This PDF file contains the front matter associated with SPIE Proceedings Volume 11060, including the Title Page, Copyright information, Table of Contents, and Conference Committee listing.

This work presents the development of an Echelle spectrometer that is optimized for the characterization of laser-driven plasma emission of biological samples for application in smart laser surgery systems. Despite the compact (portable) and cost-efficient design of the developed spectrometer, it allows analyzing the spectrum of a plasma emitted from bone, and its surrounding soft tissues (bone marrow, muscle, and fat) in nearly the same way as a full-sized Echelle spectrometer as used in commercial laser-induced breakdown spectroscopy (LIBS) systems. Most of the commercially available Echelle spectrometers on the market use a long focal length on-axis mirror to have a reasonable F number (which defines the optical throughput of the system) and low aberration. While a long focal length requires less tilting of the mirror than a shorter focal length (the higher the tilt angle, the higher the aberration), a long focal length increases the system size and decreases sensitivity (i.e., less optical throughput). In this work, a parabolic 90o off-axis mirror with a focal length of 152.4 mm and a diameter of 50.8 mm, which leads to an F-number of 3, has been used. This low F-number provides a high optical throughput compared to other similar commercial Echelle spectrometers with F-numbers of 10 or more [1-5]. Since most of the important peaks in biological tissue are in the interval of 240 to 840 nm [6], the design was done by using off-the-shelf aluminum mirrors with a UV-enhanced coating for both collimating and focusing purposes to cover this range with sub-Angstrom resolution. Both collimating and focusing mirrors were chosen with the same radius of curvature and declination angle (opposite direction) to cancel the coma. In this antiparallel configuration, the second parabolic mirror largely eliminates the aberrations from the first one. Moreover, we positioned the Echelle grating under the condition of quasi-Littrow design to have high diffraction efficiency with an off-axis angle in the horizontal plane. A ruled reflection grating with dispersion perpendicular to that of the Echelle grating was utilized as a cross dispenser (order separator) after the Echelle grating to distinguish the overlapping diffraction harmonics. The spectrometer has been connected to a gated ICCD to measure time-resolved spectra. The developed spectrometer was installed on a 3-tier utility cart, the inducing laser (Q-switched Nd:YAG) for LIBS was placed on the middle tier, and the last tier was dedicated for calibration instruments (a NIST traceable balanced Deuterium-Halogen light source for intensity calibration, and some gas/vapor spectral lamps including Mercury-Argon, Argon, Neon, and Krypton for wavelength calibration). The portability feature of this LIBS setup provides a remarkable value for testing and characterizing different biological samples on-site. This is a great capability especially if the target sample has the potential of being contagious. This setup is meant to be used for so-called smart laser osteotomies, i.e., the osteotome will be able to identify the type of the tissue being cut through the feedback provided by LIBS [6-8]. [1] M. Farsad, "A design cycle for echelle spectrometers," Proc. SPIE 10590, 105901F (2017). [2] M. Hoehse et al.,"A combined laser-induced breakdown and Raman spectroscopy Echelle system for elemental and molecular microanalysis," Spectrochimica Acta Part B: Atomic Spectroscopy 64, 1219-1227 (2009). [3] M. Sabsabi et al., "Comparative study of two new commercial echelle spectrometers equipped with intensified CCD for analysis of laser-induced breakdown spectroscopy," Applied Optics 42, 6094-6098 (2003). [4] S. Florek et al., "new, versatile echelle spectrometer relevant to laser induced plasma applications," Spectrochimica Acta Part B 56, 1027-1034 (2001). [5] C. Haisch, "Combination of an intensified charge coupled device with an echelle spectrograph for analysis of colloidal material by laser–induced plasma spectroscopy," Spectrochimica Acta Part B 53, 1657-1667 (1998). [6] H. Abbasi et al., "Differentiation of femur bone from surrounding soft tissue using laser induced breakdown spectroscopy as a feedback system for smart laserosteotomy", Proc. SPIE 10685, 1068519 (2018). [7] F. Mehari et al., "Investigation of the differentiation of ex vivo nerve and fat tissues using laser‐induced breakdown spectroscopy (LIBS): Prospects for tissue‐specific laser surgery," Journal of Biophotonics 9 (10), 1021-1032 (2016). [8] R. K. Gill et al., "Preliminary fsLIBS study on bone tumors," Biomedical optics express 6(12), 4850-4858 (2015).

Endoscopy is a key technology in biomedical engineering. It enables minimal invasive optical access deep into tissue. State of the art is to use coherent fiber bundles (CFB) in conjunction with rigid lens systems. Thus, structures can be detected in a fixed distance to the probe tip. However, the lens system limits the minimum diameter of the endoscope to several millimeters. Through imperfections, core-to-core crosstalk and bending sensitivity of the fiber only the intensity can be evaluated, and the phase information of the light gets lost. By a compensation of the phase distortion a remote phased array is enabled. Therefore, it is possible to eliminate any lens at the probe tip. Phase compensation and beam steering can be assumed by an external spatial light modulator (SLM). Thus, in principle thinner, lensless, holographic endoscopes with a three-dimensional adjustable focus for imaging and illumination can be realized. Several techniques on single mode CFB and multi-mode fibers have been presented. As a drawback they require double sided access to the fiber for the calibration, while single sided, in-vivo calibrations is essential due to the bending sensitivity of the CFB. We present the method of virtual guide star calibration by using a reflective plane with the same diameter as the CFB, only 500 μm. The design enables the generation of diffraction limited foci in a range of 150 μm x 150 μm x 1000 μm. By using a galvanometer mirror in addition to the SLM, a video rate capability of 10 Hz can be achieved for a lateral scan. The technique enables a paradigm shift for micro endoscopy and laser-assisted surgery. For the future we expect this approach will lead us to create a tool for deeper tissue imaging.

