There is great need for new diagnostic methods in order to be able to use targeted therapy as early as possible. Marker-free spectroscopy methods can be sensibly combined to a multi-contrast approach to help meet this need. Here, we will present a number of innovative multi-contrast approaches for (I) rapid diagnosis of infectious diseases for targeted antibiotic administration, which is crucial for patient survival (e.g. sepsis); (II) precise intraoperative tumor margin control, because reliable tumor margin recognition during an intervention is the key to effective tumor treatment; and (III) early diagnosis of neurodegenerative diseases at the fundus of the eye.

We present a Raman micro-spectroscopy technique applied to in-vitro monitoring of the differentiation state of salivary gland organoids. We have collected and analyzed Raman spectra of the embryonic salivary gland epithelial progenitor cells and primary mesenchymal cells. The cells were treated with Fibroblast Growth Factor 2 (FGF2) and observed over the course of several days. While the chemical signature of the epithelial cells remained the same, the mesenchymal cells exhibited protein structure changes, possibly indicating alterations in the cell differentiation state. Based on these measurements, we develop Raman metrics that can be applied to the non-invasive monitoring of organoids.

Deep near-infrared light (e.g., 1064 nm) is often used when probing highly photosensitive/photolabile specimens to suppress the strong fluorescence and to avoid photodamage. We developed a multifocal pattern approach for 1064 nm Raman imaging that can produce quality spectra under limited excitation energy dose. We demonstrate that the multifocal approach improves both the signal-to-noise ratio and the imaging speed of Raman microscopy, especially under high noise detection conditions.

The development of implants that provides a scaffold for the growth of native bone requires the ability to monitor implant biodegradation and production of soft and mineralized extracellular matrix (ECM). Raman spectroscopy provides a non-invasive, non-destructive technique for biochemical characterization. Online monitoring of tissue engineered constructs using fiber-optic Raman spectroscopy has been demonstrated for cartilage growth in hydrogels. Here we utilize the method for time resolved monitoring of a novel 3D printed resorbable bone implant in vitro. Raman spectra of live human mesenchymal stem cells seeded on implants of tricalcium phosphate in osteogenic induction medium were collected over a period of 6 weeks. Estimates of pure spectral components representing tricalcium phosphate and bone ECM were extracted using multivariate curve resolution techniques. From these the relative concentrations of ECM components were estimated.

Motions inside living tissues are ubiquitous signatures of the active processes involved in the maintenance of cellular function and health. An innovative label-free non-invasive imaging technology called Biodynamic Imaging (BDI), based on low-coherence interferometry and digital holography, captures intracellular dynamics through ultra-low-frequency Doppler spectra encoding a broad range of cellular and subcellular motions. Clinical trials of BDI assessing patient response to therapy are underway in human ovarian, esophageal and breast cancers.

By virtue of its chemical specificity and label-free nature, Raman spectroscopy is a ubiquitous tool in analytical chemistry which has recently found increasing interest in biology and medicine, as technical improvements steadily enable applications. In particular, the low-frequency region of the Raman spectrum, which contains rich information about intermolecular interactions and higher-order structure, has promise for biological applications. However, detection of low-frequency modes remains a challenge with conventional techniques for Raman spectroscopy. Here, we propose and experimentally demonstrate Sagnac-enhanced impulsive stimulated Raman scattering (SE-ISRS), a method for time-domain Raman spectroscopy that provides highly sensitive low-frequency Raman spectra at all probe frequencies.

Altered biomechanics and phase transitions are implicated as key photogenic triggers in neurodegenerative diseases. However, standard methods to measure them require invasive contact with the sample or provide low spatial resolution. Here, we demonstrate Brillouin microscopy as a potential tool to investigate liquid-to-solid phase transitions in intracellular compartments in response to expression of ALS-linked proteins. In particular, we show how intracellular stress granules exhibit altered biomechanics in response to recruitment of RNA-binding proteins, such as ELAVL4 and FUS. Results pave the way to a better understanding of the dynamics that lead to formation of solid aggregates during neurodegeneration.

Brillouin microscopy is a noncontact, label-free method for imaging the mechanical properties of materials. The Brillouin shift and broadening are expected to increase asymmetrically in frequency with increasing microscope NA. Recently, a virtually imaged phase array (VIPA) based Brillouin microscope was used to measure the NA-induced total Brillouin line broadening. The limited resolution of the spectrometer did not allow to measure the asymmetric nature of this broadening. Here, we use a stimulated Brillouin gain (SBG) spectrometer to measure with high spectral resolution the asymmetric spectral shift and broadening of the Brillouin lines of water as a function of NA.

Spectral phasor analysis applied to UV-excited autofluorescence from cellular suspensions can distinguish metabolic responses linked to various respiratory and oxidative stress pathways. In order to extend this analytical approach to the assessment of cellular metabolism in tissues, we investigate the metabolic responses of yeast cells embedded in turbid media containing collagen. Respiration and oxidative stress responses are induced using specific chemicals and by varying oxygenation. Autofluorescence is monitored in real time and spectral phasor analysis is assessed for its ability to distinguish these responses as compared with previously reported cell-only controls.

Here we demonstrate clinical in vivo microscopical imaging of the melanin distribution in human skin with absolute quantities on mass density using label-free third-harmonic-generation-enhancement-ratio (erTHG) microscopy. By adopting the resonant enhancement ratio to deal with the background calibration beacon issue, here we propose to retrieve the erTHG parameter in situ and thus recover the absolute quantity of melanin within a sub-femtoliter volume. In vivo clinical studies were conducted to validate our approach and confirm the unique capabilityof erTHG microscopy to meet the unmet clinical need.

Amyloid plaque and neurofibrillary tangles (NFT) are the neuropathological hallmarks of Alzheimer’s disease (AD). Here, we describe a combination of label-free imaging methods: second and third harmonic generation microscopies (SHGM/THGM) for the visualization these hallmarks in AD mice brain tissues. THGM is capable of imaging myelinated axons, soma along with plaque and NFT; while SHGM can distinctly image the plaque and NFT. The combined capabilities THGM and SHGM can provide us complete neuropathological features of AD brain tissues and further, can also become an alternative to traditional histopathological examination which relies on tedious immunohistochemical staining procedures.

Recent developments in label-free multiphoton histology promise a new era for real-time molecular diagnosis in the operating room and during biopsy procedures. Here we developed a deep-learning-based framework to recognize cancer versus normal human breast tissue from real-time label-free multiphoton images, with a tile-level AUC (area under receiver operating curve) of 95% and slide-level AUC of 100% on unseen samples. Furthermore, models trained on a high-quality laboratory-generated dataset can generalize to independent datasets acquired from a portable intraoperative version of the imaging technology with a physics-based adapted design.

