All-passive pixel super-resolution of time-stretch imaging

Optofluidic time-stretch imaging flow cytometry with a real-time storage rate beyond 5.9 GB/s

Optofluidic time-stretch imaging flow cytometry (OTS-IFC) provides a suitable solution for high-precision cell analysis and high-sensitivity detection of rare cells due to its high-throughput and continuous image acquisition. However, transferring and storing continuous big data streams remains a challenge. In this study, we designed a high-speed streaming storage strategy to store OTS-IFC data in real-time, overcoming the imbalance between the fast generation speed in the data acquisition and processing subsystem and the comparatively slower storage speed in the transmission and storage subsystem. This strategy, utilizing an asynchronous buffer structure built on the producer-consumer model, optimizes memory usage for enhanced data throughput and stability. We evaluated the storage performance of the high-speed streaming storage strategy in ultra-large-scale blood cell imaging on a common commercial device. The experimental results show that it can provide a continuous data throughput of up to 5891 MB/s.

Super-resolution techniques for biomedical applications and challenges

Super-resolution (SR) techniques have revolutionized the field of biomedical applications by detailing the structures at resolutions beyond the limits of imaging or measuring tools. These techniques have been applied in various biomedical applications, including microscopy, magnetic resonance imaging (MRI), computed tomography (CT), X-ray, electroencephalogram (EEG), ultrasound, etc. SR methods are categorized into two main types: traditional non-learning-based methods and modern learning-based approaches. In both applications, SR methodologies have been effectively utilized on biomedical images, enhancing the visualization of complex biological structures. Additionally, these methods have been employed on biomedical data, leading to improvements in computational precision and efficiency for biomedical simulations. The use of SR techniques has resulted in more detailed and accurate analyses in diagnostics and research, essential for early disease detection and treatment planning. However, challenges such as computational demands, data interpretation complexities, and the lack of unified high-quality data persist. The article emphasizes these issues, underscoring the need for ongoing development in SR technologies to further improve biomedical research and patient care outcomes.

Photonic Microfluidic Technologies for Phytoplankton Research

Phytoplankton is a crucial component for the correct functioning of different ecosystems, climate regulation and carbon reduction. Being at least a quarter of the biomass of the world's vegetation, they produce approximately 50% of atmospheric O2 and remove nearly a third of the anthropogenic carbon released into the atmosphere through photosynthesis. In addition, they support directly or indirectly all the animals of the ocean and freshwater ecosystems, being the base of the food web. The importance of their measurement and identification has increased in the last years, becoming an essential consideration for marine management. The gold standard process used to identify and quantify phytoplankton is manual sample collection and microscopy-based identification, which is a tedious and time-consuming task and requires highly trained professionals. Microfluidic Lab-on-a-Chip technology represents a potential technical solution for environmental monitoring, for example, in situ quantifying toxic phytoplankton. Its main advantages are miniaturisation, portability, reduced reagent/sample consumption and cost reduction. In particular, photonic microfluidic chips that rely on optical sensing have emerged as powerful tools that can be used to identify and analyse phytoplankton with high specificity, sensitivity and throughput. In this review, we focus on recent advances in photonic microfluidic technologies for phytoplankton research. Different optical properties of phytoplankton, fabrication and sensing technologies will be reviewed. To conclude, current challenges and possible future directions will be discussed.

Temporally structured illumination for ultrafast time-stretch microscopy

This work developed a temporally structured illumination scheme to conquer the detector bandwidth limitation that is increasingly becoming a stumbling block of ultrafast single-pixel measurement. Inspired by structured illumination microscopy and space-time duality, an electro-optic modulator resembling the temporal counterpart of a spatial grating is used to impart a sinusoidal pattern onto the time-stretch signal before detection. Consequently, the detector bandwidth is equivalently doubled based on three measurements and a subsequent reconstruction, thereby capturing the high-frequency components originally beyond the detector bandwidth. As a proof of concept, this method is applied to an ultrafast single-pixel imaging modality, the time-stretch microscopy, to verify its capability to surpass the resolution limit imposed by the detector bandwidth. High-quality images with ∼4.0  μm spatial resolution are acquired at ∼30  MHz frame rates by merely half of the detector bandwidth, compared to the traditional system. This Letter provides a simple and economical solution for high-speed signal acquisition, which is demanded in a variety of applications, ranging from ultrafast imaging to single-shot spectroscopy.

