Iterative Phase Recovery Research Articles

A Single-Shot Scattering Medium Imaging Method via Bispectrum Truncation.

Imaging using scattering media is a very important yet challenging technology. As one of the most widely used scattering imaging methods, speckle autocorrelation technology has important applications in several fields. However, traditional speckle autocorrelation imaging methods usually use iterative phase recovery algorithms to obtain the Fourier phase of hidden objects, posing issues such as large data calculation volumes and uncertain reconstruction results. Here, we propose a single-shot scattering imaging method based on the bispectrum truncation method. The bispectrum analysis is utilized for hidden object phase recovery, the truncation method is used to avoid the computation of redundant data when calculating the bispectrum data, and the method is experimentally verified. The experimental results show that our method does not require uncertain iterative calculations and can reduce the bispectrum data computation by more than 80% by adjusting the truncation factor without damaging the imaging quality, which greatly improves imaging efficiency. This method paves the way for rapid imaging through scattering media and brings benefits for imaging in dynamic situations.

Physics constrained unsupervised deep learning for rapid, high resolution scanning coherent diffraction reconstruction

By circumventing the resolution limitations of optics, coherent diffractive imaging (CDI) and ptychography are making their way into scientific fields ranging from X-ray imaging to astronomy. Yet, the need for time consuming iterative phase recovery hampers real-time imaging. While supervised deep learning strategies have increased reconstruction speed, they sacrifice image quality. Furthermore, these methods’ demand for extensive labeled training data is experimentally burdensome. Here, we propose an unsupervised physics-informed neural network reconstruction method, PtychoPINN, that retains the factor of 100-to-1000 speedup of deep learning-based reconstruction while improving reconstruction quality by combining the diffraction forward map with real-space constraints from overlapping measurements. In particular, PtychoPINN gains a factor of 4 in linear resolution and an 8 dB improvement in PSNR while also accruing improvements in generalizability and robustness. This blend of performance and computational efficiency offers exciting prospects for high-resolution real-time imaging in high-throughput environments such as X-ray free electron lasers (XFELs) and diffraction-limited light sources.

Fast Fourier ptychographic quantitative phase microscopy for in vitro label-free imaging.

Quantitative phase microscopy (QPM) is indispensable in biomedical research due to its advantages in unlabeled transparent sample thickness quantification and obtaining refractive index information. Fourier ptychographic microscopy (FPM) is among the most promising QPM methods, incorporating multi-angle illumination and iterative phase recovery for high-resolution quantitative phase imaging (QPI) of large cell populations over a wide field of-view (FOV) in a single pass. However, FPM is limited by data redundancy and sequential acquisition strategies, resulting in low imaging efficiency, which in turn limits its real-time application in in vitro label-free imaging. Here, we report a fast QPM based on Fourier ptychography (FQP-FPM), which uses an optimized annular downsampling and parallel acquisition strategy to minimize the amount of data required in the front end and reduce the iteration time of the back-end algorithm (3.3% and 4.4% of conventional FPM, respectively). Theoretical and data redundancy analyses show that FQP-FPM can realize high-throughput quantitative phase reconstruction at thrice the resolution of the coherent diffraction limit by acquiring only ten raw images, providing a precondition for in vitro label-free real-time imaging. The FQP-FPM application was validated for various in vitro label-free live-cell imaging. Cell morphology and subcellular phenomena in different periods were observed with a synthetic aperture of 0.75 NA at a 10× FOV, demonstrating its advantages and application potential for fast high-throughput QPI.

Fourier Ptychographic Microscopy Reconstruction Method Based on Residual Transfer Networks

Fourier ptychographic microscopy reconstruction mostly adopts the traditional alternating iterative phase recovery method and optimization method, which has high computational complexity, high redundancy of image acquisition data, low reconstruction quality and high time consumption. In this paper, the model of residual transfer networks based on Resnet152 is proposed for Fourier ptychographic microscopy reconstruction, the learning process of deep convolution neural network is introduced, and the image reconstruction method based on deep learning realizes the end-to-end reconstruction of low-resolution images to high-resolution images. Through comparative experiments and analysis, the residual network can overcome the gradient explosion, make the feature information more complete and efficient, and the incremental up-sampling reconstruction network has higher image quality, lower computational complexity and shorter running time.

Compact, low-cost Blu-Ray pickup-based digital holographic microscope

The concept of point-of-care testing is an active area of research. The trend nowadays is to develop cost-effective yet efficient units that can be used at home by non-professionals. Digital holography is an optical technique of great interest as it provides quantitative phase images from a single recorded image. However, the available setups either employ the in-line lensless configuration (which involve an iterative phase recovery process) or the complex, bulky and expensive classical Mach-Zehnder configuration. Self-referencing digital holographic systems are ideal as only few components are needed. Blu-Ray pickup heads contain a high quality objective lens and a laser diode which have been used in the past in optical microscopy. However, it has been rarely uses in digital holography. In this paper, we present for the first time a low-cost self-referencing digital holography microscope in a transmission configuration using a Blu-Ray pickup coupled with a Raspberry-Pi computer, making the whole setup very compact. A low-cost 2D motorized translation stage is developed using the mechanical components found in the Blu-Ray drive. A Graphical User Interface (GUI) written in Python allows the user to control the hardware components and to reconstruct the holograms from which continuous phase images are extracted. The interferometer is successfully tested on microspheres and red blood cells after estimating the magnification of the microscope using a USAF target.

