This PDF file contains the front matter associated with SPIE Proceedings Volume 10076 including the Title Page, Copyright information, Table of Contents, Introduction, and Conference Committee listing.

Innovations in spectroscopy principles and microscopy technology have significantly impacted modern biology and medicine. While most of the contemporary bio-imaging modalities harness electronic transition, nuclear spin or radioactivity, vibrational spectroscopy has not been widely used yet. Here we will discuss an emerging chemical imaging platform, stimulated Raman scattering (SRS) microscopy, which can enhance the otherwise feeble spontaneous Raman eight orders of magnitude by virtue of stimulated emission. When coupled with stable isotopes (e.g., deuterium and 13C) or bioorthogonal chemical moieties (e.g., alkynes), SRS microscopy is well suited for probing in vivo metabolic dynamics of small bio-molecules which cannot be labeled by bulky fluorophores. Physical principle of the underlying optical spectroscopy and exciting biomedical applications such as imaging lipid metabolism, protein synthesis, DNA replication, protein degradation, RNA synthesis, glucose uptake, drug trafficking and tumor metabolism will be presented.

Visible absorption in tissue is dominated by a very small number of chromophores (hemoglobins and melanins) with broad optical spectra; for melanins in particular, the optical absorption spectrum is typically featureless. In addition, scattering limits penetration depth. As a result, the most common microscopy application by far is with excised tissue, which can be stained. However, nonlinear optical methods have the additional advantages of greater penetration depth and reduced sensitivity to scattering. Traditional nonlinear microscopy relies on mechanisms which produce light of a different color than the irradiating lasers, such as second harmonic generation or two photon induced fluorescence, and this contrast is sparse in biological issue without expressing or injecting different chromophores. Recently, stable laser sources and pulse shaping/pulse train modulation methods have made it possible to detect a much wider range of nonlinear molecular signatures, even at modest laser powers (much less than a laser pointer). Here we show the utility of a variety of such signatures (pump-probe, pulse-shaped stimulated Raman, cross-phase modulation) to quantitatively image the biochemical composition of transparent or pigmented tissue in a variety of applications, ranging from thin, unstained tissue sections to live knockout mice. The rich biochemical information provided by this method can be used as an indicator of melanocyte activity, which in turn (for example) reflects the status of melanocytic lesions. Comparisons with model systems (synthetic melanin nanoparticles, sepia melanin) and analysis of melanin degradation pathways in vivo have led to a quantitative understanding of the molecular basis of these changes.

Microalgae have been receiving great attention for their ability to produce biomaterials that are applicable for food supplements, drugs, biodegradable plastics, and biofuels. Among such microalgae, Euglena gracilis has become a popular species by virtue of its capability of accumulating useful metabolites including paramylon and lipids. In order to maximize the production of desired metabolites, it is essential to find ideal culturing conditions and to develop efficient methods for genetic transformation. To achieve this, understanding and controlling cell-to-cell variations in response to external stress is essential, with chemically specific analysis of microalgal cells including E. gracilis. However, conventional analytical tools such as fluorescence microscopy and spontaneous Raman scattering are not suitable for evaluation of diverse populations of motile microalgae, being restricted either by the requirement for fluorescent labels or a limited imaging speed, respectively. Here we demonstrate video-rate label-free metabolite imaging of live E. gracilis using stimulated Raman scattering (SRS) – an optical spectroscopic method for probing the vibrational signatures of molecules with orders of magnitude higher sensitivity than spontaneous Raman scattering. Our SRS’s highspeed image acquisition (27 metabolite images per second) allows for population analysis of live E. gracilis cells cultured under nitrogen-deficiency - a technique for promoting the accumulation of paramylon and lipids within the cell body. Thus, our SRS system’s fast imaging capability enables quantification and analysis of previously unresolvable cell-to-cell variations in the metabolite accumulation of large motile E. gracilis cell populations.

Propagation of action potentials arises on millisecond timescales, suggesting the need for advancement of methods capable of commensurate volume rendering for in vivo brain mapping. In practice, beam-scanning multiphoton microscopy is widely used to probe brain function, striking a balance between simplicity and penetration depth. However, conventional beam-scanning platforms generally do not provide access to full volume renderings at the speeds necessary to map propagation of action potentials. By combining a sparse sampling strategy based on Lissajous trajectory microscopy in combination with temporal multiplexing for simultaneous imaging of multiple focal planes, whole volumes of cells are potentially accessible each millisecond.

In vivo molecular spectroscopic imaging is not a simple addition of a spectrometer to a microscope. Innovations are needed to break the physical limits in sensitivity, depth, speed and resolution perspectives. I will present our most recent advances in modality development, biological application, and clinical translation. My talk will focus on the development of mid-infrared photothermal microscope for depth-resolved vibrational imaging of living cells (Science Advances, in press), the discovery of a metabolic signature in cancer stem cells by hyperspectral stimulated Raman scattering imaging (Cell Stem Cell, in press), and the development of an intravascular vibrational photoacoustic catheter for label-free sensing of lipid laden plaques (Scientific Report 2016, 6:25236).