Human mesenchymal stem cells (hMSCs) are the focus of significant research focus due to their capacity to contribute to regenerative medicine. Unfortunately, significant heterogeneity exists between lines which can limit their usefulness. Consequently, the characterisation of cell lines is important for research and clinical practice. We have used the multispectral assessment of inherent cell autofluoresence to create a novel protocol which accurately assesses multiple cell properties including cell cycle, senescence, pluripotency and age, in a single test.

Tissue morpho-mechanics is gaining an increasing relevance in various fields, including biology, medicine, pathology, tissue engineering, and regenerative medicine. Here we report a correlative study performed by optical microscopies, disclosing the supramolecular collagen morphology correlated with its biomechanical and biochemical analyses in human corneal tissue, using SHG Brillouin and Raman micro-spectroscopy. In particular, we demonstrated that the peculiar mechanical functionality of so-called sutural lamellae originates from their distinctive supramolecular organization. The proposed methodology opens the way to the non-invasive assessment of tissue morpho-mechanics and holds the potential to be applicable to a broad range of biological and synthetic materials.

Automated, unbiased methods of non-invasive cell monitoring able to deal with complex biological heterogeneity are fundamentally important for biomedical research. Label-free imaging provides information about endogenous autofluorescent metabolites, enzymes and cofactors. Our multispectral fluorescence imaging technique allows precise quantification of native fluorophores in cells and tissues. This study uses label-free multispectral analysis to extract different fluorophores and redox ratio from single cells (oocytes, cultured cancer cells) as well as blastocyst embryos. Additionally, we characterise the molecular composition, structure and functional status of ex vivo healthy bovine and osteoarthritic human knee articular cartilage to assess 2 types of experimental treatments.

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive and poorly understood disease with a 7% 5-year survival rate. The PDAC tumor microenvironment has been implicated in tumor initiation, progression, and metastasis, but little is known about how tumor cells benefit from stroma. Here we perform label-free optical redox imaging of autofluorescent metabolic coenzymes reduced nicotinamide adenine dinucleotide(phosphate) (NAD(P)H) and flavin adenine dinucleotide (FAD) in a 3D pancreatic tumor organoid and pancreatic stellate cell co-culture model. Our results show that stromal cells support the growth of tumor organoids and reveal striking difference between redox states of these cell types in 3D co-culture.

Developing real-time machine-learning technology to process in vivo hyperspectral imaging data capable of detailed brain tissue characterisation requires a comprehensive reference training dataset. In this study, we describe how a dual-beam spectrophotometer may be adapted to determine the optical properties of small human brain tumour and tissue samples across a wavelength range of 400 to 1800 nm. Using our experimental setup, we measured the scattering and absorption properties of various freshly-excised brain tumour and normal cadaveric brain tissue specimens, demonstrating specific discriminatory features within their optical properties.

The pathological examination of regulatory relevant tissue samples is done manually and highly time consuming. Label free optical technologies like quantitative phase microscopy (QPM) and Optical Coherence Tomography (OCT) provide fast analysis of fixated cells and tissues by biophysical parameters. Combination of various wavelengths allows label free QPM tissue characterization equivalent to HE staining. Recent OCT studies showed 3D imaging of rat embryo details as bone structures, full vertebra, whole feet and parts of the skull. The multi-functional potential of QPM and OCT represents a promising new approach for label free phenotyping of regulatory relevant cell and tissue alterations.

Optical coherence tomography (OCT) suffers from speckle noise due to use of spatially coherent light, leading to significant reductions in image quality. Angular compounding techniques have been applied to remove speckle noise, but, existing image registration methods only guarantee pure angular compounding in the focal plane and produce spatial averaging in the defocused regions. This work develops an image registration model to correctly localize the real-space location of every pixel in OCT images captured at multiple incident angles, with digital focusing to further increase the lateral resolution and contrast. In the composite image, speckle suppression and resolution enhancement are realized.

We demonstrate wide-field intraoperative in vivo PS-OCT and OCT-A imaging of non-human primate (NHP) peripheral nerves using a portable OCT prototype. Imaging was performed on healthy and surgically repaired (12 months after graft surgery) radial nerves in upper extremity of rhesus macaques (n=17) over surgically exposed nerve segments of up to 8 cm in length. We describe the capabilities and challenges of PS-OCT and OCT-A in assessing NHP peripheral nerves. Further, guided by imaging of NHP peripheral nerves, we discuss the required advancements in core polarimetry techniques to enhance the prospects of clinical utility of PS-OCT in peripheral nerve imaging.

In this work we develop a theoretical framework for analyzing generic speckle reduction algorithms including all possible light modulations: angular compounding, spatial light modulators and others. We show that speckle reduction using Laguerre Gauss modes - LG Speckle Reduction achieves the theoretical boundary of speckle reduction using minimal number of samples and therefore is optimal. We demonstrate LG Speckle reduction in in-vitro sample and show that speckle reduction is in line with our theoretical model. We further develop LG Speckle Reduction to show that it can outperform speckle reduction outside of the focal plane by most speckle reduction methods and generates fast and high-quality images.

We have developed an ultra-high resolution optical coherence tomography (OCT) and angiography (OCTA) in vivo zebrafish imaging platform to visualize the tumor micro-environment and vascularization in a novel developed zebrafish cancer model. The system is optimized to detect subtle morphology changes and slow flow. Morphology and vascularization is significantly altered especially in small intersegmental vessels compared to the healthy control. This can be established as early biomarkers for early cancer detection and progression. OCTA results are validated with confocal fluorescence imaging showing the actual blood perfusion in a label-free and non-invasive manner.

Today's gold standard for medical diagnosis is histology of excised biopsies or surgical specimens where tissue is removed from the body, processed, sectioned, stained, and looked at under a microscope by a pathologist. There are many limitations to this paradigm, including the facts that it is inherently invasive, time consuming, costly, and dangerous for some organs. Furthermore, oftentimes the diseased tissue is not readily seen by visual inspection. In these instances, the tissue is sampled at a random location, which can be highly inaccurate. If we could instead conduct microscopy inside the body, then we could overcome these limitations and provide real-time tools for screening, targeting biopsies, making diagnoses, and guiding intervention with cellular-level precision. This promise has motivated the development of a new field, termed in vivo microscopy, the goal of which is to obtain microscopic images from living human patients. Two in vivo microscopy technologies, confocal microscopy and optical coherence tomography, are currently available and in clinical use. Upcoming developments, such as whole organ microscopy, swallowable microscopy capsules, molecular imaging, and very high resolution microscopic imaging devices are in the pipeline and will likely transform how disease is diagnosed and medicine is practiced in the future.

