Lensless light intensity model for quasi-spherical cell size measurement.

Quasi-spherical cell size measurement plays an important role in medical test. Traditional methods such as a microscope and a flow cytometer are 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 the lensless imaging system gives a good solution for obtaining the quasi-spherical cell size. The diffraction effects and the low resolution are the two main problems faced by the lensless imaging system. In this paper, a lensless light intensity model for the quasi-spherical cell size measurement is given. First, the diffraction characteristics of a quasi-spherical cell edge are given. Then, a diffraction model at an arc edge is constructed based on the Fresnel diffraction at a straight edge. Using the diffraction model at an arc edge, we explained the mechanism of the formation of the quasi-spherical cell diffraction fringes. Finally, the light intensity of the first bright ring of the quasi-spherical cell diffraction pattern is used to achieve quasi-spherical cell size measurement. The required equipment and the measurement methods are extremely simple, very suitable for point-of-care test. The experimental results show that the proposed model can realize the statistical measurement of the quasi-spherical cells and the classification of the quasi-spherical cells with a difference of 1 [Formula: see text].

Measurement of red blood cell size based on a lensless imaging system.

The variability in the size of red blood cells (RBCs) is an important additional diagnostic parameter for diseases, which has been established as a part of the complete blood count (CBC). The CBC can be performed using an automated flow cytometer, but it is too bulky and expensive for point-of-care testing. A miniaturized lensless imaging system is a competitive modality for a CBC, that is small and inexpensive. There are two challenges in developing a lensless imaging system for taking the CBC, which make the measurement of the RBC size very difficult: the diffraction effect and the low resolution. In this paper, the RBC radius measurement is replaced with a diffraction ring radius measurement. The diffraction ring radius is much larger than the RBC radius. This feature can improve the imaging resolution. Based on Fresnel diffraction, the relationship between the radius of RBCs and the diffraction fringes is analyzed. Finally, a complete measurement algorithm for determining the RBC size based on the lensless imaging system is given, which can be used to measure the variability in the size of RBCs. In our experiment, the maximum error is less than 6.74%.

Lensless Multispectral Camera Based on a Coded Aperture Array.

Multispectral imaging can be applied to water quality monitoring, medical diagnosis, and other applications, but the principle of multispectral imaging is different from the principle of hyper-spectral imaging. Multispectral imaging is generally achieved through filters, so multiple photos are required to obtain spectral information. Using multiple detectors to take pictures at the same time increases the complexity and cost of the system. This paper proposes a simple multispectral camera based on lensless imaging, which does not require multiple lenses. The core of the system is the multispectral coding aperture. The coding aperture is divided into different regions and each region transmits the light of one wavelength, such that the spectral information of the target can be coded. By solving the inverse problem of sparse constraints, the multispectral information of the target is inverted. Herein, we analyzed the characteristics of this multispectral camera and developed a principle prototype to obtain experimental results.

Development of a Point-of-Care Assay for HIV-1 Viral Load Using Higher Refractive Index Antibody-Coated Microbeads.

The detection of viruses using imaging techniques is challenging because of the weak scattering of light generated by the targets of sizes in the nanometer range. The system we have developed overcomes the light scattering problems by utilizing antibody-coated microbeads of higher index of refraction that can specifically bind with viruses and increase the acceptance angle. Using the new technology, we have developed a portable, cost-effective, and field-deployable platform for the rapid quantification of HIV-1 viral load for point-of-care (POC) settings. The system combines microfluidics with a wide field of view lensless imaging technology. Highly specific antibodies are functionalized to a glass slide inside a microchip to capture HIV-1 virions. The captured virions are then bound by antibody-conjugated microbeads, which have a higher refraction index. The microbeads-HIV-1 virions complexes generate diffraction patterns that are detected with a custom-built imaging setup and rapidly and accurately quantified by computational analysis. This platform technology enables fast nanoscale virus imaging and quantification from biological samples and thus can play a significant role in the detection and management of viral diseases.