We present a coherent Raman scattering (CRS) spectroscopy technique achieving a CRS spectral acquisition rate of 50,000 spectra/second over a Raman spectral region of 200 - 1430 cm^-1 with a resolution of 4.2 cm^-1. This ultrafast, broadband and high-resolution CRS spectroscopic performance is realized by a polygonal Fourier-domain delay line serving as an ultra-rapid optical-path-length scanner in a broadband Fourier-transform coherent anti-Stokes Raman scattering (CARS) spectroscopy platform. We present a theoretical description of the technique and demonstrate continuous, ultrafast, broadband, and high-resolution CARS spectroscopy on a liquid toluene sample using our proof-of-concept setup.

Currently, the majority of microscopic and endoscopic technologies utilize white light illumination. For a number of applications, hyper-spectral imaging can be shown to have significant improvements over standard white-light imaging techniques. This is true for both microscopy and in vivo imaging. However, hyperspectral imaging methods have suffered from slow application times. Often, minutes are required to gather a full imaging stack. Here we will describe the system and evaluate optimizations and applications of a novel excitation-scanning hyperspectral imaging system. We have developed and are optimizing a novel approach called excitation-scanning hyperspectral imaging that provides an order of magnitude increased signal strength. Optimization of the light path, optical components and illumination sources have allowed us to achieve high speed image acquisition. This high speed allows for potential live video acquisition. This excitation-scanning hyperspectral imaging technology has potential to impact a range of applications. The current system allows triggering of up to 16 wavelengths at less than 1 millisecond per image using digital strobing. Analog intensity control is also provided for a fully customizable excitation profile. A significant advantage of excitation scanning hyperspectral imaging is can identify multiple targets simultaneously in real time. We are optimizing the system to compare sensitivity and specificity of excitation-scanning hyperspectral imaging with pathology techniques. Finally, we are exploring utilizing this technology to measure cAMP distribution in three dimensions within a cell.

Laser scanning light-sheet imaging allows fast 3D image of live samples with minimal bleach and photo-toxicity. Existing light-sheet techniques have very limited capability in multi-label imaging. Hyper-spectral imaging is needed to unmix commonly used fluorescent proteins with large spectral overlaps. However, the challenge is how to perform hyper-spectral imaging without sacrificing the image speed, so that dynamic and complex events can be captured live. We report wavelength-encoded structured illumination light sheet imaging (λ-SIM light-sheet), a novel light-sheet technique that is capable of parallel multiplexing in multiple excitation-emission spectral channels. λ-SIM light-sheet captures images of all possible excitation-emission channels in true parallel. It does not require compromising the imaging speed and is capable of distinguish labels by both excitation and emission spectral properties, which facilitates unmixing fluorescent labels with overlapping spectral peaks and will allow more labels being used together. We build a hyper-spectral light-sheet microscope that combined λ-SIM with an extended field of view through Bessel beam illumination. The system has a 250-micron-wide field of view and confocal level resolution. The microscope, equipped with multiple laser lines and an unlimited number of spectral channels, can potentially image up to 6 commonly used fluorescent proteins from blue to red. Results from in vivo imaging of live zebrafish embryos expressing various genetic markers and sensors will be shown. Hyper-spectral images from λ-SIM light-sheet will allow multiplexed and dynamic functional imaging in live tissue and animals.

The process of multiple scattering has inherent characteristics that are attractive for high-speed imaging with high spatial resolution and a wide field-of-view. A coherent source passing through a multiple-scattering medium naturally generates speckle patterns with diffraction-limited features over an arbitrarily large field-of-view. In addition, the process of multiple scattering is deterministic allowing a given speckle pattern to be reliably reproduced with identical illumination conditions. Here, by exploiting wavelength dependent multiple scattering and compressed sensing, we develop a high-speed 2D time-stretch microscope. Highly chirped pulses from a 90-MHz mode-locked laser are sent through a 2D grating and a ground-glass diffuser to produce 2D speckle patterns that rapidly evolve with the instantaneous frequency of the chirped pulse. To image a scene, we first characterize the high-speed evolution of the generated speckle patterns. Subsequently we project the patterns onto the microscopic region of interest and collect the total light from the scene using a single high-speed photodetector. Thus the wavelength dependent speckle patterns serve as high-speed pseudorandom structured illumination of the scene. An image sequence is then recovered using the time-dependent signal received by the photodetector, the known speckle pattern evolution, and compressed sensing algorithms. Notably, the use of compressed sensing allows for reconstruction of a time-dependent scene using a highly sub-Nyquist number of measurements, which both increases the speed of the imager and reduces the amount of data that must be collected and stored. We will discuss our experimental demonstration of this approach and the theoretical limits on imaging speed.

