Field-portable pixel super-resolution colour microscope

Quantitative phase imaging based on holography: trends and new perspectives

In 1948, Dennis Gabor proposed the concept of holography, providing a pioneering solution to a quantitative description of the optical wavefront. After 75 years of development, holographic imaging has become a powerful tool for optical wavefront measurement and quantitative phase imaging. The emergence of this technology has given fresh energy to physics, biology, and materials science. Digital holography (DH) possesses the quantitative advantages of wide-field, non-contact, precise, and dynamic measurement capability for complex-waves. DH has unique capabilities for the propagation of optical fields by measuring light scattering with phase information. It offers quantitative visualization of the refractive index and thickness distribution of weak absorption samples, which plays a vital role in the pathophysiology of various diseases and the characterization of various materials. It provides a possibility to bridge the gap between the imaging and scattering disciplines. The propagation of wavefront is described by the complex amplitude. The complex-value in the complex-domain is reconstructed from the intensity-value measurement by camera in the real-domain. Here, we regard the process of holographic recording and reconstruction as a transformation between complex-domain and real-domain, and discuss the mathematics and physical principles of reconstruction. We review the DH in underlying principles, technical approaches, and the breadth of applications. We conclude with emerging challenges and opportunities based on combining holographic imaging with other methodologies that expand the scope and utility of holographic imaging even further. The multidisciplinary nature brings technology and application experts together in label-free cell biology, analytical chemistry, clinical sciences, wavefront sensing, and semiconductor production.

Digital holographic approaches to the detection and characterization of microplastics in water environments

Microplastic (MP) pollution is seriously threatening the environmental health of the world, which has accelerated the development of new identification and characterization methods. Digital holography (DH) is one of the emerging tools to detect MPs in a high-throughput flow. Here, we review advances in MP screening by DH. We examine the problem from both the hardware and software viewpoints. Automatic analysis based on smart DH processing is reported by highlighting the role played by artificial intelligence for classification and regression tasks. In this framework, the continuous development and availability in recent years of field-portable holographic flow cytometers for water monitoring also is discussed.

Multi-Illumination Single-Holographic-Exposure Lensless Fresnel (MISHELF) Microscopy: Principles and Biomedical Applications

Lensless holographic microscopy (LHM) comes out as a promising label-free technique since it supplies high-quality imaging and adaptive magnification in a lens-free, compact and cost-effective way. Compact sizes and reduced prices of LHMs make them a perfect instrument for point-of-care diagnosis and increase their usability in limited-resource laboratories, remote areas, and poor countries. LHM can provide excellent intensity and phase imaging when the twin image is removed. In that sense, multi-illumination single-holographic-exposure lensless Fresnel (MISHELF) microscopy appears as a single-shot and phase-retrieved imaging technique employing multiple illumination/detection channels and a fast-iterative phase-retrieval algorithm. In this contribution, we review MISHELF microscopy through the description of the principles, the analysis of the performance, the presentation of the microscope prototypes and the inclusion of the main biomedical applications reported so far.

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.

Miniaturized optimal incident light angle-fitted dark field system for contrast-enhanced real-time monitoring of 2D/3D-projected cell motions

In the field of biology, dark field microscopy provides superior insight into cells and subcellular structures. However, most dark field microscopes are equipped with a dark field filter and a light source on a 2D-based specimen, so only a flat sample can be observed in a limited space. We propose a compact cell monitoring system with built-in dark field filter with an optimized incident angle of the light source to provide real-time cell imaging and spatial cell monitoring for long-term free from phototoxicity. 2D projection imaging was implemented using a modular condenser lens to acquire high-contrast images. This enabled the long-term monitoring of cells, and the real-time monitoring of cell division and death. This system was able to image, by 2D projection, cells on the surface thinly coated with multiwalled carbon nanotubes, as well as living cells that migrated along the surface of glass beads and hydrogel droplets with a diameter of about 160 μm. The optimal incident light angle-fitted dark field system combines high-contrast imaging sensitivity and high spatial resolution to even image cells on 3D surfaces.

i-scope: A Compact automated fluorescence microscope for cell counting applications in low resource settings

Fluorescence microscopy has widespread applications across biological sciences. It has been routinely used for cell counting, which provides a preliminary diagnostic test for many infectious diseases. Conventional fluorescence microscopes are bulky, expensive, time-intensive and laborious. They often require trained operators to acquire and analyze data. We report a compact automated digital fluorescence microscopy system, i-scope, for cell counting applications. The i-scope employs a total internal reflection fluorescence (TIRF) mode of sample illumination, along with a brightfield mode. It has a magnification of 30X, an optical resolution of ~0.2 µm/pixel and offers sample scanning over 20 mm x 20 mm. A custom-written program enables automated image acquisition and analysis, thereby enhancing ease of operation. It has a compact form-factor and has been developed into a standalone system with a processing unit, screen, and other accessories to offer a portable and economic point-of-care diagnostic solution in low-resource settings. We analysed the performance of the i-scope for milk somatic cell enumeration and benchmarked it against that of a conventional fluorescence microscope.

Multi-Mode Compact Microscopy for High-Contrast and High-Resolution Imaging

We report a multi-mode compact microscope (MCM) for high-contrast and high-resolution imaging. The MCM consists of two LED illuminations, a magnification lens, a lift stage, and a housing with image processing and LED control boards. The MCM allows multi-modal imaging, including reflection, transmission, and higher magnification modes. The dual illuminations also provide high-contrast imaging of various targets such as biological samples and microcircuits. The high dynamic range (HDR) imaging reconstruction of MCM increases the dynamic range of the acquired images by 1.36 times. The microlens array (MLA)-assisted MCM also improves image resolution through the magnified virtual image of MLA. The MLA-assisted MCM successfully provides a clear, magnified image by integrating a pinhole mask to prevent image overlap without additional alignment. The magnification of MLA-assisted MCM was increased by 3.92 times compared with that of MCM, and the higher magnification mode demonstrates the image resolution of 2.46 μm. The compact portable microscope can provide a new platform for defect inspection or disease detection on site.

