Polarimetric calibrated robust dual-SLM complex-amplitude computer-generated holography.

Liquid crystal on silicon (LCoS) is a widely used spatial light modulator (SLM) in computer-generated holography (CGH). However, the phase-modulating profile of LCoS is often not ideally uniform in application, bringing about undesired intensity fringes. In this study, we overcome this problem by proposing a highly robust dual-SLM complex-amplitude CGH technique, which incorporates a polarimetric mode and a diffractive mode. The polarimetric mode linearizes the general phase modulations of the two SLMs separately, while the diffractive mode uses camera-in-the-loop optimization to achieve improved holographic display. Experimental results show the effectiveness of our proposal in improving reconstructing accuracy by 21.12% in peak signal-to-noise ratio (PSNR) and 50.74% in structure similarity index measure (SSIM), using LCoS SLMs with originally non-uniform phase-modulating profiles.

COVID-19 detection from red blood cells using highly comparative time-series analysis (HCTSA) in digital holographic microscopy.

We present an automated method for COVID-19 screening based on reconstructed phase profiles of red blood cells (RBCs) and a highly comparative time-series analysis (HCTSA). Video digital holographic data -was obtained using a compact, field-portable shearing microscope to capture the temporal fluctuations and spatio-temporal dynamics of live RBCs. After numerical reconstruction of the digital holographic data, the optical volume is calculated at each timeframe of the reconstructed data to produce a time-series signal for each cell in our dataset. Over 6000 features are extracted on the time-varying optical volume sequences using the HCTSA to quantify the spatio-temporal behavior of the RBCs, then a linear support vector machine is used for classification of individual RBCs. Human subjects are then classified for COVID-19 based on the consensus of their cells' classifications. The proposed method is tested on a dataset of 1472 RBCs from 24 human subjects (10 COVID-19 positive, 14 healthy) collected at UConn Health Center. Following a cross-validation procedure, our system achieves 82.13% accuracy, with 92.72% sensitivity, and 73.21% specificity (area under the receiver operating characteristic curve: 0.8357). Furthermore, the proposed system resulted in 21 out of 24 human subjects correctly labeled. To the best of our knowledge this is the first report of a highly comparative time-series analysis using digital holographic microscopy data.

Fast optical recording of neuronal activity by three-dimensional custom-access serial holography.

Optical recording of neuronal activity in three-dimensional (3D) brain circuits at cellular and millisecond resolution in vivo is essential for probing information flow in the brain. While random-access multiphoton microscopy permits fast optical access to neuronal targets in three dimensions, the method is challenged by motion artifacts when recording from behaving animals. Therefore, we developed three-dimensional custom-access serial holography (3D-CASH). Built on a fast acousto-optic light modulator, 3D-CASH performs serial sampling at 40 kHz from neurons at freely selectable 3D locations. Motion artifacts are eliminated by targeting each neuron with a size-optimized pattern of excitation light covering the cell body and its anticipated displacement field. Spike rates inferred from GCaMP6f recordings in visual cortex of awake mice tracked the phase of a moving bar stimulus with higher spike correlation between intra compared to interlaminar neuron pairs. 3D-CASH offers access to the millisecond correlation structure of in vivo neuronal activity in 3D microcircuits.

Hydrogel-based holographic sensors and biosensors: past, present, and future.

Hydrogel-based holographic sensors consist of a holographic pattern in a responsive hydrogel that diffracts light at different wavelengths depending on the dimensions and refractive index changes in the material. The material composition of hydrogels can be designed to be specifically responsive to different stimuli, and thus the diffraction pattern can correlate with the amount of analyte. According to this general principle, different approaches have been implemented to achieve label-free optical sensors and biosensors, with advantages such as easy fabrication or naked-eye detection. A review on the different approaches, sensing materials, measurement principles, and detection setups, and future perspectives is offered.

Imaging biological tissue with high-throughput single-pixel compressive holography.