Angle-Sensitive Detector Based on Silicon-On-Insulator Photodiode Stacked with Surface Plasmon Antenna.

We present a pixel-level angle sensitive detector composed of silicon-on-insulator (SOI) photodiode (PD) stacked with a gold surface plasmon (SP) antenna to affect the direction of the incoming light. The surface plasmons are excited in the grating-type SP antenna and enhance the diffraction efficiency of the grating. The diffracted light is coupled strongly with the propagation light in the SOI waveguide when the phase matching condition is satisfied. The phase matching takes place at a specific angle of light incidence, and the discrimination of the light based on the incident angle is achieved. As spatial patterns in the polar coordinate of the elevation-azimuth angles (θ, ϕ) of the incident light, we present the phase matching condition theoretically, the absorption efficiency in the SOI by simulation, and also the quantum efficiency of the SOI PD experimentally for different SP antennas of one-dimensional (1D) line-and-space (L/S) and two-dimensional (2D) hole array gratings under various polarization angles. 1D grating offers a polarization sensitive angle detection and 2D grating exhibits angle detection in two orthogonal directions, enabling a polarization independent angle sensitivity. A good agreement among the theory, simulation, and experiment are attained. The proposed device features relatively high quantum efficiency as an angle-sensitive pixel (ASP) and gives wider opportunities in applications such as three-dimensional (3D) imaging, depth-of-field extension, and lensless imaging.

Speckle-Correlation Scattering Matrix Approaches for Imaging and Sensing through Turbidity.

The development of optical and computational techniques has enabled imaging without the need for traditional optical imaging systems. Modern lensless imaging techniques overcome several restrictions imposed by lenses, while preserving or even surpassing the capability of lens-based imaging. However, existing lensless methods often rely on a priori information about objects or imaging conditions. Thus, they are not ideal for general imaging purposes. The recent development of the speckle-correlation scattering matrix (SSM) techniques facilitates new opportunities for lensless imaging and sensing. In this review, we present the fundamentals of SSM methods and highlight recent implementations for holographic imaging, microscopy, optical mode demultiplexing, and quantification of the degree of the coherence of light. We conclude with a discussion of the potential of SSM and future research directions.

Recovery of spatial frequencies in coherent diffraction imaging in the presence of a central obscuration.

Coherent diffraction imaging (CDI) and its scanning version, ptychography, are lensless imaging approaches used to iteratively retrieve a sample's complex scattering amplitude from its measured diffraction patterns. These imaging methods are most useful in extreme ultraviolet (EUV) and X-ray regions of the electromagnetic spectrum, where efficient imaging optics are difficult to manufacture. CDI relies on high signal-to-noise ratio diffraction data to recover the phase, but increasing the flux can cause saturation effects on the detector. A conventional solution to this problem is to place a beam stop in front of the detector. The pixel masking method is a common solution to the problem of missing frequencies due to a beam stop. This paper describes the information redundancy in the recorded data set and expands on how the reconstruction algorithm can exploit this redundancy to estimate the missing frequencies. Thereafter, we modify the size of the beam stop in experimental and simulation data to assess the impact of the missing frequencies, investigate the extent to which the lost portion of the diffraction spectrum can be recovered, and quantify the effect of the beam stop on the image quality. The experimental findings and simulations conducted for EUV imaging demonstrate that when using a beam stop, the numerical aperture of the condenser is a crucial factor in the recovery of lost frequencies. Our thorough investigation of the reconstructed images provides information on the overall quality of reconstruction and highlights the vulnerable frequencies if the beam stop size is larger than the extent of the illumination NA. The outcome of this study can be applied to other sources of frequency loss, and it will contribute to the improvement of experiments and reconstruction algorithms in CDI.

Photonic neural probe enabled microendoscopes for light-sheet light-field computational fluorescence brain imaging.

