Holography encodes the three dimensional (3D) information of a sample in form an intensity-only recording. However, to decode original image from its hologram(s), auto-focusing and phase-recovery are needed, which general cumbersome time-consuming digitally perform. Here we demonstrate convolutional neural network (CNN) based approach that simultaneously performs significantly extend depth-of-field (DOF) holographic reconstruction. For this, CNN is trained by using pairs randomly de-focused...

Abstract Recent advances in deep learning have given rise to a new paradigm of holographic image reconstruction and phase recovery techniques with real-time performance. Through data-driven approaches, these emerging overcome some the challenges associated existing methods while also minimizing hardware requirements holography. These recent open up myriad opportunities for use coherent imaging systems biomedical engineering research related applications.

We report a deep learning-enabled field-portable and cost-effective imaging flow cytometer that automatically captures phase-contrast color images of the contents continuously flowing water sample at throughput 100 mL/h. The device is based on partially coherent lens-free holographic microscopy acquires diffraction patterns micro-objects inside microfluidic channel. These are reconstructed in real time using learning-based phase-recovery image-reconstruction method to produce image each...

Translational control plays a vital role in regulating gene expression. To decipher the molecular basis of translational regulation photomorphogenic Arabidopsis thaliana, we adopted ribosome profiling method to map genome-wide positions translating ribosomes etiolated seedlings dark and after light exposure. We found that, Arabidopsis, protects an ~30-nucleotide region moves three-nucleotide periodicity, characteristics also observed Saccharomyces cerevisiae mammals. Light enhanced...

Autofocusing is essential to digital holographic imaging. Previously used autofocusing criteria exhibit challenges when applied to, e.g., connected objects with different optical properties. Furthermore, in some of the earlier criteria, polarity, i.e., whether search for peak or valley as a function depth, changes types samples, which creates another challenge. Here, we propose robust and accurate criterion that based on edge sparsity complex wavefront, termed "sparsity gradient" (SoG). We...

Rapid, accurate and high-throughput sizing quantification of particulate matter (PM) in air is crucial for monitoring improving quality. In fact, particles with a diameter ≤2.5 μm have been classified as carcinogenic by the World Health Organization. Here we present field-portable cost-effective platform using computational lens-free microscopy machine-learning. This platform, termed c-Air, also integrated smartphone application device control display results. mobile rapidly screens 6.5 L 30...

Abstract Digital holographic microscopy enables the 3D reconstruction of volumetric samples from a single-snapshot hologram. However, unlike conventional bright-field image, quality reconstructions is compromised by interference fringes as result twin images and out-of-plane objects. Here, we demonstrate that cross-modality deep learning using generative adversarial network (GAN) can endow sample volume with contrast, combining imaging capability holography speckle- artifact-free image...

In recent years, deep learning has been shown to be one of the leading machine techniques for a wide variety inference tasks. addition its mainstream applications, such as classification, it created transformative opportunities image reconstruction and enhancement in optical microscopy. Some these emerging applications range from transformations between microscopic imaging systems adding new capabilities existing techniques, well solving various inverse problems based on microscopy data....

This work presents simulation and experimental results of ultra-thin optical ring resonators, having larger Evanescent Field (EF) penetration depths, therefore sensitivities, as compared to conventional Silicon-on-Insulator (SOI)-based resonator sensors. Having higher sensitivities the changes in refractive indices cladding media is desirable for sensing applications, interactions interest take place this region. Using waveguides (<100 nm thick) shows promise enhance sensitivity both bulk...

Abstract High-resolution imaging of densely connected samples such as pathology slides using digital in-line holographic microscopy requires the acquisition several holograms, e.g., at &gt;6–8 different sample-to-sensor distances, to achieve robust phase recovery and coherent specimen. Reducing number these measurements would normally result in reconstruction artifacts loss image quality, which be detrimental especially for biomedical diagnostics-related applications. Inspired by fact that...

T-helper-17 (Th17) cells are a subset of CD4+ T that can produce the cytokine interleukin (IL)-17 and play vital roles in protecting host from bacterial fungal infections, especially at mucosal surface. These abundant small intestinal lamina propria (SILP) their differentiation associated with colonization flora. Segmented filamentous bacteria (SFB) drew attention researchers due to unique ability drive accumulation Th17 SI LP mice. Recent work has highlighted SFB used microbial...

Abstract Harnessing optical supermode interaction to construct artificial photonic molecules has uncovered a series of fundamental phenomena analogous atomic physics. Previously, the distinct energy levels and interactions in such two-level systems were provided by coupled microresonators. The reconfigurability is limited, as they often require delicate external field stimuli or mechanically altering geometric factors. These highly specific approaches also limit potential applications. Here,...

We demonstrate a field-portable and automatic yeast analysis platform that can rapidly measure cell concentration viability using on-chip microscopy machine learning.

Conventional bioaerosol sensing requires the sampled aerosols in field to be transferred a laboratory for manual inspection, which can rather costly and slow, also requiring professional labeling microscopic examination of samples. Here we demonstrate label-free using field-portable cost-effective device based on holographic microscopy deep-learning, screens bioaerosols at throughput 13 L/min. Two different deep neural networks are designed rapidly reconstruct amplitude phase images captured...

Aggregation-based assays, using micro- and nano-particles have been widely accepted as an efficient cost-effective bio-sensing tool, particularly in microbiology, where particle clustering events are used a metric to infer the presence of specific target analyte quantify its concentration. Here, we present sensitive automated readout method for aggregation-based assays wide-field lens-free on-chip microscope, with ability rapidly analyze microscopic aggregation 3D, deep learning-based...

Extracellular β-amyloid (Aβ) plaques and neurofibrillary tangles (NFTs) are the pathological hallmarks of Alzheimer's disease (AD). Mesenchymal stem cells (MSCs) have shown therapeutic efficacy in many neurodegenerative diseases, including AD. Human menstrual blood-derived (MenSCs) a novel source MSCs advantageous for their higher proliferation rate because they easy to obtain without ethical concerns. Although MenSCs exhibited some effects on AD remain elusive. In present study, we showed...

Background Methylated DNA in fluids may be a suitable biomarker for cancer patients. XAF1 has been shown to frequently down-regulated human gastric (GC). Here, we investigated if methylation GC could useful biomarker. Methods Real-time RT-PCR was used detect mRNA expression; immunohistochemistry and western blot were examine protein expression tissues (n = 202) their corresponding para-cancerous histological normal (PCHNTs). specific-PCR investigate promoter the same panel of tissues, PCHNTs...

This study of 371 identical resonators on a 16x9 mm chip fabricated by silicon photonics foundry reveals strong linear correlation between the physical distance devices and variability in their wavelength mismatch.

Lens-free holographic microscopy can achieve wide-field imaging in a cost-effective and field-portable setup, making it promising technique for point-of-care telepathology applications. However, due to relatively narrow-band sources used microscopy, conventional colorization methods that use images reconstructed at discrete wavelengths, corresponding e.g., red (R), green (G) blue (B) channels, are subject color artifacts. Furthermore, these existing RGB do not match the chromatic perception...

We report a framework based on generative adversarial network (GAN) that performs high-fidelity color image reconstruction using single hologram of sample is illuminated simultaneously by light at three different wavelengths. The trained learns to eliminate missing-phase-related artifacts, and generates an accurate transformation for the reconstructed image. Our experimentally demonstrated lung prostate tissue sections are labeled with histological stains. This envisaged be applicable...