In optical microscopy, the diffraction of the light as well as the coherence limits the resolving power of the system. Observation of nanoscale elements through an optical microscope appears often to be restricted. Assuming an incoherent light source and a circular pupil, the lateral resolution of an optical microscope can thus be quantified by the cut-off frequency of the optical transfer function, given by 0.5 λ/NA, where λ and NA are the wavelength of the light source and the numerical aperture of the microscope objective, respectively. A white-light microscope thus allows the visualisation of objects having a minimum size that is just greater than half of the wavelength of the illumination in air, in ideal cases, such as features of MOEMS-based components and bacteria. In reality, imperfections or misalignment of optical components makes the resolution limit worse. Recently, several far-field methods have been developed in order to overcome this limitation, such as stimulated-emission-depletion microscopy and the negative-refractive-index superlens. In 2004, a new potential far-field microscopy technique based on the scanning photonic jet beam was proposed, leading to a lateral resolution of ~λ/3. In 2011, Wang et al. experimentally introduced the phenomenon of two-dimensional super-resolution imaging through a glass microsphere. They showed that microsphere-assisted microscopy distinguishes itself from others by being able to perform label-free and full-field acquisitions. In addition, with only slight modifications of classical white-light microscopy, microsphere-assisted microscopy makes it possible to reach a lateral resolution of a few hundred nanometres (~λ/7) which is adequate, for example, for the visualization of adenoviruses using the fluorescence effect. Placing a microsphere on (or above) a sample allows the generation of a super-resolved virtual image of the object which is then collected by a microscope objective. Although the super-resolution phenomenon is still not well understood, we now know that the performance of microsphere-aided microscopy depends on the optical and geometrical parameters. Recently, we successfully demonstrated the label-free combination of microsphere-assisted microscopy with dark-field illumination in order to image translucent samples. Random glass nanofeatures, as well as brain cell morphology, have been observed. Future work is now in progress towards the extension of 3D object inspection using interferometry.

We will present how one can use the spatial-temporal analysis of secondary speckle patterns that are generated when laser light is back scattered from a tissue in order to measure the nano-vibrations (tilting associated vibrations) occurring in the tissue and in order to map its elastography. In addition to the fundamental nano-vibrations sensing capability, the proposed configuration allows by applying time multiplexing approach also to perform separation of photons coming from different depths of the tissue while externally stimulating the tissue via infra-sonic vibration. This yields a tomographic capability. The proposed configuration uses a modulated laser that allows combining a speckle pattern tracking method for surface tilting changes sensing with a Mach–Zehnder interferometer-based speckle patterns configuration to achieve z-axis detection (movement of the whole surface in the z direction). We will also show several methods for setup modulation to down convert high temporal frequencies to allow their sampling with a slow rate camera. As to be demonstrated in the experimental validation, the different elastographic layers (that were represented in our experiments by different concentrations of the agarose) have different temporal flickering and thereafter different temporal-spectral distribution which allows to extract their different elastographic characters.

Bacteria are often associated with the insurgence of diseases and many efforts have been made to develop methods for accurate identification of bacteria in food for industry and new generation smart farms. On the other hand, there is a wide category of “good” bacteria that are used in food and pharmaceutic industry. In particular, probiotics are microbial species that have been demonstrated to confer benefits to health, acting against pathologies such as obesity, diabetes, etc. Probiotics have to maintain their viability during their transit through the gastro-intestinal apparatus in order to act to enhance the immune system. The use of alginate microcapsules is one of the most common methods of preservation, applicable to several biological matrices, including probiotics. Here we use bio-speckle decorrelation as a tool for the rapid assessment of microencapsulation effectiveness. Although speckles are often thought as a source of noise, these can be fruitfully used to increase the sensitivity of coherent imaging sensors. Thus, it is possible to characterize bacteria motion and to use it as a contrast agent for applications in food science and industry. Through bio-speckle decorrelation, we detect the presence of bacteria in food without any chemical analysis. Moreover, we quantify the shelf-time of alginate-encapsulated Lactobacillus rhamnosus and Lactobacillus plantarum probiotic bacteria and their survival rate under simulated gastro-intestinal conditions.

The spatial phase shifting digital speckle pattern shearing interferometry (DSPSI) system has been widely used to determine map of deformation. In this paper a common-path DSPSI setup is introduced for in-plane strain measurement under dynamic loading, using two laser beams with different wavelengths that symmetrically illuminate the test object, and a single detector. The simplicity, stability and efficiency of the arrangement are provided using a glass plate as a shearing device which is capable of tuning the sensitivity continuously. The phase is recovered from a single frame by the Fourier method. In this setup the spatial carrier frequencies can be adjusted independent of the lateral shearing amount. Ultimately, the desired field of view can easily be achieved by simple imaging optics. To validate the feasibility and the flexibility of our technique, the proposed setup is used to evaluate the strain map of an aluminum plate which is deformed under dynamic stress in its plane. Experimental results are presented and discussed.

A novel method for sensing low abundant lactose in small sample volumes is proposed. It is based on a pyroelectrodynamic jet (p-jet) system able to concentrate the lactose molecules onto a solid amine support for easy and rapid detection through a fluorescence measurement. The p-jet produces droplets with sub-picoliter volumes accumulated onto a microscale area of the solid support in order to reduce the diffusion limits typically occurring in standard well-based assays. A highly reproducible linear response for lactose was obtained between 2 pM/μL and 10 pM/μL. The great advantage of the technique is the ability to concentrate the molecules directly onto the solid support ready for the readout measurement by a standard fluorescence scanner. No time-consuming and expensive sample treatments are needed. The proposed method is rapid, suitable for repeated use providing a built-in quality assurance.

