scanning electron microscopy, has revealed impairments of the painted layer in the form of cracks and biopitting, along with surface salt deposits and hidden, symptomless fungal growth. Various structures, such as fully developed fruiting bodies and melanized mycelia, clusters of microcolonial fungi and lichen soredia, as well as a conidial apparatus and numerous conidia in mass have been observed, all attesting to the presence of actively growing fungal community on the surface of the painted layer and in the interspaces between the painted layer and mortar. Based on the observed reproductive structures, the main agents of biodeterioration have been identified as fungi of Chaetomium and Cladosporium genera. The documented deterioration symptoms are most likely due to hyphal penetration and formation of fruiting bodies and other fungal structures.

Microcrack characterization of loaded Engineered Cementitious Composites via optical scans and photogrammetric analyses

Concrete cracks accelerate the ingress of harmful species and must be gauged accurately for durability evaluation and prediction. As a novel class of ultra-ductile concrete, Engineered Cementitious Composites (ECC) develops multiple sub-hairline cracks that are difficult to visualize using conventional techniques. In this study, a semi in-situ laboratory approach is proposed based on optical microscopy and photogrammetric analysis to enhance the accuracy of crack width measurement in ECC. Microscopic images scanned from the material surface were reconstructed and analyzed to extract the statistics of crack width, location, number, and spacing. Results suggested that general portable microscopes can effectively identify cracks smaller than 2 µm in loaded condition and provide magnified high-resolution crack images that are hardly achieved by regular digital cameras. Crack openings can be isolated via 2D FFT filtering and binarized to attain the datasets of crack spacing and crack width distribution. In contrast to microscopy, conventional digital image correlation (DIC) as an indirect method was found to overestimate sub-pixel crack widths particularly when the crack width and spacing are substantially smaller than the image resolution. In these scenarios, it is recommended to combine optical microscopy with DIC to ensure simultaneously accurate and holistic crack width characterization. The proposed technique can be used for general materials with multiple fine cracks.

StomataScorer: a portable and high-throughput leaf stomata trait scorer combined with deep learning and an improved CV model.

To measure stomatal traits automatically and nondestructively, a new method for detecting stomata and extracting stomatal traits was proposed. Two portable microscopes with different resolutions (TipScope with a 40× lens attached to a smartphone and ProScope HR2 with a 400× lens) are used to acquire images of living stomata in maize leaves. FPN model was used to detect stomata in the TipScope images and measure the stomata number and stomatal density. Faster RCNN model was used to detect opening and closing stomata in the ProScope HR2 images, and the number of opening and closing stomata was measured. An improved CV model was used to segment pores of opening stomata, and a total of 6 pore traits were measured. Compared to manual measurements, the square of the correlation coefficient (R 2) of the 6 pore traits was higher than 0.85, and the mean absolute percentage error (MAPE) of these traits was 0.02%–6.34%. The dynamic stomata changes between wild‐type B73 and mutant Zmfab1a were explored under drought and re‐watering condition. The results showed that Zmfab1a had a higher resilience than B73 on leaf stomata. In addition, the proposed method was tested to measure the leaf stomatal traits of other nine species. In conclusion, a portable and low‐cost stomata phenotyping method that could accurately and dynamically measure the characteristic parameters of living stomata was developed. An open‐access and user‐friendly web portal was also developed which has the potential to be used in the stomata phenotyping of large populations in the future.

Identification of Microplastics Based on the Fractal Properties of Their Holographic Fingerprint

Water plastic pollution is a serious problem affecting sealife, marine habitats, and the food chain. Artificial intelligence-enabled coherent imaging has recently shown exciting advances in the field of environmental monitoring, and portable holographic microscopes are good candidates to map the microparticles content of marine waters. The “holographic fingerprint” due to coherent light diffraction is rich in information, fully encoded into the complex wavefront scattered by the sample. Hence, proper analysis of the wavefronts reconstructed from digital holograms can unlock new possibilities in the fields of diagnostics and environmental monitoring. Fractal geometry well describes natural objects and allows inferring added-value information on the way these fill 2D spaces and 3D volumes. The most abundant micron-scale class of objects that populate marine waters consists of microalgae named diatoms, which are of interest as bioindicators of water quality. Here we investigate the fractal properties of holographic patterns of diatoms and microplastics, considering a heterogeneous mixture of five types of plastic materials and 55 different species of microalgae. We show that, different from the case of weak scattering objects, a small set of fractal parameters is able to characterize these two large ensembles. As an applicative example, we carry out classification tests to show the possibility to identify the two classes with high accuracy. This new holographic fractal description of scattering micro-objects could be used in the near future for in situ automatic mapping of microplastic pollutants and for taxonomy of diatoms as water quality bioindicators, screened onboard holographic systems.

Deep learning virtual Zernike phase contrast imaging for singlet microscopy

Singlet microscopy is very attractive for the development of cost-effective and portable microscopes. In contrast to conventional microscope objectives, which consist of multiple lenses, the manufacturing process for singlet lenses is done without extensive assembling and aligning. In this manuscript, we report a novel singlet virtual Zernike phase contrast microscopy setup for unstained pathological tumor tissue slides. In this setup, the objective consists of only one lens. There is no need for the inset Zernike phase plate, which is even more expensive than a whole brightfield microscopy setup. The Zernike phase contrast is virtually achieved by the deep learning computational imaging method. For the practical virtual Zernike phase contrast microscopy setup, the computational time is less than 100 ms, which is far less than that of other computational quantitative phase imaging algorithms. With a conceptual demo experimental setup, we proved our proposed method to be competitive with a research-level conventional Zernike phase contrast microscope and effective for the unstained transparent pathological tumor tissue slides. It is believed that our deep learning singlet virtual phase contrast microscopy is potential for the development of low-cost and portable microscopes and benefits resource-limited areas.

Deep learning virtual colorization overcoming chromatic aberrations in singlet lens microscopy

Singlet lenses are free from precise assembling, aligning, and testing, which are helpful for the development of portable and low-cost microscopes. However, balancing the spectrum dispersion or chromatic aberrations using a singlet lens made of one material is difficult. Here, a novel method combining singlet lens microscopy and computational imaging, which is based on deep learning image-style-transfer algorithms, is proposed to overcome this problem in clinical pathological slide microscopy. In this manuscript, a singlet aspheric lens is used, which has a high cut-off frequency and linear signal properties. Enhanced by a trained deep learning network, it is easy to transfer the monochromatic gray-scale microscopy picture to a colorful microscopy picture, with only one single-shot recording by a monochromatic CMOS image sensor. By experiments, data analysis, and discussions, it is proved that our proposed virtual colorization microscope imaging method is effective for H&E stained tumor tissue slides in singlet microscopy. It is believable that the computational virtual colorization method for singlet microscopes would promote the low-cost and portable singlet microscopy development in medical pathological label staining observing (e.g., H&E staining, Gram staining, and fluorescent labeling) biomedical research.

Portable Microscopes for Scientific Publications

This article reviews the use of portable microscopes in published science from Antonie van Leeuwenhoek's letters to the Royal Society to a recent paper on the phylogeny of the phorid fly by Hartop et al. [1]. The portability of a pocket microscope is a clear benefit, yet bulky compound microscopes remain the mainstay of field research and diagnosis. There is a growing interest in the impact of climate change, which drives researchers to investigate the smallest, most fragile life in remote places such as Antarctica, Mount Everest, and the Amazon Rainforest. Are pocket microscopes ready to produce publication-standard images?