In this paper, we present a high-speed single-pixel imaging (SPI) system based on all-optical discrete cosine transform (DCT) and demonstrate its capability to enable noninvasive imaging of flowing cells in a microfluidic channel. Through spectral shaping based on photonic time stretch (PTS) and wavelength-to-space conversion, structured illumination patterns are generated at a rate (tens of MHz) which is three orders of magnitude higher than the switching rate of a digital micromirror device (DMD) used in a conventional single-pixel camera. Using this pattern projector, high-speed image compression based on DCT can be achieved in the optical domain. In our proposed system, a high compression ratio (approximately 10:1) and a fast image reconstruction procedure are both achieved, which implicates broad applications in industrial quality control and biomedical imaging.

Light scattering is a primary obstacle to imaging in many environments. On small scales in biomedical microscopy and diffuse tomography scenarios scattering is caused by tissue. On larger scales scattering from dust and fog provide challenges to vision systems for self driving cars and naval remote imaging systems. We are developing scale models for scattering environments and investigation methods for improved imaging particularly using time of flight transient information. With the emergence of Single Photon Avalanche Diode detectors and fast semiconductor lasers, illumination and capture on picosecond timescales are becoming possible in inexpensive, compact, and robust devices. This opens up opportunities for new computational imaging techniques that make use of photon time of flight. Time of flight or range information is used in remote imaging scenarios in gated viewing and in biomedical imaging in time resolved diffuse tomography. In addition spatial filtering is popular in biomedical scenarios with structured illumination and confocal microscopy. We are presenting a combination analytical, computational, and experimental models that allow us develop and test imaging methods across scattering scenarios and scales. This framework will be used for proof of concept experiments to evaluate new computational imaging methods.

Many prior studies performed in the area of compressive optical coherence tomography (OCT) have mostly dealt with the problem of compressive sensing and sparse recovery of processed OCT images. Unlike these studies, in this paper, we study the application of compressive sensing in terms of efficient data storage and generating OCT images from undersampled raw unprocessed spectral domain OCT data. High resolution spectral domain OCT requires acquisition of enormous amount of data at very high sampling rate but such a large amount of the raw data impedes fast and efficient data storage and communication. To solve the problem of storing a large amount of data, we propose a specific undersampling method guided by the energy density of the spectral domain data in order to facilitate sparse representation of the raw data in terms of its salient frequency domain samples. This method takes into account not just the higher amplitude spectral data, as suggested in some previous studies but samples data based on nearly uniform distribution of energy over all the sampling intervals in the entire spectrum. Finally, we apply some state of the art sparse recovery methods involving L1 minimization to recover our desired high resolution images from the undersampled spectral domain data. We demonstrate the performance of our proposed scheme by comparing it with the recovery accuracy of some recent energy-guided undersampling methods and the conventional compressive sensing with random undersampling. We also compare the performance of our method with the other methods in terms of data compression ratio with respect to the reconstruction error.

Cell reagents used in biomedical analysis often change behavior of the cells that they are attached to, inhibiting their native signaling. On the other hand, label-free cell analysis techniques have long been viewed as challenging either due to insufficient accuracy by limited features, or because of low throughput as a sacrifice of improved precision. We present a recently developed artificial-intelligence augmented microscope, which builds upon high-throughput time stretch quantitative phase imaging (TS-QPI) and deep learning to perform label-free cell classification with record high-accuracy. Our system captures quantitative optical phase and intensity images simultaneously by frequency multiplexing, extracts multiple biophysical features of the individual cells from these images fused, and feeds these features into a supervised machine learning model for classification. The enhanced performance of our system compared to other label-free assays is demonstrated by classification of white blood T-cells versus colon cancer cells and lipid accumulating algal strains for biofuel production, which is as much as five-fold reduction in inaccuracy. This system obtains the accuracy required in practical applications such as personalized drug development, while the cells remain intact and the throughput is not sacrificed. Here, we introduce a data acquisition scheme based on quadrature phase demodulation that enables interruptionless storage of TS-QPI cell images. Our proof of principle demonstration is capable of saving 40 TB of cell images in about four hours, i.e. pictures of every single cell in 10 mL of a sample.

The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, microalgal biofuel is expected to play a key role in reducing the detrimental effects of global warming since microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid contents and fail to characterize a diverse population of microalgal cells with single-cell resolution in a noninvasive and interference-free manner. Here we demonstrate high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy. In particular, we use Euglena gracilis – an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement) within lipid droplets. Our optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch phase-contrast microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase contents of every single cell at a high throughput of 10,000 cells/s. We characterize heterogeneous populations of E. gracilis cells under two different culture conditions to evaluate their lipid production efficiency. Our method holds promise as an effective analytical tool for microalgaebased biofuel production.