Rapid antimicrobial susceptibility testing (AST) is needed for combating the threat of antimicrobial resistant bacteria. Surface enhanced Raman scattering (SERS) spectroscopy is an emerging tool for phenotypic AST and lends itself well to machine learning models. Yet SERS AST must be validated with traditional methods that require enormous resources to produce the data to train models. In this work, we demonstrate that variational autoencoders (VAEs) automatically produce meaningful latent space of SERS spectra from Psuedomonas aeruginosa lysate treated with different antibiotic conditions. We show that the VAE latent space enables an effective semi-supervised deep learning approach that enormously reduces the amount of expensive labeled data required. This method is broadly applicable to AST, with antibiotic response observed in Escherichia coli in just 10 minutes, and can identify antibiotic response in dosages up to 500 fold smaller than the minimum inhibitory concentration.

Organophosphates (OPs) are a class of pesticides and chemical warfare, several of which are highly toxic. Based on the newest report, there are nearly three million poisonings per year resulting in two hundred thousand deaths around the world. Inspired by the Liquid Crystals (LCs)’ extraordinary properties, we employed a customized LCs sensor to detect OPs with high sensitivity & selectivity, fast response time, and reusability. As proof of our research, four different measurements were operated in the experiments: sensitivity, response time, selectivity, and reusability. The results showed that the limit of detection (LOD) of our proposed sensing method can selectively detect OPs lower to the 10ppb concentration in 25 seconds in four different vapors (OPs, Steam, Ethyl alcohol, and Methylbenzene), which was far lower than the US EPA safety levels for OPs and also faster than the other competitors. Further, the sensor can be recovered by the nitrogen gas treatment in 30 seconds.

In the context of biosensing and plasmonic imaging, we will report on actual characterization of structured biological objects such as layers of cell films. To achieve this, compared to conventional plasmonic systems, one can optimize not only the optical system but also the substrates that support the plasmonic modes and diminish the propagation length associated to this non-local imaging modality. We will focus on this latter point and present both simulation and experimental results, making use of flat and nanostructured geometries that allow achieving better imaging resolution yet keeping good contrast.

The ability to accurately response pressure transients is critical for photoacoustic (PA) imaging of anatomic and functional information in biological tissues. The routinely-adopted piezoelectric transducer usually operates at limited sensitivity and bandwidth, resulting in inadequate response to PA pressure transients. Here, we propose a surface plasmonic sensing approach for PA pressure detection. Relying on modulations to the refractive index of the coupling medium caused by temporal ultrasonic perturbations, PA pressure transients are retrieved by recording variations in the reflected light. We relalize the PA detection with a broad bandwidth of ~180 MHz and a sensitivity of ~100 Pa. In vivo imaging of the microvasculature is obtained label-freely from mouse. These results suggest that the surface plasmonic sensing is potentially invaluable in PA imaging for biomedical investigations.

Photothermal effect is a highly sensitive optical phenomenon often used for label-free imaging and spectroscopy for chemical identification and quantification. We demonstrate the capability of quantitative phase imaging (QPI) for detecting photothermally generated refractive index change in a sample. We will show that a highly sensitive QPI technique, termed spectral multiplexing interferometry (SMI), is capable of sensing the weak photothermal signal. We discuss the theory of photothermal phase microscopy, its experimental implementation and utility for live cell imaging using the SMI technique.

We present assessment and validation of label-free hyperspectral imaging of Nectrotising Enterocolitis (NEC) in neonates. NEC is among the most devastating of neonatal diseases, characterized by intestinal necrosis of variable extension, potentially leading to perforation, generalized peritonitis and death. For babies undergoing NEC laparotomy, we describe and validate our exoscopic hyperspectral imaging system, capable of monitoring tissue oxygenation intraoperatively. It is designed to provide high-resolution images of oxygen saturation, blood oxygenation and blood volume. The hyperspectral images are correlated with standard RGB photography and surgical assessment of necrotic, ischaemic and normal bowel, enabling a clear interpretation of the available data.

Collagen fiber architecture plays an important role in the mechanical properties of soft tissues. However, conventional techniques for visualizing collagen structure and orientation require acquiring multiple images, which is slow and reduces the level of detail discernible. We demonstrate instant polarized light microscopy (IPOL) a label-free technique that visualizes collagen fiber color-coded orientation with only one image. Implementing IPOL on a stereo microscope allowed fast imaging (156 fps) of a large field of view (35 mm) with long working distance (65 mm) in either transmitted or reflected light setups. IPOL is a powerful label-free imaging technique ideal for time-sensitive applications.

Graded index (GRIN) lenses focus light through a radially symmetric refractive index profile. It is not widely appreciated that the ion-exchange process that creates the index profile also causes a radially symmetric birefringence variation. This property is usually considered a nuisance, such that manufacturing processes are optimized to keep it to a minimum. Here we show that this birefringence can be harnessed as a basis of a new single-shot Müller matrix polarimeter with potential for endoscopic label-free cancer diagnostics.

Polarimetric imaging is becoming increasingly accessible and is gaining recognition as a powerful modality in biomedical imaging. As larger databases of polarimetric images become accessible, machine learning tools can be used to classify tissues with complex polarimetric responses. We present a principled statistical analysis framework based on decision theory. It consists of a complete pipeline for polarimetric bioimages, comprising a preprocessing stage replacing pixels by superpixels and an analysis stage for the selection and tuning of a classifier. The use of this rigorous and versatile framework is illustrated on several use-cases.

Tissue-based diagnostic relies on histological analysis of tissue cuts by a pathologist who links data derived from microscopy image content to a specific disease. We explored the potential of Mueller microscopy combined with density-based spatial clustering algorithm for applications with noise for the automated analysis of tissue histological cuts. Mueller microscopic images of unstained artificial human skin histological cuts were analyzed by applying differential Mueller matrix decomposition. Scalar retardance, depolarization and total transmitted intensity images were used for the automated segmentation of microscopic images. An algorithm of polarimetric data post-processing which mitigates the impact of tissue thickness fluctuations was suggested.

Most of the recent super-resolution imaging techniques developed for biology are based on fluorescence properties which generally require toxic dyes. We show how super-resolution can be obtained without dyes by simply adding 20-micrometer-diameter dielectric spheres on the sample under a microscope objective. The microsphere behaves as a non-classical lens, collecting evanescent waves in a full-field imaging process. Resolutions of up to between /5 and /7 can be reached in air and in immersion, respectively. For translucent biological samples, a dark-field optical setup is proposed. Performance of the label-free super-resolution technique is demonstrated through the imaging of fixed nerve sections from a mouse embryo brain.

