Phase Retrieval Based on Deep Learning in Grating Interferometer

Grating interferometry is a promising technique to obtain differential phase contrast images with illumination source of low intrinsic transverse coherence. However, retrieving the phase contrast image from the differential phase contrast image is difficult due to the accumulated noise and artifacts from the differential phase contrast image (DPCI) reconstruction. In this paper, we implemented a deep learning-based phase retrieval method to suppress these artifacts. Conventional deep learning based denoising requires noisy-clean image pair, but it is not feasible to obtain sufficient number of clean images for grating interferometry. In this paper, we apply a recently developed neural network called Noise2Noise (N2N) that uses noise-noise image pairs for training. We obtained many differential phase contrast images through combination of phase stepping images, and these were used as noise input/target pairs for N2N training. The application of the N2N network to simulated and measured DPCI showed that the phase contrast images were retrieved with strongly suppressed phase retrieval artifacts. These results can be used in grating interferometer applications which uses phase stepping method.

Signal Retrieval from Non-Sinusoidal Intensity Modulations in X-ray and Neutron Interferometry Using Piecewise-Defined Polynomial Function

Grating-based phase-contrast and dark-field imaging systems create intensity modulations that are usually modeled with sinusoidal functions to extract transmission, differential-phase shift, and scatter information. Under certain system-related conditions, the modulations become non-sinusoidal and cause artifacts in conventional processing. To account for that, we introduce a piecewise-defined periodic polynomial function that resembles the physical signal formation process, modeling convolutions of binary periodic functions. Additionally, we extend the model with an iterative expectation-maximization algorithm that can account for imprecise grating positions during phase-stepping. We show that this approach can process a higher variety of simulated and experimentally acquired data, avoiding most artifacts.

High Spatial-Resolution Digital Phase-Stepping Shearography

Digital phase-stepping shearography is a speckle interferometric technique that uses laser speckles to generate the phase map of the displacement derivatives of a stressed object, and hence can map the stresses of a deformed object directly. Conventional digital phase-stepping shearography relies on the use of video cameras of relatively lower resolution, in the order of 5 megapixels or lower, operating at a video rate. In the present work, we propose a novel method of performing high spatial resolution phase stepping shearography. This method uses a 24 megapixel still digital imaging device (DSLR camera) and a Michelson-type shearing arrangement with an edge-clamped, center-loaded plate. Different phase-stepping algorithms were used, and all successfully generated shearograms. The system enabled extremely high-resolution phase maps to be generated from relatively large deformations applied to the test plate. Quantitative comparison of the maximum achieved spatial resolution is made with the video-rate cameras used in conventional shearography. By switching from conventional (video) imaging methods to still imaging methods, significantly higher spatial resolution (by about 5 times) can be achieved in actual phase-stepping shearography, which is of great usefulness in industrial non-destructive testing (NDT).

Fast holographic scattering compensation for deep tissue biological imaging

Scattering in biological tissues is a major barrier for in vivo optical imaging of all but the most superficial structures. Progress toward overcoming the distortions caused by scattering in turbid media has been made by shaping the excitation wavefront to redirect power into a single point in the imaging plane. However, fast, non-invasive determination of the required wavefront compensation remains challenging. Here, we introduce a quickly converging algorithm for non-invasive scattering compensation, termed DASH, in which holographic phase stepping interferometry enables new phase information to be updated after each measurement. This leads to rapid improvement of the wavefront correction, forming a focus after just one measurement iteration and achieving an order of magnitude higher signal enhancement at this stage than the previous state-of-the-art. Using DASH, we demonstrate two-photon fluorescence imaging of microglia cells in highly turbid mouse hippocampal tissue down to a depth of 530 μm.

