This PDF file contains the front matter associated with SPIE Proceedings Volume 12854, including the Title Page, Copyright information, Table of Contents, and Conference Committee information.

Bioburden detection in water is an important challenge in the contexts of both consumer and industrial water. Water-borne infections due to bacteria and fungi are becoming key public health concerns. Further, in biologics manufacturing sector, it is of key importance to use water with zero bioburden in all critical manufacturing processes. However, current methods of detecting and classifying bioburden in water samples is a tedious process involving time-consuming microbiological steps where it takes about 5-7 days to infer trace levels of pathogen contamination. It is possible to hasten the detection process using cytometry-based platforms that offer high levels of sensitivity and specificity in pathogen detection and enumeration of various pathogens. However, these solutions may not be able to determine the bacterial species and viability in a label-free set up. Here, we present Illuminate-τ, a portable label-free detection platform for rapid bioburden assessment in water samples in under 10 minutes, thereby demonstrating a >1000x improvement in detection time. This works on the principle of inferring the presence of pathogen cells in water through their native autofluorescence lifetime characteristics. The Illuminate-τ device is integrated with pulsed nanosecond UV light sources and drivers, high-speed single photon avalanche detectors, and sophisticated timing circuits controlled by an embedded electronics subsystem. In addition, the device also has an edge inferencing SVM-based machine learning algorithm that takes in autofluorescence lifetime characteristics and detects <100 CFU/ml of bioburden such as Pseudomonas, E.coli, Salmonella, Candida species etc. with an accuracy exceeding 99%. Further, we show that we the platform is also able to differentiate Pseudomonas from other bacteria and fungi with a 100% accuracy under similar conditions of concentration. In summary, we demonstrate that Illuminate-τ a device based on autofluorescence lifetime coupled with machine-learning-based detection strategies can achieve high bioburden detection sensitivity.

To track living organisms, methods have been used such as spraying substances that easily produce phosphorescence or preparation at the genetic level; however, the need for advance preparation. Alternatively, it has become clear that RTP can be produced by excitation of organic materials with ultraviolet light. Since living organisms are composed of organic materials, phosphorescence is presumed to be generated. In this study, we will test this hypothesis and investigate its application to novel bioimaging without any preparation. Specifically, using a stuffed sparrow, we irradiate 375 nm excitation light to the feather area and take images using a high-speed, high-sensitivity camera. By measuring the phosphorescence lifetime after the end of the excitation light, we will track the phosphorescence that can be used for position tracking. In the experiment, the excitation light was actually irradiated on a stuffed sparrow, and the phosphorescene light as a label-free dynamic marker was tracked.

Cryopreservation is routine in biomedical research and clinical practice for various purposes, including sample transportation, RNA preservation, and long-term storage. However, freezing poses risks of tissue damage due to ice crystal formation and cell lysis. The effects of tissue freezing and thawing on microstructural image features are not fully understood, and determining a freezing protocol that best preserves tissue integrity is essential for maximizing the transferability of imaging studies using previously frozen tissues. This study investigates the impact of freeze-thaw protocols on tissue microstructure using optical coherence tomography (OCT), an imaging technique that provides detailed 3D images of biological structures. Tissue specimens from three organs – lung, liver, and duodenum – were collected from six mice and imaged before and after freeze-thawing using different protocols. We tested protocols including slow freezing to -20 °C, slow freezing to -80 °C, and liquid nitrogen submersion. We examined immersion in both phosphate buffered saline and routine cryopreservation compounds for all methods. Using images from each specimen before and after freeze-thawing, differences in structural features were analyzed qualitatively and by using texture analysis. Texture features were extracted from OCT images using Haralick’s method, and statistical analysis was performed to compare the different protocols and tissue types. Results show that flash freezing methods and the use of cryopreservation compounds cause fewer alterations in tissue microstructure compared to slow freezing. This study provides insight into the effects of common freezing protocols on tissue integrity, which may inform the optimization of tissue preservation techniques across many disciplines.