Facile analysis of the architecture of the mammalian brain is key to understanding how brain function emerges during development and dysregulated in disorders including neurodegeneration. Immunolabeling of mammalian brain tissue, especially scarce human brain tissue, is time-consuming, can introduce sample-to-sample variation, and is not compatible with live imaging. We report joint optimization of polarization-resolved label-free imaging and deep learning to map brain architecture. We visualize diverse structures in human brain tissue by mapping optical properties of density, birefringence, orientation, and scattering. We design computationally efficient variants of U-Nets to predict tract distribution and cell types from intrinsic optical properties of the tissue.

The biggest challenge on the path towards high-dimensional imaging is obtaining spatial and spectral information of a volumetric sample in real-time. Advances in this field are of vital importance for biology, material sciences, and medical applications. For example, cancer is one of the leading causes of death in the world, thus gaining a mechanistic understanding of cancer cell processes will significantly impact therapies targeting cancer metastasis pathways. Revealing the entire process with its surrounding environment will require real-time imaging systems that will open the way for better understanding of cancer onset and tissue morphology. This talk will introduce real-time volume holographic imaging systems, which are based on multiplexed volume holographic (MVH) gratings acting as spatial-spectral filters used in conventional optical imaging systems. This allows the acquisition of spatial images with spectral selectivity but without scanning in both transverse and longitudinal directions. In addition, quantitative phase imaging with illumination-based differential phase contrast (DPC) microscopy has recently been utilized to recover 3D images of cell samples. Through multiplexed pupil engineering, different schemes of DPC under coded illumination will be presented to achieve isotropic differential phase contrast (iDPC) in more efficient fashion. Our iDPC is implemented with a partially coherent microscopy, and a programmable TFT shield as coded spatial-spectral pattern. Experimental results of quantitative phase images of standard samples (e.g. micro-lens array) and stain-free cells (e.g. human cancer cells and adipose derived stem cells) will be demonstrated via iDPC.

The recent development and integration of multiple non-linear microscopy techniques in a single instrument has provided new opportunities for integrating morphological and functional information and for correlating the observed molecular and cellular changes with disease behaviour. In particular, multimodal non-linear/linear imaging is able to perform a morpho-chemical quantitative analysis in tumour cells and tissue specimens, providing a high-resolution label-free alternative to both histological and immune-histochemical examination of tissues. In this talk, a brief overview on the non linear and linear laser brain imaging techniques will be displayed for label free detection. Morpho-chemical characterization of tissue will be displayed as an interesting tool for early diagnosis of pathologies: different kind of approaches will be shown for in vivo imaging assisted surgery operation or as tools to support anatomo-pathologists decision.

Heart failure (HF) has a large impact on patient outcomes and health care costs. Objective monitoring of the pitting edema level of a HF patient may help clinicians reduce the amount of readmissions. ChemImage is developing a Molecular Chemical Imaging (MCI) device for monitoring HF patients that will non-invasively quantify peripheral edema. Results from a completed in-human clinical trial will be presented demonstrating ability to discriminate between healthy volunteers and HF patients with all levels of pitting edema and correct prediction of peripheral edema grade across the patient population. Follow-on clinical trials will address monitoring patients during treatment.

Chemical microscopy utilizing fingerprint spectroscopic signals is able to map the chemical contents temporally and spatially. Such capacity opens a new window to visualize the orchestra of molecules and/or biological structures inside living systems. Cheng and his research team have been dedicated to pushing the boundary of chemical microscopy in the entire spectrum of molecular spectroscopy, discovering molecular signatures in diseases, and translating label-free techniques to clinic for molecule-based precision diagnosis or treatment.

We present coherent anti-Stokes Raman (CARS) imaging with our robust all-fiber optical parametric oscillator (FOPO) that is tunable across the whole bio-relevant spectral region (700 to 3530 wavenumbers) in less than 5 ms. The all-fiber operation allows to operate the FOPO on a regular laboratory cart, maximize temporal pulse overlap by dispersion management and inherently minimize beam-pointing. We present first CARS images of DMSO-d6 infiltration into mouse skin imaged in the silent as well as CH-stretch region without any alignment other than electronically tuning the wavelength. The FOPO is ideally suited for label-free, hyperspectral imaging, e.g., in translational research.

Nonlinear Raman microscopy is getting a lot of attention recently offering non-invasive, chemically specific optical imaging. Nonlinear Raman microscopy is normally presented as a full analog of spontaneous Raman spectroscopy, which permits much faster optical measurements. However, there are several benefits of coherent Raman microspectroscopy, which are often overshadowed and which have an untapped potential to provide new chemical and structural information about molecules in their natural environment.

Stimulated Raman scattering (SRS) microscopy is a powerful technique for label-free identification of molecules based on their intrinsic vibrational spectrum. Here we present two broadband SRS setups with broad spectral coverage (500 cm-1) and high frequency resolution (15 cm-1). The first is a hyperspectral SRS equipped with a diffraction grating and a galvanometric mirror after the sample to scan the Raman frequency using a commercial lock-in amplifier with 1.8-μs integration time. The second solution is a multiplex SRS setup involving a recently developed balanced low-noise multichannel lock-in amplifier [Integration, the VLSI Journal 67, 44 (2019)] with 30-μs integration time for collecting the spectrum with up to 32 channels in parallel. The broadband pulse is generated by a home-built optical parametric oscillator. We employ in-line balanced detection [Sci. Rep. 7, 10745 (2017)] to suppress laser fluctuations and achieve close to shot-noise-limited sensitivity.

We present a novel design for a Stimulated Raman Scattering (SRS) microscope based on a dual beam femtosecond laser in combination with spectral shaping through a fast and narrowband Acousto Optical Tunable Filter. This configuration allows the measurement of broad SRS spectra, all the way from fingerprint region to CH stretch region without any modification of the optical setup. High spectral resolution over a broad spectral region allows label-free quantitative imaging of biological samples. We will show the application of our SRS system to a quantitative study of lipid droplets in colon Cancer Stem Cells.

We present a flexible, compact, and multimodal nonlinear endoscope (2.2 mm outer diameter) based on a resonantly scanned negative curvature hollow-core double-clad fiber. The fiber design allows distortion-less, background-free delivery of femtosecond and picosecond excitation pulses and the back-collection of nonlinear signals through the same fiber. Sub-micron spatial resolution together with large field of view is made possible by the combination of a miniature objective lens together with a silica microsphere lens inserted into the fiber core. We demonstrate coherent anti-Stokes Raman scattering, 2-photon fluorescence and second harmonic generation imaging at a rate of 10 frames/s.

