scholarly journals Super-Resolution Lensless Imaging of Cells Using Brownian Motion

2019 ◽  
Vol 9 (10) ◽  
pp. 2080
Author(s):  
Yuan Fang ◽  
Ningmei Yu ◽  
Yuquan Jiang
Keyword(s):  
Brownian Motion ◽  
Imaging System ◽  
Imaging Technique ◽  
Super Resolution ◽  
Image Sensor ◽  
Oxide Semiconductor ◽  
Objective Lens ◽  
Cell Detection ◽  
Lensless Imaging ◽  
Cell Image

The lensless imaging technique, which integrates a microscope into a complementary metal oxide semiconductor (CMOS) digital image sensor, has become increasingly important for the miniaturization of biological microscope and cell detection equipment. However, limited by the pixel size of the CMOS image sensor (CIS), the resolution of a cell image without optical amplification is low. This is also a key defect with the lensless imaging technique, which has been studied by a many scholars. In this manuscript, we propose a method to improve the resolution of the cell images using the Brownian motion of living cells in liquid. A two-step algorithm of motion estimation for image registration is proposed. Then, the raw holographic images are reconstructed using normalized convolution super-resolution algorithm. The result shows that the effect of the collected cell image under the lensless imaging system is close to the effect of a 10× objective lens.

scholarly journals Super Field-of-View Lensless Camera by Coded Image Sensors

Sensors ◽  
2019 ◽  
Vol 19 (6) ◽  
pp. 1329 ◽  
Author(s):  
Tomoya Nakamura ◽  
Keiichiro Kagawa ◽  
Shiho Torashima ◽  
Masahiro Yamaguchi
Keyword(s):  
Imaging System ◽  
Complementary Metal Oxide Semiconductor ◽  
Image Sensor ◽  
Image Sensors ◽  
Computational Imaging ◽  
Field Of View ◽  
Oxide Semiconductor ◽  
Back Side ◽  
Cmos Image Sensors ◽  
Rich Information

A lensless camera is an ultra-thin computational-imaging system. Existing lensless cameras are based on the axial arrangement of an image sensor and a coding mask, and therefore, the back side of the image sensor cannot be captured. In this paper, we propose a lensless camera with a novel design that can capture the front and back sides simultaneously. The proposed camera is composed of multiple coded image sensors, which are complementary-metal-oxide-semiconductor (CMOS) image sensors in which air holes are randomly made at some pixels by drilling processing. When the sensors are placed facing each other, the object-side sensor works as a coding mask and the other works as a sparsified image sensor. The captured image is a sparse coded image, which can be decoded computationally by using compressive sensing-based image reconstruction. We verified the feasibility of the proposed lensless camera by simulations and experiments. The proposed thin lensless camera realized super-field-of-view imaging without lenses or coding masks and therefore can be used for rich information sensing in confined spaces. This work also suggests a new direction in the design of CMOS image sensors in the era of computational imaging.

scholarly journals Super-resolution imaging system based on integrated microsphere objective lens

2020 ◽  
Vol 69 (13) ◽  
pp. 134201
Author(s):  
Yang Song ◽  
Xi-Bin Yang ◽  
Bing Yan ◽  
Chi Wang ◽  
Jian-Mei Sun ◽  
...  
Keyword(s):  
Imaging System ◽  
Super Resolution ◽  
Objective Lens ◽  
Resolution Imaging

scholarly journals A transparent waveguide chip for versatile total internal reflection fluorescence-based microscopy and nanoscopy

2021 ◽  
Vol 2 (1) ◽  
Author(s):  
Anish Priyadarshi ◽  
Firehun Tsige Dullo ◽  
Deanna Lynn Wolfson ◽  
Azeem Ahmad ◽  
Nikhil Jayakumar ◽  
...  
Keyword(s):  
Total Internal Reflection ◽  
Imaging Technique ◽  
Super Resolution ◽  
Complementary Metal Oxide Semiconductor ◽  
Internal Reflection ◽  
Total Internal Reflection Fluorescence ◽  
Oxide Semiconductor ◽  
Glass Coverslip ◽  
Sample Handling ◽  
Transparent Substrate

AbstractTotal internal reflection fluorescence (TIRF) microscopy is an imaging technique that, in comparison to confocal microscopy, does not require a trade-off between resolution, speed, and photodamage. Here, we introduce a waveguide platform for chip-based TIRF imaging based on a transparent substrate, which is fully compatible with sample handling and imaging procedures commonly used with a standard #1.5 glass coverslip. The platform is fabricated using standard complementary metal-oxide-semiconductor techniques which can easily be scaled up for mass production. We demonstrate its performance on synthetic and biological samples using both upright and inverted microscopes, and show how it can be extended to super-resolution applications, achieving a resolution of 116 nm using super resolution radial fluctuations. These transparent chips retain the scalable field of view of opaque chip-based TIRF and the high axial resolution of TIRF, and have the versatility to be used with many different objective lenses, microscopy methods, and handling techniques. We see this as a technology primed for widespread adoption, increasing both TIRF’s accessibility to users and the range of applications that can benefit from it.