The generation and application of human stem-cell-derived functional neural circuits promises novel insights into neurodegenerative diseases. Optogenetics allows for the functional control of genetically altered cells with light stimuli at high spatiotemporal resolution. Optogenetics is expected to better understand, alleviate or even treat neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease. However, optogenetic investigations of neural networks are often conducted using full field illumination, potentially masking important functional information. This can be overcome with holographically shaped illumination. In this paper, we present a digital holographic illumination setup with micron spatial resolution and millisecond latensy. Single-cell real-time stimulation recording of stem-cell derived induced human neurons in a random neural network are presented. It will offer the opportunity for studies on connectivity in neural networks. Investigations on animal models with minimally invasive access often require endoscopic light delivery. Previous fiber optic endoscopes for optogenetics use naked multimode fibers. They show a speckle pattern, preventing cellular resolution. We introduce a novel endoscope with a multicore fiber and a novel holographic calibration technique. The lensless fiber endoscope reaches a spatial resolution of about 1 micron. The novel endoscope enables cellular optogenetic studies and can open a new window to the brain.

This paper proposes a review of the different opportunities described in literature for quantitative assessment of natural and reconstructed teeth using optical methods. These experimental method are particularly interesting for understanding the behavior of the natural tooth, but even more so for the CAD/CAM (Computerized aided design and computerized aided manufacturing) bonded ceramics reconstructions. Indeed CAD/CAM ceramics are increasingly used as therapeutic options. However, little is known about their mechanical behavior under stress, as the response of the prepared tooth supporting it. In the past years, optical approaches were proposed to get whole field and quantitative measurement of their mechanical properties. This paper discusses the main methods described in literature, as photo elasticity, digital Moiré interferometry, speckle interferometry and digital color holography.

In ophthalmologic imaging, the optical properties of the retina are essential parameters. The retina’s refractive index (RI) determines the light propagation inside the tissue towards the photoreceptors and its spatial distribution reflects biophysical tissue properties. In addition, information about the RI’s wavelength dependency is crucial for optical imaging, as it has to be considered, e.g., for dispersion compensation in high resolution optical coherence tomography (OCT). However, the spatial RI distribution in retinal tissue is difficult to access. We explored the capabilities of quantitative phase imaging (QPI) for RI characterization of murine retina utilizing digital holographic microscopy (DHM). Multispectral QPI was achieved by a Michelson interferometer-based DHM configuration that was combined with the light from a tunable supercontinuum laser light source.

Digital holography has been applied to discriminate particles with different sizes in a capillary flow. With this objective, a specific matched filter, a Wiener Filter, has been applied to the complex amplitude distribution obtained from holograms recorded with a tilted illumination set-up. Different possibilities of applying such a filter have been considered, related to the Wiener Filter definition itself and to its application in a 3D or 2D approach. The tilted illumination set-up allowed us to generate a new 2D visualization of the 3D particle scattering that has been found very useful to help in understanding the difficulties in finding particle trajectories when particle tracking methods are applied.

Several biotechnologies are currently available to quantify how cells allocate resources between growth and carbon storage, such as mass spectrometry. However, such biotechnologies require considerable amounts of cellular biomass to achieve adequate signal-to-noise ratio. In this way, existing biotechnologies inevitably operate in a ‘population averaging’ mode and, as such, they cannot unmask how cells allocate resources between growth and storage in a high-throughput fashion with single-cell, or subcellular resolution. This methodological limitation inhibits our fundamental understanding of the mechanisms underlying resource allocations between different cellular metabolic objectives. In turn, this knowledge gap also pertains to systems biology effects, such as cellular noise and the resulting cell-to-cell phenotypic heterogeneity, which could potentially lead to the emergence of distinct cellular subpopulations even in clonal cultures exposed to identical growth conditions. To address this knowledge gap, we applied a high-throughput quantitative phase imaging strategy. Using this strategy, we quantified the optical-phase of light transmitted through the cell cytosol and a specific cytosolic organelle, namely the lipid droplet (LD). With the aid of correlative secondary ion mass spectrometry (NanoSIMS) and transmission electron microscopy (TEM), we determined the protein content of different cytosolic organelles, thus enabling the conversion of the optical phase signal to the corresponding dry density and dry mass. The high-throughput imaging approach required only 2 μL of culture, yielding more than 1,000 single, live cell observations per tested experimental condition, with no further processing requirements, such as staining or chemical fixation.

Deep learning is a class of machine learning techniques that uses multi-layered artificial neural networks for automated analysis of signals or data. The name comes from the general structure of deep neural networks, which consist of several layers of artificial neurons, each performing a nonlinear operation, stacked over each other. Beyond its main stream applications such as the recognition and labeling of specific features in images, deep learning holds numerous opportunities for revolutionizing image formation, reconstruction and sensing fields. In fact, deep learning is mysteriously powerful and has been surprising optics researchers in what it can achieve for advancing optical microscopy, and introducing new image reconstruction and transformation methods. From physics-inspired optical designs and devices, we are moving toward data-driven designs that will holistically change both optical hardware and software of next generation microscopy and sensing, blending the two in new ways. Today, we sample an image and then act on it using a computer. Powered by deep learning, next generation optical microscopes and sensors will understand a scene or an object and accordingly decide on how and what to sample based on a given task – this will require a perfect marriage of deep learning with new optical microscopy hardware that is designed based on data. For such a thinking microscope, unsupervised learning would be the key to scale up its impact on various areas of science and engineering, where access to labeled image data might not be immediately available or very costly, difficult to acquire. In this presentation, I will provide an overview of some of our recent work on the use of deep neural networks in advancing computational microscopy and sensing systems, also covering their biomedical applications.