Rapid detection of an Ebola biomarker with optical microring resonators

Ebola virus (EBOV) is a highly infectious pathogen, with a case mortality rate as high as 89%. Rapid therapeutic treatments and supportive measures can drastically improve patient outcome; however, the symptoms of EBOV disease (EVD) lack specificity from other endemic diseases. Given the high mortality and significant symptom overlap, there is a critical need for sensitive, rapid diagnostics for EVD. Facile diagnosis of EVD remains a challenge. Here, we describe a rapid and sensitive diagnostic for EVD through microring resonator sensors in conjunction with a unique biomarker of EBOV infection, soluble glycoprotein (sGP). Microring resonator sensors detected sGP in under 40 min with a limit of detection (LOD) as low as 1.00 ng/mL in serum. Furthermore, we validated our assay with the detection of sGP in serum from EBOV-infected non-human primates. Our results demonstrate the utility of a high-sensitivity diagnostic platform for detection of sGP for diagnosis of EVD.

Resolution and Contrast Enhancement for Lensless Digital Holographic Microscopy and Its Application in Biomedicine

An important imaging technique in biomedicine, the conventional optical microscopy relies on relatively complicated and bulky lens and alignment mechanics. Based on the Gabor holography, the lensless digital holographic microscopy has the advantages of light weight and low cost. It has developed rapidly and received attention in many fields. However, the finite pixel size at the sensor plane limits the spatial resolution. In this study, we first review the principle of lensless digital holography, then go over some methods to improve image contrast and discuss the methods to enhance the image resolution of the lensless holographic image. Moreover, the applications of lensless digital holographic microscopy in biomedicine are reviewed. Finally, we look forward to the future development and prospect of lensless digital holographic technology.

Backscatter multiple wavelength digital holography for color micro-particle imaging

This work applies digital holography to image stationary micro-particles in color. The approach involves a Michelson interferometer to mix reference light with the weak intensity light backscattered from a distribution of particles. To enable color images, three wavelengths are used, 430, 532, and 633 nm, as primary light sources. Three separate backscattered holograms are recorded simultaneously, one for each wavelength, which are resolved without spectral cross talk using a three-CMOS prism sensor. Fresnel diffraction theory is used to render monochrome images from each hologram. The images are then combined via additive color mixing with red, green, and blue as the primary colors. The result is a color image similar in appearance to that obtained with a conventional microscope in white-light epi-illumination mode. A variety of colored polyethylene micro-spheres and nonspherical dust particles demonstrate the feasibility of the approach and illustrate the effect of simple speckle-noise suppression and white balance methods. Finally, a chromaticity analysis is applied that is capable of differentiating particles of different colors in a quantitative and objective manner.

Design, Calibration, and Application of a Robust, Cost-Effective, and High-Resolution Lensless Holographic Microscope

Lensless holographic microscope (LHM) is an emerging very promising technology that provides high-quality imaging and analysis of biological samples without utilizing any lens for imaging. Due to its small size and reduced price, LHM can be a very useful tool for the point-of-care diagnosis of diseases, sperm assessment, or microfluidics, among others, not only employed in advanced laboratories but also in poor and/or remote areas. Recently, several LHMs have been reported in the literature. However, complete characterization of their optical parameters remains not much presented yet. Hence, we present a complete analysis of the performance of a compact, reduced cost, and high-resolution LHM. In particular, optical parameters such as lateral and axial resolutions, lateral magnification, and field of view are discussed into detail, comparing the experimental results with the expected theoretical values for different layout configurations. We use high-resolution amplitude and phase test targets and several microbeads to characterize the proposed microscope. This characterization is used to define a balanced and matched setup showing a good compromise between the involved parameters. Finally, such a microscope is utilized for visualization of static, as well as dynamic biosamples.

Adaptive Parameter Model for Quasi-Spherical Cell Size Measurement Based on Lensless Imaging System

Many biological cells appear quasi-spherical, such as red blood cells, white blood cells, egg cells, cancer cells, etc. Cell size is an important basis for medical diagnosis. The traditional method is to use a microscope or flow cytometer to obtain the cell size. Either it depends on professionals and cannot be automated, or it is expensive and bulky, which are not suitable for point-of-care test. Lab-on-a-chip technology using a lensless imaging system gives a better solution for obtaining the cell size. In order to deal with the diffraction in the lensless imaging system, the distance between the light source and the cell, the distance between the cell and the CMOS image sensor and optical wavelength need to be accurately measured or controlled, which will greatly increase the complexity of the system, making it difficult to truly apply to point-of-care test. In this paper, an adaptive parameter model for quasi-spherical cell size measurement based on lensless imaging system is given. First, the diffraction theory used in the model is explained. Then, the adaptive algorithm of the system parameter is given. To illustrate the practicality of the algorithm, a quasi-spherical cell size measurement method and a super-resolution algorithm are given. Finally, the experiment proves that the adaptive parameter model is effective can meet the needs of quasi-spherical cell size measurement.

