Lensfree On-chip Microscopy Research Articles

Lens-free on-chip 3D microscopy based on wavelength-scanning Fourier ptychographic diffraction tomography

Lens-free on-chip microscopy is a powerful and promising high-throughput computational microscopy technique due to its unique advantage of creating high-resolution images across the full field-of-view (FOV) of the imaging sensor. Nevertheless, most current lens-free microscopy methods have been designed for imaging only two-dimensional thin samples. Lens-free on-chip tomography (LFOCT) with a uniform resolution across the entire FOV and at a subpixel level remains a critical challenge. In this paper, we demonstrated a new LFOCT technique and associated imaging platform based on wavelength scanning Fourier ptychographic diffraction tomography (wsFPDT). Instead of using angularly-variable illuminations, in wsFPDT, the sample is illuminated by on-axis wavelength-variable illuminations, ranging from 430 to 1200 nm. The corresponding under-sampled diffraction patterns are recorded, and then an iterative ptychographic reconstruction procedure is applied to fill the spectrum of the three-dimensional (3D) scattering potential to recover the sample’s 3D refractive index (RI) distribution. The wavelength-scanning scheme not only eliminates the need for mechanical motion during image acquisition and precise registration of the raw images but secures a quasi-uniform, pixel-super-resolved imaging resolution across the entire imaging FOV. With wsFPDT, we demonstrate the high-throughput, billion-voxel 3D tomographic imaging results with a half-pitch lateral resolution of 775 nm and an axial resolution of 5.43 μm across a large FOV of 29.85 mm2 and an imaging depth of >200 μm. The effectiveness of the proposed method was demonstrated by imaging various types of samples, including micro-polystyrene beads, diatoms, and mouse mononuclear macrophage cells. The unique capability to reveal quantitative morphological properties, such as area, volume, and sphericity index of single cell over large cell populations makes wsFPDT a powerful quantitative and label-free tool for high-throughput biological applications.

Pixel-super-resolved lens-free quantitative phase microscopy with partially coherent illumination

Lens-free on-chip microscopy (LFOCM) has been widely utilized in digital pathology, drug screening, point-of-care testing (POCT), and quantitative phase imaging (QPI) due to its high throughput imaging capability and compactness. Initially, coherent laser sources were used in LFOCM to generate interference fringes to reconstruct the intensity and phase information of an object. The use of partially coherent light-emitting diodes (LEDs) in LFOCM offers a more portable and cost-effective alternative to conventional coherent illumination sources. However, the coherence-gating effect from a relatively low degree of coherence may cause a blur of high-frequency information in holograms, leading to an inaccurate object recovery. Thus, we present a pixel-super-resolved lens-free quantitative phase microscopy (PSR-LFQPM) with partially coherent illumination, which not only compensates for the impact of low coherence without increasing the volume of the system but also suppresses the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel size (0.9 μm). Based on the partially coherent imaging model, we integrate the spatial coherence transfer function (SCTF) obtained from the pre-calibrated LED source distribution during the iteration process to obtain an accurate high-resolution recovery. Applying PSR-LFQPM to image living HeLa cells in vitro, we achieve real-time dynamic high-throughput QPI performance (half-pitch resolution of 780 nm with a 1.41-fold improvement compared to results without considering the effect of coherence) across a wide FOV (19.53 mm2). The proposed method provides a compact, low-cost, and high-throughput lens-free on-chip microscopy system for biomedical and POCT applications.

Wavelength-scanning pixel-super-resolved lens-free on-chip quantitative phase microscopy with a color image sensor

