Compact and field-portable 3D printed shearing digital holographic microscope for automated cell identification

Characterization of Optical, Thermal, and Viscoelastic Properties of Pollenkitt in Angiosperm Pollen Using In-Line Digital Holographic Microscopy

Pollen grains are remarkable material composites, with various organelles in their fragile interior protected by a strong shell made of sporopollenin. The outermost layer of angiosperm pollen grains contains a lipid-rich substance called pollenkitt, which is a natural bioadhesive that helps preserve structural integrity when the pollen grain is exposed to external environmental stresses. In addition, its viscous nature enables it to adhere to various floral and insect surfaces, facilitating the pollination process. To examine the physicochemical properties of aqueous pollenkitt droplets, we used in-line digital holographic microscopy to capture light scattering from individual pollenkitt particles. Comparison of pollenkitt holograms to those modeled using the Lorenz-Mie theory enables investigations into the minute variations in the refractive index and size resulting from changes in local temperature and pollen aging.

Simple high-resolution 3D microscopy by a dielectric microsphere: a proof of concept

We present a simple high-resolution approach for 3D and quantitative phase imaging (QPI). Our method makes the most of a glass microsphere (MS) for microscopy and a glass plate for lateral shearing self-referencing interferometry. The single MS serves all the functions of a microscope objective (MO) in digital holographic microscopy (DHM) while offering the advantages of compactness, lightness, and affordability. A proof-of-concept experiment is performed on a standard diffraction grating, and various effective parameters on the imaging performance are investigated. The results are validated by atomic force microscopy and Mirau-DHM, and 3D morphometric information of the sample under inspection is obtained. The technique is then applied for 3D quantitative measurement and visualization of a human red blood cell, proving the principle of our easy-to-implement and vibration-immune arrangement for high-contrast label-free QPI of biological samples, and its utility in cell morphology, identification, and classification.

Label-Free Digital Holotomography Reveals Ibuprofen-Induced Morphological Changes to Red Blood Cells

Understanding the dose-dependent effect of over-the-counter drugs on red blood cells (RBCs) is crucial for hematology and digital pathology. Yet, it is challenging to continuously record the real-time, drug-induced shape changes of RBCs in a label-free manner. Here, we demonstrate digital holotomography (DHTM)-enabled real-time, label-free concentration-dependent and time-dependent monitoring of ibuprofen on RBCs from a healthy donor. The RBCs are segmented based on three-dimensional (3D) and four-dimensional (4D) refractive index tomograms, and their morphological and chemical parameters are retrieved with their shapes classified using machine learning. We directly observed the formation and motion of spicules on the RBC membrane when aqueous solutions of ibuprofen were drop-cast on wet blood, creating rough-membraned echinocyte forms. At low concentrations of 0.25-0.50 mM, the ibuprofen-induced morphological change was transient, but at high concentrations (1-3 mM) the spiculated RBC remained over a period of up to 1.5 h. Molecular simulations confirmed that aggregates of ibuprofen molecules at high concentrations significantly disrupted the RBC membrane structural integrity and lipid order but produced negligible effect at low ibuprofen concentrations. Control experiments on the effect of urea, hydrogen peroxide, and aqueous solutions on RBCs showed zero spicule formation. Our work clarifies the dose-dependent chemical effects on RBCs using label-free microscopes that can be deployed for the rapid detection of overdosage of over-the-counter and prescribed drugs.

A biophotonic platform for quantitative analysis in the spatial, spectral, polarimetric, and goniometric domains

Advanced instrumentation and versatile setups are needed for understanding light interaction with biological targets. Such instruments include (1) microscopes and 3D scanners for detailed spatial analysis, (2) spectral instruments for deducing molecular composition, (3) polarimeters for assessing structural properties, and (4) goniometers probing the scattering phase function of, e.g., tissue slabs. While a large selection of commercial biophotonic instruments and laboratory equipment are available, they are often bulky and expensive. Therefore, they remain inaccessible for secondary education, hobbyists, and research groups in low-income countries. This lack of equipment impedes hands-on proficiency with basic biophotonic principles and the ability to solve local problems with applied physics. We have designed, prototyped, and evaluated the low-cost Biophotonics, Imaging, Optical, Spectral, Polarimetric, Angular, and Compact Equipment (BIOSPACE) for high-quality quantitative analysis. BIOSPACE uses multiplexed light-emitting diodes with emission wavelengths from ultraviolet to near-infrared, captured by a synchronized camera. The angles of the light source, the target, and the polarization filters are automated by low-cost mechanics and a microcomputer. This enables multi-dimensional scatter analysis of centimeter-sized biological targets. We present the construction, calibration, and evaluation of BIOSPACE. The diverse functions of BIOSPACE include small animal spectral imaging, measuring the nanometer thickness of a bark-beetle wing, acquiring the scattering phase function of a blood smear and estimating the anisotropic scattering and the extinction coefficients, and contrasting muscle fibers using polarization. We provide blueprints, component list, and software for replication by enthusiasts and educators to simplify the hands-on investigation of fundamental optical properties in biological samples.