The identification and classification of biological samples is high-demanded in biomedical imaging for diagnostic purposes. Among all imaging modalities, digital holography has gained credits as a powerful solutions, thanks to its ability to perform full-field and label –free quantitative phase imaging. On the other hand, machine learning is nowadays the most used approach for classification purposes. The robustness and the accuracy of the classification depend of the features used for the training step. Therefore, the identification of micro-organism becomes strictly related to the features that can be extracted from their images. In other word, the more the image contains information, the higher the possibility of extracting highly distinctive descriptors to differentiate biological phenotypes. Digital holography can be considered one of the richest in terms of information content due to the fact that a single digital hologram encode both amplitude and phase information about the imaged cells. This opens the way to improve the features extraction, thus making more accurate the classification step. In this paper we analyze a test case by using a holographic image dataset for classification, by extracting unique features that can be solely obtained by holographic images.

Quantitative Phase Imaging (QPI) has recently emerged as a powerful new imaging modality to non-invasively visualize transparent specimens, including living cells in culture. Among different QPI techniques, Quantitative Phase Digital Holographic Microscopy (QP-DHM) is particularly well suited to explore, with a nanometric axial sensitivity, cell structure and dynamics. Concretely, accurate interferometric measurements of the phase retardation of a light wave when transmitted through living cells are performed. This phase retardation, namely the Quantitative Phase Signal (QPS) depends on both the thickness of the observed cells as well as the difference between its refractive index (RI) nc and that of the surrounding medium nm. This RI difference is generated by the presence of organic molecules, including proteins, DNA, organelles, nuclei present in cells. QPS provides thus information about both cell morphology and cell contents. According to this intracellular RI dependency, QPI has proven to be successful in performing cell counting, recognition and classification, the monitoring of cellular dry mass, cell membrane fluctuations analysis as well as the reconstruction, through tomographic approaches, of the intracellular 3D refractive index distribution. Furthermore, thanks to the development of different experimental procedures, additional relevant biophysical cell parameters were successfully calculated, including membrane mechanical properties, osmotic membrane water permeability, transmembrane water movements and the RI of transmembrane solute flux. However, all these cell parameters can be quantitatively and accurately measured provided that both the QPS exhibits a high stability and the RI value of the surrounding medium nm is accurately known. Any changes of nm will significantly affect the measurements of all these cellular parameters, comprising thus the major advantage of QPI, its quantitative aspects. This particularly the case, for the applications claiming a quantitative evaluation of the cellular dry mass as well as when compounds are directly added to the perfusion solutions for performing either screening or specific pharmacological experiments dedicated to decipher specific cellular processes. In this talk, we will present different substrates — coverslips and do-it-yourself 3D-printed flow chambers — that we have developed, which meet the challenge, when combined with QP-DHM of obtaining highly stable QPS as well of measuring in real time and with the accuracy of ±0.00004 the absolute values of refractive index of the surrounding medium in the vicinity of living cells. Specifically, such accuracy can be obtained thanks to the high QPS stability resulting from the QP-DHM capability to propagate the whole object wave (amplitude and phase) diffracted by the observed specimen during the numerical reconstruction of the digitally recorded holograms. Indeed, this 3D wavefront numerical reconstruction can efficiently compensate for experimental artifacts including lens defects, and noise originating from vibrations or thermal drift. These results pave the way for developing, based on QP-DHM technology, label-free high-content screening approaches to study test compound effects in cellular disease‐modeling systems.

In their native environment cells are constantly exposed to biochemical and biophysical signals that guide and regulate complex biological phenomena. Many of these signals impact on the adhesion properties of cells, which define cell morphology, cytoskeleton arrangements and the mechanical identity of cells. Adhesion signals are far from being static, but change in time and space according to specific programmes. Non-correct display of signals may result in catastrophic events. Yet, our understanding on the effects of the dynamics of signal presentation on cell functions and fates is very limited. Here we present our recent developments in the engineering of light-responsive platforms to enable the dynamic presentation of patterns of adhesion signals whose features can be controlled in space and time. More specifically, by controlling the irradiation of azobenzene based substrates, surface topography can be altered in the time frame of few tens of seconds, allowing the formation of submicron features, i.e. a scale that interferes with focal adhesion formation. We show the potency of these substrates in stimulating individual cells with topographic patterns acting on different lengths and timescales. In particular we show how dynamic patterns rapidly alter cytoskeleton arrangements and cell mechanical properties. The development of platforms enabling dynamic signal display would provide valuable insights into cell-biophysical signal interactions and, more specifically, into mechanotransduction-related phenomena. This could pave the way towards the development of novel systems to mimic more closely physiologic or pathologic extracellular environments for in vitro cell stimulation.

Electron microscopic observation of the surface of orthodontic arches reveals observable differences between new and used arches after four weeks in the mouth. This qualitative observation led us to consider their study by stimulated infrared thermography. These dental arches consist of a nickel-titanium (NiTi) shape memory alloy and are highly stressed during the stay in the mouth. Over the months, there will be evolution of their mechanical properties with multifactorial causes. In this study, we will demonstrate that it is possible to differentiate between the used arcs from the new arcs by observing their thermal response during a controlled heating.

Suspensions carrying deformable inclusions are ubiquitous in nature and applications. Hence, high-throughput characterization of the mechanical properties of soft particles is of great interest. Recently, a non-invasive optofluidic technique has been developed for the measurement of the interfacial tension between two immiscible liquids.^{1, 2} We adapt such technique to the case of soft solid beads, thus designing a non-invasive optofluidic device for the measurement of the mechanical properties of deformable particles from real-time optical imaging of their deformation. The device consists of a cylindrical microfluidic channel with a cross-section reduction in which we make initially spherical soft beads flow suspended in a Newtonian carrier. By imaging the deformation of a particle in real time while it goes through the constriction, it is possible to get a measure of its elastic modulus through a theoretically derived-correlation. We provide both experimental and numerical validation of our device.