We report a wavelength-scanning-based lens-free on-chip microscope using a color CMOS sensor and a matching modified phase retrieval algorithm for pixel super-resolution. Compared to traditional monochrome industrial cameras, color sensors favored by the consumer electronics industry have smaller pixel sizes, higher performance, and lower costs. However, the color filtering array (CFA) introduces inherent modulation to the holograms acquired under quasi-monochromatic illumination, which complicates the data processing in lens-free on-chip microscopy. Without physically removing the CFA positioned on the sensor chip, we demonstrate quantitative phase imaging (QPI) with a lateral half-width resolution of 615 nm over a wide field-of-view of 51.88 mm2 by exploiting the green-channel data from Bayer-masked holograms. The resulting spatial bandwidth product is 137.2 megapixels, over 10 times that of a conventional optical microscope. The rationale for using only green-channel data is that the information from each sampling point is not lost during propagation but rather distributed to all pixels in the image. Therefore, the missing data in other channels can be recovered by exploiting the sufficient differences among the raw images captured at different wavelengths. Compared to the scheme with monochrome sensors, this method requires the acquisition of several more images to guarantee the convergence of the algorithm. Experimental results show that we can achieve high-quality QPI performance, thus demonstrating the applicability of cost-effective color sensors in the field of lens-free holographic microscopy.

High-resolution portable lens-free on-chip microscopy with RGB LED via pinhole array

High-resolution portable lens-free on-chip microscopy with RGB LED via pinhole array

Single-shot lensfree on-chip quantitative phase microscopy with partially coherent LED illumination.

We propose a single-shot lens-free phase retrieval (SSLFPR) method in a lens-free on-chip microscopy (LFOCM) system based on a partially coherent light emitting diode (LED) illumination. The finite bandwidth (∼23.95nm) of LED illumination is divided into a series of quasi-monochromatic components according to the LED spectrum measured by a spectrometer. When the "virtual wavelength scanning" phase retrieval method is combined with the dynamic phase support constraint, the resolution loss caused by the spatiotemporal partial coherence of the light source can be effectively compensated. At the same time, the nonlinearity characteristics of the support constraint help to further improve the imaging resolution, accelerate the convergence of the iteration process, and greatly eliminate the artifacts. Based on the proposed SSLFPR method, we demonstrate that the phase information of samples (including phase resolution target and polystyrene microspheres) illuminated by a LED can be accurately retrieved based on one single diffraction pattern. The SSLFPR method has a half-width resolution of 977nm across a large field-of-view (FOV) of 19.53mm2, which is 1.41 × the resolution of the conventional approach. We also imaged living Henrietta Lacks (HeLa) cells cultured in vitro, further demonstrating the real-time single-shot quantitative phase imaging (QPI) capability of SSLFPR for dynamic samples. Given its simple hardware, high throughput, and single-frame high-resolution QPI capability, SSLFPR is expected to be adopted in a wide range of biological and medical applications.

Lensfree on-chip microscopy based on single-plane phase retrieval.

We propose a novel single-plane phase retrieval method to realize high-quality sample reconstruction for lensfree on-chip microscopy. In our method, complex wavefield reconstruction is modeled as a quadratic minimization problem, where total variation and joint denoising regularization are designed to keep a balance of artifact removal and resolution enhancement. In experiment, we built a 3D-printed field-portable platform to validate the imaging performance of our method, where resolution chart, dynamic target, transparent cell, polystyrene beads, and stained tissue sections are employed for the imaging test. Compared to state-of-the-art methods, our method eliminates image degradation and obtains a higher imaging resolution. Different from multi-wavelength or multi-height phase retrieval methods, our method only utilizes a single-frame intensity data record to accomplish high-fidelity reconstruction of different samples, which contributes a simple, robust, and data-efficient solution to design a resource-limited lensfree on-chip microscope. We believe that it will become a useful tool for telemedicine and point-of-care application.

Wavelength-scanning lensfree on-chip microscopy for wide-field pixel-super-resolved quantitative phase imaging.

We propose a lensfree on-chip microscopy approach for wide-field quantitative phase imaging (QPI) based on wavelength scanning. Unlike previous methods, we found that a relatively large-range wavelength diversity not only provides information to overcome spatial aliasing of the image sensor but also creates sufficient diffraction variations that can be used to achieve motion-free, pixel-super-resolved phase recovery. Based on an iterative phase retrieval and pixel-super-resolution technique, the proposed wavelength-scanning approach uses only eight undersampled holograms to achieve a half-pitch lateral resolution of 691 nm across a large field-of-view of 29.85mm2, surpassing 2.41 times the theoretical Nyquist-Shannon sampling resolution limit imposed by the pixel size of the sensor (1.67 µm). We confirmed the effectiveness of this technique in QPI and resolution enhancement by measuring the benchmark quantitative phase microscopy target. We also showed that this method can track HeLa cell growth within an incubator, revealing cellular morphologies and subcellular dynamics of a large cell population over an extended period of time.