Single-pixel holography (SPH) is capable of generating holographic images with rich spatial information by employing only a single-pixel detector. Thanks to the relatively low dark-noise production, high sensitivity, large bandwidth, and cheap price of single-pixel detectors in comparison to pixel-array detectors, SPH is becoming an attractive imaging modality at wavelengths where pixel-array detectors are not available or prohibitively expensive. In this work, we develop a high-throughput single-pixel compressive holography with a space-bandwidth-time product (SBP-T) of 41,667 pixels/s, realized by enabling phase stepping naturally in time and abandoning the need for phase-encoded illumination. This holographic system is scalable to provide either a large field of view (~83 mm2) or a high resolution (5.80 µm × 4.31 µm). In particular, high-resolution holographic images of biological tissues are presented, exhibiting rich contrast in both amplitude and phase. This work is an important step towards multi-spectrum imaging using a single-pixel detector in biophotonics.

Probing neural codes with two-photon holographic optogenetics.

Optogenetics ushered in a revolution in how neuroscientists interrogate brain function. Because of technical limitations, the majority of optogenetic studies have used low spatial resolution activation schemes that limit the types of perturbations that can be made. However, neural activity manipulations at finer spatial scales are likely to be important to more fully understand neural computation. Spatially precise multiphoton holographic optogenetics promises to address this challenge and opens up many new classes of experiments that were not previously possible. More specifically, by offering the ability to recreate extremely specific neural activity patterns in both space and time in functionally defined ensembles of neurons, multiphoton holographic optogenetics could allow neuroscientists to reveal fundamental aspects of the neural codes for sensation, cognition and behavior that have been beyond reach. This Review summarizes recent advances in multiphoton holographic optogenetics that substantially expand its capabilities, highlights outstanding technical challenges and provides an overview of the classes of experiments it can execute to test and validate key theoretical models of brain function. Multiphoton holographic optogenetics could substantially accelerate the pace of neuroscience discovery by helping to close the loop between experimental and theoretical neuroscience, leading to fundamental new insights into nervous system function and disorder.

Feasibility of the Application of Holographic Augmented Reality in Endovascular Surgery Using Microsoft HoloLens Head-Mounted Display.

OBJECTIVES: Advances in virtual, augmented (AR) and mixed reality have led to the development of wearable technologies including head mounted displays (HMD). The aim of this study was to investigate the feasibility to use HMD during endovascular surgery. METHODS: We propose an adaptation of AR-HMD using Microsoft HoloLens. Software was developed to enable visualization of the vascular system during endovascular procedures. A video was performed to present an overview of the device and show its use in real conditions. RESULTS: The device allowed a successful visualization of perioperative angiography during peripheral angioplasty, carotid angioplasty and aortic aneurysm endovascular repair. The device was operated on voice command, preserving the environment sterility. CONCLUSION: This video illustrated the feasibility of the application of holographic AR during endovascular intervention and brings perspectives to use artificial-intelligence derived tools for image-guided surgery.

Digital holographic deep learning of red blood cells for field-portable, rapid COVID-19 screening.

Rapid screening of red blood cells for active infection of COVID-19 is presented using a compact and field-portable, 3D-printed shearing digital holographic microscope. Video holograms of thin blood smears are recorded, individual red blood cells are segmented for feature extraction, then a bi-directional long short-term memory network is used to classify between healthy and COVID positive red blood cells based on their spatiotemporal behavior. Individuals are then classified based on the simple majority of their cells' classifications. The proposed system may be beneficial for under-resourced healthcare systems. To the best of our knowledge, this is the first report of digital holographic microscopy for rapid screening of COVID-19.

Holographic tomography: techniques and biomedical applications [Invited].

Holographic tomography (HT) is an advanced label-free optical microscopic imaging method used for biological studies. HT uses digital holographic microscopy to record the complex amplitudes of a biological sample as digital holograms and then numerically reconstruct the sample's refractive index (RI) distribution in three dimensions. The RI values are a key parameter for label-free bio-examination, which correlate with metabolic activities and spatiotemporal distribution of biophysical parameters of cells and their internal organelles, tissues, and small-scale biological objects. This article provides insight on this rapidly growing HT field of research and its applications in biology. We present a review summary of the HT principle and highlight recent technical advancement in HT and its applications.

Influence of noise-reduction techniques in sparse-data sample rotation tomographic imaging.