Off-axis common-path digital holography using a cube beam splitter

An off-axis common-path digital holography is built up by inserting a 45° tilted cube beam splitter (CBS) into a 4f system that is described in this paper. Two apertures are set as the input of the 4f system, where one supports the object, and the other is vacant. The CBS divides the incoming beam into two copies, which are symmetrical with each other along the semi-reflecting layer. Due to the separation of two beams in a Fourier plane and the flipping of the field of view induced by the CBS, an off-axis hologram can be captured. Moreover, the carrier frequency can be easily modulated by translating the CBS perpendicular to the optical axis. The new proposed scheme has high light utilization, a compact setup, and high temporal stability. The experiments are carried out to demonstrate the validity and stability of the proposed method.

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.

The Field Guide to 3D Printing in Optical Microscopy for Life Sciences

The maker movement has reached the optics labs, empowering researchers to create and modify microscope designs and imaging accessories. 3D printing has a disruptive impact on the field, improving accessibility to fabrication technologies in additive manufacturing. This approach is particularly useful for rapid, low-cost prototyping, allowing unprecedented levels of productivity and accessibility. From inexpensive microscopes for education such as the FlyPi to the highly complex robotic microscope OpenFlexure, 3D printing is paving the way for the democratization of technology, promoting collaborative environments between researchers, as 3D designs are easily shared. This holds the unique possibility of extending the open-access concept from knowledge to technology, allowing researchers everywhere to use and extend model structures. Here, it is presented a review of additive manufacturing applications in optical microscopy for life sciences, guiding the user through this new and exciting technology and providing a starting point to anyone willing to employ this versatile and powerful new tool.

Linear diattenuation imaging of biological samples with digital lensless holographic microscopy

A digital lensless holographic microscope (DLHM) sensitive to the linear diattenuation produced by biological samples is reported. The insertion of a linear polarization-states generator and a linear polarization-states analyzer in a typical DLHM setup allows the proper linear diattenuation imaging of microscopic samples. The proposal has been validated for simulated and experimental biological samples containing calcium oxalate crystals extracted from agave leaves and potato starch grains. The performance of the proposed method is similar to that of a traditional polarimetric microscope to obtain linear diattenuation images of microscopic samples but with the advantages of DLHM, such as numerical refocusing, cost effectiveness, and the possibility of field-portable implementation.

Automated analysis of human cardiomyocytes dynamics with holographic image-based tracking for cardiotoxicity screening

This paper proposes a new non-invasive, low-cost, and fully automated platform to quantitatively analyze dynamics of human-induced pluripotent stem cell-derived cardiomyocytes (hiPS-CMs) at the single-cell level by holographic image-based tracking for cardiotoxicity screening. A dense Farneback optical flow method and holographic imaging informatics were combined to characterize the contractile motion of a single CM, which obviates the need for costly equipment to monitor a CM's mechanical beat activity. The reliability of the proposed platform was tested by single-cell motion characterization, synchronization analysis, motion speed measurement of fixed CMs versus live CMs, and noise sensitivity. The applicability of the motion characterization method was tested to determine the pharmacological effects of two cardiovascular drugs, isoprenaline (166 nM) and E-4031 (500 μM). The experiments were done using single CMs and multiple cells, and the results were compared to control conditions. Cardiomyocytes responded to isoprenaline by increasing the action potential (AP) speed and shortening the resting period, thus increasing the beat frequency. In the presence of E-4031, the AP speed was decreased, and the resting period was prolonged, thus decreasing the beat frequency. The findings offer insights into single hiPS-CMs' contractile motion and a deep understanding of their kinetics at the single-cell level for cardiotoxicity screening.

Roadmap on digital holography [Invited]

This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography.

PhaseRMiC: phase real-time microscope camera for live cell imaging

We design a novel phase real-time microscope camera (PhaseRMiC) for live cell phase imaging. PhaseRMiC has a simple and cost-effective configuration only consisting of a beam splitter and a board-level camera with two CMOS imaging chips. Moreover, integrated with 3-D printed structures, PhaseRMiC has a compact size of 136×91×60 mm³, comparable to many commercial microscope cameras, and can be directly connected to the microscope side port. Additionally, PhaseRMiC can be well adopted in real-time phase imaging proved with satisfied accuracy, good stability and large field of view. Considering its compact and cost-effective device design as well as real-time phase imaging capability, PhaseRMiC is a preferred solution for live cell imaging.