Spontaneous Raman spectroscopy integrated with an ultra-thin fiber-based endoscope can provide remote, local, and minimally invasive chemical analysis in many fields from biomedical diagnostics to the materials industry. Here we quantitatively analyze how the wavefront shaping technique improves the sensitivity of an ultrathin Raman probe. Such a fiber probe is well suited for minimally-invasive endoscopy and endo-microscopy in biological and medical applications. We show that with wavefront shaping the total measurements time can be decreased by several orders of magnitude over no wavefront shaping, even without any prior knowledge of the Raman particle location.

Raman spectroscopy is an efficient way to analyze molecular vibrational and rotational information in a sample. It provides non-invasive qualitative and quantitative analysis without elaborate sample preparation. We used Raman micro-spectroscopy to visualize and quantify the amount of iron-bound transferrin (Tf), which is the main carrier of iron into the cells. We have mapped the iron contents of iron-loaded Tf in T47D and MDA-MB-231 cancer cells. We have shown that the amount of Tf bound iron in cells is dependent on the internalization and endocytic trafficking of Tf.

Hirschsprung's disease (HD) is a congenital disorder in the distal intestine and is characterized by the absence of nerve ganglion cells (aganglionosis). HD affects newborns by causing severe constipation. Histology is the gold standard for definitive diagnosis. Many factors for misdiagnosis have been commonly reported. Here, for improving the identification of ganglion cells, we propose an ex-vivo study to evaluate a combination of label-free optical modalities: second harmonic generation (SHG), two-photon autofluorescence, and Raman spectroscopy for locating regions of interest and identifying ganglion cells based on their unique molecular fingerprint.

Extracellular vesicles (EVs) are biologically derived nanovectors important for intercellular communication and trafficking, yet understanding of their underlying biological mechanisms remains poor. Advances have been hampered by both the complex biological origins of EVs and a lack of suitable imaging techniques. Here, we present a strategy for simultaneous in vitro imaging and molecular characterisation of EVs in 2D and 3D based on Raman spectroscopy and minimally-obstructive metabolic deuterium labelling. Metabolically-incorporated deuterium acts as a bio-orthogonal Raman-active tag for direct Raman identification of EVs and provides insights into their biocomposition and trafficking, with implications for their development as therapeutic delivery vectors.

We examine multiphoton-produced optical signals waveguided through single ZnO nanorod (NR) using a newly developed, scanning offset-emission hyperspectral microscopy (SOHM) technique. SOHM acquires spectrally indexed and spatially resolved intensity maps/spectra of waveguided light intensity, while excitation/emission collection positions and light polarization are scanned. Hence, the powerful measurement capabilities of SOHM enable quantitative analyses of the different ZnO NR waveguiding behaviors specific to the multiphoton-generated emissions as a function of measurement position, and the optical origin of the guided signal. We subsequently reveal the distinct waveguiding behaviors of single ZnO NRs pertaining to the variously originated signals and discuss particularly attractive ZnO NR properties in CARS waveguiding. In this talk, I will present the distinctive CARS waveguiding nature through single ZnO NR, exhibiting high position and polarization-dependence.

The nature of the molecular bonds involved in the red blood cells (RBC) aggregation was studied using CARS. This technique employs infrared illumination in pulsed mode, compatible with bimodal analysis in FLIM. The pump wavelength was tuned (817-904 nm) for the CARS mode simultaneously with the Stokes beam at 1064 nm. The vibratory resonance of bonds was excited in the lipids and amino acids of the proteins to study both possible variations on the cell membrane and in the sialic acid terminals. Different lifetime emission distribution curves were obtained for the control RBC samples and altered ones with Dextran 500.

Interference reflection microscopy (IRM) is a label-free imaging technique that is underused due to the complicated nature of the image formation that makes image segmentation challenging. We will report our progress on the use of deep learning for the identification and quantification of focal adhesions in IRM images of mesothelial cells. With this approach we are studying the link between the Hippo pathway and focal adhesion function in malignant mesothelioma (MM) cancer. There is strong evidence that the Hippo pathway is dysfunctional in MM. Recent studies showed that the Hippo effector YAP/TAZ can lead to impaired focal adhesion function, underlining the potential as treatment target.

Epithelial-mesenchymal transition (EMT) is a crucial mechanism for the invasion and metastasis of epithelial tumors characterized by the biophysical changes in epithelial cell markers. These changes can be defined via changes in the refractive index (RI) of the cell membrane. We report the use of our Photonic-Crystal biosensor in a Total-Internal-Reflection (PC-TIR) configuration to construct a label-free biosensing system, which allows for detecting changes in cellular RI of prostate cancer cells due to EMT, by exposing these cells to Transforming Growth Factor Beta 1.

Daphnia has been used to monitor not only the environmental impacts under guidelines by the OECD but also evaluating the efficacy of cardioprotective drugs. The aim of this study is to automatic acquire the quantitative heart rate for monitoring the heart toxicity test. We carried out analysis the frequency of the dynamic phase by the heartbeat of Daphnia using 200-fps off-axis digital holography. The Daphnia aged less than 24 hours exposed to the Astemizole, Amiodarone, and Cappine during 24 hr and 48 hr. Also, the transfer process were monitored through real-time quantitative heart rate change process during 10 min.

Line scan Raman microspectroscopy (LSRM) provides information on the spectral properties as well as on molecular resolved spatial distribution of compounds. Classification of healthy pituitary gland and tumorous pituitary adenoma tissue as well as periostal layer via Raman spectroscopy and spectral analysis with principal component analysis (PCA) and k-nearest neighbor (kNN) classification comprise the target of this study. Based on the results of PCA, LSRM images are reconstructed at Raman bands of interest. The contrast of LSRM images arising from different amounts in present molecules might add valuable information for diagnosis in addition to the classification with accuracies exceeding 83%.

Metabolic Syndrome is one of risk factors of cardiovascular diseases and its possible relation with dementia is　suggested. To evaluate cerebral microvessels is important to investigate the disease progressions. Due to its metabolic similarities to human, a metabolic syndrome model in small fish, such as zebrafish and medaka, has been generated. Noninvasive access to cerebral vascular system in these disease models will allow us to investigate the individual disease progressions. In this study, we developed a noninvasive angiographic approach and explored cortical vascular distribution in wild type medaka with Optical coherence tomography. The minimum diameter of visualized microvessels was 8μm.

A desktop microscope was adapted for snapshot megapixel polarization imaging enabling single shot measurement of reflectivity/transmittance, phase retardation and fast birefringent axis orientation. The microscope was equipped with a micro-polarizer sensor capturing super-pixel images of four polarization angles simultaneously. Custom adapters were designed to fit polarization optics into the slots of the microscope to illuminate the sample with circular polarized light and enable Jones vector analysis. Alzheimer’s disease brain tissue was imaged to reveal the distinct birefringence patterns of neuritic extracellular plaques comprised of amyloid fibrils. Murine brain stems were imaged to visualize nerve fiber tracts in phase retardation images.