Durable phantoms with optical properties and layered structures like healthy and diseased tissues are highly desirable for reliable performance testing of novel high-resolution optical coherence tomography (HR-OCT) systems. In this context, we performed investigations on the establishment of durable 3D retina models from eyes dissected ex vivo from control mice and eyes from animals treated with N-methyl-D-aspartate (NMDA) which induces glaucoma-like tissue alterations. The comparison of data from resin-embedded tissue with native murine retina in gels demonstrates that by utilization of appropriate preparation protocols highly stable 3D samples with layered structures equivalent to native tissues can be fabricated which are suitable for reliable HR-OCT performance characterization.

Compact multispectral imaging systems can provide fast analysis of tissue properties, such as perfusion, that are useful parameters for clinicians to inform individualized care. Some sedative drugs used in both human and veterinary medicine have been found to induce changes in perfusion in small animals such as cats. The use of these drugs on veterinary patients must be carefully considered in the case of wound care or procedures such as axial pattern flaps as inhibited wound perfusion may inhibit successful treatment. In this preliminary study, we built a multispectral illumination module that consisted of a white light source and filter wheel to supplement a commercial laser speckle contrast system. A color camera of the laser speckle system was used for multispectral image acquisition. The system was used to obtain visible-light reflectance measurements of the skin of anesthesized healthy dogs undergoing routine dental cleaning. The goal of this study was to determine if multispectral data detects changes in skin reflectance as the dog was placed under anaesthesia. The changes observed may be related to changes in superficial skin perfusion as the patient receives sedation.

Label-free biomedical imaging represents a range of powerful technologies used to visualize natural sources of biological contrast. Label-free techniques such as autofluorescence and fluorescence lifetime imaging measure contrast produced by various cellular products and provide high sensitivity for detecting tissue changes that occur with disease onset. However, a major limitation of these modalities, and many label-free modalities broadly, is the lack of robust validation methods that confirm signal specificity. Moreover, existing approaches are limited to assessing correlations and fail to provide mechanistic information into pathological events. Spatially resolved gene sequencing methods (e.g., spatial transcriptomics) are a powerful tool to gain detailed biological insight into tissue properties by creating 2-D maps of variations in gene expression that influence tissue properties. Thus, these techniques represent an avenue for validation of label-free imaging markers through the examination of how label-free image features correspond to gene expression. Toward this aim, we performed autofluorescence and fluorescence lifetime imaging on tissue specimens from four patients presenting with pancreatic neuroendocrine tumors. We then performed spatial transcriptome sequencing on serial tissue sections to measure transcriptome-wide signatures. We assessed imaging biomarkers related to cellular metabolism, vasculature, and extracellular matrix properties. After registering the label-free images to the transcriptomic signatures, we performed k-means clustering, and assessed the correlation between imaging markers and differentially expressed genes associated with tissue properties of interest. Specifically, we aimed to examine correlations between gene expression and established optical biomarkers (e.g., optical redox ratio), along with identifying other potential connections between label-free optics and cellular genetics. The results show that spatial transcriptomics can be used as an effective validation tool for label-free imaging markers, while simultaneously providing additional biological insight to improve the specificity of imaging studies.

Ultraviolet (UV) microscopy of live cells has been challenging due to phototoxicity, with UV radiation affecting cellular components leading to irreversible cell death. Despite this challenge, recent advances in UV light sources and detectors have renewed interest in UV microscopy due to its high resolution and label-free molecular imaging capabilities. Indeed, UV microscopy has been recently demonstrated for a wide variety of cellular imaging applications, including multispectral imaging of cancer tissue sections, cells at varying time scales, and hematological analysis of whole blood cells. While these studies have leveraged UV microscopy to image static samples and cellular dynamics over short periods of time, UV phototoxicity remains a problem during live cell imaging sessions lasting over several hours and longitudinal imaging of a single sample. In this work, we characterize UV-induced photodamage by quantifying the flux required for cell death at notable wavelengths in the deep-UV region. We demonstrate how this flux can vary with cell adherence type using adherent and non-adherent cell lines. We then present fractionation studies conducted over time scales ranging from several hours to days and discuss the ability of cell populations to recover in each case. Finally, we provide viable live-cell imaging frameworks for UV microscopy applications ranging from single multispectral imaging sessions to long-term observation of samples.