Accurate and practical feature extraction from noisy holograms

Quantitative phase imaging using holographic microscopy is a powerful and non-invasive imaging method, ideal for studying cells and quantifying their features such as size, thickness, and dry mass. However, biological materials scatter little light, and the resulting low signal-to-noise ratio in holograms complicates any downstream feature extraction and hence applications. More specifically, unwrapping phase maps from noisy holograms often fails or requires extensive computational resources. We present a strategy for overcoming the noise limitation: rather than a traditional phase-unwrapping method, we extract the continuous phase values from holograms by using a phase-generation technique based on conditional generative adversarial networks employing a Pix2Pix architecture. We demonstrate that a network trained on random surfaces can accurately generate phase maps for test objects such as dumbbells, spheres, and biconcave discoids. Furthermore, we show that even a rapidly trained network can generate faithful phase maps when trained on related objects. We are able to accurately extract both morphological and quantitative features from the noisy phase maps of human leukemia (HL-60) cells, where traditional phase unwrapping algorithms fail. We conclude that deep learning can decouple noise from signal, expanding potential applications to real-world systems that may be noisy.

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.

Deep learning-based cell identification and disease diagnosis using spatio-temporal cellular dynamics in compact digital holographic microscopy

We demonstrate a successful deep learning strategy for cell identification and disease diagnosis using spatio-temporal cell information recorded by a digital holographic microscopy system. Shearing digital holographic microscopy is employed using a low-cost, compact, field-portable and 3D-printed microscopy system to record video-rate data of live biological cells with nanometer sensitivity in terms of axial membrane fluctuations, then features are extracted from the reconstructed phase profiles of segmented cells at each time instance for classification. The time-varying data of each extracted feature is input into a recurrent bi-directional long short-term memory (Bi-LSTM) network which learns to classify cells based on their time-varying behavior. Our approach is presented for cell identification between the morphologically similar cases of cow and horse red blood cells. Furthermore, the proposed deep learning strategy is demonstrated as having improved performance over conventional machine learning approaches on a clinically relevant dataset of human red blood cells from healthy individuals and those with sickle cell disease. The results are presented at both the cell and patient levels. To the best of our knowledge, this is the first report of deep learning for spatio-temporal-based cell identification and disease detection using a digital holographic microscopy system.

Common-path phase-shift microscope based on measurement of Stokes parameters S2 and S3 for 3D phase extraction

In this paper, we report a common-path, phase-shift optical microscope based on measurement of Stokes parameters S₂ and S₃ to extract the three-dimensional (3D) phase map of transparent objects with high precision. The microscope employs three polarizers and two identical quarter-wave plates to extract S₂ and S₃. The reference phase in the absence of the object is subtracted from the total phase in the presence of the object to extract the 3D phase of the object. The microscope is tested on imaging a USAF resolution test target and a reticle test pattern with excellent results. To the best of our knowledge, this is the first report of a common-path phase-shift optical microscope for 3D phase extraction based on measurement of Stokes parameters S₂ and S₃.

Continuous-wave terahertz self-referencing digital holography based on Fresnel's mirrors

Continuous-wave terahertz digital holography (TDH) is a booming full-field phase-contrast imaging method validated in both in-line and Mach-Zehnder off-axis geometries. In this Letter, a self-referencing TDH approach is proposed based on the Fresnel's mirrors, by which the object wavefront is partitioned and reflected. Two beams interfere with each other to form an off-axis hologram. The proposed recording configuration is immune from a superposed twin image and has higher temporal stability than Mach-Zehnder interferometers. To evaluate the phase-contrast imaging performance, different types of samples are measured.

Autofocusing and image fusion for multi-focus plankton imaging by digital holographic microscopy

Digital holographic microscopy is becoming increasingly useful for the analysis of marine plankton. In this study, we investigate autofocusing and image fusion in digital holographic microscopy. We propose an area metric autofocusing method and an improved wavelet-based image fusion method. In the area metric autofocusing method, a hologram image is initially segmented into several plankton regions for focus plane detection, and an area metric is then applied to these regions. In the improved wavelet-based image fusion method, a marked map is introduced for labeling each plankton region with the order of refocus plane images that accounts for the most pixels. The results indicate that the area metric autofocusing method applied to each plankton region provides a higher depth resolution accuracy than a number of general autofocusing methods, and the mean accuracy increases by approximately 33%. The improved wavelet-based image fusion method can fuse more than nine reconstructed plane images at a time and effectively eliminate fringes and speckle noise, and the fused image is much clearer than that of a general wavelet-based method, a sparse decomposition method, and a pulse-coupled neural networks method. This work has practical value for plankton imaging using digital holographic microscopy.

