Transport-of-intensity computational ghost imaging

Quantitative Phase Imaging: Recent Advances and Expanding Potential in Biomedicine

Quantitative phase imaging (QPI) is a label-free, wide-field microscopy approach with significant opportunities for biomedical applications. QPI uses the natural phase shift of light as it passes through a transparent object, such as a mammalian cell, to quantify biomass distribution and spatial and temporal changes in biomass. Reported in cell studies more than 60 years ago, ongoing advances in QPI hardware and software are leading to numerous applications in biology, with a dramatic expansion in utility over the past two decades. Today, investigations of cell size, morphology, behavior, cellular viscoelasticity, drug efficacy, biomass accumulation and turnover, and transport mechanics are supporting studies of development, physiology, neural activity, cancer, and additional physiological processes and diseases. Here, we review the field of QPI in biology starting with underlying principles, followed by a discussion of technical approaches currently available or being developed, and end with an examination of the breadth of applications in use or under development. We comment on strengths and shortcomings for the deployment of QPI in key biomedical contexts and conclude with emerging challenges and opportunities based on combining QPI with other methodologies that expand the scope and utility of QPI even further.

Compressive phase object classification using single-pixel digital holography

A single-pixel camera (SPC) is a computational imaging system that obtains compressed signals of a target scene using a single-pixel detector. The compressed signals can be directly used for image classification, thereby bypassing image reconstruction, which is computationally intensive and requires a high measurement rate. Here, we extend this direct inference to phase object classification using single-pixel digital holography (SPDH). Our method obtains compressed measurements of target complex amplitudes using SPDH and trains a classifier using those measurements for phase object classification. Furthermore, we present a joint optimization of the sampling patterns used in SPDH and a classifier to improve classification accuracy. The proposed method successfully classified phase object images of handwritten digits from the MNIST database, which is challenging for SPCs that can only capture intensity images.

Common-path off-axis single-pixel holographic imaging

Common-path off-axis single-pixel holographic imaging (COSHI) is proposed to obtain complex amplitude information using an in-line interferometer and a single-pixel (point-like) detector. COSHI is more robust to disturbances such as vibration than the conventional single-pixel digital holography technique because of its common-path configuration. In addition, the number of measurements can be reduced due to COSHI's reconstruction process based on the Fourier fringe analysis. In COSHI, an off-axis digital hologram can be obtained using the structured patterns composed of Hadamard basis patterns and stationary tilted phase distribution. Interestingly, COSHI's space bandwidth is larger than of the conventional off-axis digital holography because COSHI does not reconstruct the self-correlation term of an object. The proposed method is theoretically confirmed and numerical and experimental results show its feasibility.

Roadmap on digital holography [Invited]

This Roadmap article on digital holography provides an overview of a vast array of research activities in the field of digital holography. The paper consists of a series of 25 sections from the prominent experts in digital holography presenting various aspects of the field on sensing, 3D imaging and displays, virtual and augmented reality, microscopy, cell identification, tomography, label-free live cell imaging, and other applications. Each section represents the vision of its author to describe the significant progress, potential impact, important developments, and challenging issues in the field of digital holography.

Single-shot higher-order transport-of-intensity quantitative phase imaging using deep learning

Single-shot higher-order transport-of-intensity quantitative phase imaging (SHOT-QPI) is proposed to realize simple, in-line, scanless, and single-shot QPI. However, the light-use efficiency of SHOT-QPI is low because of the use of an amplitude-type computer-generated hologram (CGH). Although a phase-type CGH overcomes the problem, the accuracy of the measured phase is degraded owing to distortion of the defocused intensity distributions, which is caused by a quantization error of the CGH. Alternative SHOT-QPI with the help of deep learning, termed Deep-SHOT, is proposed to solve a nonlinear problem between the distorted intensities and the phase. In Deep-SHOT, a neural network learns the relationship between a series of distorted intensity distributions and the ground truth phase distribution. Because the distortion of intensity distributions is intrinsic to an optical system, the neural network is optimized for the system, and the proposed method improves the accuracy of the measured phase. The results of a proof-of-principle experiment indicate that the use of multiple defocused intensities also improves accuracy, even the nonlinear problem.