In neuroscience research, it is crucial to measure action potentials accurately with high spatiotemporal resolution and sensitivity. Current approaches rely on electrodes or optogenetics. New approaches providing higher spatial resolution close to a single neuron, immunity to biological noise, and lesser tissue damage during measurements are always desired. Here, we present a feasibility study on a novel label-free integrated approach by combining the electro-optic (EO) properties of lithium niobate (LN) with a microring resonator (MRR) and coherent detection to enable highly sensitive and precise measurement of action potentials. Specifically, we discuss the feasibility of this so-called opto-probe by carrying the action potential signal with light modulation and beating it through homodyne detection to detect weak signals. The MRR structure obtains the modulation of the light through the refractive index change of LN under the electric field generated by the action potential. Then, at the homodyne detection part, the action potential information is extracted from the beating of these two signals by mixing the modulated signal with a local oscillator signal. We estimate that the electric field generated by action potentials as small as 15 μV is detectable with high resolution. Furthermore, the spatial resolution of the opto-probe can reach up to 249 electrodes/mm² when configured as an array, which offers scalability and potential for multiplexed sensing applications. The research findings present a promising advancement towards a novel tool that overcomes the limitations of electrode-based methods, enabling highly accurate and precise measurements of action potentials and enhancing our understanding of neuronal activity in the brain.

Bacterial infections often pose a time-sensitive concern; however, the current diagnostic methods are comprised of lengthy processes. This study explores label-free imaging techniques based on two-photon excitation of intrinsic molecules found in various bacterial species. Specifically, two-photon excitation microscopy (TPEF) and fluorescence lifetime imaging microscopy (FLIM) are employed. These methods have been extensively utilized in the area of animal cells, yielding favorable outcomes, yet their application to bacteria remains largely unexplored. Analogous to the work on animal cells, initial attention is directed towards the metabolic coenzymes, namely nicotinamide adenine dinucleotide (phosphate) (NADPH) and flavin adenine dinucleotide (FAD). The extra time component of the FLIM setup was used to further investigate differences between the decay curves of the emitted autofluorescence in their different growth phases, corresponding to different internal microenvironments. Bacteria were excited at 740nm and 900nm and TPEF and FLIM signals were recorded with fitting bandpass filters, respectively. Different species (Escherichia coli K12, Pseudomonas fluorescens and Staphylococcus aureus) and different growth phases were examined to identify characteristic signal combinations. The two image channels and both wavelengths are compared and plotted against each other. The results show that the bacteria can already be classified by their autofluorescence signals. The growth phase seems to have less influence than the species. Based on this data, a classification is made to uniquely identify them. For this purpose, the database will next be expanded to include additional species and the classification will be automated.

Pancreatic neuroendocrine tumors (PNETs) present significant diagnostic and therapeutic challenges due to their heterogeneity and complex nature as a subtype of pancreatic cancer. The treatment approach varies considerably based on the tumor's location, grading, and focality. Accurate prognosis and management typically necessitate the expertise of a pathologist to evaluate histological slides of the tissue, a process that is often time-consuming and labor-intensive. Developing point-of-care techniques for automatic classification of PNETs would greatly improve the ability to treat and manage this disease by providing real-time decision-making information. In response to these challenges, our study introduces a highly efficient and versatile diagnostic strategy. This innovative approach synergistically integrates label-free multiphoton microscopy with finely adjusted, pre-trained deep learning models, optimized for performance even with limited data availability. We have meticulously optimized four pre-trained convolutional neural networks, utilizing a dataset comprising only 49 images, which includes both two-photon excitation fluorescence and second-harmonic generation imaging. This refined approach has resulted in an impressive average classification accuracy of over 95% for the development dataset and more than 90% for the test dataset. These results are significantly superior when compared to the preoperative misdiagnosis rates of conventional diagnostic modalities such as ultrasound (US) and computed tomography (CT), which stand at 81.8% and 61.5%, respectively. This methodology represents a significant advancement in the diagnostic process for PNETs, promising a more streamlined, rapid, and accurate approach to treatment. Furthermore, it opens substantial potential for the automated classification of various tumor types using multiphoton microscopic imaging, even in scenarios characterized by limited data availability.