Deep learning-based optical field screening for robust optical diffraction tomography

In tomographic reconstruction, the image quality of the reconstructed images can be significantly degraded by defects in the measured two-dimensional (2D) raw image data. Despite the importance of screening defective 2D images for robust tomographic reconstruction, manual inspection and rule-based automation suffer from low-throughput and insufficient accuracy, respectively. Here, we present deep learning-enabled quality control for holographic data to produce robust and high-throughput optical diffraction tomography (ODT). The key idea is to distil the knowledge of an expert into a deep convolutional neural network. We built an extensive database of optical field images with clean/noisy annotations, and then trained a binary-classification network based upon the data. The trained network outperformed visual inspection by non-expert users and a widely used rule-based algorithm, with >90% test accuracy. Subsequently, we confirmed that the superior screening performance significantly improved the tomogram quality. To further confirm the trained model's performance and generalisability, we evaluated it on unseen biological cell data obtained with a setup that was not used to generate the training dataset. Lastly, we interpreted the trained model using various visualisation techniques that provided the saliency map underlying each model inference. We envision the proposed network would a powerful lightweight module in the tomographic reconstruction pipeline.

Micrometric size measurement of biological samples using a simple and non-invasive transmission interferometric set up

An interferometer with a minimum of optical hardware is employed to measure invasiveness the size of biological samples. Nowadays, there are several techniques in microscopy that render high quality resolved images. For instance, consider optical microscopy that has been around for over a century and has since developed in different configurations such as: bright and dark field, phase contrast, confocal, polarized, and so on. However, only a few of these use interferometry to retrieve not only the sample's amplitude but also its phase. An interesting example of the latter is digital holography which normally uses a Mach Zehnder interferometer setup. In the research work reported here a transmission digital holographic interferometer designed with a simple and minimal optical hardware, that avoids the drawback of the small field of view present in classical optical microscopic systems, is used to measure the microscopic dimensions of pollen grains. This optical configuration can be manipulated to magnify and project the image of a semitransparent sample over a neutral phase screen. The use of a collimated beam through the sample prevents geometrical distortions for high magnification values. The measurements using this novel configuration have been validated using a standard precision pattern displacement specimen with certified dimensions. As proof of principle, microscopically characterized pollen grains are placed in the transmission set up in order to estimate their dimensions from the interferometrically retrieved optical phase. Results match and thus show a relation between the sample's size and the optical phase magnitude.

Quantitative phase imaging based on simple Michelson-type lateral shearing interferometry with rotational right-angle prisms

By using a kind of simple Michelson-type lateral shearing interferometry, in this paper, the precise quantitative phase measurement of transparent microscopic objects is realized successfully. For this interferometry, on the basis of the fundamental structure of the traditional Michelson interferometer, the two plane mirrors are replaced with two ordinary right-angle prisms. In the beginning, the ridges of the two right-angle prisms are set to align with the optical axis and be in the vertical direction. Subsequently, to achieve the lateral shear, one of these two right-angle prisms is rotated around its ridge. Furthermore, the goal to obtain more lateral shear can be achieved by introducing a bigger rotating angle or rotating another prism simultaneously. In addition, owing to the simple structure of the Michelson interferometer and the inexpensive optical components used, the system is compact, portable, easy to operate, and low cost. The experimental results show the practicability of this system.

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.

Cycle-consistent deep learning approach to coherent noise reduction in optical diffraction tomography

We present a deep neural network to reduce coherent noise in three-dimensional quantitative phase imaging. Inspired by the cycle generative adversarial network, the denoising network was trained to learn a transform between two image domains: clean and noisy refractive index tomograms. The unique feature of this network, distinct from previous machine learning approaches employed in the optical imaging problem, is that it uses unpaired images. The learned network quantitatively demonstrated its performance and generalization capability through denoising experiments of various samples. We concluded by applying our technique to reduce the temporally changing noise emerging from focal drift in time-lapse imaging of biological cells. This reduction cannot be performed using other optical methods for denoising.

