Imaging of the interior of object with light has long been a challenge for optical imaging. Optical diffraction tomography (ODT) is able to obtain three-dimensional (3D) object information through object rotation. We will discuss harmonic optical tomography (HOT) that exploits a defocused illumination beam for nonlinear optical tomography. We will also discuss our demonstration of coherent ODT with incoherent light emission in a new optical tomography technique called fluorescent diffraction tomography (FDT) and the use of spatial frequency imaging for high speed nonlinear optical microscopy.

High-speed laser scanning microscopy is crucial for monitoring fast dynamical events. We here present a novel strategy that enables ultrafast lateral optical scanning for high-speed high-throughput laser scanning microscopes. Our technique is flexible that it can be adapted to one-dimensional line scan or two-dimensional frame scan, with pixel rate up to tens of megahertz. We integrate this strategy into a two-photon microscope for kilohertz frame-rate imaging.

I will present a new category of computational ultrafast imaging technique, light field tomography (LIFT), which can perform 3D snapshot transient (time-resolved) imaging at an unprecedented frame rate with full-fledged light field imaging capabilities including depth retrieval, post-capture refocusing, and extended depth of field.

In modern digital imaging systems, the recording of high-speed, high-resolution video has been hindered by the limited data transfer bandwidth of electronics. Here we demonstrate ultrahigh-pixel-rate compressed photography using time delay integration (TDI) in which both the spatial and temporal resolutions are greatly enhanced. A dynamic scene is spatially encoded with a pseudo-random pattern, temporally modulated by the TDI camera, and streamed to a host computer for post-processing. The system can record a 0.85-megapixel video at a 200kHz frame rate (170 gigapixels per second). The corresponding pixel rate is two orders of magnitude greater than that of a conventional camera.

Nitrogen vacancy (NV) magnetometers can provide sensitive field measurements via optically detected magnetic resonance (ODMR). Built-in photo-isolation and biocompatibility of diamond have enabled many applications for biological systems. Since small changes in field strength yield commensurate intensity fluctuations, dynamic measurements require fast sensitive detectors such as photomultiplier tubes which inhibits spatial resolution. EMCCD and sCMOS cameras can make sensitive measurements, however, temporal resolution is limited by low frame rates. Recently compressed photography enabled intermediate time steps spatially encoded in a single acquisition. We propose compressed microscopy for capturing dynamic magnetic field fluctuations using sCMOS, moving towards label-free neural sensing.

We discuss our recent efforts to achieve highly multiplexed fast fluorescence imaging and quantitative biosensing through camera frame-synchronized scanning of the excitation wavelength in the wide field. For live-cell microscopy, we thus attain low (~1%) crosstalks and ~10 ms temporal resolutions for up to six fluorophores via linear unmixing, and further develop novel, quantitative imaging schemes for both bi-state and FRET fluorescent biosensors. These capabilities are further integrated to multiplex absolute pH imaging with three additional target proteins in the mitophagy pathway. Together, excitation spectral microscopy provides exceptional opportunities for highly multiplexed fluorescence imaging without fluorescence dispersion.

Imaging the spatial and temporal effects of millisecond duration pulses of infrared light on neurons requires image frame rates approaching 1000+ Hz to capture neural activity. Autofluorescence imaging of the metabolic coenzymes reduced nicotinamide adenine dinucleotide and flavin adenine dinucleotide provides information about cellular metabolism and can be a surrogate measurement of neural activity. Here, we are combining fast fluorescence microscopy techniques with modeling and machine learning to image autofluorescence dynamics in cells following exposure to infrared light.

Zebrafish is a useful biological model for analyzing genetic modification and large-scale screening. Its morphological evaluation, carrying meaningful information about genotype-phenotype relationship, is equally important. However, analysis of large amounts across development stages is a labor-intensive task. Here, we suggest a high-throughput monitoring technique using office scanner. Moreover, we developed deep learning models for extraction and analysis of massive statistical information. CNN-based architecture, forming the core of segmentation, serves as a basis for quantitative analysis and an early signal for embryo’s abnormal growth. Finally, compared to conventional microscope imaging, our scanning technique offers high-throughput, accurate, and fast quantitative phenotype analysis.

We present a quantitative phase image (QPI) reconstruction method using generative deep learning (with high similarity of 91% and low error rate of < 1%), and its ability to integrate with a high-throughput microfluidic multimodal imaging flow cytometry platform (called multi-ATOM) that can consistently classify cancer cells in heterogeneous tumors from human non-small cell lung cancer patients at large scale (~200,000 cells) and high accuracy (~98%); and can reveal biophysical heterogeneity of tumors. This work represents another groundwork of synergizing high-throughput QPI and deep learning for future label-free intelligent clinical cancer diagnosis.

We created a highly-tilted light sheet in oblique plane microscopy (OPM) by using a transmission grating such that the angle of illumination does not rely on the numerical aperture (NA) of the primary objective lens. By decoupling the light sheet angle from the NA, MOPM breaks the diffraction-limited resolution in the axial direction imposed by the NA of the primary lens. Centimeter-scale field-of-view and near-isotropic resolutions can be achieved in OPM by utilizing low NA objective lens. Imaging speed of 2 volumes per second (VPS) and 12 VPS has been demonstrated in imaging the neurons and heartbeat in whole zebrafish.

