High-speed super-resolution imaging with compressive imaging-based structured illumination microscopy

New approaches for low phototoxicity imaging of living cells and tissues

Fluorescence microscopy is a powerful tool used in scientific and medical research, but it is inextricably linked to phototoxicity. Neglecting phototoxicity can lead to erroneous or inconclusive results. Recently, several reports have addressed this issue, but it is still underestimated by many researchers, even though it can lead to cell death. Phototoxicity can be reduced by appropriate microscopic techniques and carefully designed experiments. This review focuses on recent strategies to reduce phototoxicity in microscopic imaging of living cells and tissues. We describe digital image processing and new hardware solutions. We point out new modifications of microscopy methods and hope that this review will interest microscopy hardware engineers. Our aim is to underscore the challenges and potential solutions integral to the design of microscopy systems. Simultaneously, we intend to engage biologists, offering insight into the latest technological advancements in imaging that can enhance their understanding and practice.

Snapshot compressive structured illumination microscopy

We propose a snapshot compressive structured illumination microscopy (SoSIM) system to increase the number of reconstructed resolution-enhanced (RE) images per second and reduce the data bandwidth by capturing compressed measurements. In this system, multiple low-resolution images are encoded by a high-speed digital micro-mirror device with random binary masks. These images are then captured by a low-speed camera as a snapshot compressed measurement. Following this, we adopt an efficient deep neural network to reconstruct nine images with different structured illumination patterns from a single measurement. The reconstructed images are then combined into a single-frame RE image using the method of spectral synthesis in the frequency domain. When the camera operates at 100 frames per second (fps), we can eventually recover dynamic RE videos at the same speed with 100 fps.

Video snapshot compressive imaging using adaptive progressive coding for high-quality reconstruction under different illumination circumstances

We consider capturing high-speed color video under different illumination conditions using a video snapshot compressive imaging system (video SCI). An adaptive progressive coding method is proposed, and we conduct an integrated design of the imaging system in terms of optics, mechanics, and control. Compared to previous video SCI systems, this adaptive progressive coding method mitigates the image stability issues in various illumination conditions, ensuring high-quality imaging while greatly improving the light throughput of the system. Based on the analysis of both simulation and real experimental results, we found that this imaging system can achieve color video shooting under an illumination range of 2 lux to 60 lux.

Parallel interrogation of the chalcogenide-based micro-ring sensor array for photoacoustic tomography

Photoacoustic tomography (PAT), also known as optoacoustic tomography, is an attractive imaging modality that provides optical contrast with acoustic resolutions. Recent progress in the applications of PAT largely relies on the development and employment of ultrasound sensor arrays with many elements. Although on-chip optical ultrasound sensors have been demonstrated with high sensitivity, large bandwidth, and small size, PAT with on-chip optical ultrasound sensor arrays is rarely reported. In this work, we demonstrate PAT with a chalcogenide-based micro-ring sensor array containing 15 elements, while each element supports a bandwidth of 175 MHz (-6 dB) and a noise-equivalent pressure of 2.2 mPaHz^-1/2. Moreover, by synthesizing a digital optical frequency comb (DOFC), we further develop an effective means of parallel interrogation to this sensor array. As a proof of concept, parallel interrogation with only one light source and one photoreceiver is demonstrated for PAT with this sensor array, providing images of fast-moving objects, leaf veins, and live zebrafish. The superior performance of the chalcogenide-based micro-ring sensor array and the effectiveness of the DOFC-enabled parallel interrogation offer great prospects for advancing applications in PAT.

Weighted multi-scale denoising via adaptive multi-channel fusion for compressed ultrafast photography

Being capable of passively capturing transient scenes occurring in picoseconds and even shorter time with an extremely large sequence depth in a snapshot, compressed ultrafast photography (CUP) has aroused tremendous attention in ultrafast optical imaging. However, the high compression ratio induced by large sequence depth brings the problem of low image quality in image reconstruction, preventing CUP from observing transient scenes with fine spatial information. To overcome these restrictions, we propose an efficient image reconstruction algorithm with multi-scale (MS) weighted denoising based on the plug-and-play (PnP) based alternating direction method of multipliers (ADMM) framework for multi-channel coupled CUP (MC-CUP), named the MCMS-PnP algorithm. By removing non-Gaussian distributed noise using weighted MS denoising during each iteration of the ADMM, and adaptively adjusting the weights via sufficiently exploiting the coupling information among different acquisition channels collected by MC-CUP, a synergistic combination of hardware and algorithm can be realized to significantly improve the quality of image reconstruction. Both simulation and experimental results demonstrate that the proposed adaptive MCMS-PnP algorithm can effectively improve the accuracy and quality of reconstructed images in MC-CUP, and extend the detectable range of CUP to transient scenes with fine structures.