The near infrared (NIR) and mid-infrared (MIR) spectral regions contain absorption features that can identify specific molecular bonds and chemical species in a sample. For example, lignan and proteins in plants have specific absorption signatures in the NIR. However, because detectors are inefficient in the NIR and MIR, infrared spectroscopy requires high light levels to overcome detector limitations. Cameras in particular do not perform well in this spectral range, and microscopy methods such as Fourier transform infrared spectroscopy (FT-IR) typically rely on scanning confocal arrangements with single-element detectors to spatially map chemical information. To overcome these limitations, we have developed and exploited a new quantum ghost imaging microscope for obtaining absorption measurements in the NIR without the need of scanning or high light intensities. We report on the use of a novel detector–NCam–in quantum ghost imaging using non-degenerate photon pairs generated by spontaneous parametric down conversion (SPDC). NCam records single-photon arrival events with ∼100 ps resolution, enhancing the correlation window of SPDC pairs over previous wide-field ghost imaging by 30-fold. This permits ghost imaging of living and intact plant samples at light levels lower than what the plants would experience from starlight. For photosynthesizing organisms, this low-light imaging method enables the study of plants without disturbing or eliciting responses from the plant due to the measurement itself.

Stimulated Brillouin scattering (SBS) is a valuable technique for studying the mechanical properties of biological samples. We propose a novel scheme utilizing low duty cycle, nanosecond pulses for pump and probe beams. Our approach achieves higher signal-to-noise (SNR) than SBS microscopy and continuous-wave Brillouin microscopy, even with reduced average power exposure. Experimental results demonstrate a shot noise-limited SNR exceeding 1000 with precise mapping of cellular features. The interlaced boxcar method effectively retrieves the SBS signal, while optimizing pulse width and peak power further enhances optical power efficiency. This pulse scheme offers improved precision and reduced laser power exposure compared to spontaneous Brillouin and continuous wave (cw) SBS approaches.

Circadian rhythm exerts a critical role for the determination of health and consequently diseases. We investigate the dependence of this parameter non-invasively by measuring the refractive index of saliva from human beings. The refractive index measurement is conducted by a probe developed with focused surface plasmons.

Quantitation of cell dynamics is a prerequisite for challenging biosensing and biomedical applications, ranging from cancer progression and metastatic potential evaluation, to assessment of cytopathic effects. Targeting fast label-free retrieval of electrical and optical parameters of cell-cell, cell surface interaction dynamics and of the temporal nanometer-scale fluctuations, we advance a novel concept of a multimodal, label free, functional imaging instrument. We report on ways to exploit the AC electrical modulation of the refractive index of a tailored (sensing) interfaces, e.g. custom designed conductive microscope slides, via an externally applied AC voltage, and time lapse optical assays to provide label free contrast of the local electrical impedances and surface charge densities - beyond the limitations of standard electrode-based technologies. This enables high content assessment of single cell relevant biophysical parameters and of their dynamics as well as of cellular fluctuation profiles. The concept grounds a wide range of electrically-modulated optical assays for measuring the electric field locally at nanoscale including quantitative phase microscopy or reflected light microscopy. The virtues of this novel enabling tool to monitor intracellular trafficking and electrical impedance contrasts and dynamical cellular response in living cells include: quantitative assessment of cytopathic effect (evaluation of relevance for viral infection), cell signaling, drug screening and hazard evaluation (e.g. last resort antibiotics, toxic compounds).

