Insertable Glucose Sensor Using a Compact and Cost-Effective Phosphorescence Lifetime Imager and Machine Learning.

Optical continuous glucose monitoring (CGM) systems are emerging for personalized glucose management owing to their lower cost and prolonged durability compared to conventional electrochemical CGMs. Here, we report a computational CGM system, which integrates a biocompatible phosphorescence-based insertable biosensor and a custom-designed phosphorescence lifetime imager (PLI). This compact and cost-effective PLI is designed to capture phosphorescence lifetime images of an insertable sensor through the skin, where the lifetime of the emitted phosphorescence signal is modulated by the local concentration of glucose.

Sub-picomolar lateral flow antigen detection with two-wavelength imaging of composite nanoparticles.

Lateral flow tests, commonly based on metal plasmonic nanoparticles, are rapid, robust, and low-cost. However, improvements in analytical sensitivity are required to allow detection of low-abundance biomarkers, for example detection of low antigen concentrations for earlier or asymptomatic diagnosis of infectious diseases. Efforts to improve sensitivity often require changes to the assay.

Label-free detection of cysts using a deep learning-enabled portable imaging flow cytometer.

We report a field-portable and cost-effective imaging flow cytometer that uses deep learning and holography to accurately detect Giardia lamblia cysts in water samples at a volumetric throughput of 100 mL h-1. This flow cytometer uses lens free color holographic imaging to capture and reconstruct phase and intensity images of microscopic objects in a continuously flowing sample, and automatically identifies Giardia lamblia cysts in real-time without the use of any labels or fluorophores. The imaging flow cytometer is housed in an environmentally-sealed enclosure with dimensions of 19 cm × 19 cm × 16 cm and weighs 1.

Smartphone-based turbidity reader.

Water quality is undergoing significant deterioration due to bacteria, pollutants and other harmful particles, damaging aquatic life and lowering the quality of drinking water. It is, therefore, important to be able to rapidly and accurately measure water quality in a cost-effective manner using e.g.

Air quality monitoring using mobile microscopy and machine learning.

Rapid, accurate and high-throughput sizing and quantification of particulate matter (PM) in air is crucial for monitoring and improving air quality. In fact, particles in air with a diameter of ≤2.5 μm have been classified as carcinogenic by the World Health Organization.

Computational On-Chip Imaging of Nanoparticles and Biomolecules using Ultraviolet Light.

Significant progress in characterization of nanoparticles and biomolecules was enabled by the development of advanced imaging equipment with extreme spatial-resolution and sensitivity. To perform some of these analyses outside of well-resourced laboratories, it is necessary to create robust and cost-effective alternatives to existing high-end laboratory-bound imaging and sensing equipment. Towards this aim, we have designed a holographic on-chip microscope operating at an ultraviolet illumination wavelength (UV) of 266 nm.

Quantitative Fluorescence Sensing Through Highly Autofluorescent, Scattering, and Absorbing Media Using Mobile Microscopy.

Compact and cost-effective systems for in vivo fluorescence and near-infrared imaging in combination with activatable reporters embedded inside the skin to sample interstitial fluid or blood can enable a variety of biomedical applications. However, the strong autofluorescence of human skin creates an obstacle for fluorescence-based sensing. Here we introduce a method for quantitative fluorescence sensing through highly autofluorescent, scattering, and absorbing media.

Pixel super-resolution using wavelength scanning.

Undersampling and pixelation affect a number of imaging systems, limiting the resolution of the acquired images, which becomes particularly significant for wide-field microscopy applications. Various super-resolution techniques have been implemented to mitigate this resolution loss by utilizing sub-pixel displacements in the imaging system, achieved, for example, by shifting the illumination source, the sensor array and/or the sample, followed by digital synthesis of a smaller effective pixel by merging these sub-pixel-shifted low-resolution images. Herein, we introduce a new pixel super-resolution method that is based on wavelength scanning and demonstrate that as an alternative to physical shifting/displacements, wavelength diversity can be used to boost the resolution of a wide-field imaging system and significantly increase its space-bandwidth product.

Propagation phasor approach for holographic image reconstruction.

To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications.

Enhanced light collection in fluorescence microscopy using self-assembled micro-reflectors.

In fluorescence microscopy, the signal-to-noise ratio (SNR) of the optical system is directly linked to the numerical aperture (NA) of the microscope objective, which creates detection challenges for low-NA, wide-field and high-throughput imaging systems. Here we demonstrate a method to increase the light collection efficiency from micron-scale fluorescent objects using self-assembled vapor-condensed polyethylene glycol droplets, which act as micro-reflectors for fluorescent light. Around each fluorescent particle, a liquid meniscus is formed that increases the excitation efficiency and redirects part of the laterally-emitted fluorescent light towards the detector due to internal reflections at the liquid-air interface of the meniscus.

