A human erythrocytes hologram dataset for learning-based model training.

This manuscript presents a paired dataset with experimental holograms and their corresponding reconstructed phase maps of human red blood cells (RBCs). The holographic images were recorded using an off-axis telecentric Digital Holographic Microscope (DHM). The imaging system consists of a 40 × /0.65NA infinity-corrected microscope objective (MO) lens and a tube lens (TL) with a focal distance of 200 mm, recording diffraction-limited holograms. A CMOS camera with dimensions of 1920 × 1200 pixels and a pixel pitch of 5.86 µm was located at the back focal plane of the TL lens, capturing image-plane holograms. The off-axis, telecentric, and diffraction-limited DHM system guarantees accurate quantitative phase maps. Initially comprising 300 holograms, the dataset was augmented to 36,864 instances, enabling the investigation (i.e., training and testing) of learning-based models to reconstruct aberration-free phase images from raw holograms. This dataset facilitates the training and testing of end-to-end models for quantitative phase imaging using DHM systems operating at the telecentric regime and non-telecentric DHM systems where the spherical wavefront has been compensated physically. In other words, this dataset holds promise for advancing investigations in digital holographic microscopy and computational imaging.

In-focus quantitative phase imaging from defocused off-axis holograms: synergistic reconstruction framework.

Digital holographic microscopy (DHM) enables the three-dimensional (3D) reconstruction of quantitative phase distributions from a defocused hologram. Traditional computational algorithms follow a sequential approach in which one first reconstructs the complex amplitude distribution and later applies focusing algorithms to provide an in-focus phase map. In this work, we have developed a synergistic computational framework to compensate for the linear tilt introduced in off-axis DHM systems and autofocus the defocused holograms by minimizing a cost function, providing in-focus reconstructed phase images without phase distortions. The proposed computational tool has been validated in defocused holograms of human red blood cells and three-dimensional images of dynamic sperm cells.

Comprehensive tool for a phase compensation reconstruction method in digital holographic microscopy operating in non-telecentric regime.

Quantitative phase imaging (QPI) via Digital Holographic microscopy (DHM) has been widely applied in material and biological applications. The performance of DHM technologies relies heavily on computational reconstruction methods to provide accurate phase measurements. Among the optical configuration of the imaging system in DHM, imaging systems operating in a non-telecentric regime are the most common ones. Nonetheless, the spherical wavefront introduced by the non-telecentric DHM system must be compensated to provide undistorted phase measurements. The proposed reconstruction approach is based on previous work from Kemper's group. Here, we have reformulated the problem, reducing the number of required parameters needed for reconstructing phase images to the sensor pixel size and source wavelength. The developed computational algorithm can be divided into six main steps. In the first step, the selection of the +1-diffraction order in the hologram spectrum. The interference angle is obtained from the selected +1 order. Secondly, the curvature of the spherical wavefront distorting the sample's phase map is estimated by analyzing the size of the selected +1 order in the hologram's spectrum. The third and fourth steps are the spatial filtering of the +1 order and the compensation of the interference angle. The next step involves the estimation of the center of the spherical wavefront. An optional final optimization step has been included to fine-tune the estimated parameters and provide fully compensated phase images. Because the proper implementation of a framework is critical to achieve successful results, we have explicitly described the steps, including functions and toolboxes, required for reconstructing phase images without distortions. As a result, we have provided open-access codes and a user interface tool with minimum user input to reconstruct holograms recorded in a non-telecentric DHM system.

Global Stress Detection Framework Combining a Reduced Set of HRV Features and Random Forest Model.