Fast holographic scattering compensation for deep tissue biological imaging

Scattering in biological tissues is a major barrier for in vivo optical imaging of all but the most superficial structures. Progress toward overcoming the distortions caused by scattering in turbid media has been made by shaping the excitation wavefront to redirect power into a single point in the imaging plane. However, fast, non-invasive determination of the required wavefront compensation remains challenging. Here, we introduce a quickly converging algorithm for non-invasive scattering compensation, termed DASH, in which holographic phase stepping interferometry enables new phase information to be updated after each measurement. This leads to rapid improvement of the wavefront correction, forming a focus after just one measurement iteration and achieving an order of magnitude higher signal enhancement at this stage than the previous state-of-the-art. Using DASH, we demonstrate two-photon fluorescence imaging of microglia cells in highly turbid mouse hippocampal tissue down to a depth of 530 μm.

Generalized reverse projection method for grating-based phase tomography

The reverse projection protocol results in fast phase-contrast imaging thanks to its compatibility with conventional computed-tomography scanning. Many researchers have proposed variants. However, all these reverse projection methods in grating-based phase-contrast imaging are built on the hypothesis of the synchronous phase of reference shifting curves in the whole field of view. The hypothesis imposes uniformity and alignment requirements on the gratings, thus the field of view is generally limited. In this paper, a generalized reverse projection method is presented analytically for the case of non-uniform reference in grating-based phase tomography. The method is demonstrated by theoretical derivation, numerical simulations and synchrotron radiation experiments. The influence of imaging position to sensitivity, and the phase-wrapping phenomenon are also discussed. The proposed method combines the advantages of the high efficiency of the reverse projection method and the universal applicability of the phase-stepping method. The authors believe that the method would be used widely in fast and dose-constrained imaging.

Imaging biological tissue with high-throughput single-pixel compressive holography

Single-pixel holography (SPH) is capable of generating holographic images with rich spatial information by employing only a single-pixel detector. Thanks to the relatively low dark-noise production, high sensitivity, large bandwidth, and cheap price of single-pixel detectors in comparison to pixel-array detectors, SPH is becoming an attractive imaging modality at wavelengths where pixel-array detectors are not available or prohibitively expensive. Moreover, SPH is particularly advantageous when imaging through scattering media or in scarce illumination with compressive sensing. In the current practice of SPH, the throughput of the system is mainly limited by the phase-encoded illumination and the ways to realize phase stepping. In this work, we developed a high-through single-pixel compressive holography, achieving a space-bandwidth-time product (SBP-T) of 41,667 pixels/s. This result indicates that by using a single-pixel detector, information of holographic images containing up to 65,536 pixels can be collected within only 3 seconds. The high-throughput was realized by enabling phase stepping naturally in time and abandoning the need for phase-encoded illumination. We further show that compressive sensing can be conveniently adapted to significantly reduce the acquisition time. Besides being high throughput, we also show that this holographic system is scalable to provide either a large field of view (~83 mm2) or a high resolution (5.8 μm × 4.3 μm). In particular, high-resolution holographic images of a piece of rat tail were presented, exhibiting rich information of mussel, cortical bone, and cancellous bone. Given that microscopic images of biological tissue has rarely been explored in the current practice of SPH, we anticipate the developed high-throughput SPH is promising to nourish the development of multi-spectrum imaging by providing high-quality holographic images for biological tissues.

Influence of Data Acquisition Algorithms on X-Ray Phase Contrast Imaging Computed Tomography

X-ray phase contrast imaging (XPCI) is a nondestructive evaluation technique that enables high-contrast detection of low-attenuation materials that are largely transparent in traditional radiography. Extending a grating-based Talbot-Lau XPCI system to three-dimensional imaging with computed tomography (CT) imposes two motion requirements: the analyzer grating must translate transverse to the optical axis to capture image sets for XPCI reconstruction, and the sample must rotate to capture angular data for CT reconstruction. The acquisition algorithm choice determines the order of movement and positioning of the two stages. The choice of the image acquisition algorithm for XPCI CT is instrumental to collecting high fidelity data for reconstruction. We investigate how data acquisition influences XPCI CT by comparing two simple data acquisition algorithms and determine that capturing a full phase-stepping image set for a CT projection before rotating the sample results in higher quality data.