Autofocusing Algorithm for Pixel-Super-Resolved Lensfree On-Chip Microscopy

In recent years, lensfree on-chip microscopy has developed into a promising and powerful computational optical microscopy technique that allows for wide-field, high-throughput microscopic imaging without using any lenses. However, due to the limited pixel size of the state-of-the-art image sensors, lens-free on-chip microscopy generally suffers from low imaging resolution, which is far from enough to meet the current demand for high-resolution microscopy. Many pixel super-resolution techniques have been developed to solve or at least partially solve this problem by acquiring a series of low-resolution holograms with multiple lateral sub-pixel shifting or axial distances. However, the prerequisite of these pixel super-resolution techniques is that the propagation distance of each low-resolution hologram can be obtained precisely, which faces two major challenges. On the one hand, the captured hologram is inherent pixelated and of low resolution, making it difficult to determine the focal plane by evaluating the image sharpness accurately. On the other hand, the twin-image is superimposed on the backpropagated raw hologram, further exacerbating the difficulties in accurate focal plane determination. In this study, we proposed a high-precision autofocusing algorithm for multi-height pixel-super-resolved lensfree on-chip microscopy. Our approach consists of two major steps: individual preliminary estimation and global precise estimation. First, an improved critical function that combines differential critical function and frequency domain critical function is proposed to obtain the preliminary focus distances of different holograms. Then, the precise focus distances can be determined by further evaluating the global offset of the averaged, low-noise reconstruction from all backpropagated holograms with preliminary focus distances. Simulations and experimental results verified the validity and effectiveness of the proposed algorithm.

Lensfree super-resolved imaging based on adaptive Wiener filter and guided phase retrieval algorithm

We present a data-efficient framework to achieve a super-resolved reconstruction in lensfree on-chip microscopy. Instead of using conventional 3D-stack holograms, our method accomplishes a 5 × reduction of data size without the loss of the imaging resolution, in which merely 30 raw holograms are recorded. The experiment of the resolution target demonstrates a half-pitch lateral resolution of 780 nm across a large field-of-view (FOV) of 28.6 mm2. For the view of H&E stained intestine pathology slide, our method shows an equivalent resolution but a 20-fold expansion of FOV in comparison with a 10 × commercial wide-field microscope. This work will be a useful tool for the miniaturization of whole slide pathological microscopy.

Pixel super-resolved lens-free on-chip microscopy based on dual laterally shifting modulation.

Achieving high spatial resolution over a wide field of view (FOV) is the goal of many imaging systems. In a traditional lens-based microscope, designing a complex objective with high numerical aperture (NA) to achieve this goal is a tough and challenging task. The lens-free wide-field imaging method based on phase retrieval provides a new way to bypass the trade-off between the spatial resolution and FOV of conventional microscopy. However, the typical lens-free microscopy usually requires mechanical devices with high precision and repeatability. In this paper, we report a robust and cost-effective pixel super-resolved lens-free imaging method based on dual laterally shifting modulation. A thin diffuser is inserted between the object and the image sensor to be used as the modulator. The diffuser and the object are transversely scanned at the same time to add diversities for phase retrieval and pixel super-resolution, respectively. In this way, the positional shifts of the diffuser and the object can be directly recovered with the registration algorithm, thus addressing the low stability and inaccuracy issues of translation stages. We also propose a pixel super-resolution phase-retrieval algorithm to recover the object and the unknown diffuser. We first use numerical simulations to evaluate the proposed scheme. Then, we validate this approach by imaging a resolution target and a pollen sample, thus achieving an FOV of ${\sim}{30}\;{\text{mm}^2}$∼30mm2 and a half-pitch resolution of 0.78 µm, which surpasses 2.14 times the theoretical Nyquist-Shannon sampling resolution limit. Finally, the 3D refocusing ability is also verified by imaging a thick mosquito sample.