Alzheimer’s disease (AD) is a neurodegenerative disease with pathological signatures of Amyloid-β plaques deposited in the brain. In this study, we propose a real-time, label-free biosensor for the ultrasensitive detection of Amyloid-β 1-42, a representative biomarker for AD early diagnosis. The detection relies on Amyloid-β evanescently interacting with a whispering gallery mode (WGM) of a microtoroid optical resonator, shifting the resonant frequency. Measuring the shift in resonant frequency enables real-time, label-free measurement of Amyloid-β levels in fluid. Our results show discrimination between non-AD and AD patients and has potential for early detection of AD.

The myelin sheath that insulates axons in the central and peripheral nervous systems is essential for maintaining complex neural function. Due to its compact, layered structure, however, studying myelin with conventional molecular labeling techniques proves to be difficult. On the other hand, by using polarized-light microscopy to image myelin birefringence, the same properties that hinder molecular labeling can be leveraged to image details of the myelin sheath’s structural integrity. We have developed a flexible platform for birefringence microscopy that facilitates both qualitative and quantitative imaging of the myelin degradation associated with various neuropathies, with initial studies of age-related dementia in primates.

Current histological and imaging techniques are inapposite to study large scale tissues like central nervous system. In this study, we suggest a novel method to visualize volumetric spinal cord injury based on optical coherence tomography (OCT) and tissue clearing technique. Through this study, we can show the clear whole structure of spinal cord with border of white and gray matter. Also, we can get information of injured region. We found a new research platform to study the regeneration of spinal cord, using OCT imaging with clearing technique, that could not be achieved by conventional histopathology and optical imaging.

Sarcopenia is one of the diseases that often occur in elderly people. We studied to check the feasibility of the diagnosis of sarcopenia by measuring the concentration change of hemoglobin in real-time. We used continuous-wave diffuse optical spectroscopy for a low cost and near-infrared light that can be penetrated deeply. Customized LabVIEW program calculates the concentration change of hemoglobin using Modified Beer-Lambert Law and Least Square Method. As a result, the concentration of hemoglobin decreased overall when we pressed the arteries. On the other hand, a sudden change in the concentration of hemoglobin was confirmed when the pressure was released.

OCT-Angiography (OCTA) images are based on the nature that light backscattered from the vascular and neighboring tissue exhibiting different temporal scattering features. In this research, we built a swept-source OCT system with a 1060 nm wavelength-swept laser providing a high imaging speed (200,000 Ascans/sec) over the biological samples. By analyzing the variation of the OCT signal intensity in the OCT images acquired at different time points, the OCTA images of the mouse ear skin and mouse brain tumor models with an effective interscan time of 10 milliseconds and 20 milliseconds are performed. In addition, the changes of microvasculature during the mouse brain tumor progression are demonstrated.

Single-pixel imaging (SPI) could be a superior solution for imaging applications outside the visible spectrum. Unlike imaging by sensor array, the number measurements in series (proportional to acquisition time) and image quality are generally trade-off in a SPI system, i.e., full sampling is often considered to provide the best image quality with the lowest frame rate. However, in a low signal-to-noise ratio (SNR) scenario, the competition between adding image information and adding noise in each coefficient measurement results in an optimum number of measurements for reconstruction image quality. Here, we discuss the performance of two different types of transform in SPI: Hadamard transform (HT) and discrete cosine transform (DCT) then put forward a quality control technique to increase the efficiency of measurement. Our simulation and experiment results show the monotonic increase of imaging quality with the increase of measurements and reach maximum at full sampling with high SNR.

Uterine cervical cancer(UCC) is a common but preventable disease in women of reproductive age. In Africa, the incidence and mortality rate of UCC is very high due to economic and postitional limitations. In this study, we developed a low cost smartphone-based colposcopy and conducted clinical trials for a total of 353 patients in Kingdom of Eswatini. Smartphone cases and vaginal insertion parts were made using 3D printing. And light source and adapter were connected to it. The cervix images were acquired before and after applying acetic acid. Pap smear were also performed to support the imaging results.

Computer-aided diagnosis is a growing field of research and showed potential applications for the medical area. Moreover, label-free optical techniques are of great interest since it not requires the addition of any markers. Furthermore, metabolic changes due to diseases processes also showed great results in the last years. Joining these three fields, this work measured fluorescence lifetime of endogenous fluorophores (collagen/elastin, NADH and FAD) in skin cancer patient lesions, and classified it through multivariate algorithms. It was demonstrated a dermatologist-level classification between malignant and benign skin cancer lesions, for both pigmented and non-pigmented lesions.

The Photonic Crystal-Total Internal Reflection biosensor has been used for label-free quantification of cardiac troponin I, with a detection limit of 0.1ng/mL. To further improve on this, we deliver a silanated PEG sample to the sensor surface as a linker molecule. Functional biotin groups on the PEG provide a connection for streptavidin and biotinylated Recombinant Protein G (RPG). The addition of the RPG allows for proper orientation of cTnI antibodies. The combination of the fluidity of the PEG and the increase in active antibodies allow for improved sensitivity.

We present a deep learning algorithm for automated chondrocyte viability assessment. U-net based algorithms allow segmentation of cell areas using the second harmonic generation (SHG) imaging of cartilage samples. Once cell regions were isolated, fluorescence channels were extracted to calculate the intensity ratio defined by NADH/(NADH+FP). The results showed that the root mean square error of viability ratio between the proposed U-net/intensity ratio method was 19.8% with the accuracy of 80.2%.

Bone is comprised of collagen, mineral and organic material, but only mineral is evaluated to determine bone health. Despite the scattering nature of bone, we can recover the angle of polarized light using second harmonic generation deep in full thickness bone. We can use this polarization recovery method that accounts for diattenuation, birefringence, and polarization cross talk to describe collagen structure in bone and discriminate between diseased and healthy states. This work seeks to provide a complimentary technique to x-rays to allow for a more complete analysis of bone health and disease progression.

In regenerative medicine and preclinical hair research, the visualization of living human scalp hair follicles (HFs) is of high interest to hair transplant surgeons. However, HFs typically have to be fixed for histology (and thereby killed) to discern their anatomy in sufficient detail. We explored optical coherence tomography (OCT) for label-free 3D imaging of viable human microdissected HFs. Our results show that by using OCT it is possible to distinguish between different HF stages, i.e., anagen, early, mid or late catagen, in living microdissected HFs. In summary, OCT represents a promising label-free method for the observation of live HFs.