Red blood cell recognition and posture estimation in microfluidic chip based on lensless imaging

On the one hand, lensless imaging technology has become one of the key technologies to achieve point-of-care testing; on the other hand, microfluidic technology has shown great application potential in the field of biological detection. Using mainstream lensless imaging technology to achieve biological cell imaging in microfluidic chips has technical limitations. In particular, it is more difficult to achieve lensless imaging for non-spherical cells in microfluidic chips such as red blood cells. Achieving red blood cell recognition and posture estimation in a microfluidic chip under the lensless imaging, combined with mainstream lensless imaging technology, can provide more effective red blood cell morphological parameters for medical diagnosis. In this paper, the method for red blood cell recognition and posture estimation in microfluidic chips based on lensless imaging is given. First, the relevant theoretical basis is introduced. Then, the models of red blood cell recognition and posture estimation in microfluidic chips based on lensless imaging are given. The effect of red blood cell flipping on lensless imaging is analyzed in the modeling process. Finally, the effectiveness of the proposed method is verified by experiments. Experiments show that the proposed method can well achieve red blood cell recognition and posture estimation through the shape characteristics of red blood cells.

High-resolution multi-wavelength lensless diffraction imaging with adaptive dispersion correction

Multi-wavelength imaging diffraction system is a promising phase imaging technology due to its advantages of no mechanical movement and low complexity. In a multi-wavelength focused system, spectral bandwidth and dispersion correction are critical for high resolution reconstruction. Here, an optical setup for the multi-wavelength lensless diffraction imaging system with adaptive dispersion correction is proposed. Three beams with different wavelengths are adopted to illuminate the test object, and then the diffraction patterns are recorded by a image sensor. The chromatic correction is successfully realized by a robust refocusing technique. High-resolution images can be finally retrieved through phase retrieval algorithm. The effectiveness and reliability of our method is demonstrated in numerical simulation and experiments. The proposed method has the potential to be an alternative technology for quantitative biological imaging.

Inline holographic microscopy through fiber imaging bundles

Fiber imaging bundles are widely used as thin, passive image conduits for miniaturized and endoscopic microscopy, particularly for confocal fluorescence imaging. Holographic microscopy through fiber bundles is more challenging; phase conjugation approaches are complex and require extensive calibration. This paper describes how simple inline holographic microscopy can be performed through an imaging bundle using a partially coherent illumination source from a multimode fiber. The sample is imaged in transmission, with the intensity hologram sampled by the bundle and transmitted to a remote camera. The hologram can then be numerically refocused for volumetric imaging, achieving a resolution of approximately 6 µm over a depth range of 1 mm. The scheme does not require any complex prior calibration and hence is insensitive to bending.

Imaging atmospheric aerosol particles from a UAV with digital holography

The lack of quantitative characterization of aerosol particles and their loading in the atmosphere is one of the greatest uncertainties in climate-change science. Improved instrumentation capable of determining the size and shape of aerosol particles is needed in efforts to reduce this uncertainty. We describe a new instrument carried by an unmanned aerial vehicle (UAV) that images free-floating aerosol particles in the atmosphere. Using digital holography, the instrument obtains the images in a non-contact manner, resolving particles larger than ten micrometers in size in a sensing volume of approximately three cubic centimeters. The instrument, called the holographic aerosol particle imager (HAPI), has the unique ability to image multiple particles freely entering its sensing volume from any direction via a single measurement. The construction of HAPI consists of 3D printed polymer structures that enable a sufficiently low size and weight that it may be flown on a commercial-grade UAV. Examples from field trials of HAPI show images of freshly emitted tree pollen and mineral dust.

Fully-automated and field-deployable blood leukocyte separation platform using multi-dimensional double spiral (MDDS) inertial microfluidics

A fully-automated and portable leukocyte separation platform was developed based on a new type of inertial microfluidic device, multi-dimensional double spiral (MDDS) device, as an alternative to centrifugation. By combining key innovations in inertial microfluidic device designs and check-valve-based recirculation processes, highly purified and concentrated WBCs (up to >99.99% RBC removal, ∼80% WBC recovery, >85% WBC purity, and ∼12-fold concentrated WBCs compared to the input sample) were achieved in less than 5 minutes, with high reliability and repeatability (coefficient of variation, CV < 5%). Using this, one can harvest up to 0.4 million of intact WBCs from 50 μL of human peripheral blood (50 μL), without any cell damage or phenotypic changes in a fully-automated operation. Alternatively, hand-powered operation is demonstrated with comparable separation efficiency and speed, which eliminates the need for electricity altogether for truly field-friendly sample preparation. The proposed platform is therefore highly deployable for various point-of-care applications, including bedside assessment of the host immune response and blood sample processing in resource-limited environments.

CytoPAN-Portable cellular analyses for rapid point-of-care cancer diagnosis

Rapid, automated, point-of-care cellular diagnosis of cancer remains difficult in remote settings due to lack of specialists and medical infrastructure. To address the need for same-day diagnosis, we developed an automated image cytometry system (CytoPAN) that allows rapid breast cancer diagnosis of scant cellular specimens obtained by fine needle aspiration (FNA) of palpable mass lesions. The system is devoid of moving parts for stable operations, harnesses optimized antibody kits for multiplexed analysis, and offers a user-friendly interface with automated analysis for rapid diagnoses. Through extensive optimization and validation using cell lines and mouse models, we established breast cancer diagnosis and receptor subtyping in 1 hour using as few as 50 harvested cells. In a prospective patient cohort study (n = 68), we showed that the diagnostic accuracy was 100% for cancer detection and the receptor subtyping accuracy was 96% for human epidermal growth factor receptor 2 and 93% for hormonal receptors (ER/PR), two key biomarkers associated with breast cancer. A combination of FNA and CytoPAN offers faster, less invasive cancer diagnoses than the current standard (core biopsy and histopathology). This approach should enable the ability to more rapidly diagnose breast cancer in global and remote settings.

Deep learning-based color holographic microscopy

We report a framework based on a generative adversarial network that performs high-fidelity color image reconstruction using a single hologram of a sample that is illuminated simultaneously by light at three different wavelengths. The trained network learns to eliminate missing-phase-related artifacts, and generates an accurate color transformation for the reconstructed image. Our framework is experimentally demonstrated using lung and prostate tissue sections that are labeled with different histological stains. This framework is envisaged to be applicable to point-of-care histopathology and presents a significant improvement in the throughput of coherent microscopy systems given that only a single hologram of the specimen is required for accurate color imaging.