Significance: Light-sheet fluorescence microscopy is widely used for high-speed, high-contrast, volumetric imaging. Application of this technique to in vivo brain imaging in non-transparent organisms has been limited by the geometric constraints of conventional light-sheet microscopes, which require orthogonal fluorescence excitation and collection objectives. We have recently demonstrated implantable photonic neural probes that emit addressable light sheets at depth in brain tissue, miniaturizing the excitation optics. Here, we propose a microendoscope consisting of a light-sheet neural probe packaged together with miniaturized fluorescence collection optics based on an image fiber bundle for lensless, light-field, computational fluorescence imaging. Aim: Foundry-fabricated, silicon-based, light-sheet neural probes can be packaged together with commercially available image fiber bundles to form microendoscopes for light-sheet light-field fluorescence imaging at depth in brain tissue. Approach: Prototype microendoscopes were developed using light-sheet neural probes with five addressable sheets and image fiber bundles. Fluorescence imaging with the microendoscopes was tested with fluorescent beads suspended in agarose and fixed mouse brain tissue. Results: Volumetric light-sheet light-field fluorescence imaging was demonstrated using the microendoscopes. Increased imaging depth and enhanced reconstruction accuracy were observed relative to epi-illumination light-field imaging using only a fiber bundle. Conclusions: Our work offers a solution toward volumetric fluorescence imaging of brain tissue with a compact size and high contrast. The proof-of-concept demonstrations herein illustrate the operating principles and methods of the imaging approach, providing a foundation for future investigations of photonic neural probe enabled microendoscopes for deep-brain fluorescence imaging in vivo.

A Multimodal Sensing CMOS Imager Based on Dual-Focus Imaging.

Advanced machine intelligence is empowered not only by the ever-increasing computational capability for information processing but also by sensors for collecting multimodal information from complex environments. However, simply assembling different sensors can result in bulky systems and complex data processing. Herein, it is shown that a complementary metal-oxide-semiconductor (CMOS) imager can be transformed into a compact multimodal sensing platform through dual-focus imaging. By combining lens-based and lensless imaging, visual information, chemicals, temperature, and humidity can be detected with the same chip and output as a single image. As a proof of concept, the sensor is equipped on a micro-vehicle, and multimodal environmental sensing and mapping is demonstrated. A multimodal endoscope is also developed, and simultaneous imaging and chemical profiling along a porcine digestive tract is achieved. The multimodal CMOS imager is compact, versatile, and extensible and can be widely applied in microrobots, in vivo medical apparatuses, and other microdevices.

Robust and compact digital Lensless Holographic microscope for Label-Free blood smear imaging.

The lack of equipped healthcare infrastructure in isolated hard-to-reach zones exposes their population to a higher risk of complications in common diseases. With a timely diagnosis setting a life-altering difference, worldwide efforts have been conducted for the development of point-of-care testing (PoCT) with cost-effective devices. Among the most common interests in PoCT is the analysis of blood smear samples, as they can help to detect, diagnose, and monitor a wide range of diseases and disorders. With microscopy being the traditional tool for these analyses, a significative advance has been the development of cost-effective digital holographic microscopy systems, driven in part by its label-free imaging capabilities that waive the need for any sample preprocessing. Here, a robust and portable digital lensless holographic microscope, functionalized for the analysis of non-preprocessed blood smear samples in PoCT environments, is presented, and its viability is tested in the observation of red blood cells. The device uses an optical fiber with a cone-shaped tip instead of a pinhole, which ensures the sturdiness of the system and eliminates the need for challenging alignment. While the distances of the microscope can be tuned before fabrication, the herein-reported operational parameters are functionalized for the specific analysis of blood samples.

Pixel Super-Resolution Phase Retrieval for Lensless On-Chip Microscopy via Accelerated Wirtinger Flow.