There’s a constant need for improvement of optical bio/chemosensoristic devices on key aspects such as portability, cheapness, integration and simplification of experimental protocol. Moreover, new requirements are rapidly gaining ground: connectivity for real time remote access and big data analysis, needs for easy design approaches of customized components, suitability in resource-poor settings or educational context. According to this scenario, the combination of consumer electronics, open-source 3D printing and microcontrollers running on free software are opening completely new possibilities to develop powerful, low-cost and highly customizable research tools for students, scientists, engineers, and lab personnel

Laser Doppler holography (LDH) is a full-field imaging technique that was recently used in the human eye to reveal blood flow contrasts in the retinal and choroidal vasculature non-invasively, and with high temporal resolution. We here demonstrate that the ability of LDH to perform quantitative flow measurements with high temporal resolution enables arteriovenous differentiation in the retina and choroid. In the retina, arteries and veins can be differentiated on the basis of their respective power Doppler waveforms. Choroidal arteries and veins can instead be discriminated by computing low and high frequency power Doppler images to reveal low and high blood flow images, respectively.

Deficient myelination in the internal capsule of the brain is associated with neurodevelopmental delays, particularly in high-risk infants such as those born small for gestational age (SGA). MRI technology has been effective at measuring brain growth and composition but lacks myelin specificity and is low resolution. There is an unmet need for developing of new quantitative approaches that are rapid and precise, which can complement MRI and provide insight into the pathology of deficient myelination and efficacy of nutritional interventions. To meet this challenge, we developed Color Spatial Light Interference Microscopy (cSLIM), a method that is cable of generating refractive index maps of stained specimens. Using paraffin embedded brain tissue sections, stained myelin was segmented from a brightfield image and, using a binary mask, those portions were quantitatively analyzed by cSLIM. Due to cSLIM’s nanoscale sensitivity to optical pathlengths and independence with respect to the stain intensity, we quantified subtle variations in myelin density at the single axon scale.

In previous study, a tomographic imaging system is built up for measuring the three-dimensional refractive index distribution inside the micrometer-sized biological cell by optically driven full-angle rotation scheme based on digital holographic microscopy, named as optical-driven tomographic DHM (OT-DHM) system. However, a small perturbation of the system will lead the inaccurate of the positions and the orientation of the micrometer-sized sample, thus the automatic calibration of the reconstructed phase images in the OT-DHM system is required. For this purpose, a novel model-based algorithm is proposed, in which we employ a 3-D ellipse shape for modeling the samples. The parameters of the ellipse-like shape on a small number of the projections are estimated and used them to build up the 3-D ellipse model of the samples. In advance, the reconstructed phase images are highly contaminated by the uneven background and coherence speckle noise. The block-based between-class criterion is used to suppress the effect of the non-uniform background, and the anisotropic diffusion process is utilized for the noise cleaning, including shot noise and speckles noise on the reconstructed phase. The boundary of the cell in each projection can be considered as the 2-D ellipse, and used to estimate the parameters of the 2-D ellipse. The established 3-D ellipse shape is applied for the calibration of the spatial positions and the orientations of the all other rotational angles. With the automatic calibration algorithm, the OT-DHM system can effectively reconstructed the three-dimensional refractive index distribution inside the micrometer-sized samples.

Learning to perform various tasks by training neural networks has been linked to optics for a long time. The remarkable progress that has been achieved in recent years with “deep learning” networks, has led to new many ideas for how to use learning techniques in the design and operation of optical systems and vice-versa. We will present results from this recent activity with particular emphasis of how deep neural networks can enhance the capabilities of optical microscopy.

Deep learning has become an extremely effective tool for image classification and image restoration problems. Here, we address two fundamental problems of localization microscopy using machine learning: emitter density, and color determination. Modern microscopy can produce images of biological specimen at very high (super) resolution, by precisely determining the positions of numerous blinking light emitting molecules over time. To achieve fast acquisition time, a high density of molecules is required, which poses a significant challenge in terms of image processing. Existing approaches use elaborate algorithms with many parameters that require tuning and a long computation time. Here, we report an ultra-fast, precise, and parameter-free method for super-resolution microscopy that utilizes deep-learning: by feeding the computer images of dense molecules along with their correct positions, it is trained to automatically produce super-resolution images from blinking data. Next, we demonstrate how neural networks can exploit the chromatic dependence of the point-spread function to classify the colors of single emitters imaged on a grayscale camera. While existing single-molecule methods for spectral classification require additional optical elements in the emission path, e.g. spectral filters, prisms, or phase masks, our neural net correctly identifies static as well as mobile emitters with high efficiency using a standard, unmodified single-channel configuration – based on inherent chromatic aberrations in a standard microscope. Finally, we demonstrate how deep learning can be used to design phase-modulating elements that, when implemented into the imaging path, result in further improved color differentiation between species. While point-spread-function engineering for spectral differentiation has been implemented in various applications in recent years, the optimal way to design such a PSF remains unclear. Here, we use a neural net to perform such design automatically, directly optimizing the desired cost function, namely, simultaneous localization and color detection of point emitters.