The field of infrared spectral imaging and microscopy is advancing rapidly due in large measure to the recent commercialization of the first high-throughput, high-spatial-definition quantum cascade laser (QCL) microscope. Having speed, resolution and noise performance advantages while also eliminating the need for cryogenic cooling, its introduction has established a clear path to translating the well-established diagnostic capability of infrared spectroscopy into clinical and pre-clinical histology, cytology and hematology workflows. Demand for even higher throughput while maintaining high-spectral fidelity and low-noise performance continues to drive innovation in QCL-based spectral imaging instrumentation. In this talk, we will present for the first time, recent technological advances in tunable QCL photonics which have led to an additional 10X enhancement in spectral image data collection speed while preserving the high spectral fidelity and SNR exhibited by the first generation of QCL microscopes. This new approach continues to leverage the benefits of uncooled microbolometer focal plane array cameras, which we find to be essential for ensuring both reproducibility of data across instruments and achieving the high-reliability needed in clinical applications. We will discuss the physics underlying these technological advancements as well as the new biomedical applications these advancements are enabling, including automated whole-slide infrared chemical imaging on clinically relevant timescales.

According to WHO, approximately 10 million new cases of thrombotic disorders are diagnosed worldwide every year. In the U.S. and Europe, their related diseases kill more people than those from AIDS, prostate cancer, breast cancer and motor vehicle accidents combined. Although thrombotic disorders, especially arterial ones, mainly result from enhanced platelet aggregability in the vascular system, visual detection of platelet aggregates in vivo is not employed in clinical settings. Here we present a high-throughput label-free platelet aggregate detection method, aiming at the diagnosis and monitoring of thrombotic disorders in clinical settings. With optofluidic time-stretch microscopy with a spatial resolution of 780 nm and an ultrahigh linear scanning rate of 75 MHz, it is capable of detecting aggregated platelets in lysed blood which flows through a hydrodynamic-focusing microfluidic device at a high throughput of 10,000 particles/s. With digital image processing and statistical analysis, we are able to distinguish them from single platelets and other blood cells via morphological features. The detection results are compared with results of fluorescence-based detection (which is slow and inaccurate, but established). Our results indicate that the method holds promise for real-time, low-cost, label-free, and minimally invasive detection of platelet aggregates, which is potentially applicable to detection of platelet aggregates in vivo and to the diagnosis and monitoring of thrombotic disorders in clinical settings. This technique, if introduced clinically, may provide important clinical information in addition to that obtained by conventional techniques for thrombotic disorder diagnosis, including ex vivo platelet aggregation tests.

Obtaining gigapixel images is a challenging task because of the aberrations present in a conventional optical system, small sensor sizes and limited data-capture rates of cameras. Multi-aperture Fourier ptychography (MAFP) was proposed recently by us to solve the issue of increasing the data acquisition bandwidth by parallelizing data capture using an array of lenses coupled with discrete detectors. We present an advanced MAFP system based on the Scheimpflug configuration to improve the MAFP system performance at high NAs. This system requires a complicated optical system due to the large number of degrees of freedom present in the system. Hence we developed a 3D-printed system which solves this issue and decreases the cost of the setup tremendously. In this manuscript we present the details of our 3D printed design and preliminary images obtained using this system.

Acquired drug resistance is a fundamental predicament in cancer therapy. Early detection of drug-resistant cancer cells during or after treatment is expected to benefit patients from unnecessary drug administration and thus play a significant role in the development of a therapeutic strategy. However, the development of an effective method of detecting drug-resistant cancer cells is still in its infancy due to their complex mechanism in drug resistance. To address this problem, we propose and experimentally demonstrate label-free image-based drug resistance detection with optofluidic time-stretch microscopy using leukemia cells (K562 and K562/ADM). By adding adriamycin (ADM) to both K562 and K562/ADM (ADM-resistant K562 cells) cells, both types of cells express unique morphological changes, which are subsequently captured by an optofluidic time-stretch microscope. These unique morphological changes are extracted as image features and are subjected to supervised machine learning for cell classification. We hereby have successfully differentiated K562 and K562/ADM solely with label-free images, which suggests that our technique is capable of detecting drug-resistant cancer cells. Our optofluidic time-stretch microscope consists of a time-stretch microscope with a high spatial resolution of 780 nm at a 1D frame rate of 75 MHz and a microfluidic device that focuses and orders cells. We compare various machine learning algorithms as well as various concentrations of ADM for cell classification. Owing to its unprecedented versatility of using label-free image and its independency from specific molecules, our technique holds great promise for detecting drug resistance of cancer cells for which its underlying mechanism is still unknown or chemical probes are still unavailable.

