Numerical wave propagation in ImageJ

Open-access database for digital lensless holographic microscopy and its application on the improvement of deep-learning-based autofocusing models

Among modern optical microscopy techniques, digital lensless holographic microscopy (DLHM) is one of the simplest label-free coherent imaging approaches. However, the hardware simplicity provided by the lensless configuration is often offset by the demanding computational postprocessing required to match the retrieved sample information to the user's expectations. A promising avenue to simplify this stage is the integration of artificial intelligence and machine learning (ML) solutions into the DLHM workflow. The biggest challenge to do so is the preparation of an extensive and high-quality experimental dataset of curated DLHM recordings to train ML models. In this work, a diverse, open-access dataset of DLHM recordings is presented as support for future research, contributing to the data needs of the applied research community. The database comprises 11,760 experimental DLHM holograms of bio and non-bio samples with diversity on the main recording parameters of the DLHM architecture. The database is divided into two datasets of 10 independent imaged samples. The first group, named multi-wavelength dataset, includes 8160 holograms and was recorded using laser diodes emitting at 654 nm, 510 nm, and 405 nm; the second group, named single-wavelength dataset, is composed of 3600 recordings and was acquired using a 633 nm He-Ne laser. All the experimental parameters related to the dataset acquisition, preparation, and calibration are described in this paper. The advantages of this large dataset are validated by re-training an existing autofocusing model for DLHM and as the training set for a simpler architecture that achieves comparable performance, proving its feasibility for improving existing ML-based models and the development of new ones.

Dual-wavelength off-axis digital holography in ImageJ: toward real-time phase retrieval using CUDA streams

An ImageJ plug-in is developed to realize automatic real-time phase reconstruction for dual-wavelength digital holography (DH). This plug-in assembles the algorithms, including automatic phase reconstruction based on the division algorithm and post-processing. These algorithms are implemented and analyzed using a CPU and GPU, respectively. To hide the CPU-to-GPU data transfer latency, an optimization scheme using Compute Unified Device Architecture (CUDA) streams is proposed in ImageJ. Experimental results show that the proposed plug-in can perform faster reconstruction for dual-wavelength DH, resulting in frame rates up to 48 fps even for one-megapixel digital holograms on a normal PC. In other words, the proposed plug-in can realize real-time phase reconstruction for dual-wavelength digital holographic videos.

Recent advances in experimental design and data analysis to characterize prokaryotic motility

Bacterial motility plays a key role in important cell processes such as chemotaxis and biofilm formation, but is challenging to quantify due to the small size of the individual microorganisms and the complex interplay of biological and physical factors that influence motility phenotypes. Swimming, the first type of motility described in bacteria, still remains largely unquantified. Light microscopy has enabled qualitative characterization of swimming patterns seen in different strains, such as run and tumble, run-reverse-flick, run and slow, stop and coil, and push and pull, which has allowed for elucidation of the underlying physics. However, quantifying these behaviors (e.g., identifying run distances and speeds, turn angles and behavior by surfaces or cell-cell interactions) remains a challenging task. A qualitative and quantitative understanding of bacterial motility is needed to bridge the gap between experimentation, omics analysis, and bacterial motility theory. In this review, we discuss the strengths and limitations of how phase contrast microscopy, fluorescence microscopy, and digital holographic microscopy have been used to quantify bacterial motility. Approaches to automated software analysis, including cell recognition, tracking, and track analysis, are also discussed with a view to providing a guide for experimenters to setting up the appropriate imaging and analysis system for their needs.

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.

High-speed measurement of mechanical micro-deformations with an extended phase range using dual-wavelength digital holographic interferometry

The implementation of a digital holographic interferometry setup for high-speed micro-deformation measurement is presented. This proposal uses a dual-wavelength recording strategy to reconstruct micro-deformations up to 4.85 µm with no phase wrapping. The numerical processing required to recover the phase maps containing the information of micro-deformations is carried out in a general-purpose computing on graphics processing unit environment to boost its performance. The method completely processes recorded holograms of 1024×1024pixels in 48 ms, i.e., 21 frames per second (FPS) for a single-wavelength acquisition and 96 ms or 11 FPS for dual-wavelength recordings. The method is experimentally evaluated measuring deformations ranging from 0.033 µm to 4.85 µm with no need for phase unwrapping algorithms for an 8 cm diameter aluminum plate in a 110cm² field of view.