Empowered by pixel super-resolution (PSR) and phase retrieval techniques, lensless on-chip microscopy opens up new possibilities for high-throughput biomedical imaging. However, the current PSR phase retrieval approaches are time consuming in terms of both the measurement and reconstruction procedures. In this work, we present a novel computational framework for PSR phase retrieval to address these concerns. Specifically, a sparsity-promoting regularizer is introduced to enhance the well posedness of the nonconvex problem under limited measurements, and Nesterov's momentum is used to accelerate the iterations. The resulting algorithm, termed accelerated Wirtinger flow (AWF), achieves at least an order of magnitude faster rate of convergence and allows a twofold reduction in the measurement number while maintaining competitive reconstruction quality. Furthermore, we provide general guidance for step size selection based on theoretical analyses, facilitating simple implementation without the need for complicated parameter tuning. The proposed AWF algorithm is compatible with most of the existing lensless on-chip microscopes and could help achieve label-free rapid whole slide imaging of dynamic biological activities at subpixel resolution.

GEOMScope: Large Field-of-view 3D Lensless Microscopy with Low Computational Complexity.

Imaging systems with miniaturized device footprint, real-time processing speed and high resolution three-dimensional (3D) visualization are critical to broad biomedical applications such as endoscopy. Most of existing imaging systems rely on bulky lenses and mechanically refocusing to perform 3D imaging. Here, we demonstrate GEOMScope, a lensless single-shot 3D microscope that forms image through a single layer of thin microlens array and reconstructs objects through an innovative algorithm combining geometrical-optics-based pixel back projection and background suppressions. We verify the effectiveness of GEOMScope on resolution target, fluorescent particles and volumetric objects. Comparing to other widefield lensless imaging devices, we significantly reduce the required computational resource and increase the reconstruction speed by orders of magnitude. This enables us to image and recover large volume 3D object in high resolution with near real-time processing speed. Such a low computational complexity is attributed to the joint design of imaging optics and reconstruction algorithms, and a joint application of geometrical optics and machine learning in the 3D reconstruction. More broadly, the excellent performance of GEOMScope in imaging resolution, volume, and reconstruction speed implicates that geometrical optics could greatly benefit and play an important role in computational imaging.

Detection of Bacterial and Viral Pathogens Using Photonic Point-of-Care Devices.

Infectious diseases caused by bacteria and viruses are highly contagious and can easily be transmitted via air, water, body fluids, etc. Throughout human civilization, there have been several pandemic outbreaks, such as the Plague, Spanish Flu, Swine-Flu, and, recently, COVID-19, amongst many others. Early diagnosis not only increases the chance of quick recovery but also helps prevent the spread of infections. Conventional diagnostic techniques can provide reliable results but have several drawbacks, including costly devices, lengthy wait time, and requirement of trained professionals to operate the devices, making them inaccessible in low-resource settings. Thus, a significant effort has been directed towards point-of-care (POC) devices that enable rapid diagnosis of bacterial and viral infections. A majority of the POC devices are based on plasmonics and/or microfluidics-based platforms integrated with mobile readers and imaging systems. These techniques have been shown to provide rapid, sensitive detection of pathogens. The advantages of POC devices include low-cost, rapid results, and portability, which enables on-site testing anywhere across the globe. Here we aim to review the recent advances in novel POC technologies in detecting bacteria and viruses that led to a breakthrough in the modern healthcare industry.

Lensless Three-Dimensional Quantitative Phase Imaging Using Phase Retrieval Algorithm.

Quantitative phase imaging (QPI) techniques are widely used for the label-free examining of transparent biological samples. QPI techniques can be broadly classified into interference-based and interferenceless methods. The interferometric methods which record the complex amplitude are usually bulky with many optical components and use coherent illumination. The interferenceless approaches which need only the intensity distribution and works using phase retrieval algorithms have gained attention as they require lesser resources, cost, space and can work with incoherent illumination. With rapid developments in computational optical techniques and deep learning, QPI has reached new levels of applications. In this tutorial, we discuss one of the basic optical configurations of a lensless QPI technique based on the phase-retrieval algorithm. Simulative studies on QPI of thin, thick, and greyscale phase objects with assistive pseudo-codes and computational codes in Octave is provided. Binary phase samples with positive and negative resist profiles were fabricated using lithography, and a single plane and two plane phase objects were constructed. Light diffracted from a point object is modulated by phase samples and the corresponding intensity patterns are recorded. The phase retrieval approach is applied for 2D and 3D phase reconstructions. Commented codes in Octave for image acquisition and automation using a web camera in an open source operating system are provided.