Computational Image Analysis of Guided Acoustic Waves Enables Rheological Assessment of Sub-nanoliter Volumes

We present a method for the computational image analysis of high frequency guided sound waves based upon the measurement of optical interference fringes, produced at the air interface of a thin film of liquid. These acoustic actuations induce an affine deformation of the liquid, creating a lensing effect that can be readily observed using a simple imaging system. We exploit this effect to measure and analyze the spatiotemporal behavior of the thin liquid film as the acoustic wave interacts with it. We also show that, by investigating the dynamics of the relaxation processes of these deformations when actuation ceases, we are able to determine the liquid's viscosity using just a lens-free imaging system and a simple disposable biochip. Contrary to all other acoustic-based techniques in rheology, our measurements do not require monitoring of the wave parameters to obtain quantitative values for fluid viscosities, for sample volumes as low as 200 pL. We envisage that the proposed methods could enable high throughput, chip-based, reagent-free rheological studies within very small samples.

Accurate color imaging of pathology slides using holography and absorbance spectrum estimation of histochemical stains

Holographic microscopy presents challenges for color reproduction due to the usage of narrow-band illumination sources, which especially impacts the imaging of stained pathology slides for clinical diagnoses. Here, an accurate color holographic microscopy framework using absorbance spectrum estimation is presented. This method uses multispectral holographic images acquired and reconstructed at a small number (e.g., three to six) of wavelengths, estimates the absorbance spectrum of the sample, and projects it onto a color tristimulus. Using this method, the wavelength selection is optimized to holographically image 25 pathology slide samples with different tissue and stain combinations to significantly reduce color errors in the final reconstructed images. The results can be used as a practical guide for various imaging applications and, in particular, to correct color distortions in holographic imaging of pathology samples spanning different dyes and tissue types.

Taking connected mobile-health diagnostics of infectious diseases to the field

Mobile health, or 'mHealth', is the application of mobile devices, their components and related technologies to healthcare. It is already improving patients' access to treatment and advice. Now, in combination with internet-connected diagnostic devices, it offers novel ways to diagnose, track and control infectious diseases and to improve the efficiency of the health system. Here we examine the promise of these technologies and discuss the challenges in realizing their potential to increase patients' access to testing, aid in their treatment and improve the capability of public health authorities to monitor outbreaks, implement response strategies and assess the impact of interventions across the world.

Inorganic Complexes and Metal-Based Nanomaterials for Infectious Disease Diagnostics

Infectious diseases claim millions of lives each year. Robust and accurate diagnostics are essential tools for identifying those who are at risk and in need of treatment in low-resource settings. Inorganic complexes and metal-based nanomaterials continue to drive the development of diagnostic platforms and strategies that enable infectious disease detection in low-resource settings. In this review, we highlight works from the past 20 years in which inorganic chemistry and nanotechnology were implemented in each of the core components that make up a diagnostic test. First, we present how inorganic biomarkers and their properties are leveraged for infectious disease detection. In the following section, we detail metal-based technologies that have been employed for sample preparation and biomarker isolation from sample matrices. We then describe how inorganic- and nanomaterial-based probes have been utilized in point-of-care diagnostics for signal generation. The following section discusses instrumentation for signal readout in resource-limited settings. Next, we highlight the detection of nucleic acids at the point of care as an emerging application of inorganic chemistry. Lastly, we consider the challenges that remain for translation of the aforementioned diagnostic platforms to low-resource settings.

Mobile Technologies for the Discovery, Analysis, and Engineering of the Global Microbiome

The microbiome has been heralded as a gauge of and contributor to both human health and environmental conditions. Current challenges in probing, engineering, and harnessing the microbiome stem from its microscopic and nanoscopic nature, diversity and complexity of interactions among its members and hosts, as well as the spatiotemporal sampling and in situ measurement limitations induced by the restricted capabilities and norm of existing technologies, leaving some of the constituents of the microbiome unknown. To facilitate significant progress in the microbiome field, deeper understanding of the constituents' individual behavior, interactions with others, and biodiversity are needed. Also crucial is the generation of multimodal data from a variety of subjects and environments over time. Mobile imaging and sensing technologies, particularly through smartphone-based platforms, can potentially meet some of these needs in field-portable, cost-effective, and massively scalable manners by circumventing the need for bulky, expensive instrumentation. In this Perspective, we outline how mobile sensing and imaging technologies could lead the way to unprecedented insight into the microbiome, potentially shedding light on various microbiome-related mysteries of today, including the composition and function of human, animal, plant, and environmental microbiomes. Finally, we conclude with a look at the future, propose a computational microbiome engineering and optimization framework, and discuss its potential impact and applications.

Using machine-learning to optimize phase contrast in a low-cost cellphone microscope

Cellphones equipped with high-quality cameras and powerful CPUs as well as GPUs are widespread. This opens new prospects to use such existing computational and imaging resources to perform medical diagnosis in developing countries at a very low cost. Many relevant samples, like biological cells or waterborn parasites, are almost fully transparent. As they do not exhibit absorption, but alter the light’s phase only, they are almost invisible in brightfield microscopy. Expensive equipment and procedures for microscopic contrasting or sample staining often are not available. Dedicated illumination approaches, tailored to the sample under investigation help to boost the contrast. This is achieved by a programmable illumination source, which also allows to measure the phase gradient using the differential phase contrast (DPC) [1, 2] or even the quantitative phase using the derived qDPC approach [3]. By applying machine-learning techniques, such as a convolutional neural network (CNN), it is possible to learn a relationship between samples to be examined and its optimal light source shapes, in order to increase e.g. phase contrast, from a given dataset to enable real-time applications. For the experimental setup, we developed a 3D-printed smartphone microscope for less than 100 $ using off-the-shelf components only such as a low-cost video projector. The fully automated system assures true Koehler illumination with an LCD as the condenser aperture and a reversed smartphone lens as the microscope objective. We show that the effect of a varied light source shape, using the pre-trained CNN, does not only improve the phase contrast, but also the impression of an improvement in optical resolution without adding any special optics, as demonstrated by measurements.