We explored the capabilities of quantitative phase imaging (QPI) with digital holographic microscopy (DHM) for the characterization and classification of urine sediments. Bright-field images and off-axis holograms from a liquid control for urine analysis and human urine samples were acquired with a modular DHM system. From the retrieved images, particle morphology parameters were extracted by threshold and convolution neural network (CNN)-based segmentation procedures. Moreover, the ability of supervised machine learning algorithms to classify and identify urine sediment components based on biophysical parameters was evaluated. Our results demonstrate DHM as a reliable urine sediment analysis tool.

Quantitative oblique back illumination microscopy (qOBM) is a recently developed phase imaging modality that enables 3D quantitative phase imaging and refractive index (RI) tomography of thick scattering samples. The approach uses four oblique illumination images (acquired in epi-mode) at a given focal plane to obtain cross sectional quantitative information. In order to quantify the information, qOBM uses a deconvolution algorithm which requires an estimate of the angular distribution of light at the focal plane to obtain the system’s optical transfer function (OTF). This information is obtained using Monte Carlo numerical simulations which uses published scattering parameters of tissues. While this approach has shown robust results with high quantitative fidelity, the reliance on available published scattering parameters is not optimal. Here we present an experimental approach to measure the angular distribution of the back-scattered light at the focal plane. The approach simultaneously obtains information from the imaging plane and the Fourier plane to provide insight into the overall angular distribution of light at the focal plane. Together with the pupil function, given by the known numerical aperture of the system, this approach directly yields the OTF. A theoretical analysis and experimental results will be presented. This approach has the potential to widen the utility of qOBM to also include tissues and samples whose scattering properties are not well documented in the literature.

Programmed cell death, or apoptosis, can be triggered in C6 glial cells through exposure to the drug methamphetamine. Non-invasive, quantitative tracking of apoptotic glial cell morphology can be difficult, as many cellular samples are weakly scattering, and therefore traditional bright field images may be of low contrast. Higher contrast images may be found through incorporation of the quantitative phase delay a beam can undergo due to transmission through a sample. In addition, quantitative phase information can be used, non-invasively, to track meaningful morphological quantities over time. Digital holographic microscopy (DHM) and utilization of the transport of intensity equation (TIE) are two label-free, high-resolution phase imaging techniques. DHM quantitatively retrieves phase through measurement of a hologram, or the interference pattern created when combining object and reference beams. The TIE quantifies the relationship between a field’s phase and intensity upon propagation. Solving the TIE requires measurement of an in-focus intensity, and images in symmetric planes about focus. On a setup capable of simultaneous data collection for both techniques, phase reconstructions were retrieved of C6 rat glial cells undergoing methamphetamine induced apoptosis. The two techniques’ measurements of total optical volume of cell clusters were compared over time. Additionally, the behavior of cells’ index of refraction during apoptosis was explored through optical diffraction tomography (ODT) retrieved reconstructions. Through these reconstructions, both cell volume and cell optical volume were tracked. The average relative refractive index behavior measured by ODT was extended to extrapolate volume from the TIE/DHM optical volume measurements.

Quantitative phase imaging (QPI) has emerged as a valuable method in biomedical research by providing label-free, high-resolution phase distribution of transparent cells and tissues. While QPI is limited to transparent samples, quantitative oblique back-illumination microscopy (qOBM) is a novel imaging technology that enables epi-mode 3D quantitative phase imaging and refractive index (RI) tomography of thick scattering samples. This technology employs four oblique back illumination images taken at the same focal planes, along with a rapid 2D deconvolution reconstruction algorithm, to generate 2D phase cross-sections of thick samples. Alternatively, a through-focus z-stack of oblique back illumination images can be utilized to produce 3D RI tomograms, offering enhanced RI quantitative accuracy. However, 3D RI generation requires a more computationally intensive reconstruction process, preventing its potential of a real-time 3D RI tomography. In this paper, we propose a neural network-involved reconstruction technique that significantly reduces the processing time to a third while maintaining high fidelity compared to the deconvolution-based results.