Approximately 65% of the worldwide adult population has experienced stress, affecting their daily routine at least once in the past year. Stress becomes harmful when it occurs for too long or is continuous (i.e., chronic), interfering with our performance, attention, and concentration. Chronic high stress contributes to major health issues such as heart disease, high blood pressure, diabetes, depression, and anxiety. Several researchers have focused on detecting stress through combining many features with machine/deep learning models. Despite these efforts, our community has not agreed on the number of features to identify stress conditions using wearable devices. In addition, most of the reported studies have been focused on person-specific training and testing. Thanks to our community's broad acceptance of wearable wristband devices, this work investigates a global stress detection model combining eight HRV features with a random forest (RF) algorithm. Whereas the model's performance is evaluated for each individual, the training of the RF model contains instances of all subjects (i.e., global training). We have validated the proposed global stress model using two open-access databases (the WESAD and SWELL databases) and their combination. The eight HRV features with the highest classifying power are selected using the minimum redundancy maximum relevance (mRMR) method, reducing the training time of the global stress platform. The proposed global stress monitoring model identifies person-specific stress events with an accuracy higher than 99% after a global training framework. Future work should be focused on testing this global stress monitoring framework in real-world applications.

Focus Issue Introduction: 3D Image Acquisition and Display: Technology, Perception and Applications.

This Feature Issue of Optics Express is organized in conjunction with the 2022 Optica conference on 3D Image Acquisition and Display: Technology, Perception and Applications which was held in hybrid format from 11 to 15, July 2022 as part of the Imaging and Applied Optics Congress and Optical Sensors and Sensing Congress 2022 in Vancouver, Canada. This Feature Issue presents 31 articles which cover the topics and scope of the 2022 3D Image Acquisition and Display conference. This Introduction provides a summary of these published articles that appear in this Feature Issue.

pyDHM: A Python library for applications in digital holographic microscopy.

pyDHM is an open-source Python library aimed at Digital Holographic Microscopy (DHM) applications. The pyDHM is a user-friendly library written in the robust programming language of Python that provides a set of numerical processing algorithms for reconstructing amplitude and phase images for a broad range of optical DHM configurations. The pyDHM implements phase-shifting approaches for in-line and slightly off-axis systems and enables phase compensation for telecentric and non-telecentric systems. In addition, pyDHM includes three propagation algorithms for numerical focusing complex amplitude distributions in DHM and digital holography (DH) setups. We have validated the library using numerical and experimental holograms.

Single-Shot 3D Topography of Transmissive and Reflective Samples with a Dual-Mode Telecentric-Based Digital Holographic Microscope.

Common path DHM systems are the most robust DHM systems as they are based on self-interference and are thus less prone to external fluctuations. A common issue amongst these DHM systems is that the two replicas of the sample's information overlay due to self-interference, making them only suitable for imaging sparse samples. This overlay has restricted the use of common-path DHM systems in material science. The overlay can be overcome by limiting the sample's field of view to occupy only half of the imaging field of view or by using an optical spatial filter. In this work, we have implemented optical spatial filtering in a common-path DHM system using a Fresnel biprism. We have analyzed the optimal pinhole size by evaluating the frequency content of the reconstructed phase images of a star target. We have also measured the accuracy of the system and the sensitivity to noise for different pinhole sizes. Finally, we have proposed the first dual-mode common-path DHM system using a Fresnel biprism. The performance of the dual-model DHM system has been evaluated experimentally using transmissive and reflective microscopic samples.

Selection of Noninvasive Features in Wrist-Based Wearable Sensors to Predict Blood Glucose Concentrations Using Machine Learning Algorithms.

Glucose monitoring technologies allow users to monitor glycemic fluctuations (e.g., blood glucose levels). This is particularly important for individuals who have diabetes mellitus (DM). Traditional self-monitoring blood glucose (SMBG) devices require the user to prick their finger and extract a blood drop to measure the blood glucose based on chemical reactions with the blood. Unlike traditional glucometer devices, noninvasive continuous glucose monitoring (NICGM) devices aim to solve these issues by consistently monitoring users' blood glucose levels (BGLs) without invasively acquiring a sample. In this work, we investigated the feasibility of a novel approach to NICGM using multiple off-the-shelf wearable sensors and learning-based models (i.e., machine learning) to predict blood glucose. Two datasets were used for this study: (1) the OhioT1DM dataset, provided by the Ohio University; and (2) the UofM dataset, created by our research team. The UofM dataset consists of fourteen features provided by six sensors for studying possible relationships between glucose and noninvasive biometric measurements. Both datasets are passed through a machine learning (ML) pipeline that tests linear and nonlinear models to predict BGLs from the set of noninvasive features. The results of this pilot study show that the combination of fourteen noninvasive biometric measurements with ML algorithms could lead to accurate BGL predictions within the clinical range; however, a larger dataset is required to make conclusions about the feasibility of this approach.

Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network.

The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as numerical focusing may be needed to reconstruct free-of-distortion quantitative phase images based on the optical configuration of the DHM system. Regardless of the implementation, any DHM computational processing leads to long processing times, hampering the use of DHM for video-rate renderings of dynamic biological processes. In this study, we report on a conditional generative adversarial network (cGAN) for robust and fast quantitative phase imaging in DHM. The reconstructed phase images provided by the GAN model present stable background levels, enhancing the visualization of the specimens for different experimental conditions in which the conventional approach often fails. The proposed learning-based method was trained and validated using human red blood cells recorded on an off-axis Mach-Zehnder DHM system. After proper training, the proposed GAN yields a computationally efficient method, reconstructing DHM images seven times faster than conventional computational approaches.

Fast-iterative automatic reconstruction method for quantitative phase image with reduced phase perturbations in off-axis digital holographic microscopy.

This works presents a reconstruction algorithm to recover the complex object information for an off-axis digital holographic microscope (DHM) operating in the telecentric regimen. We introduce an automatic and fast method to minimize a cost function that finds the best numerical conjugated reference beam to compensate the filtered object information, eliminating any undesired phase perturbation due to the tilt between the reference and object waves. The novelties of the proposed approach, to the best of our knowledge, are a precise estimation of the interference angle between the object and reference waves, reconstructed phase images without phase perturbations, and reduced processing time. The method has been validated using a manufactured phase target and biological samples.

Fast-iterative blind phase-shifting digital holographic microscopy using two images.

Digital holographic microscopy (DHM) has consolidated as a tool for diagnosis and measuring in life sciences, thanks to its capability to perform quantitative phase imaging. The reduction of the acquisition and computation time has driven the development of diverse reconstruction methodologies using a single-shot and two-frame approach. Methods based on the Fourier transform, the Hilbert transform, and the phase derivative are counted among the most utilized. The sensitivity of those methods is highly dependent on the compensation of the phase step, which requires the accurate knowledge of the phase shift between the two recorded holograms. Here, an alternative fast-iterative method based on the demodulation of the different components of the recorded interferograms is presented. The novelties of the proposed two-frame approach are: minimum number of images, since it requires 2 recorded holograms; a minimum phase error of the order of 0.005% independently of the phase step ranging from 0 to 180 deg.; a maximum correlation coefficient equal to 1 between the phase and the retrieved phase image; and, finally, a reduced processing time compared with the previous three-frame approach. Experimental results demonstrate the goodness and feasibility of the proposed technique.

Advantages of Fresnel biprism-based digital holographic microscopy in quantitative phase imaging.

SIGNIFICANCE: The hallmarks of digital holographic microscopy (DHM) compared with other quantitative phase imaging (QPI) methods are high speed, accuracy, spatial resolution, temporal stability, and polarization-sensitivity (PS) capability. The above features make DHM suitable for real-time quantitative PS phase imaging in a broad number of biological applications aimed at understanding cell growth and dynamic changes occurring during physiological processes and/or in response to pharmaceutical agents. AIM: The insertion of a Fresnel biprism (FB) in the image space of a light microscope potentially turns any commercial system into a DHM system enabling QPI with the five desired features in QPI simultaneously: high temporal sensitivity, high speed, high accuracy, high spatial resolution, and PS. To the best of our knowledge, this is the first FB-based DHM system providing these five features all together. APPROACH: The performance of the proposed system was calibrated with a benchmark phase object. The PS capability has been verified by imaging human U87 glioblastoma cells. RESULTS: The proposed FB-based DHM system provides accurate phase images with high spatial resolution. The temporal stability of our system is in the order of a few nanometers, enabling live-cell studies. Finally, the distinctive behavior of the cells at different polarization angles (e.g., PS capability) can be observed with our system. CONCLUSIONS: We have presented a method to turn any commercial light microscope with monochromatic illumination into a PS QPI system. The proposed system provides accurate quantitative PS phase images in a new, simple, compact, and cost-effective format, thanks to the low cost (a few hundred dollars) involved in implementing this simple architecture, enabling the use of this QPI technique accessible to most laboratories with standard light microscopes.