Effect of counting chamber depth on the accuracy of lensless microscopy for the assessment of boar sperm motility

Sperm motility is one of the most significant parameters in the prediction of male fertility. Until now, both motility analysis using an optical microscope and computer-aided sperm analysis (CASA-Mot) entailed the use of counting chambers with a depth to 20 µm. Chamber depth significantly affects the intrinsic sperm movement, leading to an artificial motility pattern. For the first time, laser microscopy offers the possibility of avoiding this interference with sperm movement. The aims of the present study were to determine the different motility patterns observed in chambers with depths of 10, 20 and 100 µm using a new holographic approach and to compare the results obtained in the 20-µm chamber with those of the laser and optical CASA-Mot systems. The ISAS®3D-Track results showed that values for curvilinear velocity (VCL), straight line velocity, wobble and beat cross frequency were higher for the 100-µm chambers than for the 10- and 20-µm chambers. Only VCL showed a positive correlation between chambers. In addition, Bayesian analysis confirmed that the kinematic parameters observed with the 100-µm chamber were significantly different to those obtained using chambers with depths of 10 and 20 µm. When an optical analyser CASA-Mot system was used, all kinematic parameters, except VCL, were higher with ISAS®3D-Track, but were not relevant after Bayesian analysis. Finally, almost three different three-dimensional motility patterns were recognised. In conclusion, the use of the ISAS®3D-Track allows for the analysis of the natural three-dimensional pattern of sperm movement.

Lensless digital holographic microscopy and its applications in biomedicine and environmental monitoring

Optical compound microscope has been a major tool in biomedical imaging for centuries. Its performance relies on relatively complicated, bulky and expensive lenses and alignment mechanics. In contrast, the lensless microscope digitally reconstructs microscopic images of specimens without using any lenses, as a result of which it can be made much smaller, lighter and lower-cost. Furthermore, the limited space-bandwidth product of objective lenses in a conventional microscope can be significantly surpassed by a lensless microscope. Such lensless imaging designs have enabled high-resolution and high-throughput imaging of specimens using compact, portable and cost-effective devices to potentially address various point-of-care, global-health and telemedicine related challenges. In this review, we discuss the operation principles and the methods behind lensless digital holographic on-chip microscopy. We also go over various applications that are enabled by cost-effective and compact implementations of lensless microscopy, including some recent work on air quality monitoring, which utilized machine learning for high-throughput and accurate quantification of particulate matter in air. Finally, we conclude with a brief future outlook of this computational imaging technology.

3D imaging of optically cleared tissue using a simplified CLARITY method and on-chip microscopy

High-throughput sectioning and optical imaging of tissue samples using traditional immunohistochemical techniques can be costly and inaccessible in resource-limited areas. We demonstrate three-dimensional (3D) imaging and phenotyping in optically transparent tissue using lens-free holographic on-chip microscopy as a low-cost, simple, and high-throughput alternative to conventional approaches. The tissue sample is passively cleared using a simplified CLARITY method and stained using 3,3'-diaminobenzidine to target cells of interest, enabling bright-field optical imaging and 3D sectioning of thick samples. The lens-free computational microscope uses pixel super-resolution and multi-height phase recovery algorithms to digitally refocus throughout the cleared tissue and obtain a 3D stack of complex-valued images of the sample, containing both phase and amplitude information. We optimized the tissue-clearing and imaging system by finding the optimal illumination wavelength, tissue thickness, sample preparation parameters, and the number of heights of the lens-free image acquisition and implemented a sparsity-based denoising algorithm to maximize the imaging volume and minimize the amount of the acquired data while also preserving the contrast-to-noise ratio of the reconstructed images. As a proof of concept, we achieved 3D imaging of neurons in a 200-μm-thick cleared mouse brain tissue over a wide field of view of 20.5 mm2. The lens-free microscope also achieved more than an order-of-magnitude reduction in raw data compared to a conventional scanning optical microscope imaging the same sample volume. Being low cost, simple, high-throughput, and data-efficient, we believe that this CLARITY-enabled computational tissue imaging technique could find numerous applications in biomedical diagnosis and research in low-resource settings.

Computational sensing of herpes simplex virus using a cost-effective on-chip microscope

Caused by the herpes simplex virus (HSV), herpes is a viral infection that is one of the most widespread diseases worldwide. Here we present a computational sensing technique for specific detection of HSV using both viral immuno-specificity and the physical size range of the viruses. This label-free approach involves a compact and cost-effective holographic on-chip microscope and a surface-functionalized glass substrate prepared to specifically capture the target viruses. To enhance the optical signatures of individual viruses and increase their signal-to-noise ratio, self-assembled polyethylene glycol based nanolenses are rapidly formed around each virus particle captured on the substrate using a portable interface. Holographic shadows of specifically captured viruses that are surrounded by these self-assembled nanolenses are then reconstructed, and the phase image is used for automated quantification of the size of each particle within our large field-of-view, ~30 mm². The combination of viral immuno-specificity due to surface functionalization and the physical size measurements enabled by holographic imaging is used to sensitively detect and enumerate HSV particles using our compact and cost-effective platform. This computational sensing technique can find numerous uses in global health related applications in resource-limited environments.