3D-printed miniaturized fluidic tools in chemistry and biology

3D printing (3DP), an additive manufacturing (AM) approach allowing for rapid prototyping and decentralized fabrication on-demand, has become a common method for creating parts or whole devices. The wide scope of the AM extends from organized sectors of construction, ornament, medical, and R&D industries to individual explorers attributed to the low cost, high quality printers along with revolutionary tools and polymers. While progress is being made but big manufacturing challenges are still there. Considering the quickly shifting narrative towards miniaturized analytical systems (MAS) we focus on the development/rapid prototyping and manufacturing of MAS with 3DP, and application dependent challenges in engineering designs and choice of the polymeric materials and provide an exhaustive background to the applications of 3DP in biology and chemistry. This will allow readers to perceive the most important features of AM in creating (i) various individual and modular components, and (ii) complete integrated tools.

Sickle cell disease diagnosis based on spatio-temporal cell dynamics analysis using 3D printed shearing digital holographic microscopy

We present a spatio-temporal analysis of cell membrane fluctuations to distinguish healthy patients from patients with sickle cell disease. A video hologram containing either healthy red blood cells (h-RBCs) or sickle cell disease red blood cells (SCD-RBCs) was recorded using a low-cost, compact, 3D printed shearing interferometer. Reconstructions were created for each hologram frame (time steps), forming a spatio-temporal data cube. Features were extracted by computing the standard deviations and the mean of the height fluctuations over time and for every location on the cell membrane, resulting in two-dimensional standard deviation and mean maps, followed by taking the standard deviations of these maps. The optical flow algorithm was used to estimate the apparent motion fields between subsequent frames (reconstructions). The standard deviation of the magnitude of the optical flow vectors across all frames was then computed. In addition, seven morphological cell (spatial) features based on optical path length were extracted from the cells to further improve the classification accuracy. A random forest classifier was trained to perform cell identification to distinguish between SCD-RBCs and h-RBCs. To the best of our knowledge, this is the first report of machine learning assisted cell identification and diagnosis of sickle cell disease based on cell membrane fluctuations and morphology using both spatio-temporal and spatial analysis.

Single-shot dual-wavelength off-axis quasi-common-path digital holography using polarization-multiplexing

We present a dual-wavelength off-axis quasi-common-path digital holography for quantitative phase imaging using polarization-multiplexing in a single shot. Employing an off-axis nearly common-path configuration, our approach separates the two-wavelength information using a polarizing beam splitter, while modulates the orthogonal fringe directions for each wavelength using two retro-reflector mirrors, and thus generates a single multiplexed off-axis interferogram on a monochrome CCD camera. The information of a specimen, including phase and height, is reconstructed through a division algorithm for dual wavelengths with the help of a specimen-free multiplexed interferogram. The experimental results obtained on a square step target and a circular step target illustrate the validity and stability of our setup.

Double-channel angular-multiplexing polarization holography with common-path and off-axis configuration

We propose a double-channel angular-multiplexing polarization holographic imaging system with common-path and off-axis configurations. In the system, its input plane is spatially divided into three windows: an object window and two reference windows, and two orthogonal linear polarizers are attached, respectively, on the two reference windows; a two-dimensional cross grating is inserted between the input and output planes of the system. Thus the object beam passing through the object window and the two orthogonal polarized reference beams passing through the two reference windows can overlap each other at the output plane of the system and form a double-channel angular-multiplexing polarization hologram (DC-AM-PH). Using this system, the complex amplitude distributions of two orthogonal polarized components from an object can be recorded and reconstructed by one single-shot DC-AM-PH at the same time. Theoretical analysis and experimental results demonstrated that the system can be used to measure the Jones matrix parameters of polarization-sensitive or birefringent materials.

Compact lensless off-axis transmission digital holographic microscope

Current compact lensless holographic microscopes are based on either multiple angle in-line holograms, multiple wavelength illumination or a combination thereof. Complex computational algorithms are necessary to retrieve the phase image which slows down the visualization of the image. Here we propose a simple compact lensless transmission holographic microscope with an off-axis configuration which simplifies considerably the computational processing to visualize the phase images and opens the possibility of real time phase imaging using off the shelf smart phone processors and less than $3 worth of optics and detectors, suitable for broad educational dissemination. This is achieved using a side illumination and analog hologram gratings to shape the reference and signal illumination beams from one light source. We demonstrate experimentally imaging of cells with a field of view (FOV) of ~12mm², and a resolution of ~3.9μm.

Modern imaging: introduction to the feature issue

This special issue of Applied Optics contains selected papers reflecting the various disciplines that are needed for the design, implementation and advancement of imaging technology and systems, and it highlights the state-of-the-art research developments in the areas of modern imaging use.