Realistic simulation and real-time reconstruction of digital holographic microscopy experiments in ImageJ

The description, implementation, and validation of an ImageJ plugin that allows the realistic simulation and real-time reconstruction of digital holographic microscopy (DHM) experiments are presented. The simulation module implements a telecentric image-plane DHM recording scheme with fully configurable imaging system, interference, and scaling parameters, including the possibility of defining an estimate of the roughness distribution of the sample to produce realistic coherent-noise affectations. The reconstruction module allows the computation of amplitude, intensity, or phase, from digital holograms' input as either single images or video streams for real-time processing; this module also implements user-defined fine-tuning parameters, allowing subpixel linear phase compensations and digital refocusing of the complex-valued reconstructed fields. In this note, the functionality of the plugin is illustrated by simulating the noisy DHM recording of a phase-only resolution test target and the reconstruction of both the resulting synthetic hologram and an equivalent experimental recording; the results show good agreement between the simulation and the experimental recording, and accurate measurements on the reconstructed information, thus granting the use of either module with full confidence according to needs and possibilities.

Digital lensless holographic microscopy: numerical simulation and reconstruction with ImageJ

The description and validation of an ImageJ open-source plugin to numerically simulate and reconstruct digital lensless holographic microscopy (DLHM) holograms are presented. Two modules compose the presented plugin: the simulation module implements a discrete version of the Rayleigh-Somerfield diffraction formula, which allows the user to directly build a simulated hologram from a known phase and/or amplitude object by just introducing the geometry parameters of the simulated setup; the plugin's reconstruction module implements a discrete version of the Kirchhoff-Helmholtz diffraction integral, thus allowing the user to reconstruct DLHM holograms by introducing the parameters of the acquisition setup and the desired reconstruction distance. The plugin offers the two said modules within the robust environment provided by a complete set of built-in tools for image processing available in ImageJ. While the simulation module has been validated through the evaluation of the forecasted lateral resolution of a DLHM setup in terms of the numerical aperture, the reconstruction module is tested by means of reconstructing experimental DLHM holograms of biological samples.

Off-axis digital holography with multiplexed volume Bragg gratings

We report on an optical imaging design based on common-path off-axis digital holography, using a multiplexed volume Bragg grating. In the reported method, a reference optical wave is made by deflection and spatial filtering through a volume Bragg grating. This design has several advantages, including simplicity, stability, and robustness against misalignment.

Single-shot 3D topography of reflective samples with digital holographic microscopy

In this work, an off-axis digital holographic microscope operating in reflection mode and a telecentric regimen to produce 3D topography of a microscopy sample is shown. The main characteristics of the proposed method, which make it different from the previous works in the field, are the possibility of producing the 3D topography by a single shot over the complete field of view with sensitivity of λ/100, without phase perturbations introduced by the illuminating-imaging system, and with no further numerical processing beyond that required for recovering the phase map of the sample. A complete analysis of the illuminating-imaging system of the digital holographic microscope is presented. The proposed digital holographic microscope is tested on imaging a USAF resolution test target and some micro-electromechanical systems (MEMs).

Quantifying Microorganisms at Low Concentrations Using Digital Holographic Microscopy (DHM)

Accurately detecting and counting sparse bacterial samples has many applications in the food, beverage, and pharmaceutical processing industries, in medical diagnostics, and for life detection by robotic missions to other planets and moons of the solar system. Currently, sparse bacterial samples are counted by culture plating or epifluorescence microscopy. Culture plates require long incubation times (days to weeks), and epifluorescence microscopy requires extensive staining and concentration of the sample. Here, we demonstrate how to use off-axis digital holographic microscopy (DHM) to enumerate bacteria in very dilute cultures (100-10⁴ cells/mL). First, the construction of the custom DHM is discussed, along with detailed instructions on building a low-cost instrument. The principles of holography are discussed, and a statistical model is used to estimate how long videos should be to detect cells, based on the optical performance characteristics of the instrument and the concentration of the bacterial solution (Table 2). Video detection of cells at 10⁵, 10⁴, 10³, and 100 cells/mL is demonstrated in real time using un-reconstructed holograms. Reconstruction of amplitude and phase images is demonstrated using an open-source software package.

High speed optical holography of retinal blood flow

We performed noninvasive video imaging of retinal blood flow in a pigmented rat by holographic interferometry of near-infrared laser light backscattered by retinal tissue, beating against an off-axis reference beam sampled at a frame rate of 39 kHz with a high throughput camera. Local Doppler contrasts emerged from the envelopes of short-time Fourier transforms and the phase of autocorrelation functions of holograms rendered by Fresnel transformation. This approach permitted imaging of blood flow in large retinal vessels (∼30 microns diameter) over 400×400  pixels with a spatial resolution of ∼8 microns and a temporal resolution of ∼6.5  ms.