Expansion Mini-Microscopy: An Enabling Alternative in Point-of-Care Diagnostics

Diagnostics play a significant role in health care. In the developing world and low-resource regions the utility for point-of-care (POC) diagnostics becomes even greater. This need has long been recognized, and diagnostic technology has seen tremendous progress with the development of portable instrumentation such as miniature imagers featuring low complexity and cost. However, such inexpensive devices have not been able to achieve a resolution sufficient for POC detection of pathogens at very small scales, such as single-cell parasites, bacteria, fungi, and viruses. To this end, expansion microscopy (ExM) is a recently developed technique that, by physically expanding preserved biological specimens through a chemical process, enables super-resolution imaging on conventional microscopes and improves imaging resolution of a given microscope without the need to modify the existing microscope hardware. Here we review recent advances in ExM and portable imagers, respectively, and discuss the rational combination of the two technologies, that we term expansion mini-microscopy (ExMM). In ExMM, the physical expansion of a biological sample followed by imaging on a mini-microscope achieves a resolution as high as that attainable by conventional high-end microscopes imaging non-expanded samples, at significant reduction in cost. We believe that this newly developed ExMM technique is likely to find widespread applications in POC diagnostics in resource-limited and remote regions by expanded-scale imaging of biological specimens that are otherwise not resolvable using low-cost imagers.

All-passive pixel super-resolution of time-stretch imaging

Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate - hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (≈2-5 GSa/s)-more than four times lower than the originally required readout rate (20 GSa/s) - is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time-stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing.

Compact, cost-effective and field-portable microscope prototype based on MISHELF microscopy

We report on a reduced cost, portable and compact prototype design of lensless holographic microscope with an illumination/detection scheme based on wavelength multiplexing, working with single hologram acquisition and using a fast convergence algorithm for image processing. All together, MISHELF (initials coming from Multi-Illumination Single-Holographic-Exposure Lensless Fresnel) microscopy allows the recording of three Fresnel domain diffraction patterns in a single camera snap-shot incoming from illuminating the sample with three coherent lights at once. Previous implementations have proposed an illumination/detection procedure based on a tuned (illumination wavelengths centered at the maximum sensitivity of the camera detection channels) configuration but here we report on a detuned (non-centered ones) scheme resulting in prototype miniaturization and cost reduction. Thus, MISHELF microscopy in combination with a novel and fast iterative algorithm allows high-resolution (μm range) phase-retrieved (twin image elimination) quantitative phase imaging of dynamic events (video rate recording speed). The performance of this microscope prototype is validated through experiments using both amplitude (USAF resolution test) and complex (live swine sperm cells and flowing microbeads) samples. The proposed method becomes in an alternative instrument improving some capabilities of existing lensless microscopes.

Smartphone based hand-held quantitative phase microscope using the transport of intensity equation method

In order to realize high contrast imaging with portable devices for potential mobile healthcare, we demonstrate a hand-held smartphone based quantitative phase microscope using the transport of intensity equation method. With a cost-effective illumination source and compact microscope system, multi-focal images of samples can be captured by the smartphone's camera via manual focusing. Phase retrieval is performed using a self-developed Android application, which calculates sample phases from multi-plane intensities via solving the Poisson equation. We test the portable microscope using a random phase plate with known phases, and to further demonstrate its performance, a red blood cell smear, a Pap smear and monocot root and broad bean epidermis sections are also successfully imaged. Considering its advantages as an accurate, high-contrast, cost-effective and field-portable device, the smartphone based hand-held quantitative phase microscope is a promising tool which can be adopted in the future in remote healthcare and medical diagnosis.

Achieving magnification smaller than 1 in lensless microscopy by illumination with a convergent wavefront

Lensless or lensfree microscopy is now available commercially. With these new microscopes, it is possible to record images in contact mode with a magnification of 1 or in holographic mode with a magnification larger than 1. In this Letter, we present an original setup that allows us to record the image of an object whose surface is larger than that of the image sensor without placing an optical component between the object and the image sensor.

Rapid, portable and cost-effective yeast cell viability and concentration analysis using lensfree on-chip microscopy and machine learning

Monitoring yeast cell viability and concentration is important in brewing, baking and biofuel production. However, existing methods of measuring viability and concentration are relatively bulky, tedious and expensive. Here we demonstrate a compact and cost-effective automatic yeast analysis platform (AYAP), which can rapidly measure cell concentration and viability. AYAP is based on digital in-line holography and on-chip microscopy and rapidly images a large field-of-view of 22.5 mm². This lens-free microscope weighs 70 g and utilizes a partially-coherent illumination source and an opto-electronic image sensor chip. A touch-screen user interface based on a tablet-PC is developed to reconstruct the holographic shadows captured by the image sensor chip and use a support vector machine (SVM) model to automatically classify live and dead cells in a yeast sample stained with methylene blue. In order to quantify its accuracy, we varied the viability and concentration of the cells and compared AYAP's performance with a fluorescence exclusion staining based gold-standard using regression analysis. The results agree very well with this gold-standard method and no significant difference was observed between the two methods within a concentration range of 1.4 × 10⁵ to 1.4 × 10⁶ cells per mL, providing a dynamic range suitable for various applications. This lensfree computational imaging technology that is coupled with machine learning algorithms would be useful for cost-effective and rapid quantification of cell viability and density even in field and resource-poor settings.