We have developed and evaluated the large full well capacity (FWC) for wide signal detection range and low temporal noise for high sensitivity lock-in pixel CMOS image sensor (CIS) embedded with two storage-diodes (SDs). In addition, for fast charge transfer from photodiode (PD) to SDs, a lateral electric field charge modulator (LEFM) is used for the developed lock-in pixel. As a result, the time-resolved CIS achieves a very large FWC of approximately 7000e-, low temporal random noise of 1.17e-rms at 45fps with true correlated double sampling (CDS) operation, and fast intrinsic response less than 500ps at 635nm. The proposed imager has an effective pixel array of 128(H)×256(V) and a pixel size of 11.2×11.2μm². The sensor chip is fabricated by a Dongbu HiTek 1P4M 0.11μm CIS process.

We demonstrated confocal phase imaging with scan-less dual comb microscopy, in which the confocal 2D image of a sample was encoded on OFC spectrum by the 2D spectral disperser, and then the image-encoded OFC spectrum is acquired by dual comb spectrometer to decode the 2D image. This approach enables us to not only establish both confocality and full-field imaging under the scan-less condition but also depth-resolve the confocal volume of the sample within the wavelength by use of the phase spectrum. We demonstrated a proof-of-principle experiment of the proposed method by confocal phase imaging of a test chart.

Imaging live cells at a resolution higher than achieved using optical microscopy is a challenge. Ultra-fast coherent diffractive imaging with X-ray free-electron lasers (XFELs) has the potential to achieve sub-nanometer resolution on micron-sized living cells. Our container-free injection method can introduce a beam of live cyanobacteria into the micron-sized focus of the Linac Coherent Light Source (LCLS) to record of diffraction patterns from individual cells, with very low noise at high hit rates (millions of cells/day). We used iterative phase retrieval to derive two-dimensional projection images directly from the diffraction patterns. In a first experiment, we collected diffraction patterns to 33-46 nm full-period resolution, and reconstructed the exit wave front to 76 nm full-period resolution. In a second experiment, we demonstrate that it is indeed possible to record diffraction data to nanometer resolution on live cells with an intense, ultra-short X-ray pulse as predicted earlier. These results are encouraging, and future developments to the XFELs and improvements to the X-ray area-detectors will bring sub-nanometer resolution reconstructions of living cells within reach. Utilizing this type of diffraction data will require the development of new analysis methods and algorithms for studying structure and structural variability in large populations of cells and to create abstract models. Such studies will allow us to understand living cells and populations of cells in new ways.

Photonic time-stretch microscopy (TSM) provides an ideal platform for high-throughput imaging flow cytometry, affording extremely high shutter speeds and frame rates with high sensitivity. In order to resolve weakly scattering cells in biofluid and solve the issue of signal-to-noise in cell labeling specificity of biomarkers in imaging flow cytometry, several quantitative phase (QP) techniques have recently been adapted to TSM. However, these techniques have relied primarily on sensitive free-space optical configurations to generate full electric field measurements. The present work draws from the field of ultrashort pulse characterization to leverage the coherence of the ultrashort optical pulses integral to all TSM systems in order to do self-referenced single-shot quantitative phase imaging in a TSM system. Self-referencing is achieved via spectral shearing interferometry in an exceptionally stable and straightforward Sagnac loop incorporating an electro-optic phase modulator and polarization-maintaining fiber that produce sheared and unsheared copies of the pulse train with an inter-pulse delay determined by polarization mode dispersion. The spectral interferogram then yields a squared amplitude and a phase derivative image that can be integrated for conventional phase. We apply this spectral shearing contrast microscope to acquire QP images on a high-speed flow microscope at 90-MHz line rates with <400 pixels per line. We also consider the extension of this technique to compressed sensing (CS) acquisition by intensity modulating the interference spectra with pseudorandom binary waveforms to reconstruct the images from a highly sub-Nyquist number of random inner products, providing a path to even higher operating rates and reduced data storage requirements.

