Multiframe super resolution reconstruction method based on light field angular images

NASA Astrophysics Data System (ADS)

Zhou, Shubo; Yuan, Yan; Su, Lijuan; Ding, Xiaomin; Wang, Jichao

2017-12-01

The plenoptic camera can directly obtain 4-dimensional light field information from a 2-dimensional sensor. However, based on the sampling theorem, the spatial resolution is greatly limited by the microlenses. In this paper, we present a method of reconstructing high-resolution images from the angular images. First, the ray tracing method is used to model the telecentric-based light field imaging process. Then, we analyze the subpixel shifts between the angular images extracted from the defocused light field data and the blur in the angular images. According to the analysis above, we construct the observation model from the ideal high-resolution image to the angular images. Applying the regularized super resolution method, we can obtain the super resolution result with a magnification ratio of 8. The results demonstrate the effectiveness of the proposed observation model.

Super-resolution imaging applied to moving object tracking

NASA Astrophysics Data System (ADS)

Swalaganata, Galandaru; Ratna Sulistyaningrum, Dwi; Setiyono, Budi

2017-10-01

Moving object tracking in a video is a method used to detect and analyze changes that occur in an object that being observed. Visual quality and the precision of the tracked target are highly wished in modern tracking system. The fact that the tracked object does not always seem clear causes the tracking result less precise. The reasons are low quality video, system noise, small object, and other factors. In order to improve the precision of the tracked object especially for small object, we propose a two step solution that integrates a super-resolution technique into tracking approach. First step is super-resolution imaging applied into frame sequences. This step was done by cropping the frame in several frame or all of frame. Second step is tracking the result of super-resolution images. Super-resolution image is a technique to obtain high-resolution images from low-resolution images. In this research single frame super-resolution technique is proposed for tracking approach. Single frame super-resolution was a kind of super-resolution that it has the advantage of fast computation time. The method used for tracking is Camshift. The advantages of Camshift was simple calculation based on HSV color that use its histogram for some condition and color of the object varies. The computational complexity and large memory requirements required for the implementation of super-resolution and tracking were reduced and the precision of the tracked target was good. Experiment showed that integrate a super-resolution imaging into tracking technique can track the object precisely with various background, shape changes of the object, and in a good light conditions.

Single-shot and single-sensor high/super-resolution microwave imaging based on metasurface

PubMed Central

Wang, Libo; Li, Lianlin; Li, Yunbo; Zhang, Hao Chi; Cui, Tie Jun

2016-01-01

Real-time high-resolution (including super-resolution) imaging with low-cost hardware is a long sought-after goal in various imaging applications. Here, we propose broadband single-shot and single-sensor high-/super-resolution imaging by using a spatio-temporal dispersive metasurface and an imaging reconstruction algorithm. The metasurface with spatio-temporal dispersive property ensures the feasibility of the single-shot and single-sensor imager for super- and high-resolution imaging, since it can convert efficiently the detailed spatial information of the probed object into one-dimensional time- or frequency-dependent signal acquired by a single sensor fixed in the far-field region. The imaging quality can be improved by applying a feature-enhanced reconstruction algorithm in post-processing, and the desired imaging resolution is related to the distance between the object and metasurface. When the object is placed in the vicinity of the metasurface, the super-resolution imaging can be realized. The proposed imaging methodology provides a unique means to perform real-time data acquisition, high-/super-resolution images without employing expensive hardware (e.g. mechanical scanner, antenna array, etc.). We expect that this methodology could make potential breakthroughs in the areas of microwave, terahertz, optical, and even ultrasound imaging. PMID:27246668

Localization-based super-resolution imaging of cellular structures.

PubMed

Kanchanawong, Pakorn; Waterman, Clare M

2013-01-01

Fluorescence microscopy allows direct visualization of fluorescently tagged proteins within cells. However, the spatial resolution of conventional fluorescence microscopes is limited by diffraction to ~250 nm, prompting the development of super-resolution microscopy which offers resolution approaching the scale of single proteins, i.e., ~20 nm. Here, we describe protocols for single molecule localization-based super-resolution imaging, using focal adhesion proteins as an example and employing either photoswitchable fluorophores or photoactivatable fluorescent proteins. These protocols should also be easily adaptable to imaging a broad array of macromolecular assemblies in cells whose components can be fluorescently tagged and assemble into high density structures.

New learning based super-resolution: use of DWT and IGMRF prior.