We demonstrate video-rate spontaneous Raman imaging by combining lightsheet microscopy that harnesses non-diffracting Airy beams to efficiently illuminate large specimen regions with image acquisition and reconstruction at the subphoton per pixel levels. We validated these benefits by imaging a wide variety of samples, including organic materials and the metabolic activity of single living yeast cells. Overall, our method not only enables video-rate imaging rates, but also requires 1000-fold less irradiance levels than state-of-the-art coherent Raman microscopy. As such, we expect this approach will greatly accelerate the reliability and reproducibility of Raman imaging in both fundamental research and clinical applications.

It is a well-established fact that iron metabolism is disrupted in breast cancer cells. Assessment of iron transport and metabolism is necessary to understand molecular mechanism of breast cancer progression. Previously, Raman spectroscopy has been used to measure the Raman spectral profile of iron-bound proteins in breast cancer cells. By harnessing the principle of inelastic scattering of light, Raman spectroscopy offers a powerful, label-free, and nondestructive tool for determination of molecular structures and analysis of chemical bonds. The current study employed a specific experimental approach to capture shifts in the Raman signature of iron-binding proteins, such as transferrin. Focusing on cytoplasmic regions (exclusive of the nucleus) permits improved analysis of iron-binding proteins localized to vesicles present in the cytoplasm. The acquired spectra were subjected to rigorous analysis using singular value decomposition (SVD), a powerful mathematical technique that possesses the ability to reveal underlying trends and enhance biological analysis and interpretation. It involves detecting overlapping frequency patterns in the dataset. By applying SVD to distinguish the Raman spectral profiles of iron-bound transferrin in breast cancer cells, we obtained accurate results that have played a pivotal role in discerning and characterizing the Raman spectral profile of iron-bound transferrin in breast cancer cells.

Cytochrome c, an essential protein integral to the electron transport chain within cellular mitochondria, plays a crucial role in the intricate process of apoptosis, or programmed cell death. An early event in apoptosis involves the release of cytochrome c from the mitochondria's intermembrane space into the cytoplasm. This paper explores the detection of cytochrome c during apoptosis using Raman spectroscopy, with a specific focus on its release from the mitochondria of human microglial cells (HTHμ). Raman spectroscopy, a non-invasive and label-free analytical technique, allows the examination of biomolecular changes based on their chemical properties. Our experimental approach induced apoptosis in HTHμ cells using methamphetamine (METH) and utilized Raman spectroscopy on both control and apoptotic samples. Through the analysis of spectra by singular value decomposition (SVD), which reveals subtle trends and facilitates biological interpretation, distinct spectral features corresponding to cytochrome c were identified. This evidence supports the concept of cytochrome c release from the mitochondria during apoptosis. The label-free nature and high sensitivity of Raman spectroscopy position it as a promising technique for studying apoptosis in biomedical research and contributing to the development of innovative diagnostic approaches for apoptotic-related disorders.

Alginate is a natural polysaccharide found in brown algae and has a unique feature, the ability to form a hydrogel upon encountering Ca²⁺. Its exceptional characteristics make alginate hydrogels highly desirable for a range of biomedical applications, such as drug delivery, wound healing, and in particular, tissue engineering and cell therapy, where it is used as scaffolding or as a cell delivery vehicle. After using alginate hydrogel for cell delivery in vivo, one of our objectives was to specifically detect alginate in mouse tissue cryosections containing cell-scaffold constructs to evaluate scaffold cell-scaffold integration with host tissue and degradation. Due to difficulties encountered in detecting alginate using immunohistochemistry with mouse-derived antibodies, we aimed to develop an alternative method to definitively identify alginate within tissue cryosection samples using Raman spectroscopy. The Raman spectra of pure tissue had specific peaks convenient for identification. We identified a region where alginate consistently had stronger signal than either tissue or tissue freezing media. We also detected alginate-specific Raman peaks at 816, 888, 959, 1309, 1433 cm^-1. By collecting the Raman spectra of the samples containing all three substances (alginate, freezing media, and tissue), analyzing them either by characteristic spectral peaks or classical least squares (CLS) method, and mapping the media, alginate, and tissue on the brightfield sample image, we were able to discriminate the alginate from tissue and freezing media. The notable sensitivity and specificity of Raman spectroscopy renders it a promising method for the identification of alginate and alginate-based materials in tissue engineering.