Phase and amplitude reconstruction in single-pixel transmission microscopy: a comparison of Hadamard, cosine, and noiselet bases

Hadamard, cosine, and noiselet bases are implemented into a digital holographic microscope based on single-pixel imaging with the capability to retrieve images of complex objects. The object is illuminated with coherent light modulated with different patterns deployed in a digital micromirror device, and the resulting fields are captured by single-pixel detection. For amplitude images, the experimental results of the three bases are evaluated with the peak SNR criteria. It is shown that the cosine basis recovers amplitude distributions with the best quality. Regarding phase images, the recovered ones compare well with those obtained with a CMOS camera.

Pupil-modulation ghost phase imaging

Computational ghost imaging (CGI) allows us to reconstruct images under a low signal-to-noise-ratio condition. However, CGI cannot retrieve phase information; it is unsuitable for observation of transparent objects such as living cells. A phase imaging method with CGI architecture is proposed. The proposed method realizes phase imaging with a simple optical setup by introducing pupil modulation differential phase contrast (PMDPC) to CGI. In PMDPC, phase information can be obtained from intensity distributions, which have phase gradient information, and its optical setup is similar to that of CGI. Therefore, the two methods are highly compatible, and the introduction of PMDPC to CGI can be easily achieved. Numerical simulation and an optical experiment demonstrated the feasibility of the proposed method.

Single-shot higher-order transport-of-intensity quantitative phase imaging based on computer-generated holography

The imaging quality of quantitative phase imaging (QPI) based on the transport of intensity equation (TIE) can be improved using a higher-order approximation for defocused intensity distributions. However, this requires mechanically scanning an image sensor or object along the optical axis, which in turn requires a precisely aligned optical setup. To overcome this problem, a computer-generated hologram (CGH) technique is introduced to TIE-based QPI. A CGH generating defocused point spread function is inserted in the Fourier plane of an object. The CGH acts as a lens and grating with various focal lengths and orientations, allowing multiple defocused intensity distributions to be simultaneously detected on an image sensor plane. The results of a numerical simulation and optical experiment demonstrated the feasibility of the proposed method.

Motionless optical scanning holography

Optical scanning holography (OSH) is an attractive technique since 3D information can be obtained with a single pixel detector. However, OSH requires an interferometer, scanning architecture, and a frequency shifter to scan a time-varying Fresnel zone plate (FZP), which makes the optical setup complicated. To reduce the complexity, the polarization sensitivity of a spatial light modulator (SLM) is applied. The proposed method implements a time-varying FZP with an in-line optical setup by using only an SLM. Observing results for a USAF pattern and a fluorescent bead reveals the feasibility of the new motionless holographic 3D imaging technique.

Deep ghost phase imaging

Deep-learning-based single-pixel phase imaging is proposed. The method, termed deep ghost phase imaging (DGPI), succeeds the advantages of computational ghost imaging, i.e., has the phase imaging quality with high signal-to-noise ratio derived from the Fellgett's multiplex advantage and the point-like detection of diffracted light from objects. A deep convolutional neural network is learned to output a desired phase distribution from an input of a defocused intensity distribution reconstructed by the single-pixel imaging theory. Compared to the conventional interferometric and transport-of-intensity approaches to single-pixel phase imaging, the DGPI requires neither additional intensity measurements nor explicit approximations. The effects of defocus distance and light level are investigated by numerical simulation and an optical experiment confirms the feasibility of the DGPI.

Transport-of-intensity phase imaging with polarization directed flat lenses

A phase imaging technique based on the transport of intensity equation with polarization directed flat lenses is demonstrated. Transport-of-intensity phase imaging enables one to obtain a phase distribution from through-focus intensity distributions by solving the transport of intensity equation. In general, the through-focus intensity distributions are obtained by mechanical scanning of an image sensor or target object. Therefore, a precise alignment of an optical system is required. To solve this issue, the introduction of polarization directed flat lenses is presented. In the proposed method, two intensity distributions at different depth positions on the optical axis are obtained without mechanical scanning by changing polarization states of incident light. The feasibility of the proposed method is confirmed by an optical experiment.

Computational ghost imaging with designed low spatial frequency masks

Minimally invasive imaging using weak illumination is required in the biomedical field. Computational ghost imaging (CGI) achieves imaging under illumination. However, CGI requires a large number of measurements to obtain an image. The number of measurements increases as illumination weakens. In this paper, decreasing the number of measurements of CGI with designed low spatial frequency masks is proposed. The proposed method allows us to image an object with a smaller number of measurements than with the conventional method. Numerical simulations and experiments confirm the feasibility of the proposed method.