Rapid imaging, detection and quantification of Giardia lamblia cysts using mobile-phone based fluorescent microscopy and machine learning.

Rapid and sensitive detection of waterborne pathogens in drinkable and recreational water sources is crucial for treating and preventing the spread of water related diseases, especially in resource-limited settings. Here we present a field-portable and cost-effective platform for detection and quantification of Giardia lamblia cysts, one of the most common waterborne parasites, which has a thick cell wall that makes it resistant to most water disinfection techniques including chlorination. The platform consists of a smartphone coupled with an opto-mechanical attachment weighing ~205 g, which utilizes a hand-held fluorescence microscope design aligned with the camera unit of the smartphone to image custom-designed disposable water sample cassettes.

Biomedical imaging and sensing using flatbed scanners.

In this Review, we provide an overview of flatbed scanner based biomedical imaging and sensing techniques. The extremely large imaging field-of-view (e.g.

Special multicolor illumination and numerical tilt correction in volumetric digital holographic microscopy.

We introduce a color imaging method in our digital holographic microscope system (DHM). This DHM can create color images of freely floating, or moving objects inside a large volume by simultaneously capturing three holograms using three different illumination wavelengths. In this DHM a new light source assembly is applied, where we use single mode fibers according to the corresponding wavelengths that are tightly and randomly arranged into a small array in a single FC/PC connector.

Giga-pixel fluorescent imaging over an ultra-large field-of-view using a flatbed scanner.

We demonstrate a new fluorescent imaging technique that can screen for fluorescent micro-objects over an ultra-wide field-of-view (FOV) of ~532 cm(2), i.e., 19 cm × 28 cm, reaching a space-bandwidth product of more than 2 billion.

Fluorescent imaging of single nanoparticles and viruses on a smart phone.

Optical imaging of nanoscale objects, whether it is based on scattering or fluorescence, is a challenging task due to reduced detection signal-to-noise ratio and contrast at subwavelength dimensions. Here, we report a field-portable fluorescence microscopy platform installed on a smart phone for imaging of individual nanoparticles as well as viruses using a lightweight and compact opto-mechanical attachment to the existing camera module of the cell phone. This hand-held fluorescent imaging device utilizes (i) a compact 450 nm laser diode that creates oblique excitation on the sample plane with an incidence angle of ~75°, (ii) a long-pass thin-film interference filter to reject the scattered excitation light, (iii) an external lens creating 2× optical magnification, and (iv) a translation stage for focus adjustment.

On-chip biomedical imaging.

Lab-on-a-chip systems have been rapidly emerging to pave the way toward ultra-compact, efficient, mass producible and cost-effective biomedical research and diagnostic tools. Although such microfluidic and microelectromechanical systems have achieved high levels of integration, and are capable of performing various important tasks on the same chip, such as cell culturing, sorting and staining, they still rely on conventional microscopes for their imaging needs. Recently, several alternative on-chip optical imaging techniques have been introduced, which have the potential to substitute conventional microscopes for various lab-on-a-chip applications.

In-line hologram segmentation for volumetric samples.

We propose a fast, noniterative method to segment an in-line hologram of a volumetric sample into in-line subholograms according to its constituent objects. In contrast to the phase retrieval or twin image elimination algorithms, we do not aim or require to reconstruct the complex wave field of all the objects, which would be a more complex task, but only provide a good estimate about the contribution of the particular objects to the original hologram quickly. The introduced hologram segmentation algorithm exploits the special inner structure of the in-line holograms and applies only the estimated supports and reconstruction distances of the corresponding objects as parameters.

Imaging without lenses: achievements and remaining challenges of wide-field on-chip microscopy.

We discuss unique features of lens-free computational imaging tools and report some of their emerging results for wide-field on-chip microscopy, such as the achievement of a numerical aperture (NA) of ∼0.8-0.9 across a field of view (FOV) of more than 20 mm(2) or an NA of ∼0.

Hologram positioning servo for phase-encoded holographic data storage systems.

We propose a method using phase encryption and hologram multiplexing to encode positional information into the hologram, which can be used during readout to find the correct position of the reference beam. We also include a method to align the position of the phase code in the reference beam during readout, with which we achieved approximately 1/100 hologram size (4.4 microm) precision electronically, without the need of a precise mechanical hologram positioning device.

Hybrid multinary modulation using a phase modulating spatial light modulator and a low-pass spatial filter.

We propose a method for performing binary intensity and continuous phase modulation of beams with a spatial light modulator (SLM) and a low-pass spatial filtering 4-f system. With our method it is possible to avoid the use of phase masks in holographic data storage systems or to enhance the phase encoding of the SLM by making it capable of binary amplitude modulation. The data storage capabilities and the limitations of the method are studied.