Data acquisition and processing is a critical issue for high-speed applications, especially in three-dimensional live cell imaging and analysis. This paper focuses on sparse-data sample rotation tomographic reconstruction and analysis with several noise-reduction techniques. For the sample rotation experiments, a live Candida rugosa sample is used and controlled by holographic optical tweezers, and the transmitted complex wavefronts of the sample are recorded with digital holographic microscopy. Three different cases of sample rotation tomography were reconstructed for dense angle with a step rotation at every 2°, and for sparse angles with step rotation at every 5° and 10°. The three cases of tomographic reconstruction performance are analyzed with consideration for data processing using four noise-reduction techniques. The experimental results demonstrate potential capability in retaining the tomographic image quality, even at the sparse angle reconstructions, with the help of noise-reduction techniques.

Digital holographic microscope for human eye retinal structures recording in vivo.

We introduce the digital holographic microscope for recording in vivo human eye retinal structures. Current eye imaging technologies cannot provide images with resolutions better than 1 µm within depths of a few hundred micrometers. This can be improved with digital holography, in which a hologram of the eye captured with digital camera contains information about structures over the full depth of the eye. This information can be reconstructed either optically or numerically. Our hologram recording scheme utilizes working principles of the off-axis digital holographic microscope, designed for reflective micro-object investigation. The eye cornea and lens form the microscope objective. We can record in vivo digital holograms of the human eye retina with resolution after reconstruction of at least 1.3 micrometer.

Single-shot common-path off-axis digital holography: applications in bioimaging and optical metrology [Invited].

The demand for single-shot and common-path holographic systems has become increasingly important in recent years, as such systems offer various advantages compared to their counterparts. Single-shot holographic systems, for example, reduce computational complexity as only a single hologram with the object information required to process, making them more suitable for the investigation of dynamic events; and common-path holographic systems are less vibration-sensitive, compact, inexpensive, and high in temporal phase stability. We have developed a single-shot common-path off-axis digital holographic setup based on a beam splitter and pinhole. In this paper, we present a concise review of the proposed digital holographic system for several applications, including the quantitative phase imaging to investigate the morphological and quantitative parameters, as a metrological tool for testing of micro-optics, industrial inspection and measurement, and sound field imaging and visualization.

Open-source, cost-effective, portable, 3D-printed digital lensless holographic microscope.

In this work, the design, construction, and testing of the most cost-effective digital lensless holographic microscope to date are presented. The architecture of digital lensless holographic microscopy (DLHM) is built by means of a 3D-printed setup and utilizing off-the-shelf materials to produce a DLHM microscope costing US$52.82. For the processing of the recorded in-line holograms, an open-source software specifically developed to process this type of recordings is utilized. The presented DLHM setup has all the degrees of freedom needed to achieve different fields of view, levels of spatial resolution, and 2D scanning of the sample. The feasibility of the presented platform is tested by imaging non-bio and bio samples; the resolution test targets, a section of the head of a Drosophila melanogaster fly, red blood cells, and cheek cells are imaged on the built microscope.

Biodynamic digital holographic speckle microscopy for oocyte and embryo metabolic evaluation.

Assisted reproductive technologies seek to improve the success rate of pregnancies. Morphology scoring is a common approach to evaluate oocyte and embryo viability prior to embryo transfer in utero, but the efficacy of the method is low. We apply biodynamic imaging, based on dynamic light scattering and low-coherence digital holography, to assess the metabolic activity of oocytes and embryos. A biodynamic microscope, developed to image small and translucent biological specimens, is inserted into the bay of a commercial inverted microscope that can switch between conventional microscopy channels and biodynamic microscopy. We find intracellular Doppler spectral features that act as noninvasive proxies for embryo metabolic activity that may relate to embryo viability.

Incoherent color digital holography with computational coherent superposition for fluorescence imaging [Invited].

We present color fluorescence imaging using an incoherent digital holographic technique in which holographic multiplexing of multiple wavelengths is exploited. Self-interference incoherent digital holography with a single-path in-line configuration and the computational coherent superposition scheme are adopted to obtain color holographic three-dimensional information of self-luminous objects with a monochrome image sensor and no mechanical scanning. We perform not only simultaneous color three-dimensional sensing of multiple self-luminous objects but also color fluorescence imaging of stained biological samples. Color fluorescence imaging with an improved point spread function is also demonstrated experimentally by adopting a Fresnel incoherent correlation holography system.