Manual blood smear analysis remains the gold standard to diagnose hematological disorders and infections of blood parasites. However, the analysis and interpretation of peripheral blood smears requires expert users, is time consuming, depends on inter-observer variation, and is not compatible with a high-throughput workflow for clinical routine diagnostics (Dunning & Safo, Biotech. Histochem. 2011, 86, 69–75; Pierre, Clin. Lab. Med., 2002, 22, 279–297). Instead, automated hematology analyzers only flag atypical results which provides no clear classification of diseases and require extensive sample preparation. Label-free image analysis of untouched blood cells would reduce pre-analytical efforts and potentially allows characterization of samples with higher information content compared to both smear analysis and conventional automated flow cytometry, as the blood cell morphology is preserved. Furthermore, preclinical research work is in need for non-invasive analysis of e.g. cancer cells or infected cells to support the discovery of new drugs. We suggest to apply high-throughput and label-free workflows based on digital holographic microscopy for standardizable image analysis relevant for pre- and clinical diagnosis. In the case of parasitic infections, the label-free detection and analysis of malaria parasites has been addressed by various studies (Anand et al., IEEE Photonics J., 2012, 4, 1456-1464; Seo et al., Appl. Phys. Lett., 2014, 104, 1-4; Park et al, PloS One, 2016, 11, 1-19; Ugele et al., Lab Chip, 2018, 18, 1704-1712). The detection of neglected tropical diseases affecting livestock and humans, such as Chagas disease and Leishmaniosis, has not been addressed so far by the community. Our platform technology is based on a customized differential holographic microscopy setup, which has been previously described (Ugele et al., Lab Chip, 2018, 18, 1704-1712; Ugele et al., Adv. Sci., 2018, 5, 1800761). Reference data sets of clinical leukemic samples, cancer cell cultures in solution, and in vitro cultures of various parasites were collected to understand the translational potential for this methodology. Hydrodynamic and viscoelastic focusing in a microfluidics channel was used for high-throughput imaging and enrichment/depletion of cell populations without the need for any autofocusing procedures. Morphological parameters describing the inner consistency were calculated from segmented phase images of the cells/parasites and combined with machine learning algorithms for improved analysis by the discovery of label-free biomarkers. In this way, improved subtyping of acute and chronic leukemias, myeloproliferative neoplasms, and further hematological disorders was achieved. Second, a detection of Trypanosoma and Leishmania parasites could be shown and in vitro cultures of Schistosomia mansoni were classified according to different viability stages. Third, the capability of anti-cancer drug candidate screening was demonstrated by monitoring the mesenchymal-epithelial transition of pancreas cancer cell cultures. We envision, that our platform technology has the potential as a cost-efficient method for automated diagnosis of various hematological disorders, parasitic infections, drug screening and monitoring of therapy efficacy. With further integration effort we also believe that the technology can be applied in resource limited settings.

We investigated subclasses of living peripheral blood cells in a microfluidic-based system, with the aim to characterize their morphometric and optical properties, and to track their position in flow in a label-free modality. We employed two coherent imaging techniques: a scattering approach of precisely aligned single cells, and a digital holography approach to achieve optical cell reconstructions in flow. Cells were first 3D-aligned in round shaped capillary and subsequently measured in a following square shaped channel. Results were obtained at two fixed measurement positions, the first one was chosen close to the entrance of the measurement channel to ensure 3D cell alignment for scattering investigations; the second was placed 15 mm after to study additional cell properties by digital holography and to investigate possible variations of axial cell positions. First, the refractive index, ratio of the nucleus over cytoplasm, and cell dimension were investigated from scattering investigations. Further quantitative phase-contrast reconstructions by digital holography were employed to calculate surface area, dry mass, biovolume and positions of cells using the scattering outcomes as input parameters. The precise cell alignment at the first measurement position could be confirmed. At the second measurement position a full label-free characterization of cell classes in distinct vertical positions was realized and supported by applied microfluidic force calculations, which can be used to align, deform and/or separate cells. Our results confirm the possibility to differentiate cell classes in flow, thus avoiding chemical cell staining or labeling, which are nowadays used.

The two new approaches to dynamic light scattering (DLS) biosensing are presented. The first method based on the effect of the slowing-down of nanoparticles rotational diffusion due aggregation and the high sensitivity of the autocorrelation function (ACF) of depolarized component of the scattered light to the rotational diffusion coefficient. This way it is possible to significantly increase the sensitivity of the analysis. The second approach implements a competitive immunoassay in the DLS version, while increasing the analyte concentration reduces the degree of aggregation of the conjugates therefore leads to a decrease in the average hydrodynamic diameter. On the basis of the proposed approaches, nanosensors for the PSA tumor marker and the antibiotic cloramphenicol were developed.

Wound healing assay is a method for evaluating of cell migration rate in vitro. In this assay, a scratch is performed in a confluent cell monolayer that usually contains only one type of cells. Interferometric phase microscopy (IPM) is a quantitative imaging technique, by which the optical path difference (OPD) of a sample is extracted. The OPD is equal to the thickness of the sample multiplied by its integral refractive index, and therefore provides us with quantitative information about the sample without labeling. Fluorescent probes are fluorescent compounds that can be attached to specific cells in order to provide ability of imaging the cells with specific contrast enhancement under fluorescence microscopy. Using a fluorescent microscope combined with an interferometric phase microscope, wound healing assay of a cell confluent monolayer that contains two types of cells is performed, while one type of cells is labeled with fluorescent probes for cell differentiation purposes. This allows us to check which cell type closes the wound faster, and to continually measure the dry mass of each cell population.

Infrared Thermography (IRT) was introduced to medicine in 1956 by the Canadian surgeon Lawson as a promising modality for diagnosing breast cancer. It became quickly obvious, that IRT does not give much anatomical/morphological information but provide an easily obtainable map of measurable skin temperatures. Consequently, extracting temperatures from thermal images became the standard method of analysis in medical thermography. However, the awareness of errors in obtained measurements did develop quite slowly. In 2017, a checklist was developed in a Delphi process to address conditions that should be reported in thermographic studies since they could affect thermography-based temperature readings. These potential sources of uncertainty include individual data of participants and their preparation for thermal imaging; extrinsic factors such as recent physical activity or physiotherapy; wetness of the skin; ambient temperature, humidity and infrared sources in the examination space; acclimation time; camera type, camera settings, emissivity; size of field of view; camera position in relation to the imaged subject; image analysis. Presented are examples of the magnitude of uncertainties caused by the camera performance, size of the field and angel of view and size and position of regions of interest. Due to the manifold of possible uncertainties in clinical thermography, the use of high thresholds for clinical meaningful temperature differences are recommended.