A Real-Time Coprime Line Scan Super-Resolution System for Ultra-Fast Microscopy

A fundamental technical challenge for ultra-fast cell microscopy is the tradeoff between imaging throughput and resolution. In addition to throughput, real-time applications such as image-based cell sorting further requires ultra-low imaging latency to facilitate rapid decision making on a single-cell level. Using a novel coprime line scan sampling scheme, a real-time low-latency hardware super-resolution system for ultra-fast time-stretch microscopy is presented. The proposed scheme utilizes analog-to-digital converter with a carefully tuned sampling pattern (shifted sampling grid) to enable super-resolution image reconstruction using line scan input from an optical front-end. A fully pipelined FPGA-based system is built to efficiently handle the real-time high-resolution image reconstruction process with the input subpixel samples while achieving minimal output latency. The proposed super-resolution sampling and reconstruction scheme is parametrizable and is readily applicable to different line scan imaging systems. In our experiments, an imaging latency of 0.29 μs has been achieved based on a pixel-stream throughput of 4.123 giga pixels per second, which translates into imaging throughput of approximately 120000 cells per second.

A high-throughput all-optical laser-scanning imaging flow cytometer with biomolecular specificity and subcellular resolution

Image-based cellular assay advances approaches to dissect complex cellular characteristics through direct visualization of cellular functional structures. However, available technologies face a common challenge, especially when it comes to the unmet need for unraveling population heterogeneity at single-cell precision: higher imaging resolution (and thus content) comes at the expense of lower throughput, or vice versa. To overcome this challenge, a new type of imaging flow cytometer based upon an all-optical ultrafast laser-scanning imaging technique, called free-space angular-chirp-enhanced delay (FACED) is reported. It enables an imaging throughput (>20 000 cells s^-1 ) 1 to 2 orders of magnitude higher than the camera-based imaging flow cytometers. It also has 2 critical advantages over optical time-stretch imaging flow cytometry, which achieves a similar throughput: (1) it is widely compatible to the repertoire of biochemical contrast agents, favoring biomolecular-specific cellular assay and (2) it enables high-throughput visualization of functional morphology of individual cells with subcellular resolution. These capabilities enable multiparametric single-cell image analysis which reveals cellular heterogeneity, for example, in the cell-death processes demonstrated in this work-the information generally masked in non-imaging flow cytometry. Therefore, this platform empowers not only efficient large-scale single-cell measurements, but also detailed mechanistic analysis of complex cellular processes.

Improved Resolution Optical Time Stretch Imaging Based on High Efficiency In-Fiber Diffraction

Most overlooked challenges in ultrafast optical time stretch imaging (OTSI) are sacrificed spatial resolution and higher optical loss. These challenges are originated from optical diffraction devices used in OTSI, which encode image into spectra of ultrashort optical pulses. Conventional free-space diffraction gratings, as widely used in existing OTSI systems, suffer from several inherent drawbacks: limited diffraction efficiency in a non-Littrow configuration due to inherent zeroth-order reflection, high coupling loss between free-space gratings and optical fibers, bulky footprint, and more importantly, sacrificed imaging resolution due to non-full-aperture illumination for individual wavelengths. Here we report resolution-improved and diffraction-efficient OTSI using in-fiber diffraction for the first time to our knowledge. The key to overcome the existing challenges is a 45° tilted fiber grating (TFG), which serves as a compact in-fiber diffraction device offering improved diffraction efficiency (up to 97%), inherent compatibility with optical fibers, and improved imaging resolution owning to almost full-aperture illumination for all illumination wavelengths. 50 million frames per second imaging of fast moving object at 46 m/s with improved imaging resolution has been demonstrated. This conceptually new in-fiber diffraction design opens the way towards cost-effective, compact and high-resolution OTSI systems for image-based high-throughput detection and measurement.