Optical time-stretch microscopy enables cellular images captured at tens of MHz line-scan rate and becomes a potential tool for ultrafast dynamics monitoring and high throughput screening in scientific and biomedical applications. In time-stretch microscopy, to achieve the fast line-scan rate, optical fibers are used as the pulse-stretching device that maps the spectrum of a light pulse to a temporal waveform for fast digitization. Consequently, existing time-stretch microscopy is limited to work at telecom windows (e.g. 1550 nm) where optical fiber has significant pulse-stretching and small loss. This limitation circumscribes the potential application of time-stretch microscopy. Here we present a new optical time-stretch imaging modality by exploiting a novel pulse-stretching technique, free-space angular-chirp-enhanced delay (FACED), which has three benefits: (1) Pulse-stretching in FACED generates substantial, reconfigurable temporal dispersion in free-space with low intrinsic loss at visible wavelengths; (2) Pulse-stretching in FACED inherently provides an ultrafast all-optical laser-beam scanning mechanism for time-stretch imaging. (3) Pulse-stretching in FACED can be wavelength-invariant, which enables time-stretch microscopy implemented without spectral-encoding. Using FACED, we demonstrate optical time-stretch microscopy with visible light (~700 nm). Compared to the prior work, bright-field time-stretch images captured show superior contrast and resolution, and can be effectively colorized to generate color time-stretch images. More prominently, accessing the visible spectrum regime, we demonstrate that FACED enables ultrafast fluorescence time-stretch microscopy. Our results suggest FACED could unleash a wider scope of applications that were once forbidden with the fiber based time-stretch imaging techniques.

We present single-shot real-time video recording of light scattering dynamics by second-generation compressed ultrafast photography (G2-CUP). Using G2-CUP at 100 billion frames per second, in a single camera exposure, we experimentally captured the evolution of the light intensity distribution in an engineered thin scattering plate assembly. G2-CUP, which implements a new reconstruction paradigm and a more efficient hardware design than its predecessors, markedly improves the reconstructed image quality. The ultrafast imaging reveals the instantaneous light scattering pattern as a photonic Mach cone. We envision that our technology will find a diverse range of applications in biomedical imaging, materials science, and physics.

Fluorescent lifetime imaging is an optical technique that facilitates imaging molecular interactions and cellular functions. Because the excited lifetime of a fluorophore is sensitive to its local microenvironment,^{1, 2} measurement of fluorescent lifetimes can be used to accurately detect regional changes in temperature, pH, and ion concentration. However, typical state of the art fluorescent lifetime methods are severely limited when it comes to acquisition time (on the order of seconds to minutes) and video rate imaging. Here we show that compressed ultrafast photography (CUP) can be used in conjunction with fluorescent lifetime imaging to overcome these acquisition rate limitations. Frame rates up to one hundred billion frames per second have been demonstrated with compressed ultrafast photography using a streak camera.³ These rates are achieved by encoding time in the spatial direction with a pseudo-random binary pattern. The time domain information is then reconstructed using a compressed sensing algorithm, resulting in a cube of data (x,y,t) for each readout image. Thus, application of compressed ultrafast photography will allow us to acquire an entire fluorescent lifetime image with a single laser pulse. Using a streak camera with a high-speed CMOS camera, acquisition rates of 100 frames per second can be achieved, which will significantly enhance our ability to quantitatively measure complex biological events with high spatial and temporal resolution. In particular, we will demonstrate the ability of this technique to do single-shot fluorescent lifetime imaging of cells and microspheres.

Optical imaging techniques provide much important information in understanding life science especially cellular structure and morphology because “seeing is believing”. However, the resolution of optical imaging is limited by the diffraction limit, which is discovered by Ernst Abbe, i.e. λ/2(NA) (NA is the numerical aperture of the objective lens). Fluorescence super-resolution microscopic techniques such as Stimulated emission depletion microscopy (STED), Photoactivated localization microscopy (PALM), and Stochastic optical reconstruction microscopy (STORM) are invented to have the capability of seeing biological entities down to molecular level that are smaller than the diffraction limit (around 200-nm in lateral resolution). These techniques do not physically violate the Abbe limit of resolution but exploit the photoluminescence properties and labelling specificity of fluorescence molecules to achieve super-resolution imaging. However, these super-resolution techniques limit most of their applications to the 2D imaging of fixed or dead samples due to the high laser power needed or slow speed for the localization process. Extended from 2D imaging, light sheet microscopy has been proven to have a lot of applications on 3D imaging at much better spatiotemporal resolutions due to its intrinsic optical sectioning and high imaging speed. Herein, we combine the advantage of localization microscopy and light-sheet microscopy to have super-resolved cellular imaging in 3D across large field of view. With high-density labeled spontaneous blinking fluorophore and wide-field detection of light-sheet microscopy, these allow us to construct 3D super-resolution multi-cellular imaging at high speed (~minutes) by light-sheet single-molecule localization microscopy.

Genetically encoded light-sensitive channels and reporters enable both neuronal activity optical control and read-out. Full explotation of these optogenetic tools requires single-cell scale methods to pattern light into neural tissue. Computer Generated Holography (CGH) can powerfully enhance optogenetic stimulation by efficiently shaping light onto multiple cellular targets. However, a linear proportionality between lateral shape area and axial extent degrades axial precision for cases demanding extended lateral patterning i.e., to cover entire soma of multiple cells. To address this limitation, we previously combined CGH with temporal focusing (TF) to stretch laser pulses outside of the focal plane, which combined with two-photon’s nonlinear fluorescence dependence, axially confines fluorescence regardless of lateral extent. However, this configuration restricts nonlinear excitation to a single spatiotemporal focal plane: which is the objective focal plane. Here we demonstrate a novel scheme enabling generation of spatiotemporally focused pattern generation in three dimensions. We demonstrate that this approach enables simultaneous photoconversion of tens of zebrafish larvae spinal cord neurons occupying separate axial planes.

