Quantum imaging holds potential benefits over classical imaging but has faced challenges such as poor signal-to-noise ratios, low resolvable pixel counts, difficulty in imaging biological organisms, and inability to quantify full birefringence properties. Here, we introduce quantum imaging by coincidence from entanglement (ICE), using spatially and polarization-entangled photon pairs to overcome these challenges. With spatial entanglement, ICE offers higher signal-to-noise ratios, greater resolvable pixel counts, and the ability to image biological organisms. With polarization entanglement, ICE provides quantitative quantum birefringence imaging capability, where both the phase retardation and the principal refractive index axis angle of an object can be remotely and instantly quantified without changing the polarization states of the photons incident on the object. Furthermore, ICE enables 25 times greater suppression of stray light than classical imaging. ICE has the potential to pave the way for quantum imaging in diverse fields, such as life sciences and remote sensing.

Techniques for imaging haemodynamics use ionizing radiation or contrast agents or are limited by imaging depth (within approximately 1 mm), complex and expensive data-acquisition systems, or low imaging speeds, system complexity or cost. Here we show that ultrafast volumetric photoacoustic imaging of haemodynamics in the human body at up to 1 kHz can be achieved using a single laser pulse and a single element functioning as 6,400 virtual detectors. The technique, which does not require recalibration for different objects or during long-term operation, enables the longitudinal volumetric imaging of haemodynamics in vasculature a few millimetres below the skin’s surface. We demonstrate this technique in vessels in the feet of healthy human volunteers by capturing haemodynamic changes in response to vascular occlusion. Single-shot volumetric photoacoustic imaging using a single-element detector may facilitate the early detection and monitoring of peripheral vascular diseases and may be advantageous for use in biometrics and point-of-care testing.

Many ultrafast phenomena in biology and physics are fundamental to our scientific understanding but have not yet been visualized owing to the extreme speed and sensitivity requirements in imaging modalities. Two examples are the propagation of passive current flows through myelinated axons and electromagnetic pulses through dielectrics, which are both key to information processing in living organisms and electronic devices. Here, we demonstrate differentially enhanced compressed ultrafast photography (Diff-CUP) to directly visualize propagations of passive current flows at approximately 100 m/s along internodes, i.e., continuous myelinated axons between nodes of Ranvier, from Xenopus laevis sciatic nerves and of electromagnetic pulses at approximately 5 × 10^7 m/s through lithium niobate. The spatiotemporal dynamics of both propagation processes are consistent with the results from computational models, demonstrating that Diff-CUP can span these two extreme timescales while maintaining high phase sensitivity. With its ultrahigh speed (picosecond resolution), high sensitivity, and noninvasiveness, Diff-CUP provides a powerful tool for investigating ultrafast biological and physical phenomena.

Traditional fluorescence microscopy is blind to molecular microenvironment information that is present in a fluorescence lifetime, which can be measured by fluorescence lifetime imaging microscopy (FLIM). However, most existing FLIM techniques are slow to acquire and process lifetime images, difficult to implement, and expensive. Here we present instant FLIM, an analog signal processing method that allows real-time streaming of fluorescence intensity, lifetime, and phasor imaging data through simultaneous image acquisition and instantaneous data processing. Instant FLIM can be easily implemented by upgrading an existing two-photon microscope using cost-effective components and our open-source software. We further improve the functionality, penetration depth, and resolution of instant FLIM using phasor segmentation, adaptive optics, and super-resolution techniques. We demonstrate through-skull intravital 3D FLIM of mouse brains to depths of 300 µm and present the first in vivo 4D FLIM of microglial dynamics in intact and injured zebrafish and mouse brains for up to 12 h.

Fluorescence microscopy has enabled a dramatic development in modern biology. Due to its inherently weak signal, fluorescence microscopy is not only much noisier than photography, but also presented with Poisson-Gaussian noise where Poisson noise, or shot noise, is the dominating noise source. To get clean fluorescence microscopy images, it is highly desirable to have effective denoising algorithms and datasets that are specifically designed to denoise fluorescence microscopy images. While such algorithms exist, no such datasets are available. In this paper, we fill this gap by constructing a dataset - the Fluorescence Microscopy Denoising (FMD) dataset - that is dedicated to Poisson-Gaussian denoising. The dataset consists of 12,000 real fluorescence microscopy images obtained with commercial confocal, two-photon, and wide-field microscopes and representative biological samples such as cells, zebrafish, and mouse brain tissues. We use image averaging to effectively obtain ground truth images and 60,000 noisy images with different noise levels. We use this dataset to benchmark 10 representative denoising algorithms and find that deep learning methods have the best performance. To our knowledge, this is the first real microscopy image dataset for Poisson-Gaussian denoising purposes and it could be an important tool for high-quality, real-time denoising applications in biomedical research.