Deep-learning based flat-fielding quantitative phase contrast microscopy.

Quantitative phase contrast microscopy (QPCM) can realize high-quality imaging of sub-organelles inside live cells without fluorescence labeling, yet it requires at least three phase-shifted intensity images. Herein, we combine a novel convolutional neural network with QPCM to quantitatively obtain the phase distribution of a sample by only using two phase-shifted intensity images. Furthermore, we upgraded the QPCM setup by using a phase-type spatial light modulator (SLM) to record two phase-shifted intensity images in one shot, allowing for real-time quantitative phase imaging of moving samples or dynamic processes. The proposed technique was demonstrated by imaging the fine structures and fast dynamic behaviors of sub-organelles inside live COS7 cells and 3T3 cells, including mitochondria and lipid droplets, with a lateral spatial resolution of 245 nm and an imaging speed of 250 frames per second (FPS). We imagine that the proposed technique can provide an effective way for the high spatiotemporal resolution, high contrast, and label-free dynamic imaging of living cells.

Phase image correlation spectroscopy for detecting microfluidic dynamics.

It is essential to quantify the physical properties and the dynamics of flowing particles in many fields, especially in microfluidic-related applications. We propose phase image correlation spectroscopy (PICS) as a versatile tool to quantify the concentration, hydro-diameter, and flow velocity of unlabeled particles by correlating the pixels of the phase images taken on flowing particles in a microfluidic device. Compared with conventional image correlation spectroscopy, PICS is minimally invasive, relatively simple, and more efficient, since it utilizes the intrinsic phase of the particles to provide a contrast instead of fluorescent labeling. We demonstrate the feasibility of PICS by measuring flowing polymethylmethacrylate (PMMA) microspheres and yeast in a microfluidic device. We can envisage that PICS will become an essential inspection tool in biomedicine and industry.

Panoramic quantitative phase imaging of adherent live cells in a microfluidic environment.

Understanding how cells respond to external stimuli is crucial. However, there are a lack of inspection systems capable of simultaneously stimulating and imaging cells, especially in their natural states. This study presents a novel microfluidic stimulation and observation system equipped with flat-fielding quantitative phase contrast microscopy (FF-QPCM). This system allowed us to track the behavior of organelles in live cells experiencing controlled microfluidic stimulation. Using this innovative imaging platform, we successfully quantified the cellular response to shear stress including directional cellular shrinkage and mitochondrial distribution change in a label-free manner. Additionally, we detected and characterized the cellular response, particularly mitochondrial behavior, under varying fluidic conditions such as temperature and drug induction time. The proposed imaging platform is highly suitable for various microfluidic applications at the organelle level. We advocate that this platform will significantly facilitate life science research in microfluidic environments.