Opposite-view digital holographic microscopy with autofocusing capability

Phase-based reconstruction optimization method for digital holographic measurement of microstructures

Digital holography has transformative potential in measuring stacked-chip microstructures due to its noninvasive, single-shot, full-field characteristics. However, uncertainties in reconstruction distance inevitably lead to resolving blur and reconstruction distortion. Herein, we propose a phase-based reconstruction optimization method that consists of a phase-evaluation function and a structured surface-characterization model. Our proposed method involves setting a reconstruction distance range, obtaining phase information using sliced numerical reconstruction, and optimizing the reconstruction distance by finding the extreme value of the function, which identifies the focal plane of the reconstructed image. The structure of the surface topography is then characterized using the characterization model. We perform simulations of the recording, reconstruction, and characterization to verify the effectiveness of the proposed method. To further demonstrate the approach, a simple holographic recording system is constructed to measure a standard resolution target, and the measurement results are compared with a commercial instrument. The simulation and experiment demonstrate, respectively, 31.16% and 34.41% improvement in step-height characterization accuracy.

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.

Smart filtering of phase residues in noisy wrapped holograms

Phase unwrapping is one of the major challenges in multiple branches of science that extract three-dimensional information of objects from wrapped signals. In several applications, it is important to extract the unwrapped information with minimal signal resolution degradation. However, most of the denoising techniques for unwrapping are designed to operate on the entire phase map to remove a limited number of phase residues, and therefore they significantly degrade critical information contained in the image. In this paper, we present a novel, smart, and automatic filtering technique for locally minimizing the number of phase residues in noisy wrapped holograms, based on the phasor average filtering (PAF) of patches around each residue point. Both patch sizes and PAF filters are increased in an iterative algorithm to minimize the number of residues and locally restrict the artifacts caused by filtering to the pixels around the residue pixels. Then, the improved wrapped phase can be unwrapped using a simple phase unwrapping technique. The feasibility of our method is confirmed by filtering, unwrapping, and enhancing the quality of a noisy hologram of neurons; the intensity distribution of the spatial frequencies demonstrates a 40-fold improvement, with respect to previous techniques, in preserving the higher frequencies.

Methamphetamine-induced apoptosis in glial cells examined under marker-free imaging modalities

We used phase microscopy and Raman spectroscopic measurements to assess the response of in vitro rat C6 glial cells following methamphetamine treatment in real time. Digital holographic microscopy (DHM) and three-dimensional (3-D) tomographic nanoscopy allow measurements of live cell cultures, which yield information about cell volume changes. Tomographic phase imaging provides 3-D information about the refractive index distribution associated with the morphology of biological samples. DHM provides similar information, but for a larger population of cells. Morphological changes in cells are associated with alterations in cell cycle and initiation of cell death mechanisms. Raman spectroscopy measurements provide information about chemical changes within the cells. Our Raman data indicate that the chemical changes in proteins preceded morphological changes, which were seen with DHM. Our study also emphasizes that tomographic phase imaging, DHM, and Raman spectroscopy are imaging tools that can be utilized for noninvasive simultaneous monitoring of morphological and chemical changes in cells during apoptosis and can also be used to monitor other dynamic cell processes.

Fast phase retrieval in off-axis digital holographic microscopy through deep learning

Traditional digital holographic imaging algorithms need multiple iterations to obtain focused reconstructed image, which is time-consuming. In terms of phase retrieval, there is also the problem of phase compensation in addition to focusing task. Here, a new method is proposed for fast digital focus, where we use U-type convolutional neural network (U-net) to recover the original phase of microscopic samples. Generated data sets are used to simulate different degrees of defocused image, and verify that the U-net can restore the original phase to a great extent and realize phase compensation at the same time. We apply this method in the construction of real-time off-axis digital holographic microscope and obtain great breakthroughs in imaging speed.