Resolution Analysis in a Lens-Free On-Chip Digital Holographic Microscope

Lens-free on-chip digital holographic microscopy (LFOCDHM) is a modern imaging technique whereby the sample is placed directly onto or very close to the digital sensor, and illuminated by a partially coherent source located far above it. The scattered object wave interferes with the reference (unscattered) wave at the plane where a digital sensor is situated, producing a digital hologram that can be processed in several ways to extract and numerically reconstruct an in-focus image using the back propagation algorithm. Without requiring any lenses and other intermediate optical components, the LFOCDHM has unique advantages of offering a large effective numerical aperture (NA) close to unity across the native wide field-of-view (FOV) of the imaging sensor in a cost-effective and compact design. However, unlike conventional coherent diffraction limited imaging systems, where the limiting aperture is used to define the system performance, typical lens-free microscopes only produce compromised imaging resolution that far below the ideal coherent diffraction limit. At least five major factors may contribute to this limitation, namely, the sample-to-sensor distance, spatial and temporal coherence of the illumination, finite size of the equally spaced sensor pixels, and finite extent of the image sub-FOV used for the reconstruction, which have not been systematically and rigorously explored until now. In this work, we derive five transfer function models that account for all these physical effects and interactions of these models on the imaging resolution of LFOCDHM. We also examine how our theoretical models can be utilized to optimize the optical design or predict the theoretical resolution limit of a given LFOCDHM system. We present a series of simulations and experiments to confirm the validity of our theoretical models.

Lensfree on-chip microscopy based on dual-plane phase retrieval.

In lensfree on-chip microscopy, the iterative phase retrieval with defocused images easily enables a high-resolution and whole field reconstruction. However, on the reconstruction of the dense sample, conventional methods suffer from the stagnation problem and noise affection under two intensity measurements, which gives rise to a remarkable loss of the image contrast and resolution. Here we propose a novel dual-plane phase retrieval algorithm to perform a stable and versatile lensless reconstruction. A weighted feedback constraint was utilized to speed up the convergence. Then, a gradient descent minimization based on total variation metric was proposed to suppress the noise affection. With these two object constraints, a smoothed but resolution-preserving result can be achieved. Numerical simulations of Gaussian and Poisson noise were given to prove the noise-robustness of our method. The experiments of USAF resolution target, H&E stained pathological slide, and label-free microglia cell demonstrated the superior performance of our approach compared to other state-of-the-art methods.

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.

Laser Light-field Fusion for Wide-field Lensfree On-chip Phase Contrast Microscopy of Nanoparticles.

Wide-field lensfree on-chip microscopy, which leverages holography principles to capture interferometric light-field encodings without lenses, is an emerging imaging modality with widespread interest given the large field-of-view compared to lens-based techniques. In this study, we introduce the idea of laser light-field fusion for lensfree on-chip phase contrast microscopy for detecting nanoparticles, where interferometric laser light-field encodings acquired using a lensfree, on-chip setup with laser pulsations at different wavelengths are fused to produce marker-free phase contrast images of particles at the nanometer scale. As a proof of concept, we demonstrate, for the first time, a wide-field lensfree on-chip instrument successfully detecting 300 nm particles across a large field-of-view of ~30 mm2 without any specialized or intricate sample preparation, or the use of synthetic aperture- or shift-based techniques.

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.

Wide-field pathology imaging using on-chip microscopy.

As the primary imaging tool to assist the examination of pathological samples, the conventional light microscope suffers from limited throughput, relatively high cost, bulky size, lack of portability, and requirement for focus adjustment. All of these drawbacks partially limit the use of light microscopy tools in resource-limited settings. Lens-free on-chip microscopy can help to address these drawbacks and achieve high-throughput pathology slide imaging without using lenses or objectives. Here, we review the performance of this lens-free imaging platform by showing examples of its performance with various samples including normal and sickle-cell disease blood smears and human carcinoma of the breast. This lens-free computational microscopy platform is a promising tool that can serve high-throughput pathology needs especially in resource-poor settings.