Exploiting scattering media for exploring 3D objects.

Scattering media, such as diffused glass and biological tissue, are usually treated as obstacles in imaging. To cope with the random phase introduced by a turbid medium, most existing imaging techniques recourse to either phase compensation by optical means or phase recovery using iterative algorithms, and their applications are often limited to two-dimensional imaging. In contrast, we utilize the scattering medium as an unconventional imaging lens and exploit its lens-like properties for lensless three-dimensional (3D) imaging with diffraction-limited resolution. Our spatially incoherent lensless imaging technique is simple and capable of variable focusing with adjustable depths of focus that enables depth sensing of 3D objects that are concealed by the diffusing medium. Wide-field imaging with diffraction-limited resolution is verified experimentally by a single-shot recording of the 1951 USAF resolution test chart, and 3D imaging and depth sensing are demonstrated by shifting focus over axially separated objects.

Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution.

In this paper, an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame processing. The samples are illuminated by a nearly coherent illumination system, where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging sensor. To increase the resolution, a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene, with small planar displacements. Displacements are resolved by a hybrid approach: (i) alignment of the LR images by a fast feature-based registration method, and (ii) fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum solution. Numerical method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed sample. The presented approach was evaluated with various biological samples including sperm and platelets, whose dimensions are in the order of a few microns. The obtained results demonstrate a spatial resolution of 1.55 µm on a field-of-view of ≈30 mm2.

Oversampling smoothness: an effective algorithm for phase retrieval of noisy diffraction intensities.

Coherent diffraction imaging (CDI) is high-resolution lensless microscopy that has been applied to image a wide range of specimens using synchrotron radiation, X-ray free-electron lasers, high harmonic generation, soft X-ray lasers and electrons. Despite recent rapid advances, it remains a challenge to reconstruct fine features in weakly scattering objects such as biological specimens from noisy data. Here an effective iterative algorithm, termed oversampling smoothness (OSS), for phase retrieval of noisy diffraction intensities is presented. OSS exploits the correlation information among the pixels or voxels in the region outside of a support in real space. By properly applying spatial frequency filters to the pixels or voxels outside the support at different stages of the iterative process (i.e. a smoothness constraint), OSS finds a balance between the hybrid input-output (HIO) and error reduction (ER) algorithms to search for a global minimum in solution space, while reducing the oscillations in the reconstruction. Both numerical simulations with Poisson noise and experimental data from a biological cell indicate that OSS consistently outperforms the HIO, ER-HIO and noise robust (NR)-HIO algorithms at all noise levels in terms of accuracy and consistency of the reconstructions. It is expected that OSS will find application in the rapidly growing CDI field, as well as other disciplines where phase retrieval from noisy Fourier magnitudes is needed. The MATLAB (The MathWorks Inc., Natick, MA, USA) source code of the OSS algorithm is freely available from http://www.physics.ucla.edu/research/imaging.

Chip-scale microscopy imaging.

Chip-scale microscopy imaging platforms are pivotal for improving the efficiency of modern biomedical and bioscience experiments. Their integration with other lab-on-a-chip techniques would allow rapid, reliable and high-throughput sample analysis for applications in diverse disciplines. In typical chip-scale microscopy imaging platforms, the light path can be generalized to the following steps: photons leave the light source, interact with the sample and finally are detected by the sensor. Based on the light path of these platforms, the current review aims to provide some insights on design strategies for chip-scale microscopy. Specifically, we analyze current chip-scale microscopy approaches from three aspects: illumination design, sample manipulation and substrate/imager modification. We also discuss some opportunities for future developments of chip-scale microscopy, such as time multiplexed structured illumination and hydrodynamic focusing for high throughput sample manipulation.