Phase-shifting digital holographic microscopy with an iterative blind reconstruction algorithm.

In phase-shifting digital holographic microscopy (PS-DHM), the reconstructed phase map is obtained after processing several holograms of the same scene with a phase shift between them. Most of the reconstruction algorithms in PS-DHM require an accurate and known phase shift between the recorded holograms. This requirement limits the applicability of the method. To ease the use of PS-DHM, this paper presents an iterative-blind phase shift extraction method based on demodulation of the different components of the recorded holograms. The method uses a DHM system operating in a slightly off-axis architecture. The proposed method uses three-frame holograms with arbitrary and unequal phase shifts between them and therefore eases the use of the PS-DHM. We believe both simulated and experimental results demonstrate the goodness and feasibility of the proposed technique.

Structured illumination in compact and field-portable 3D-printed shearing digital holographic microscopy for resolution enhancement.

A compact and field-portable three-dimensional (3D)-printed structured illumination (SI) digital holographic microscope based on shearing geometry is presented. By illuminating the sample using a SI pattern, the lateral resolution in both reconstructed phase and amplitude images can be improved up to twice the resolution provided by conventional illumination. The use of a 3D-printed system and shearing geometry reduces the complexity of the system, while providing high temporal stability. The experimental results for the USAF resolution target show a resolution improvement of a factor of two which corroborates the theoretical prediction. Resolution enhancement in phase imaging is also demonstrated by imaging a biological sample. To the best of our knowledge, this is the first report of a compact and field-portable SI digital holographic system based on shearing geometry.

Optical transfer function engineering for a tunable 3D structured illumination microscope.

Two important features of three-dimensional structured illumination microscopy (3D-SIM) are its optical sectioning (OS) and super-resolution (SR) capabilities. Previous works on 3D-SIM systems show that these features are coupled. We demonstrate that a 3D-SIM system using a Fresnel biprism illuminated by multiple linear incoherent sources provides a structured illumination pattern whose lateral and axial modulation frequencies can be tuned separately. Therefore, the compact support of the synthetic optical transfer function (OTF) can be engineered to achieve the highest OS and SR capabilities for a particular imaging application. Theoretical performance of our engineered system based on the OTF support is compared to that achieved by other well-known SIM systems.

Wollaston prism-based structured illumination microscope with tunable frequency.

This work proposes an alternative structured illumination (SI) system based on a Wollaston prism (WP) illuminated by the diffracted field of an incoherent linear source. The proposed WP-based SI system presents several advantages. First, the generated fringes can be approximated by a pure sinusoidal pattern; thereby, computational methods developed for sinusoidal SI can be used without the need for additional processing. Second, the SI pattern's period can be continuously varied up to the cutoff frequency of the native widefield system. Most significantly, the phase shifting of the SI pattern required for demodulation in SI microscopy can be easily accomplished using a de Sénarmont compensator, which provides accurate lateral displacement of the fringes independently of the lateral modulation frequency. Experimental verifications confirm the presented theoretical predictions.

Tunable-frequency three-dimensional structured illumination microscopy with reduced data-acquisition.