In this keynote address paper, we overview recently published works on the current techniques and methods for automated cell identification with 3D optical imaging using compact and field portable systems. 3D imaging systems including digital holographic microscopy systems as well as lensless pseudorandom phase encoding systems are capable of capturing 3D information of microscopic objects such as biological cells which allows for highly accurate automated cell identification. Systems based on digital holography enable reconstruction of the cell’s 3D optical path length profile. The reconstructed 3D profiles can be used to extract morphological and spatio-temporal cell features from biological samples for classification and cell identification. Similarly, pseudorandom encoding techniques such as single random phase encoding (SRPE) and double random phase encoding (DRPE) can be used to encode 3D cell information into opto-biological signatures which can be used for cell identification tasks. Recent advancements in these areas are presented including compact and field-portable 3D-printed shearing digital holographic microscopy systems, integration of digital holographic microscopy with head mounted augmented reality devices, and the use of spatio-temporal features extracted from cell membrane fluctuations for sickle cell disease diagnosis.

Acoustofluidics exploits ultrasounds and microfluidic platforms to achieve label-free and contactless manipulation of micro sized objects. Here, we demonstrate the use of off-axis digital holography to investigate the behavior of erythrocytes dispersed in water and exposed to ultrasound standing waves. We consider two different regimes of manipulation. In the first case, the sample is stilled inside the microfluidic channel. Under the influence of acoustic forces, the cells move to the first nodal plane, where they start an aggregation process. We follow the formation of clusters in different regions of the channel, highlighting the different structures that emerge. As a second regime, we monitor the axial position of cells flowing during the application of ultrasuonds. By using a resonance frequency that originates multiple nodal positions, we show how holographic imaging can be used to image the cells distributed in the different nodes.

Partially coherent optical diffraction tomography (PC-ODT) is a labelfree quantitative 3D imaging technique based on the refractive index contrast. It provides fast non-interferometric speckle noise-free imaging compatible with conventional wide-field transmission microscopes, but suffers from two principal inconveniences. One of them is the missing cone problem, which is a common drawback for all tomographic modalities with limited-angle inspection, including interferometric coherent ODT. The second one, considered in this paper, is a nonhomogeneous contrast for different spatial frequency regions. Analyzing the microscope 3D optical transfer functions for various illuminations over the condenser aperture we have found that the Gaussian illumination shape is a proper one. Numerical simulations and experimental results support this finding. A future line in the development of post-deconvolution processing is also discussed.

We report on a smart solution to obtain Tomographic Phase Microscopy (TPM) of samples in microfluidic environment, by exploiting their tumbling while flowing in a microchip. This method permits to observe full 360° of rotating cells, this avoiding the limitation in the accuracy of tomograms, and no mechanical contact neither holographic optical tweezers are needed to rotate the sample. Moreover, it is suitable for application in flowing conditions with high-throughput performances. In fact, it allows to monitor a large number of cells, the only limit being the frame rate of the camera used to acquire data, and to analyze in principle each single cell with high resolution, regardless of its shape or symmetry. This would allow real microfluidic biomedical applications on a large scale. Summarizing, the whole process is accomplished following the subsequent steps: (i) holograms acquisition of cells flowing in microfluidic channels; (ii) 3D tracking and realignment by using either biolens effect or particular symmetries (depending on the object’s structure); (iii) connection between rotation angles and phase maps; (iv) complete 3D image retrieving, displaying the inner structure of the object (i.e. tomography).

In this paper we discuss the influence of the camera noise in holographic projections measurements on the accuracy of reconstruction in the limited projection angle optical diffraction tomography (LAODT). To counteract the shortcomings of LAODT due to “missing cone” problem we apply generalized total variation iterative constraint (GTVIC) algorithm which replenishes the spectral contents of the reconstruction. To investigate the influence of the noise on result of the GTVIC reconstruction we perform systematic numerical experiments based on simulated phantom mimicking a cell and tailored to the measurement parameters of LAODT system. Next, to mitigate the disruptive influence of noise we test the efficiency of two denoising procedures based on blockmatching technique, namely BM3D and BM4D. Thanks to the properties of those algorithms, the denoising may be applied directly on holograms or hologram stacks, without destroying the fringes. The tomographic GTVIC reconstruction results from data after filtration will be compared with noise-free reconstruction, in reference to the simple median filtering of the noisy reconstruction.

The particle characteristics in a suspension affect the performance and quality of the end product of many chemical industries. The shape of the suspended particles can be influenced by changes in the manufacturing process conditions. Thus, there is a need for a robust method for continuous monitoring of particle characteristics through the process. This study investigates the feasibility of using spatially and angularly resolved diffuse reflectance measurements as a method of determining particle shape. A forward calculation was developed using the discrete dipole approximation to estimate optical properties of the single particle and the diffuse approximation for the reflectance of the particle suspension. The method was used to study aqueous suspensions of randomly-oriented polystyrene ellipsoids. Our objectives were to determine and elucidate the contribution of aspect ratio on optical measurement in vis-NIR spectra. The results suggest that the method is suitable for determining particle shape for suspensions where the particle and the solvent have significantly different optical properties. For these systems, the study suggests that diffusion reflectance measurements can be developed into an in-line method for particle shape determination.

Optical tweezers are of particular interest in various fields of science and technology such as atomic physics, nanotechnology and micromechanics. Today, there are many devices for manipulating microscopic objects using optical tweezers. In comparison with the most of known manipulation systems, the acousto-optic deflection is characterized by higher speed, the possibility to control several optical traps independently, high-precision movement of the trap within the field of view. In optical tweezers, longitudinal movement of micro-objects is also required. For this, special optical systems with variable characteristics, may be used. In this paper, we propose to combine these two approaches in one setup for 3D manipulation, i.e. to use acousto-optic scanning, using Bessel optical beams and an optical variosystem designed for longitudinal movement of the Gaussian beam waist at its constant diameter.