scholarly journals In situ Observations of Porcine Ocular Surface Cells with Handheld 2K-pixel Microscope

2020 ◽  
Vol 14 (1) ◽  
pp. 66-69
Author(s):  
Tatsuya Mimura ◽  
Atsushi Mizota ◽  
Toshihiro Hayashi ◽  
Satoshi Nishimura
Keyword(s):  
Epithelial Cells ◽  
Ocular Surface ◽  
Imaging System ◽  
Single Cells ◽  
Numerical Aperture ◽  
Complementary Metal Oxide Semiconductor ◽  
Oxide Semiconductor ◽  
Objective Lens ◽  
Imaging Device

Introduction: To present our findings of the porcine ocular surface that were obtained with an ultra-compact hand-held microscope that weighs less than 500 g, we examined the corneal epithelial cells with this hand-held microscope. Methods: This device is equipped with an automatic focusing mechanism that enabled us to observe living cells in macro to micro magnifications with a series of operations. The focus is semi-automatically adjusted by the infrared and ultrasonic distance sensor. The instrument has a commercially-available microscope objective lens of 20x or 40x magnification and has a high-resolution 2K Complementary Metal-Oxide-Semiconductor (CMOS) camera. The theoretical spatial resolution is around 300 nm with a higher Numerical Aperture (high-NA) lenses. The widefield reflectance-based imaging system is equipped with three-color visible Light-Emitting Diodes (LEDs) for use in bright environments and an infrared LED for dark environments. Ten normal and two injured porcine corneas were examined with this hand-held microscope. Results: Our observations showed that the corneal and conjunctival epithelial cells could be continuously observed. The epithelial cells of the central cornea, limbus, and conjunctiva were clearly seen. The epithelial cells on the injured corneal surface were also easily and clearly observed. Conclusion: This hand-held microscopic imaging device allows medical health care workers such as ophthalmologists and endoscopists to obtain real-time in vivo optical biopsies without collecting tissues and cells. Our system enables us to observe single cells in the superficial layers without any fluorescein or other dyes.

scholarly journals DENOISING ALGORITHM FOR THE PIXEL-RESPONSE NON-UNIFORMITY CORRECTION OF A SCIENTIFIC CMOS UNDER LOW LIGHT CONDITIONS

2016 ◽  
Vol XLI-B3 ◽  
pp. 749-753 ◽  
Author(s):  
Changmiao Hu ◽  
Yang Bai ◽  
Ping Tang
Keyword(s):  
Imaging System ◽  
Complementary Metal Oxide Semiconductor ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Oxide Semiconductor ◽  
Integrating Sphere ◽  
Light Conditions ◽  
Low Light ◽  
Spatial Uniformity ◽  
High Level

We present a denoising algorithm for the pixel-response non-uniformity correction of a scientific complementary metal–oxide–semiconductor (CMOS) image sensor, which captures images under extremely low-light conditions. By analyzing the integrating sphere experimental data, we present a pixel-by-pixel flat-field denoising algorithm to remove this fixed pattern noise, which occur in low-light conditions and high pixel response readouts. The response of the CMOS image sensor imaging system to the uniform radiance field shows a high level of spatial uniformity after the denoising algorithm has been applied.

scholarly journals DENOISING ALGORITHM FOR THE PIXEL-RESPONSE NON-UNIFORMITY CORRECTION OF A SCIENTIFIC CMOS UNDER LOW LIGHT CONDITIONS

2016 ◽  
Vol XLI-B3 ◽  
pp. 749-753
Author(s):  
Changmiao Hu ◽  
Yang Bai ◽  
Ping Tang
Keyword(s):  
Imaging System ◽  
Complementary Metal Oxide Semiconductor ◽  
Cmos Image Sensor ◽  
Image Sensor ◽  
Oxide Semiconductor ◽  
Integrating Sphere ◽  
Light Conditions ◽  
Low Light ◽  
Spatial Uniformity ◽  
High Level

We present a denoising algorithm for the pixel-response non-uniformity correction of a scientific complementary metal–oxide–semiconductor (CMOS) image sensor, which captures images under extremely low-light conditions. By analyzing the integrating sphere experimental data, we present a pixel-by-pixel flat-field denoising algorithm to remove this fixed pattern noise, which occur in low-light conditions and high pixel response readouts. The response of the CMOS image sensor imaging system to the uniform radiance field shows a high level of spatial uniformity after the denoising algorithm has been applied.