Continuous monitoring of retinal pigment epithelium (RPE) cell growth and functionality is imperative in both pre- and post- RPE transplantation phases. We propose a telecentric add-on scan lens design that is integrated with the probe arm of a polarization-sensitive optical coherence tomography (PS-OCT) system for in vitro retinal organoid imaging. The system can be switched to in vivo or in vitro imaging mode depending on the requirement. In the context of retinal imaging, the polarization information of the RPE layer and other layers, along with their conventional morphology, can be effectively contrasted using the in vivo mode. The add-on lens attachment enables a wide field of view retinal organoid growth monitoring and its functionality visualization. It includes a field flattener to compensate for field curvature. The comprehensive PS-OCT system provides a 12 mm x 12 mm field of view on the retina and can cover up to 15 mm x 15 mm on retinal organoids. The system successfully images young and mature retinal organoids, capturing well-defined layered structures and highly pigmented outer RPE boundaries using polarimetric entropy contrast. Intensity based segmentation on the cross-section image of retinal organoid is performed to retrieve the thickness heatmap which provides the insight of organoids’ growth statistics.

Hyperspectral imaging is gaining importance in many areas of research, industry and medicine. It makes it possible to visualize information almost in real time. In order to realize a measuring station for inverse hyperspectral imaging, a fiber-coupled light source was developed to increase the spectral power density with 40 LEDs with 17 wavelengths in the range from 388 nm to 805 nm. An automated measuring station was developed in which both illumination types, bright field and dark field, as well as the imaging unit were integrated. The automated control of the components of the measuring station makes it possible to record the spectral information of the sample within 15 seconds. A liquid lens is used for this purpose. It enables correction of the focus difference of all wavelengths for a resolution of up to 3.5 μm. Furthermore, the use of a highly sensitive industrial camera without color filters maximizes the spatial resolution. To evaluate the system, a standardized sample and prepared skin, muscle, tendon and bone tissue were examined. With the realized measuring station for inverse hyperspectral imaging and the numerical processing of the resulting image data, cellular structures and features of the biological tissue can be made visible and thus differentiated.

One common limitation of spectral-domain optical coherence tomography (SD-OCT) is the mismatch between line-scan camera pixels and the wavelength of the source spectrum, causing image thickening in deeper regions and compromising imaging quality. Various studies have addressed this issue by attempting to improve the alignment between camera pixels and wavelength, with a focus on mitigating the nonlinearity of wavenumbers in SD-OCT systems. To enhance signal quality in deeper imaging regions, several wavenumber linearization (k-linearization) methods have been explored. In our research, we have introduced a novel k-linearization approach based on the diffraction grating equation. The specifications of the light source in our SD-OCT system were utilized for algorithm simulation. Our method concentrated on the difference in diffraction angles at the diffraction grating within the spectrometer to determine the incident wavenumber per pixel. By applying the acquired k-index to our system, we observed an improvement in intensity roll-off and a reduction in the thickening of images in the high-frequency region of the sample. One notable advantage of our proposed method is its effectiveness in obtaining a suitable k-index for systems with simple specifications. Additionally, it can be easily tailored to meet the specific requirements of different systems. This ensures that our approach is not only innovative but also adaptable to diverse SD-OCT setups.

Dental cervical abrasion is wear on the neck of the tooth where it meets the gums. To treat cervical abrasion, a therapeutic resin is used to fill the worn area. It is difficult to check whether the resin has structural defects such as internal voids. If the resin is not properly cured or has internal voids and bubbles, it can easily fall off when subjected to an external impact. OCT can be used to non-destructively inspect the internal structure after treatment. By acquiring cross-sectional images of the treated area, OCT can be used to check if bubbles have formed inside the resin. In addition, to check the volume of resin used in the treatment, an algorithm is used to extract the resin portion from each tomographic image.