We have attempted to image three-dimensional distribution of fluorescence beads embedded within gels in a glass capillary using light-sheet illumination, as a primary step towards developing a three-dimensional molecular imaging flow cytometer. An illumination and a detection path were arranged orthogonal to the longer axis of the capillary. The light-sheet illumination was tilted with respect to the illumination axis to image a projection of a section of the sample by a CCD. Different sections of the sample were imaged through scanning the capillary itself, along its length. By stacking the images after inverse transformation, the three-dimensional distribution of the fluorescence beads was imaged.

Optical coherence microscopy (OCM) is an interferometric imaging technique that enables high resolution, non-invasive imaging of 3D cell cultures and biological tissues. Volumetric imaging with OCM suffers a trade-off between high transverse resolution and poor depth-of-field resulting from defocus, optical aberrations, and reduced signal collection away from the focal plane. While defocus and aberrations can be compensated with computational methods such as interferometric synthetic aperture microscopy (ISAM) or computational adaptive optics (CAO), reduced signal collection must be physically addressed through optical hardware. Axial scanning of the focus is one approach, but comes at the cost of longer acquisition times, larger datasets, and greater image reconstruction times. Given the capabilities of CAO to compensate for general phase aberrations, we present an alternative method to address the signal collection problem without axial scanning by using intentionally aberrated optical hardware. We demonstrate the use of an astigmatic spectral domain (SD-)OCM imaging system to enable single-acquisition volumetric OCM in 3D cell culture over an extended depth range, compared to a non-aberrated SD-OCM system. The transverse resolution of the non-aberrated and astigmatic imaging systems after application of CAO were 2 um and 2.2 um, respectively. The depth-range of effective signal collection about the nominal focal plane was increased from 100 um in the non-aberrated system to over 300 um in the astigmatic system, extending the range over which useful data may be acquired in a single OCM dataset. We anticipate that this method will enable high-throughput cellular-resolution imaging of dynamic biological systems over extended volumes.

Femtosecond laser processing is a promising tool for fabricating novel and useful structures on the surfaces of and inside materials. An enormous number of pulse irradiation points will be required for fabricating actual structures with millimeter scale, and therefore, the throughput of femtosecond laser processing must be improved for practical adoption of this technique. One promising method to improve throughput is parallel pulse generation based on a computer-generated hologram (CGH) displayed on a spatial light modulator (SLM), a technique called holographic femtosecond laser processing. The holographic method has the advantages such as high throughput, high light use efficiency, and variable, instantaneous, and 3D patterning. Furthermore, the use of an SLM gives an ability to correct unknown imperfections of the optical system and inhomogeneity in a sample using in-system optimization of the CGH. Furthermore, the CGH can adaptively compensate in response to dynamic unpredictable mechanical movements, air and liquid disturbances, a shape variation and deformation of the target sample, as well as adaptive wavefront control for environmental changes. Therefore, it is a powerful tool for the fabrication of biological cells and tissues, because they have free form, variable, and deformable structures. In this paper, we present the principle and the experimental setup of holographic femtosecond laser processing, and the effective way for processing the biological sample. We demonstrate the femtosecond laser processing of biological materials and the processing properties.

The conventional spectral domain (SD) and Fourier domain (FD) OCT method deliver a 1D reflectivity profile in the sample investigated by applying a Fourier transform (FT) to the channeled spectrum, CS, at the interferometer output. We discuss here the advantages of a novel OCT technology, Master Slave (MS). The MS method radically changes the main building blocks of a SD (FD)-OCT set-up. The serially provided electrical signal in conventional technology is replaced by multiple signals, a signal for each OPD point along an electrical output for each depth in the object investigated. In this way, it is possible to: (1) direct access to information from selected depths; (ii) eliminate the process of resampling, required by the FT based conventional technology, with immediate consequences in improving the decay of sensitivity with depth, achieving the expected axial resolution limit, reduction in the time to display an image and lower cost OCT assembly; (iii) OCT interferometer tolerant to dispersion left unbalanced.