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.

High throughput on-chip analysis of high-energy charged particle tracks using lensfree imaging

We demonstrate a high-throughput charged particle analysis platform, which is based on lensfree on-chip microscopy for rapid ion track analysis using allyl diglycol carbonate, i.e., CR-39 plastic polymer as the sensing medium. By adopting a wide-area opto-electronic image sensor together with a source-shifting based pixel super-resolution technique, a large CR-39 sample volume (i.e., 4 cm × 4 cm × 0.1 cm) can be imaged in less than 1 min using a compact lensfree on-chip microscope, which detects partially coherent in-line holograms of the ion tracks recorded within the CR-39 detector. After the image capture, using highly parallelized reconstruction and ion track analysis algorithms running on graphics processing units, we reconstruct and analyze the entire volume of a CR-39 detector within ∼1.5 min. This significant reduction in the entire imaging and ion track analysis time not only increases our throughput but also allows us to perform time-resolved analysis of the etching process to monitor and optimize the growth of ion tracks during etching. This computational lensfree imaging platform can provide a much higher throughput and more cost-effective alternative to traditional lens-based scanning optical microscopes for ion track analysis using CR-39 and other passive high energy particle detectors.

Synthetic aperture-based on-chip microscopy

Wide field-of-view (FOV) and high-resolution imaging requires microscopy modalities to have large space-bandwidth products. Lensfree on-chip microscopy decouples resolution from FOV and can achieve a space-bandwidth product greater than one billion under unit magnification using state-of-the-art opto-electronic sensor chips and pixel super-resolution techniques. However, using vertical illumination, the effective numerical aperture (NA) that can be achieved with an on-chip microscope is limited by a poor signal-to-noise ratio (SNR) at high spatial frequencies and imaging artifacts that arise as a result of the relatively narrow acceptance angles of the sensor's pixels. Here, we report, for the first time, a synthetic aperture-based on-chip microscope in which the illumination angle is scanned across the surface of a dome to increase the effective NA of the reconstructed lensfree image to 1.4, achieving e.g., ∼250-nm resolution at 700-nm wavelength under unit magnification. This synthetic aperture approach not only represents the largest NA achieved to date using an on-chip microscope but also enables color imaging of connected tissue samples, such as pathology slides, by achieving robust phase recovery without the need for multi-height scanning or any prior information about the sample. To validate the effectiveness of this synthetic aperture-based, partially coherent, holographic on-chip microscope, we have successfully imaged color-stained cancer tissue slides as well as unstained Papanicolaou smears across a very large FOV of 20.5 mm2. This compact on-chip microscope based on a synthetic aperture approach could be useful for various applications in medicine, physical sciences and engineering that demand high-resolution wide-field imaging. An on-chip microscope that offers both a high-resolution and a wide field of view looks set to benefit the biological and physical sciences. The lensfree imaging device, developed by researchers at the University of California at Los Angeles, CA, USA, makes use a synthetic aperture approach to provide a very large effective numerical aperture of 1.4 over a field of view of >20 mm2; this is a much larger numerical aperture than previous lensfree approaches had realized (<0.9). Consequently, very high spatial resolution (for example, 250 nm at a wavelength of 700 nm) was achieved. By illuminating samples with light of three different wavelengths (470 nm, 532 nm and 632 nm), the researchers also obtained lens-free color images of samples such as breast cancer tissue.

Lens‐free Microscope Can Detect Cancer at the Cellular Level

Optik & PhotonikVolume 10, Issue 1 p. 18-18 Research & TechnologyFree Access Lens-free Microscope Can Detect Cancer at the Cellular Level UCLA researchers develop device that can do the work of pathology lab microscopes. First published: 16 February 2015 https://doi.org/10.1002/opph.201590017AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. REFERENCES 1 A. Greenbaum et al.: Wide-field computational imaging of pathology slides using lens-free on-chip microscopy, Sci. Transl. Med. 6 (2014) 267; DOI:10.1126/scitranslmed.3009850 Volume10, Issue1February 2015Pages 18-18 ReferencesRelatedInformation