Blood vessel imaging is essential for diagnosing and treating ear-related diseases like tinnitus caused by altered blood flow. However, existing methods using cadaver samples have limitations due to vessel collapse or loss. This study utilizes optical coherence tomography angiography (OCTA), a non-invasive, label-free imaging of ear blood vessels. Customized imaging tips and a complex differential variance algorithm enhance OCTA image quality. Vascular distribution in 10 volunteers (5 male, 5 female) is successfully imaged. Internal factors, such as skin condition and body fat percentage, affect image quality by influencing light penetration, signal-to-noise ratio, and system robustness. Quantitative values for 20 parameters are obtained, enabling comparative analysis of blood vessel images. The findings demonstrate OCTA's potential in diagnosing and treating ear-related diseases and provide insights into blood vessel dynamics.

An epifluorescence microscope setup has been developed and tested featuring Raman and multiplex-CARS capabilities. Samples were stored in 96 multi well plates on a sample stage with triaxial piezo drive stages for sample scanning. Raman excitation was achieved by a 785 nm laser with up to 100 mW output power and below 1 pm wavelength bandwidth (FWHM). Multiplex CARS was excited by a laser system providing 1064 nm primary pulses with 1 ns duration and broadband “white” anti-Stokes radiation (1100 nm … 1700 nm) generated by a non-linear optical fiber. Repetition rates around 30 kHz resulted in an average excitation power of up to 200 mW. For both excitation principles the signal was captured by a Raman spectrograph (Ocean Insight QEPRO) designed for 790 nm … 1070 nm spectral range, resolution below 1 nm and a thermoelectrically cooled detector for a good signal-to-noise ratio (SNR) to detect weak RAMAN and CARS signals. First measurements have been performed on selected samples and promising results have been achieved.

This manuscript reports the application of Surface Plasmon Resonance imaging for analysing C. elegans nematodes. Our aim is to utilise this simulation to examine the effect of refractive index and geometry of C. elegans in order to gain deeper insights into the nematode's biological features. Employing Fresnel equations and the Transfer-Matrix Method, we investigated these aspects at the sensor-nematode interface, which is part of a multilayer model consisting of a 50 nm gold thin film deposited on a semi-infinite glass substrate. The nematode is immobilised on the thin film via an agarose sheet that forms a microfluidics channel filled with phosphate-buffered saline (PBS). The worm is modelled as an ellipsoidal crosssection allowing us to varying ellipse parameters and adherence profile on the gold thin film. Our findings illustrate the effects of the gap between the gold film and the worm, the geometry of the worm’s body, and its refractive index on SPR imaging. Our results indicate variations in the SPR response due to the geometry of both agarose and worm tissue with no observed response beyond the penetration depth of the SPR sensor. The observed range of SPR angle change was from 0 to 7°, with the most substantial changes noted in the worm area. This research highlights the potential for employing highly sensitive, label-free SPR microscopy techniques in the biological imaging of the C. elegans cuticle.

Mitochondria are highly dynamic organelles that continuously go through fission and fusion, a process that characterizes mitochondrial dynamics. These dynamics are important for the maintenance of the cell and are factors in aging, metabolic-related diseases, and cancer. Autofluorescence imaging (AFI) is used to study metabolic changes in the cell using the endogenous fluorophores reduced nicotinamide adenine dinucleotide (phosphate) NAD(P)H and flavin adenine dinucleotive (FAD). AFI can be used to study the dynamics of mitochondria, but requires high imaging speeds to capture the mitochondria movement. Here, we describe a multiphoton imaging technique that simultaneously captures NAD(P)H and FAD with a single excitation wavelength of 790 nm, reducing imaging times. A cyanide experiment was performed to verify that AFI at this optimal wavelength captures metabolic changes in cells. The optical redox ratios were computed from NAD(P)H and FAD images obtained both simultaneously using a single excitation wavelength and sequentially using the absorption-matched excitation wavelengths. The AFI results at 790 nm support the simultaneous acquisition of NAD(P)H and FAD for further research of mitochondrial dynamics and the metabolic state of the cell.