Dual comb spectroscopy (DCS) is based on the combination of Fourier transform spectroscopy with an optical frequency comb (OFC), and has a spectral resolution below MHz order over a spectral range over several tens THz. Furthermore, non-mechanical time-delay scanning enables the rapid data acquisition. However, in order to expand DCS into spectral imaging, a CCD or a CMOS camera cannot be used because a high-speed, point detector is indispensable to acquire the fast interferogram signal in DCS. Therefore, the first demonstration of DCS imaging was based on the mechanical scanning of the sample position. If DCS imaging can be achieved without the need for mechanical scanning, the application field of the DCS imaging will be largely expanded. One promising method to achieve the scan-less 2D imaging is a single-pixel imaging (SPI), enabling scan-less 2D imaging by use of pattern illumination on the sample and a point detector. Also, the accumulation effect in the random pattern illumination increases a signal-to-noise ratio. In this paper, we present combination of DCS with SPI, namely a scan-less DCS imaging. Spectral imaging of a sample indicated the effectiveness and potential of scan-less DCS imaging.

The utility and accuracy of computational modeling often requires direct validation against experimental measurements. The work presented here is motivated by taking a combined experimental and computational approach to determine the ability of large-scale computational fluid dynamics (CFD) simulations to understand and predict the dynamics of circulating tumor cells in clinically relevant environments. We use stroboscopic light sheet fluorescence imaging to track the paths and measure the velocities of fluorescent microspheres throughout a human aorta model. Performed over complex physiologicallyrealistic 3D geometries, large data sets are acquired with microscopic resolution over macroscopic distances.

Red blood cells (RBCs) stored in hypothermic environments for the purpose of transfusion have been documented to undergo structural and functional changes over time. One sign of the so-called RBC storage lesion is irreversible damage to the cell membrane. Consequently, RBCs undergo a morphological transformation from regular, deformable biconcave discocytes to rigid spheroechinocytes. The spherically shaped RBCs lack the deformability to efficiently enter microvasculature, thereby reducing the capacity of RBCs to oxygenate tissue. Blood banks currently rely on microscope techniques that include fixing, staining and cell counting in order to morphologically characterize RBC samples; these methods are labor intensive and highly subjective. This study presents a novel, high-throughput RBC morphology characterization technique using image flow cytometry (IFC). An image segmentation template was developed to process 100,000 images acquired from the IFC system and output the relative spheroechinocyte percentage. The technique was applied on samples extracted from two blood bags to monitor the morphological changes of the RBCs during in vitro hypothermic storage. The study found that, for a given sample of RBCs, the IFC method was twice as fast in data acquisition, and analyzed 250-350 times more RBCs than the conventional method. Over the lifespan of the blood bags, the mean spheroechinocyte population increased by 37%. Future work will focus on expanding the template to segregate RBC images into more subpopulations for the validation of the IFC method against conventional techniques; the expanded template will aid in establishing quantitative links between spheroechinocyte increase and other RBC storage lesion characteristics.

Optical coherence tomography (OCT) imaging systems can now produce MB=s to GB=s data streams. We present a complete solution for signal acquisition up to 4 GS/s and on-board field programmable gate array (FPGA) OCT processing matching the high acquisition speed. On-board OCT signal processing virtually eliminates the downstream signal processing and data throughput bottleneck. Complex filtering allows for windowing and dispersion compensation. Data is zero-padded when the number of samples is not a power of 2. The Fast Fourier Transform (FFT) engine can match the maximum acquisition speed when performing 4096-point FFTs. Output data can be linear amplitude or logarithmic and represented on several floating-point or integer precisions. This hardware solution comes with dedicated software and software development kit.

We have simulated the effects of the number of bits and the sampling rate of a digitizer on the performance of lifetime measurements. We found that the number of bits of a digitizer is important to obtain certain accuracy in lifetime measurement. There exists a certain critical sampling frequency of a digitizer required to separate a certain lifetime differences in a double exponentially decaying intensity profile. We did these simulations by using Monte Carlo simulations with least-square curve fitting algorithms.

Oral cancer incidences have been increasing in recent years and late detection often leads to poor prognosis. Raman spectroscopy has been identified has a valuable diagnostic tool for cancer but its time consuming nature has prevented its clinical use. For Raman to become a realistic aid to histopathology, a rapid pre-screening technique is required to find small regions of interest on tissue sections ^[1]. The aim of this work is to investigate the feasibility of hyperspectral imaging in the visible spectral range as a fast imaging technique before Raman is performed. We have built a hyperspectral microscope which captures 300 focused and intensity corrected images with wavelength ranging from 450- 750 nm in around 30 minutes with sub-micron spatial resolution and around 10 nm spectral resolution. Hyperstacks of known absorbing samples, including fluorescent dyes and dried blood droplets, show excellent results with spectrally accurate transmission spectra and concentration-dependent intensity variations. We successfully showed the presence of different components from a non-absorbent saliva droplet sample. Data analysis is the greatest hurdle to the interpretation of more complex data such as unstained tissue sections.