Accurate Phase Imaging Research Articles

Eliminating the systematic error of spatial light interference microscopy by the wavefront comparison iterative algorithm

Spatial light interference microscopy (SLIM) is a unique quantitative phase imaging technology. Since the phase of direct light is simply assumed to be 0, it has a non-negligible systematic error. Based on the theory of partially coherent SLIM, here we propose a wavefront comparison iterative (WCI) algorithm to eliminate this error for accurate phase imaging. In this paper, we clarified the existence of this systematic error by phase imaging of oil-immersed polystyrene microspheres, and we demonstrated the feasibility of the WCI algorithm by phase imaging of red blood cells. Furthermore, through computer simulation, we have confirmed that for phase imaging of large adherent cells, if the SLIM system compresses the phase of direct light sufficiently small, the WCI algorithm will be feasible too.

Fast automated quantitative phase reconstruction in digital holography with unsupervised deep learning

Digital holography can provide quantitative phase images related to the morphology and content of biological samples. To reconstruct an accurate phase image, several processes, such as phase unwrapping, focusing, and calculation of digital reference wave and numerical propagation, are essential. However, this process is time-consuming. We propose a model that performs phase reconstruction in one-step and two-step using an unsupervised image-to-image translation structure. The two-step reconstruction model translates the phase image, which is obtained by performing numerical propagation on the hologram, into an accurate phase image, whereas the one-step reconstruction model directly translates the hologram into an accurate phase image. The proposed model shows similar high-performance reconstruction to the supervised learning model used in many previous studies. However, since supervised learning is trained in strict pairs, many target domain data (accurate phase imagery) is required. Since the proposed model is trained by unsupervised learning, phase reconstruction can be performed with a small amount of target domain data. The proposed method can help to observe the morphology and movement of biological cells in real-time applications.

Proposal of a compact grating-based phase contrast imaging system using an x-ray polycapillary lens

As the grating-based phase contrast imaging has drawn much attention in various scientific fields, there is an increasing demand for a compact imaging system with high efficiency in practical applications. In this paper, a compact imaging configuration by replacing the source grating in a conventional imaging system with a robust, easily-fabricated, and cost-effective x-ray polycapillary lens is proposed and its feasibility is examined using a full-scale Monte Carlo simulation. A typical x-ray spectrum for diagnostic mammography is adopted in the simulation. Under this spectrum, a new polycapillary lens is designed and optimized to meet the requirement of the imaging system. The phantom consists of polyethylene, cortical bone, and adipose tissue spheres of different sizes. An accurate phase image of the phantom is successfully reconstructed using an eight-step phase-stepping method. Excellent agreement of the phase shift and attenuation of the phantom is obtained between the simulation and the theoretical prediction. Compared with a conventional imaging system using a source grating at the same parameters, the imaging efficiency of our proposed system is improved 1.7 times, while its background visibility is reduced from 44.4% to 12.4%. Our results suggest the possibility of developing such a bench-top system for flexible phase contrast imaging applications.

Non-interferometric accurate phase imaging via linear-convergence iterative optimization

This paper reported a general non-interferometric high-accuracy quantitative phase imaging (QPI) method for arbitrary complex-valued objects. Given by a typical 4-f optical configuration as the imaging system, three frames of small-window phase modulation are applied on the object's Fourier spectrum so that redistributed intensity patterns are produced on the image plane, in which the object phase emerges at different degree. Then, an algebraic relationship that connects the object phase with the output intensity is established to provide us with an approximate closed-form phase recovery. Further, an efficient iterative optimization strategy is developed to turn that approximate solution into an accurate one. Due to the linear convergence property of the iteration, a high-accuracy phase recovery is achieved without requiring heavy iterations. The feasibility and accuracy of the proposed method are verified by both numerical simulations and experiments on diverse phase objects including biomedical tissues.

Quantitative phase radiography with polychromatic neutrons.

We develop and experimentally demonstrate a formalism that allows accurate phase imaging using neutron sources producing highly polychromatic beams. The results of measurements from a rectangular block of silicon compare favorably with theoretical simulations based upon the known composition and geometry of the block. The increased flux and reduced exposure times will permit a simple extension of the technique to tomographic phase imaging.