Fluorescence lifetime imaging microscopy (FLIM) adds an additional dimension to fluorescence microscopy by measuring the fluorophore interactions with the microenvironment in addition to all the benefits and power of fluorescence microscopy. Real-time FLIM, however, requires overcoming unique technical challenges to achieve similar imaging speeds as can be achieved through standard in vivo microscopy techniques. This talk will present an “InstantFLIM” system that achieves real-time (acquisition and processing), super-resolution, 3D in vivo multiphoton FLIM by overcoming these limitations. The system is demonstrated in intact-skull mouse and zebrafish brain imaging models, and 3D autofluorescence FLIM of highly scattering plant tissue.

Brillouin microscopy has recently emerged as a promising modality to provide label-free contrast mechanisms to characterize the biophysical properties of cells, tissues and biomaterials. However Brillouin spectroscopy has historically been slow to be viable in biological applications. This talk will discuss the advancements in Brillouin spectroscopy of the past several years that have made possible to demonstrate biological applications. Finally, several promising directions for high-throughput Brillouin measurements will be discussed.

High-speed broadband Raman spectroscopy (>1000 cm^−1 bandwidth) provides label-free molecular vibrational information with fine temporal resolution, making it valuable for biomedical applications such as vibrational imaging or detecting transient molecular dynamics. Current techniques for high-speed broadband Raman spectroscopy, such as Fourier-transform coherent anti-Stokes Raman scattering (FT-CARS) spectroscopy, can probe the Raman “fingerprint” region (500-1800 cm^−1), but lack sensitivity in the low-frequency or THz region (<200 cm^−1, <6 THz), preventing measurement of rich intermolecular vibrational information. Here we demonstrate a technique combining FT-CARS spectroscopy-like optical filtering with Sagnac interferometry for simultaneous acquisition of THz and fingerprint Raman spectra at 24,000 spectra/sec.

Traditional drug sensitivity assay confirms the cell death by time-consuming fixation and labeling. This snapshot evaluation neglects valuable time-course details that may provide new insight for the speed-up of drug screening. Here we develop a label-free method to early report cell senescence by the endogenous lipofuscin autofluorescence. After drug treatment, we found the lipofuscin red autofluorescence greatly increased in apoptotic and necrotic cells. This approach allows the time-course observation of pharmacodynamics in 3D tumor organoids and could determine the drug sensitivity earlier than Annexin V/PI assay. This metabolic fluorescence hallmark could improve the throughput of drug sensitivity test.

Raman flow cytometry is a promising approach for large-scale single-cell analysis in a label-free manner. However, due to the limited sensitivity of Raman spectral measurements, its application range is still limited compared to fluorescence-based flow cytometry. Here we present the developments of a high-throughput Raman-based spectroscopic flow cytometer and a Raman-activated cell sorter realized by integrating state-of-the-art coherent Raman techniques and acoustofluidic devices for cell manipulation in a flow stream. We demonstrate analysis and sorting of microalgal cells based on their bioproducts’ contents such as palamyron, starch, and carotenoids.

We report the use of high-throughput quantitative phase imaging (QPI) flow cytometry (based on multiplexed asymmetric-detection time-stretch optical microscopy (multi-ATOM)) to investigate biophysical profiles of single cells infected by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). This technique reveals the subtle biophysical heterogeneity of SARS-CoV-2 infection under the same multiplicity of infection. Furthermore, analyzing the label-free high-dimensional single-cell biophysical profiles (derived from multi-ATOM images) based on an unsupervised trajectory inference algorithm accurately recovers the infection progression over time. This study could offer biophysical insight of cellular morphogenesis of SARS-CoV-2 and shows the potential of label-free morphological profiling as a complementary drug discovery strategy for SARS-CoV-2.

Vascular stenosis is a pathological hallmark of atherosclerosis, but its transient process is not well understood due to the lack of analytical tools to study it. Here we report spatiotemporally resolved observation of shear-induced platelet aggregation by combining a microfluidic on-chip stenosis model and optofluidic time-stretch microscopy. Our results indicate a synergistic effect of stenosis and agonists on platelet activation and aggregation. Particularly, an agonist, thrombin receptor activator peptide 6, causes preferential enhancement of platelet aggregation. Our findings are expected to deepen our understanding of stenosis-induced platelet aggregation and pave ways for developing effective antithrombotic therapeutics.

We have recently demonstrated a high throughput three-dimensional (3D) image flow cytometry method, in which a machine-learning algorithm is used to retrieve the 3D refractive index maps of cells from one angle-multiplexing interferogram. Using this system, we have imaged flowing red blood cells and NIH/3T3 cells with a throughput of more than < 10,000 volumes/second. To further demonstrate its potential on cell phenotyping for clinical testing, we plan to apply this platform to image large populations of various cell types and extracting their morphological and biophysical parameters.