Rolling angle recovery of flowing cells in holographic tomography exploiting the phase similarity.

Holographic tomography allows the 3D mapping of the refractive index of biological samples thanks to reconstruction methods based on the knowledge of illumination directions or rotation angles of the imaged sample. Recently, phase contrast tomographic flow cytometry by digital holography has been demonstrated to reconstruct the three-dimensional refractive index distribution of single cells while they are flowing along microfluidic channels. In this system, the illumination direction is fixed while the sample's rotation is not deterministically known a priori but induced by hydrodynamic forces. We propose here a technique to retrieve the rolling angles, based on a new phase images similarity metric that is capable of identifying a cell's orientations from its 3D positioning while it is flowing along the microfluidic channel. The method is experimentally tested and also validated through appropriate numerical simulations. We provide demonstration of concept by achieving reconstruction of breast cancer cells tomography.

Measurement of morphology thickness and refractive index in a melanoma A375 cell line using digital holographic microscopy.

Digital holographic microscopy (DHM) is a technique that has high potential for analyzing biological samples and has been successfully applied to the study of cells and cell lines providing information about important parameters such as refractive index, morphology, and dry mass, among others; it has also found applicability to study the effects of therapeutic treatments. Finding the size and shape of cells is important since they tend to change in the presence of some pathologies. In this research work, we obtain the morphology thickness and refractive index of the A375 melanoma cell line through a slight tilting of the cell in a DHM setup. Further, the development of a novel mathematical expression based on this tilt and in the optical phase difference is presented. We show images of melanoma cells with the refractive index information included, and their morphology thickness as rendered from the holographic phase maps recorded with DHM.

Using Augmented Reality to Reduce Fear and Promote Cooperation During Pediatric Otolaryngologic Procedures.

This case series examines interactive AR during minor otolaryngologic procedures. Although VR has been successfully used for pediatric vascular access, removing children from comforting people in the real world has resulted in patient anxiety. AR offers a potential advantage, utilizing distracting holographic images when patients maintain eye contact with parents. The primary objective was to determine the effect of AR on fear during pediatric otolaryngologic procedures. Secondary objectives included evaluating pain; procedure compliance; and patient, parent and physician attitudes toward AR, as well as assessing the feasibility of adding AR to a busy outpatient otolaryngologic clinic. Laryngoscope, 131:E1342-E1344, 2021.

Red blood cell classification in lensless single random phase encoding using convolutional neural networks.

Rapid cell identification is achieved in a compact and field-portable system employing single random phase encoding to record opto-biological signatures of living biological cells of interest. The lensless, 3D-printed system uses a diffuser to encode the complex amplitude of the sample, then the encoded signal is recorded by a CMOS image sensor for classification. Removal of lenses in this 3D sensing system removes restrictions on the field of view, numerical aperture, and depth of field normally imposed by objective lenses in comparable microscopy systems to enable robust 3D capture of biological volumes. Opto-biological signatures for two classes of animal red blood cells, situated in a microfluidic device, are captured then input into a convolutional neural network for classification, wherein the AlexNet architecture, pretrained on the ImageNet database is used as the deep learning model. Video data was recorded of the opto-biological signatures for multiple samples, then each frame was treated as an input image to the network. The pre-trained network was fine-tuned and evaluated using a dataset of over 36,000 images. The results show improved performance in comparison to a previously studied Random Forest classification model using extracted statistical features from the opto-biological signatures. The system is further compared to and outperforms a similar shearing-based 3D digital holographic microscopy system for cell classification. In addition to improvements in classification performance, the use of convolutional neural networks in this work is further demonstrated to provide improved performance in the presence of noise. Red blood cell identification as presented here, may serve as a key step toward lensless pseudorandom phase encoding applications in rapid disease screening. To the best of our knowledge this is the first report of lensless cell identification in single random phase encoding using convolutional neural networks.