In the field of biomedical optics, laparoscopes for high temperature treatment of various internal tissues are widely used. With the help of medical endoscopes, it is possible to examine the internal cavities of the human body, biopsy, administer medications, remove tumors, and use laser radiation for surgical and therapeutic purposes. To achieve high performance of optical system’s combination of components made of optical polymers which are transparent in the long-wavelength spectrum are proposed. Technological aspects of optical systems are observed. Computer modeling of infrared endoscope system using Zemax software is presented. Selection of appropriate optical materials is described. Discussion of effective introduction of polymer components into the optical design is provided. Optical performance of the achieved endoscopic systems is shown.

The whole loading and unloading operation of automated container terminal is carried out by means of mechanization and large-scale production, which requires close cooperation of various operations to realize the high efficiency of loading and unloading process system. Reasonable layout of facilities on container terminals and their organic connection form an organic whole of coordinated and coordinated operations, forming an efficient and perfect assembly line. In order to shorten the berthing time of vehicles, ships and boxes at port terminals, accelerate the turnover of vehicles, ships and boxes, reduce transportation costs and loading and unloading costs, and achieve the best economic benefits. In this paper, the container transshipment vehicle based on lidar navigation is taken as the research object, so that the container autopilot has certain autopilot ability and is suitable for the needs of the automated container terminal.

Microplastics are worrisome water pollutants that are more and more spread in deep sea and coastal waters. Plastic items can take decades to biodegrade, have the potential to affect the food chain and are harmful to marine life. Hence, there is the urgent need to define protocols and to create reliable tools to map the presence of microplastics in heterogeneous liquid samples. However, well established protocols and tools to identify microplastics in water have not been proposed yet. Here we investigate this class of objects by means of coherent imaging, in particular relying on Digital Holography (DH) microscopy. We provide a DH characterization of the “plastic” class that can be used as a global identifier independently on the plastic material under analysis. We probe microplastics of various materials through our DH microscope and show that the phase contrast map of microplastics can be used to define a fingerprint for the microplastics population. Thanks to the DH flexible refocusing, volumetric counting of microplastics in flow is feasible by DH with high-throughput. Remarkably, field-deployable, cost effective DH microscopes exist that can bring the DH characterization potential out of the lab for in situ environmental monitoring.

Currently, optical methods for diagnosing skin are becoming more common and are widely used in medicine. The spread of optical methods is explained by the safety of the application and the ability to non-invasively obtain a number of parameters in real time. The use of optical radiation allows to obtain information about the structure and composition of the skin, to study the processes occurring in biotissue without adverse effects. The use of optical radiation in accordance with the diagnostic windows of the transmission of the skin allows you to explore deep-lying structures. Despite the proliferation of optical methods for diagnosing the skin, a dermatologist is not always able to correctly assess the state of the neoplasm. This is due to the lack of extensive practical experience with neoplasms, insufficient information content of the research method, complexity of neoplasm classification. The development of optical diagnostic methods will allow a person to be protected from the development of malignant pathologies. In order to improve the quality of diagnosis of skin pathologies for safe human life, the development of a test bench for the study of the surface layers of the skin is relevant.

We developed a method for reconstructing the THz dielectric response of a thin liquid sample. A self-made sample cuvette was designed for the transmission-mode THz pulsed spectroscopy of liquids. Numerical simulations and theoretical studies of the proposed reconstruction procedure were performed in order to optimize the sample geometry and predict uncertainties in reconstructed dielectrical properties. A number of agents for immersion optical clearing of tissues was studied using the proposed method in the THz range. The developed method can be applied for all types of sufficiently transparent liquid samples.

Silver nanoparticles were prepared by pulsed laser ablation technique using a second harmonic wavelength (532 nm) of Q switched Nd:YAG laser of 7 ns pulse width and 10 Hz repetition rates. Formation of Ag NPs was confirmed from characteristic surface Plasmon resonance induced absorption (~418 nm). Spherical shape morphology and crystalline nature of structure were revealed from SEM and TEM analysis. Nonlinear optical studies were conducted by z scan analysis with the same laser system used for ablation. A switching of nonlinear absorption (saturable absorption to reverse saturable absorption) in Ag NPs were observed when on axis input intensity increased from 0.27 GW/cm² to 0.83 GW/cm² and it could be attributed to interplay of different nonlinear absorption mechanisms, that is strongly depends on the intensity of the excitation source. Self-defocusing nature of the sample was revealed from the closed aperture z scan analysis.

The main goal of this work was to verify the hypothesis about the possibility of inducing small artificial venous pulsations in the terminal area of the forearm vascular tree by using a local orthostatic maneuver. That pulsations could be used for measurement, of the regional venous blood oxygenation (rSvO₂) without any additional apparatus as it is practiced in the classic occlusion method. The complexity of the research object, as well as dynamically changing environmental and hemodynamic conditions that occurs in this type of measurement, significantly impedes the comprehensive analysis of anatomical reactions occurring during the implementation of the mentioned maneuver. For that reason, research was done by the modified HOMS model. The basic variant of the chosen model was expanded by a quasi–hydrostatic factor P_h(t) affecting on the area under consideration. The extension was realized by using the complex θ_δ[abc] function, defined in details in chapter 3. The results obtained during the work indicate the possibility of obtaining venular quasi–pulsations several times higher (modulation ratio M_V ≈ 30%) than the arterial pulsations observed for the typical pulse oximetry (typical M_A = 1 ÷ 2%). This confirms the hypothesis given in the introduction and proves the possibility of inducing pulsations with using the local orthostatic maneuver. Moreover, obtained values of the coefficient MV show the potential possibility of the empirical detection with using standard pulse oximetry tools.