White light phase-shifting interference microscopy (WL-PSIM) is a prominent technique for high-resolution quantitative phase imaging (QPI) of industrial and biological specimens. However, multiple interferograms with accurate phase-shifts are essentially required in WL-PSIM for measuring the accurate phase of the object. Here, we present single-shot phase-shifting interferometric techniques for accurate phase measurement using filtered white light phase-shifting interference microscopy (F-WL-PSIM) and deep neural network (DNN). The methods are incorporated by training the DNN to generate 1) four phase-shifted frames and 2) direct phase from a single interferogram. The training of network is performed on two different samples i.e., optical waveguide and MG63 osteosarcoma cells. Further, performance of F-WL-PSIM+DNN framework is validated by comparing the phase map extracted from network generated and experimentally recorded interferograms. The current approach can further strengthen QPI techniques for high-resolution phase recovery using a single frame for different biomedical applications.
Université de Tunis El Manar（突尼斯埃尔马纳尔大学）；Faculté des Sciences de Tunis（突尼斯科学学院）
Cells segmentation shows rapid growth in biology. Indeed, using the classical segmentation methods only is not enough to segment this type of images. In this manuscript, we will present a new method of ribosomes segmentation. A pre-treatment phase will precedes the segmentation process and after that a post-processing will proceed.
High-content biological microscopy targets high-resolution imaging across large fields-of-view (FOVs). Recent works have demonstrated that computational imaging can provide efficient solutions for high-content microscopy. Here, we use speckle structured illumination microscopy (SIM) as a robust and cost-effective solution for high-content fluorescence microscopy with simultaneous high-content quantitative phase (QP). This multi-modal compatibility is essential for studies requiring cross-correlative biological analysis. Our method uses laterally-translated Scotch tape to generate high-resoluti…
Confocal and multiphoton microscopy are effective techniques to obtain high-contrast images of 2-D sections within bulk tissue. However, scattering limits their application to depths only up to ~1 millimeter. Multimode fibers make excellent ultrathin endoscopes that can penetrate deep inside the tissue with minimal damage. Here, we present Multiview Scattering Scanning Imaging Confocal (MUSSIC) Microscopy that enables high signal-to-noise ratio (SNR) imaging through a multimode fiber, hence combining the optical sectioning and resolution gain of confocal microscopy with the minimally invasive …
A low cost remote imaging platform for biological applications was developed. The "Picroscope" is a device that allows the user to perform longitudinal imaging studies on multi-well cell culture plates. Here we present the network architecture and software used to facilitate communication between modules within the device as well as external cloud services. A web based console was created to control the device and view experiment results. Post processing tools were developed to analyze captured data in the cloud. The result is a platform for controlling biological experiments from outside the …
Institute of Biophysics, Chinese Academy of Sciences（中国科学院生物物理研究所）；College of Life Sciences, University of Chinese Academy of Sciences（中国科学院大学生命科学学院）；National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences（中国科学院自动化研究所模式识别国家重点实验室）
Super-resolution microscopy overcomes the diffraction limit of conventional light microscopy in spatial resolution. By providing novel spatial or spatio-temporal information on biological processes at nanometer resolution with molecular specificity, it plays an increasingly important role in life sciences. However, its technical limitations require trade-offs to balance its spatial resolution, temporal resolution, and light exposure of samples. Recently, deep learning has achieved breakthrough performance in many image processing and computer vision tasks. It has also shown great promise in pu…
The most realistic information about the transparent sample such as a live cell can be obtained only using bright-field light microscopy. At high-intensity pulsing LED illumination, we captured a primary 12-bit-per-channel (bpc) response from an observed sample using a bright-field microscope equipped with a high-resolution (4872x3248) image sensor. In order to suppress data distortions originating from the light interactions with elements in the optical path, poor sensor reproduction (geometrical defects of the camera sensor and some peculiarities of sensor sensitivity), we propose a spectros…
The high-content image-based assay is commonly leveraged for identifying the phenotypic impact of genetic perturbations in biology field. However, a persistent issue remains unsolved during experiments: the interferential technical noise caused by systematic errors (e.g., temperature, reagent concentration, and well location) is always mixed up with the real biological signals, leading to misinterpretation of any conclusion drawn. Here, we show a mean teacher based deep learning model (DeepNoise) that can disentangle biological signals from the experimental noise. Specifically, we aim to class…
Reflection phase imaging provides label-free, high-resolution characterization of biological samples, typically using interferometric-based techniques. Here, we investigate reflection phase microscopy from intensity-only measurements under diverse illumination. We evaluate the forward and inverse scattering model based on the first Born approximation for imaging scattering objects above a glass slide. Under this design, the measured field combines linear forward-scattering and height-dependent nonlinear back-scattering from the object that complicates object phase recovery. Using only the forw…