Real-time Fluorescent PCR suffers from PCR inefficiency, high cost, and false results because of intercalating dye contamination, complication in fluorophore-labeled primer sequencing, and degraded quencher molecule. Therefore, we aimed for a purely optical method to avoid the need for any additional reagents. Our method relies on structure dependent UV absorption of bases in nucleotides. Free nucleotides have the highest UV absorption among other PCR ingredients. During polymerization, free nucleotides are incorporated; therefore, at the end of each cycle, we expect less UV absorption for a successful PCR. Our work is able to not only reliably differentiate successful and failed PCR but also fully quantify the amplicon production based on threshold cycle. Integration of our real-time fluorophore-free amplicon monitoring with plasmonic thermocycler introduces new generation of PCR machines.

Mitochondrial dynamics are closely related to their functionalities in both somatic tissues and the germline. As a key cellular phenotype in Caenorhabditis elegans, mitochondrial dynamics have been investigated extensively in somatic organs using fluorescence microscopy. Majorly due to transgene silencing and dye inaccessibility, it has been challenging to apply these methods to the germline of C. elegans. Here, we analyze mitochondrial dynamics by imaging mitochondrial assembly based on two-photon excited autofluorescence of NADH, a co-enzyme concentrated in mitochondria. In oocytes of two mutants, drp-1 and fzo-1 that drive mitochondrial fission and fusion, respectively, the extracted feature parameter by Fourier transform based analysis can clearly distinguish fused vs. fragmented mitochondria. We then applied the methods on wild type worms at different ages. Statistics has revealed the change of mitochondria assembly in oocytes during aging.

Raman spectroscopy is commonly used for sample characterization in biology because vibrational information is very specific for the chemical bonds in molecules. In addition, Raman spectroscopy has a unique capability of providing label-free intrinsic chemical information, such as molecular bonds in living biological samples. However, Raman signals are inherently weak; therefore, acquiring a spectrum with good signal to noise ratio requires long acquisition time. To overcome the disadvantage of low signal intensities from most biomolecules, enhancement effects are utilized. In this study, a home built Raman spectroscopy optical system combined with a gold thin film deposition was used to detect HIV gp120 antibody using a gold thin film deposition substrate. From the preliminary data produced by this study, significant enhancement of Raman signal was observed. These findings indicate the potential application of Raman spectroscopy in rapid biosensing and detection of micro-organisms.

We describe a novel implementation of deep learning time stretch flow cytometry which avoids the computationally intensive tasks image processing and feature extraction prior to deep learning. Time stretch laser pulses, each representing one image frame, are fed directly into a 16 layer convolutional neural network. This direct classification of raw time stretched data reduced the inference time by orders of magnitude, from seconds to 700 micro-second on a GPU accelerated processor. At a flow speed of 1 m/s the cells only move less than a millimeter. Therefore, this ultrashort inference time is fast enough to provide a decision to a cell sorter. We demonstrate the applicability of our new method in the classification of OT-II white blood cells and SW-480 epithelial cancer cells with more than 95% accuracy in a label-free fashion and with low latency inference.

The selection of sperm cells is crucial for many assisted reproductive technologies. We present a novel platform for real-time quantitative analysis and selection of individual sperm cells, utilizing interferometric phase microscopy (IPM), for label-free quantitative sperm imaging, combined with a disposable microfluidic device. Furthermore, IPM images of sperm were captured without labeling, and were then compared to fluorescence images of the same sperm after staining, revealing the correlation between DNA fragmentation and IPM-based parameters. We believe that these techniques may significantly improve the way in which sperm are selected for IVF, making the selection process more objective, quantitative, and automatic.

Many studies suggest that external forces applied to cells generate signals that are as potent as those of biochemical stimuli. To understand how these forces are transmitted to the molecular structures of cells, and how they might be transduced into biochemical reactions, require measuring both cell biophysical properties (CBPs) and specific biological pathways in a physiological environment. For this purpose, we will present simultaneous measurements, through rheological approaches, of both important CBPs and specific biochemical pathways performed thanks to an automated multi-modality imaging system devoted to live cells combining quantitative-phase digital holographic microscopy, fluorescence microscopy and dedicated flow assays.

Fourier Ptychography is a computational imaging technique able to decouple high resolution from wide field of view, bypassing the diffraction limit of the microscope. LED-array misalignment, optical system aberrations and partial coherent sources are common issues which have been addressed with calibration algorithms. Physical interpretation of how these factors influence the algorithm and cause mismatches between theory and practice has had little attention. We prescribe optimal design configuration based on the correlation between the NA of the objectives and the illumination pattern of the LED array, mitigating the effect of partial coherence and improving the convergence of the reconstruction algorithms.

Six-pack holography (6PH) is the first holographic imaging modality that is more spatial bandwidth efficient than on-axis holography. 6PH utilizes a low-coherence light source and a phase delay plate to enable the spatial multiplexing of six off-axis holograms without cross-talk between the six sample and six reference beams, and is thus capable of acquiring six off-axis holograms in a single camera exposure. We applied 6PH to synthetic aperture (SA) superresolution, and produced an SA capable of dynamically increasing the resolution by a factor of 1.62. 6PH presents a valuable general purpose technique for all holography applications and label-free imaging.

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 this presentation, I will provide an overview of some of our recent work on the use of deep neural networks in advancing holographic microscopy and sensing systems, also covering their biomedical applications.

We explored the capabilities of quantitative phase imaging (QPI) with digital holographic microscopy (DHM) for monitoring the differentiation of human erythroid precursor cells towards erythrocytes. Suspended cells were observed with a Michelson interferometer-based DHM setup for several days. From the resulting series of quantitative phase images cellular volume, refractive index, and dry mass were determined. The retrieved experimental data demonstrate that label-free cell monitoring with biophysical parameter sets as are assessable with DHM allows to quantify the cell differentiation status with high reliability and that similar volume, refractive index and dry mass values are obtained for different human donors.

Tomographic phase microscopy (TPM) is a well-known technique for imaging cells without staining and visualizing their inherent 3-D refractive index profile. We proposed a new low-cost TPM approach using sample rotation of single cells. The cells are inserted into a capillary and trapped in a low-density gel. Cell rotation is performed by mechanically rotating the capillary. Projection acquisition is performed using an imaging interferometer. This technique is expected to be useful for label-free cell sorting and analysis.

Digital magnitude image rendering in Gabor holography can be performed by a convolutional neural network trained with a fully synthetic database formed by image pairs generated randomly. These pairs are linked by a numerical model propagation of a scalar wave field from the object to the sensor array. The synthetic database is formed by generating images made from source points at random locations with random brightness on a black background. Successful prediction of experimental Gabor holograms of microscopic worms by a UNet trained with 50,000 random image pairs is achieved, and a classifier-based regularization for twin-image removal is investigated.