The performance of a tunable three-dimensional (3D) structured illumination microscope (SIM) system and its ability to provide simultaneously super-resolution (SR) and optical-sectioning (OS) capabilities are investigated. Numerical results show that the performance of our 3D-SIM system is comparable with the one provided by a three-wave interference SIM, while requiring 40% fewer images for the reconstruction and providing frequency tunability in a cost-effective implementation. The performance of the system has been validated experimentally with images from test samples, which were also imaged with a commercial SIM based on incoherent-grid projection for comparison. Restored images from data acquired from an axially-thin fluorescent layer show a 1.6× improvement in OS capability compared to the commercial instrument while results from a fluorescent tilted USAF target show the OS and SR capabilities achieved by our system.

Image restoration approach to address reduced modulation contrast in structured illumination microscopy.

The performance of structured illumination microscopy (SIM) is hampered in many biological applications due to the inability to modulate the light when imaging deep into the sample. This is in part because sample-induced aberration reduces the modulation contrast of the structured pattern. In this paper, we present an image restoration approach suitable for processing raw incoherent-grid-projection SIM data with a low fringe contrast. Restoration results from simulated and experimental ApoTome SIM data show results with improved signal-to-noise ratio (SNR) and optical sectioning compared to the results obtained from existing methods, such as 2D demodulation and 3D SIM deconvolution. Our proposed method provides satisfactory results (quantified by the achieved SNR and normalized mean square error) even when the modulation contrast of the illumination pattern is as low as 7%.

Improvement of two-dimensional structured illumination microscopy with an incoherent illumination pattern of tunable frequency.

In two-dimensional structured illumination microscopy (2D-SIM), high-resolution images with optimal optical sectioning (OS) cannot be obtained simultaneously. This tradeoff can be overcome by using a tunable-frequency 2D-SIM system and a proper reconstruction method. The goal of this work is twofold. First, we present a computational approach to reconstruct optical-sectioned images with super-resolution enhancement (OS-SR) by using a tunable SIM system. Second, we propose an incoherent tunable-frequency 2D-SIM system based on a Fresnel biprism implementation. Integration of the proposed computational method with this tunable structured illumination (SI) system results in a new 2D-SIM system that is advantageous compared to other 2D-SIM systems with comparable complexity, because it provides high-resolution OS images independent of the objective lens used, without the presence of coherent noise and without reducing the contrast of the structured pattern, as in other incoherent implementations. Evaluation of our proposed system is demonstrated with comparative studies of simulated and experimental reconstructed images to validate our theoretical findings. Our experimental results show a simultaneous improvement of the lateral resolution by a factor of 1.8× with the desired OS capability achieved in the resulting OS-SR combination image. Our experimental results also verify that our system can provide better OS capability than the commercial Zeiss ApoTome-SIM system in the investigated study.

Experimental validation of a customized phase mask designed to enable efficient computational optical sectioning microscopy through wavefront encoding.

In this paper, wavefront-encoded (WFE) computational optical sectioning microscopy (COSM) using a fabricated square cubic (SQUBIC) phase mask, designed to render the system less sensitive to depth-induced aberration, is investigated. The WFE-COSM system is characterized by a point spread function (PSF) that does not vary as rapidly with imaging depth compared to the conventional system. Thus, in WFE-COSM, image restoration from large volumes can be achieved using computationally efficient space-invariant (SI) algorithms, thereby avoiding the use of depth-variant algorithms. The fabricated SQUBIC phase mask was first evaluated and found to have a 75% fidelity compared to the theoretical design; it was then integrated in a commercial wide-field microscope to implement a WFE-COSM system. Evaluation of the WFE-COSM system is demonstrated with comparative studies of theoretical and experimental PSFs and simulated and measured images of spherical shells located at different depths in a test sample. These comparisons show that PSF and imaging models capture major trends in experimental data with a 99% correlation between forward image intensity distribution in experimental and simulated images of spherical shells. Our experimental SI restoration results demonstrate that the WFE-COSM system achieves more than a twofold performance improvement over the conventional system of up to a 65 µm depth below the coverslip investigated in this study.