Colocalization is a powerful tool to study the interactions between fluorescently labeled molecules in biological fluorescence microscopy. However, existing techniques for colocalization analysis have not undergone continued development especially in regards to robust statistical support. In this paper, we examine two of the most popular quantification techniques for colocalization and argue that they could be improved upon using ideas from nonparametric statistics and scan statistics. In particular, we propose a new colocalization metric that is robust, easily implementable, and optimal in a …
Fluorescence microscopy has become a widely used tool for studying various biological structures of in vivo tissue or cells. However, quantitative analysis of these biological structures remains a challenge due to their complexity which is exacerbated by distortions caused by lens aberrations and light scattering. Moreover, manual quantification of such image volumes is an intractable and error-prone process, making the need for automated image analysis methods crucial. This paper describes a segmentation method for tubular structures in fluorescence microscopy images using convolutional neura…
In this paper, we review spatial light interference microscopy (SLIM), a common-path, phase-shifting interferometer, built onto a phase-contrast microscope, with white-light illumination. As one of the most sensitive quantitative phase imaging (QPI) methods, SLIM allows for speckle-free phase reconstruction with sub-nanometer path-length stability. We first review image formation in QPI, scattering, holography, and microcopy. Then, we outline SLIM imaging from theory to instrumentation. Zernike phase-contrast microscopy, phase retrieval in SLIM, and halo removal algorithms are discussed. Next,…
Fourier ptychographic microscopy allows for the collection of images with a high space-bandwidth product at the cost of temporal resolution. In Fourier ptychographic microscopy, the light source of a conventional widefield microscope is replaced with a light-emitting diode (LED) matrix, and multiple images are collected with different LED illumination patterns. From these images, a higher-resolution image can be computationally reconstructed without sacrificing field-of-view. We use deep learning to achieve single-shot imaging without sacrificing the space-bandwidth product, reducing the acqui…
Histological visualizations are critical to clinical disease management and are fundamental to biological understanding. However, current approaches that rely on bright-field microscopy require extensive tissue preparation prior to imaging. These processes are labor intensive and contribute to delays in clinical feedback that can extend to two to three weeks for standard paraffin-embedded tissue preparation and interpretation. Here, we present a label-free reflection-mode imaging modality that reveals cellular-scale morphology by detecting intrinsic endogenous contrast. We accomplish this with…
3D fluorescence microscopy of living organisms has increasingly become an essential and powerful tool in biomedical research and diagnosis. An exploding amount of imaging data has been collected, whereas efficient and effective computational tools to extract information from them are still lagging behind. This is largely due to the challenges in analyzing biological data. Interesting biological structures are not only small, but are often morphologically irregular and highly dynamic. Although tracking cells in live organisms has been studied for years, existing tracking methods for cells are n…
Compressed sensing fluorescence microscopy (CS-FM) proposes a scheme whereby less measurements are collected during sensing and reconstruction is performed to recover the image. Much work has gone into optimizing the sensing and reconstruction portions separately. We propose a method of jointly optimizing both sensing and reconstruction end-to-end under a total measurement constraint, enabling learning of the optimal sensing scheme concurrently with the parameters of a neural network-based reconstruction network. We train our model on a rich dataset of confocal, two-photon, and wide-field micr…
Single molecule localization microscopy is widely used in biological research for measuring the nanostructures of samples smaller than the diffraction limit. This study uses multifocal plane microscopy and addresses the 3D single molecule localization problem, where lateral and axial locations of molecules are estimated. However, when we multifocal plane microscopy is used, the estimation accuracy of 3D localization is easily deteriorated by the small lateral drifts of camera positions. We formulate a 3D molecule localization problem along with the estimation of the lateral drifts as a compres…
Denoising diffusion models for high-resolution microscopy image restoration
Frankfurt Institute for Advanced Studies (FIAS)（法兰克福高级研究所）；Goethe University Frankfurt（法兰克福大学）；Institute of Physical and Theoretical Chemistry（物理与理论化学研究所）
Self-Supervised Z-Slice Augmentation for 3D Bio-Imaging via Knowledge Distillation
Collège de France（法兰西学院）；Université PSL（巴黎文理研究大学）；Université Grenoble-Alpes（格勒诺布尔-阿尔卑斯大学）；Sorbonne University（索邦大学）；National Institutes of Health（美国国立卫生研究院）；Hospices Civils de Lyon（里昂公立医院）；Claude Bernard Lyon 1 University（里昂第一大学克洛德·贝尔纳）
California Institute of Technology（加州理工学院）；Brazilian Synchrotron Light Laboratory (LNLS)（巴西同步辐射光实验室（LNLS））；Brazilian Center for Research in Energy and Materials (CNPEM)（巴西能源与材料研究中心（CNPEM））
Current in vivo microscopy allows us detailed spatiotemporal imaging (3D+t) of complete organisms and offers insights into their development on the cellular level. Even though the imaging speed and quality is steadily improving, fully-automated segmentation and analysis methods are often not accurate enough. This is particularly true while imaging large samples (100um - 1mm) and deep inside the specimen. Drosophila embryogenesis, widely used as a developmental paradigm, presents an example for such a challenge, especially where cell outlines need to imaged - a general challenge in other system…