High-Precision Lensless Microscope on a Chip Based on In-Line Holographic Imaging.

The lensless on-chip microscope is an emerging technology in the recent decade that can realize the imaging and analysis of biological samples with a wide field-of-view without huge optical devices and any lenses. Because of its small size, low cost, and being easy to hold and operate, it can be used as an alternative tool for large microscopes in resource-poor or remote areas, which is of great significance for the diagnosis, treatment, and prevention of diseases. To improve the low-resolution characteristics of the existing lensless shadow imaging systems and to meet the high-resolution needs of point-of-care testing, here, we propose a high-precision on-chip microscope based on in-line holographic technology. We demonstrated the ability of the iterative phase recovery algorithm to recover sample information and evaluated it with image quality evaluation algorithms with or without reference. The results showed that the resolution of the holographic image after iterative phase recovery is 1.41 times that of traditional shadow imaging. Moreover, we used machine learning tools to identify and count the mixed samples of mouse ascites tumor cells and micro-particles that were iterative phase recovered. The results showed that the on-chip cell counter had high-precision counting characteristics as compared with manual counting of the microscope reference image. Therefore, the proposed high-precision lensless microscope on a chip based on in-line holographic imaging provides one promising solution for future point-of-care testing (POCT).

Multi-plane phase retrieval methods to recover free- aberrations object complex field via SLM

This paper explains two iterative phase recovery methods where the goal of each one is different. The Phase Diversity method is used to recover the wavefront aberrations in optical incoherent imaging systems when an extended object is illuminated. The purpose of the Multi-plane Phase Retrieval method is recovering the object complex field seen from the image plane, therefore the object has to be illuminated with coherent light. Both methods are simultaneously used to pick out the aberrations and free aberrations object phase. The use of both methods is proposed as a methodology for the integration of optical instruments.

Lensless Imaging and Sensing

High-resolution optical microscopy has traditionally relied on high-magnification and high-numerical aperture objective lenses. In contrast, lensless microscopy can provide high-resolution images without the use of any focusing lenses, offering the advantages of a large field of view, high resolution, cost-effectiveness, portability, and depth-resolved three-dimensional (3D) imaging. Here we review various approaches to lensless imaging, as well as its applications in biosensing, diagnostics, and cytometry. These approaches include shadow imaging, fluorescence, holography, superresolution 3D imaging, iterative phase recovery, and color imaging. These approaches share a reliance on computational techniques, which are typically necessary to reconstruct meaningful images from the raw data captured by digital image sensors. When these approaches are combined with physical innovations in sample preparation and fabrication, lensless imaging can be used to image and sense cells, viruses, nanoparticles, and biomolecules. We conclude by discussing several ways in which lensless imaging and sensing might develop in the near future.

Field-portable wide-field microscopy of dense samples using multi-height pixel super-resolution based lensfree imaging

We report a field-portable lensfree microscope that can image dense and connected specimens with sub-micron resolution over a large field-of-view of ~30 mm(2) (i.e., ~6.4 mm × ~4.6 mm) using pixel super-resolution and iterative phase recovery techniques. Weighing ~122 grams with dimensions of 4 cm × 4 cm × 15 cm, this microscope records lensfree in-line holograms of specimens onto an opto-electronic sensor-array using partially coherent illumination. To reconstruct the phase and amplitude images of dense samples (with >0.3 billion pixels in each image, i.e., >0.6 billion pixels total), we employ a multi-height imaging approach, where by using a mechanical interface the sensor-to-sample distance is dynamically changed by random discrete steps of e.g., ~10 to 80 μm. By digitally propagating back and forth between these multi-height super-resolved holograms (corresponding to typically 2-5 planes), phase and amplitude images of dense samples can be recovered without the need for any spatial masks or filtering. We demonstrate the performance of this field-portable multi-height lensfree microscope by imaging Papanicolaou smears (also known as Pap tests). Our results reveal the promising potential of this multi-height lensfree computational microscopy platform for e.g., pathology needs in resource limited settings.

Performance Analysis of Reconstruction Techniques for Frequency-Domain Optical-Coherence Tomography

We address the issue of noise robustness of reconstruction techniques for frequency-domain optical-coherence tomography (FDOCT). We consider three reconstruction techniques: Fourier, iterative phase recovery, and cepstral techniques. We characterize the reconstructions in terms of their statistical bias and variance and obtain approximate analytical expressions under the assumption of small noise. We also perform Monte Carlo analyses and show that the experimental results are in agreement with the theoretical predictions. It turns out that the iterative and cepstral techniques yield reconstructions with a smaller bias than the Fourier method. The three techniques, however, have identical variance profiles, and their consistency increases linearly as a function of the signal-to-noise ratio.

Iterative phase recovery using wavelet domain constraints

Phase retrieval is a central problem in coherent x-ray diffraction microscopy. Various methods have been proposed to solve the problem with the most successful being iterative methods with a finite spatial support constraint. In this work, a new constraint is formulated in the wavelet domain using low-resolution a priori information. Experimental results indicate that the constraint is sufficient to reconstruct an object from Fourier modulus measurements.