We report the full-field imaging of the mechanical deformations accompanying the action potential in primary cortical neurons using ultrafast quantitative phase imaging (QPI) with a temporal resolution of 0.1 ms and a membrane displacement sensitivity of <0.2 nm per pixel. The average displacements were ~0.7 nm on cell somas and ~0.5 nm on neurites. Finite element modeling based on the 3D shape extracted from confocal imaging and on scaling of the surface tension with trans-membrane voltage yielded the deformation map during action potential, which matched the features of the experimental results, including the displacement amplitude, time course, and spatial distribution.

We apply label-free imaging using digital holographic microscopy to analyze different cancer cell lines. Separation of cell lines based on extraction of amplitude and phase map variations along with post-processed, population specific parameters, was accomplished using machine learning. These data are used to train a neural network algorithm that attains accurate discrimination of non-adherent cancer cells.

Computational imaging involves the joint design of imaging system hardware and software, optimizing across the entire pipeline from acquisition to reconstruction. Computers can replace bulky and expensive optics by solving computational inverse problems. This talk will describe new microscopes that use computational imaging to enable 3D fluorescence and phase measurement using image reconstruction algorithms that are based on large-scale nonlinear non-convex optimization combined with unrolled neural networks. We further discuss engineering of data capture for computational microscopes by end-to-end learned design.

Progression of acute diseases such as cancer often depend on a small number of specialized cells. Identification and isolation of the cells intact is of utmost importance. Label-based approaches are incompatible with noninvasive cell processing. We propose a a new label-free technique for noninvasive and automated cell processing and discrimination of individual cells. By acquiring holograms of each cell and achieving its optical path delay (OPD) profile, we extract features that highly differentiate cancerous cells from heterogeneous blood sample. Using a dielectrophoresis flow chamber to control each cell, we can than collect the cancerous cells for further analysis and classification.

Common path interferometer based quantitative phase microscopy (QPM) system with high temporal phase stability and high spatial phase sensitivity is proposed. To achieve high spatial phase sensitivity we used partially spatially coherent (pseudo-thermal) light source for illumination.Common path QPM based on Fresnel biprism as well as lateral shearing interferometers are demonstrated. Due to partial spatial coherent nature of the light source a speckle-free hologram is recorded over entire field-of-view. Spurious interference fringes are also removed thus leading to uniform illumination over entire area. Therefore, high spatial phase sensitivity is guaranteed. The temporal stability obtained ~10 mrad without using any vibration isolation table. Results demonstrated on USAF resolution chart, polystyrene spheres (dia. 4.5 micron) and human red blood cells (RBCs). The membrane fluctuation of healthy human RBCs is further successfully measured and found to be equal to 63 nm.

Recently, we have shown that differential detection at pupil plane of a scanning microscope produces a phase gradient image in a thick scattering tissue similar to scanning oblique back illumination microscopy with detectors placed at the image plane. Here, we have demonstrated that the extended pupil plane differential detection (eP2D2) technique can obtain phase contrast images without compromising the numerical aperture of the objective lens, and can be added in any scanning microscopes using a beam splitter and a quadrature photodiode. As a proof of the principle, we compared confocal and eP2D2 in-vivo of mouse ear skin.

We demonstrate rapid, sensitive and label-free detection of whole-cell E. coli utilizing interferometric reflectance imaging enhancement technique, with a limit of detection of 2.2 CFU/ml from a buffer solution with no sample preparation. Our sensor platform provides visualizing and counting individual pathogens captured on the large sensor surface, as well as morphological characterization of the captured particles by high optical magnification imaging modality for validating the recorded detection events as the target bacteria. In addition, we show that our biosensor's detection capability is unaffected by the sample complexity by testing its performance in tap water. Also, the specificity of our biosensor is validated by comparing its response to target bacteria E. coli and non-target bacteria S. aureus, K. pneumonia and P. aeruginosa. Therefore, our sensitive and label-free detection method offers new perspectives for direct bacterial detection in real matrices and clinical sample.

Quantitative phase imaging (QPI) is an important tool in biomedicine that yields label-free access to cellular and subcellular structures with nanometer-scale sensitivity. However, implementation of QPI involves a transmission-based geometry and requires thin samples, severely hindering its overall utility in biomedicine. Here we describe our recently developed method, quantitative oblique back illumination microscopy (qOBM), which overcomes this significant limitation and achieves epi-mode, tomographic, quantitative phase imaging in thick samples, including intact thick tissues. In this presentation, we will describe the method in detail, show validation experiments and results from thick samples including blood in storage bags, intact whole mouse brains, and organoids.

The lens-less digital holography techniques enable a simple and cost-effective approach to obtain label-free cell images with large field of view and microscopic spatial resolution. The holograms of four kinds of cells were recorded by a lab-built lens-less digital holographic system. The holograms are preprocessed by a high-pass filter. The amplitude images of the cells are recovered by using the angular spectrum algorithm combining with autofocusing criteria. Significant difference occurs among the shape and texture features of different cell types. Results demonstrated that this technique holds great promise in the application of cell classification and image-based cell analysis.

Ultraviolet microscopy enables label-free, quantitative molecular imaging of biological samples and can play a crucial role in the study of disease. Here we present a UV hyperspectral microscopy approach to recover quantitative absorption properties using a simple set-up which leverages chromatic aberrations to recover phase by iteratively solving the transport of intensity equation, without prior knowledge of the sample’s dispersion or absorption properties. We demonstrate that the non-interferometrically retrieved phase can correct chromatic aberrations and refocus the through-focus intensity stack, obtained by line-scanning using an imaging spectrometer, to compute quantitative absorption information accurately without any a priori information.

In order to advance quantitative phase microscopy as a significant clinical tool, we have implemented a new modality, holographic cytometry, which provides high resolution phase maps at high frame rates using several novel advances such as high speed line scan cameras integrated with microfluidic and illuminated with pulsed light source. The system is used to examine carcinogenic changes in epithelial cells which have been exposed to heavy metals in population sizes that are diagnostically relevant.

We describe a microscope implementing both digital holographic microscopy (DHM) and transport of intensity (TIE) phase imaging of live cells. DHM provides robust phase reconstructions but requires a sophisticated interferometric imaging system, while TIE is directly compatible with bright-field microscope but produces phase reconstructions more susceptible to noise artifacts. Comparing both methods on live specimens is a challenge due to the different imaging systems required. Our microscope allows both DHM and TIE to be applied in rapid succession on the same specimen, which allows the accuracy of the results of both measurements to be quantitatively compared for live cells.