Time-lapse lens-free imaging of cell migration in diverse physical microenvironments

Time-lapse imaging of biological samples is important for understanding complex (patho)physiological processes. A growing number of point-of-care biomedical assays rely on real-time imaging of flowing or migrating cells. However, the cost and complexity of integrating experimental models simulating physiologically relevant microenvironments with bulky imaging systems that offer sufficient spatiotemporal resolution limit the use of time-lapse assays in research and clinical settings. This paper introduces a compact and affordable lens-free imaging (LFI) device based on the principle of coherent in-line, digital holography for time-lapse cell migration assays. The LFI device combines single-cell resolution (1.2 μm) with a large field of view (6.4 × 4.6 mm(2)), thus rendering it ideal for high-throughput applications and removing the need for expensive and bulky programmable motorized stages. The set-up is so compact that it can be housed in a standard cell culture incubator, thereby avoiding custom-built stage top incubators. LFI is thoroughly benchmarked against conventional live-cell phase contrast microscopy for random cell motility on two-dimensional (2D) surfaces and confined migration on 1D-microprinted lines and in microchannels using breast adenocarcinoma cells. The quality of the results obtained by the two imaging systems is comparable, and they reveal that cells migrate more efficiently upon increasing confinement. Interestingly, assays of confined migration more readily distinguish the migratory potential of metastatic MDA-MB-231 cells from non-metastatic MCF7 cells relative to traditional 2D migration assays. Altogether, this single-cell migration study establishes LFI as an elegant and useful tool for live-cell imaging.

Unconventional methods of imaging: computational microscopy and compact implementations

In the past two decades or so, there has been a renaissance of optical microscopy research and development. Much work has been done in an effort to improve the resolution and sensitivity of microscopes, while at the same time to introduce new imaging modalities, and make existing imaging systems more efficient and more accessible. In this review, we look at two particular aspects of this renaissance: computational imaging techniques and compact imaging platforms. In many cases, these aspects go hand-in-hand because the use of computational techniques can simplify the demands placed on optical hardware in obtaining a desired imaging performance. In the first main section, we cover lens-based computational imaging, in particular, light-field microscopy, structured illumination, synthetic aperture, Fourier ptychography, and compressive imaging. In the second main section, we review lensfree holographic on-chip imaging, including how images are reconstructed, phase recovery techniques, and integration with smart substrates for more advanced imaging tasks. In the third main section we describe how these and other microscopy modalities have been implemented in compact and field-portable devices, often based around smartphones. Finally, we conclude with some comments about opportunities and demand for better results, and where we believe the field is heading.

Wide-field imaging of birefringent synovial fluid crystals using lens-free polarized microscopy for gout diagnosis

Gout is a form of crystal arthropathy where monosodium urate (MSU) crystals deposit and elicit inflammation in a joint. Diagnosis of gout relies on identification of MSU crystals under a compensated polarized light microscope (CPLM) in synovial fluid aspirated from the patient's joint. The detection of MSU crystals by optical microscopy is enhanced by their birefringent properties. However, CPLM partially suffers from the high-cost and bulkiness of conventional lens-based microscopy, and its relatively small field-of-view (FOV) limits the efficiency and accuracy of gout diagnosis. Here we present a lens-free polarized microscope which adopts a novel differential and angle-mismatched polarizing optical design achieving wide-field and high-resolution holographic imaging of birefringent objects with a color contrast similar to that of a standard CPLM. The performance of this computational polarization microscope is validated by imaging MSU crystals made from a gout patient's tophus and steroid crystals used as negative control. This lens-free polarized microscope, with its wide FOV (>20 mm(2)), cost-effectiveness and field-portability, can significantly improve the efficiency and accuracy of gout diagnosis, reduce costs, and can be deployed even at the point-of-care and in resource-limited clinical settings.

Color calibration and fusion of lens-free and mobile-phone microscopy images for high-resolution and accurate color reproduction

Lens-free holographic microscopy can achieve wide-field imaging in a cost-effective and field-portable setup, making it a promising technique for point-of-care and telepathology applications. However, due to relatively narrow-band sources used in holographic microscopy, conventional colorization methods that use images reconstructed at discrete wavelengths, corresponding to e.g., red (R), green (G) and blue (B) channels, are subject to color artifacts. Furthermore, these existing RGB colorization methods do not match the chromatic perception of human vision. Here we present a high-color-fidelity and high-resolution imaging method, termed “digital color fusion microscopy” (DCFM), which fuses a holographic image acquired at a single wavelength with a color-calibrated image taken by a low-magnification lens-based microscope using a wavelet transform-based colorization method. We demonstrate accurate color reproduction of DCFM by imaging stained tissue sections. In particular we show that a lens-free holographic microscope in combination with a cost-effective mobile-phone-based microscope can generate color images of specimens, performing very close to a high numerical-aperture (NA) benchtop microscope that is corrected for color distortions and chromatic aberrations, also matching the chromatic response of human vision. This method can be useful for wide-field imaging needs in telepathology applications and in resource-limited settings, where whole-slide scanning microscopy systems are not available.

Design of New Procedures for Diagnosing Prevalent Diseases Using a Low-Cost Telemicroscopy System

BACKGROUND

Currently, the diagnosis of prevalent diseases such as malaria, tuberculosis, or diarrheal diseases in rural areas of developing countries requires the displacement of the patient from their community health post to their reference health center or to ship a sample. This delays diagnosis and the treatment of disease.

OBJECTIVE

Conduct research to develop a new method for rapid low-cost diagnosis of prevalent diseases in rural areas of developing countries (malaria, tuberculosis, parasitic infections, vaginal infections, and cervical cancer).

METHODS

The study was divided into three phases. The first related to the drafting and validating of new protocols for the preparation of samples that should be adapted to be carried out in areas without power and with little trained personnel. The second phase consisted of developing a telemicroscopy system looking for low cost, software compatibility, and technical quality. Finally, the third phase evaluated the system as a diagnostic tool using direct observation with a conventional microscope as the gold standard.

RESULTS

The validation of the new protocols showed that 100% of the vaginal swabs were processed correctly when using direct smear, while they were only 86.3% correct when using Gram stain; 68.3% of fecal samples were correctly processed using Kinyoun stain; 61.7% of blood samples when using thin film; and 83.8% when using thick film. Phase 2 permitted the development of a low-cost (<$250) and low-power (<15 W) telemicroscopy system that allows real-time consultation between health technicians and specialists. Finally, phase 3 proved that there was no difference between the diagnostics obtained by direct observation in a microscope and those ones obtained through the new telemicroscopy system.