Elliptocyte detection technology based on super-resolution algorithms for a lensless imaging system

2020 ◽  
Vol 32 (2) ◽  
pp. 025701
Author(s):  
Jianwei Li ◽  
Li Dai ◽  
Ningmei Yu ◽  
Zhengpeng Li ◽  
Shuaijun Li
Keyword(s):  
Imaging System ◽  
Super Resolution ◽  
Lensless Imaging ◽  
Detection Technology

scholarly journals A Sensor Image Super-Resolution via Advanced Generative Adversarial Network

2018 ◽  
Author(s):  
Shiping Wang ◽  
Linyuan He ◽  
Duyan Bi ◽  
Chen Wang
Keyword(s):  
Weather Condition ◽  
Super Resolution ◽  
Image Sensor ◽  
Oxide Semiconductor ◽  
Learning Ability ◽  
Generative Adversarial Networks ◽  
Great Success ◽  
Adversarial Networks ◽  
Wide Range ◽  
Cmos Sensor

Complementary Metal-Oxide-Semiconductor (CMOS) is a typical image sensor that has a wide range of applications. However, considering the limitations of the weather condition and hardware cost, it is hard to capture high-resolution images by CMOS sensor. Recently, Super-Resolution (SR) techniques for image restoration has been gaining attentions due to its excellent performance. Under the powerful learning ability, Generative Adversarial Networks (GANs) have been proved to achieve great success. In this paper, we propose the Advanced Generative Adversarial Networks (AGAN) to efficiently correct these issues; 1) we design a Laplacian pyramid framework as pre-trained module, which is beneficial to provide multi-scale features for our input. 2) at each feature block, a convolutional skip-connections network, which may contain some latent information, is significant for generative model to reconstruct a plausible-looking image; 3) considering that edge details usually play an important role in image generation, a novel perceptual loss function is defined to train and seek optimal parameters. It is effective to achieve excellent and compelling quality captured by CMOS sensor. Quantitative and qualitative evaluations have been demonstrated that our algorithm not only fully takes advantage of Convolutional Neural Networks (CNNs) to improve the image quality, but also performs better than previous GAN algorithms for super-resolution task.

scholarly journals Super Field-of-View Lensless Camera by Coded Image Sensors

2019 ◽  
Author(s):  
Tomoya Nakamura ◽  
Keiichiro Kagawa ◽  
Shiho Torashima ◽  
Masahiro Yamaguchi
Keyword(s):  
Imaging System ◽  
Complementary Metal Oxide Semiconductor ◽  
Image Sensor ◽  
Image Sensors ◽  
Computational Imaging ◽  
Field Of View ◽  
Oxide Semiconductor ◽  
Back Side ◽  
Cmos Image Sensors ◽  
Rich Information

A lensless camera is an ultra-thin computational-imaging system. Existing lensless cameras are based on the axial arrangement of an image sensor and a coding mask, and therefore, the back side of the image sensor cannot be captured. In this paper, we propose a lensless camera with a novel design that can capture the front and back sides simultaneously. The proposed camera is composed of multiple coded image sensors, which are complementary-metal-oxide-semiconductor~(CMOS) image sensors in which air holes are randomly made at some pixels by drilling processing. When the sensors are placed facing each other, the object-side sensor works as a coding mask and the other works as a sparsified image sensor. The captured image is a sparse coded image, which can be decoded computationally by using compressive-sensing-based image reconstruction. We verified the feasibility of the proposed lensless camera by simulations and experiments. The proposed thin lensless camera realizes super field-of-view imaging without lenses or coding masks, and therefore can be used for rich information sensing in confined spaces. This work also suggests a new direction in the design of CMOS image sensors in the era of computational imaging.

New Aspects in the Design of Electron Optical Magnification Systems

1972 ◽  
Vol 30 ◽  
pp. 606-607
Author(s):  
Willem H.J. Andersen
Keyword(s):  
Electron Microscope ◽  
Imaging System ◽  
Chromatic Aberration ◽  
Research Tool ◽  
Energy Losses ◽  
Objective Lens ◽  
Theoretical Limit ◽  
Optical Magnification ◽  
Chromatic Aberrations ◽  
High Degree

Electron microscope design, and particularly the design of the imaging system, has reached a high degree of perfection. Present objective lenses perform up to their theoretical limit, while the whole imaging system, consisting of three or four lenses, provides very wide ranges of magnification and diffraction camera length with virtually no distortion of the image. Evolution of the electron microscope in to a routine research tool in which objects of steadily increasing thickness are investigated, has made it necessary for the designer to pay special attention to the chromatic aberrations of the magnification system (as distinct from the chromatic aberration of the objective lens). These chromatic aberrations cause edge un-sharpness of the image due to electrons which have suffered energy losses in the object.There exist two kinds of chromatic aberration of the magnification system; the chromatic change of magnification, characterized by the coefficient Cm, and the chromatic change of rotation given by Cp.

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