CONCLUSIONS

This study has verified the effectiveness of the telemicroscopy system as a diagnostic tool, given the complete agreement between the diagnoses made with it and those made with the gold standard.

Lensless Imaging and Sensing

High-resolution optical microscopy has traditionally relied on high-magnification and high-numerical aperture objective lenses. In contrast, lensless microscopy can provide high-resolution images without the use of any focusing lenses, offering the advantages of a large field of view, high resolution, cost-effectiveness, portability, and depth-resolved three-dimensional (3D) imaging. Here we review various approaches to lensless imaging, as well as its applications in biosensing, diagnostics, and cytometry. These approaches include shadow imaging, fluorescence, holography, superresolution 3D imaging, iterative phase recovery, and color imaging. These approaches share a reliance on computational techniques, which are typically necessary to reconstruct meaningful images from the raw data captured by digital image sensors. When these approaches are combined with physical innovations in sample preparation and fabrication, lensless imaging can be used to image and sense cells, viruses, nanoparticles, and biomolecules. We conclude by discussing several ways in which lensless imaging and sensing might develop in the near future.

An ultra-compact multiplexed holographic microscope using a multiple-pinhole aperture

In this paper, we present a low-cost and ultra-compact holographic microscope with multiple imaging areas. Instead of a dual-pinhole aperture as presented in our previous work, a multi-pinhole aperture is employed to filter the light source and to generate a reference wave as well as multiple object waves. The reference wave and the object waves interfere at the digital sensor and form multiplexed off-axis holograms without any lenses, splitters or combiners. The optimal number of object waves is determined which does not only fit our system but also brings some inspiration for traditional multiplexed off-axis holography. Our new system is tested to be able to retrieve quantitative phase images along with the amplitude images of multiple imaging areas at the same time with a lateral resolution of ∼ 2.2µm and an accuracy of the optical path of tens of nanometers.

Development of inexpensive blood imaging systems: where are we now?

Clinical applications in the developing world, such as malaria and anemia diagnosis, demand a change in the medical paradigm of expensive care given in central locations by highly trained professionals. There has been a recent explosion in optical technologies entering the consumer market through the widespread adoption of smartphones and LEDs. This technology commoditization has enabled the development of small, portable optical imaging systems at an unprecedentedly low cost. Here, we review the state-of-the-field of the application of these systems for low-cost blood imaging with an emphasis on cellular imaging systems. In addition to some promising results addressing specific clinical issues, an overview of the technology landscape is provided. We also discuss several key issues that need to be addressed before these technologies can be commercialized.

Democratization of Nanoscale Imaging and Sensing Tools Using Photonics

Providing means for researchers and citizen scientists in the developing world to perform advanced measurements with nanoscale precision can help to accelerate the rate of discovery and invention as well as improve higher education and the training of the next generation of scientists and engineers worldwide. Here, we review some of the recent progress toward making optical nanoscale measurement tools more cost-effective, field-portable, and accessible to a significantly larger group of researchers and educators. We divide our review into two main sections: label-based nanoscale imaging and sensing tools, which primarily involve fluorescent approaches, and label-free nanoscale measurement tools, which include light scattering sensors, interferometric methods, photonic crystal sensors, and plasmonic sensors. For each of these areas, we have primarily focused on approaches that have either demonstrated operation outside of a traditional laboratory setting, including for example integration with mobile phones, or exhibited the potential for such operation in the near future.

Concentrating nanoparticles in environmental monitoring

There are significant challenges in assessing the toxicity of nanoparticles in the environment in which effective methods for detection are crucial. An inexpensive method that uses superhydrophobic well with an evaporating droplet followed by a simple squeeze flow is described here and found to provide practical high nanoparticle collection from samples for detection. The process could be hastened by placing a radiant heater close to the droplet if temperature rises in the sample can be tolerated.

Bayesian-based aberration correction and numerical diffraction for improved lensfree on-chip microscopy of biological specimens

Lensfree on-chip microscopy is an emerging imaging technique that can be used to visualize and study biological specimens without the need for imaging lens systems. Important issues that can limit the performance of lensfree on-chip microscopy include interferometric aberrations, acquisition noise, and image reconstruction artifacts. In this study, we introduce a Bayesian-based method for performing aberration correction and numerical diffraction that accounts for all three of these issues to improve the effective numerical aperture (NA) and signal-to-noise ratio (SNR) of the reconstructed microscopic image. The proposed method was experimentally validated using the USAF resolution target as well as real waterborne Anabaena flos-aquae samples, demonstrating improvements in NA by ∼25% over the standard method, and improvements in SNR of 2.8 and 8.2 dB in the reconstructed image when compared to the reconstructed images produced using the standard method and a maximum likelihood estimation method, respectively.

Digital diffraction analysis enables low-cost molecular diagnostics on a smartphone

The widespread distribution of smartphones, with their integrated sensors and communication capabilities, makes them an ideal platform for point-of-care (POC) diagnosis, especially in resource-limited settings. Molecular diagnostics, however, have been difficult to implement in smartphones. We herein report a diffraction-based approach that enables molecular and cellular diagnostics. The D3 (digital diffraction diagnosis) system uses microbeads to generate unique diffraction patterns which can be acquired by smartphones and processed by a remote server. We applied the D3 platform to screen for precancerous or cancerous cells in cervical specimens and to detect human papillomavirus (HPV) DNA. The D3 assay generated readouts within 45 min and showed excellent agreement with gold-standard pathology or HPV testing, respectively. This approach could have favorable global health applications where medical access is limited or when pathology bottlenecks challenge prompt diagnostic readouts.