PubMed

Gajjar, Prakash P; Joshi, Manjunath V

2010-05-01

In this paper, we propose a new learning-based approach for super-resolving an image captured at low spatial resolution. Given the low spatial resolution test image and a database consisting of low and high spatial resolution images, we obtain super-resolution for the test image. We first obtain an initial high-resolution (HR) estimate by learning the high-frequency details from the available database. A new discrete wavelet transform (DWT) based approach is proposed for learning that uses a set of low-resolution (LR) images and their corresponding HR versions. Since the super-resolution is an ill-posed problem, we obtain the final solution using a regularization framework. The LR image is modeled as the aliased and noisy version of the corresponding HR image, and the aliasing matrix entries are estimated using the test image and the initial HR estimate. The prior model for the super-resolved image is chosen as an Inhomogeneous Gaussian Markov random field (IGMRF) and the model parameters are estimated using the same initial HR estimate. A maximum a posteriori (MAP) estimation is used to arrive at the cost function which is minimized using a simple gradient descent approach. We demonstrate the effectiveness of the proposed approach by conducting the experiments on gray scale as well as on color images. The method is compared with the standard interpolation technique and also with existing learning-based approaches. The proposed approach can be used in applications such as wildlife sensor networks, remote surveillance where the memory, the transmission bandwidth, and the camera cost are the main constraints.

Super-resolution image reconstruction from UAS surveillance video through affine invariant interest point-based motion estimation

NASA Astrophysics Data System (ADS)

He, Qiang; Schultz, Richard R.; Wang, Yi; Camargo, Aldo; Martel, Florent

2008-01-01

In traditional super-resolution methods, researchers generally assume that accurate subpixel image registration parameters are given a priori. In reality, accurate image registration on a subpixel grid is the single most critically important step for the accuracy of super-resolution image reconstruction. In this paper, we introduce affine invariant features to improve subpixel image registration, which considerably reduces the number of mismatched points and hence makes traditional image registration more efficient and more accurate for super-resolution video enhancement. Affine invariant interest points include those corners that are invariant to affine transformations, including scale, rotation, and translation. They are extracted from the second moment matrix through the integration and differentiation covariance matrices. Our tests are based on two sets of real video captured by a small Unmanned Aircraft System (UAS) aircraft, which is highly susceptible to vibration from even light winds. The experimental results from real UAS surveillance video show that affine invariant interest points are more robust to perspective distortion and present more accurate matching than traditional Harris/SIFT corners. In our experiments on real video, all matching affine invariant interest points are found correctly. In addition, for the same super-resolution problem, we can use many fewer affine invariant points than Harris/SIFT corners to obtain good super-resolution results.

Single image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction.

PubMed

Yang, Qi; Zhang, Yanzhu; Zhao, Tiebiao; Chen, YangQuan

2017-04-04

Image super-resolution using self-optimizing mask via fractional-order gradient interpolation and reconstruction aims to recover detailed information from low-resolution images and reconstruct them into high-resolution images. Due to the limited amount of data and information retrieved from low-resolution images, it is difficult to restore clear, artifact-free images, while still preserving enough structure of the image such as the texture. This paper presents a new single image super-resolution method which is based on adaptive fractional-order gradient interpolation and reconstruction. The interpolated image gradient via optimal fractional-order gradient is first constructed according to the image similarity and afterwards the minimum energy function is employed to reconstruct the final high-resolution image. Fractional-order gradient based interpolation methods provide an additional degree of freedom which helps optimize the implementation quality due to the fact that an extra free parameter α-order is being used. The proposed method is able to produce a rich texture detail while still being able to maintain structural similarity even under large zoom conditions. Experimental results show that the proposed method performs better than current single image super-resolution techniques. Copyright © 2017 ISA. Published by Elsevier Ltd. All rights reserved.

Patch-Based Super-Resolution of MR Spectroscopic Images: Application to Multiple Sclerosis

PubMed Central

Jain, Saurabh; Sima, Diana M.; Sanaei Nezhad, Faezeh; Hangel, Gilbert; Bogner, Wolfgang; Williams, Stephen; Van Huffel, Sabine; Maes, Frederik; Smeets, Dirk

2017-01-01

Purpose: Magnetic resonance spectroscopic imaging (MRSI) provides complementary information to conventional magnetic resonance imaging. Acquiring high resolution MRSI is time consuming and requires complex reconstruction techniques. Methods: In this paper, a patch-based super-resolution method is presented to increase the spatial resolution of metabolite maps computed from MRSI. The proposed method uses high resolution anatomical MR images (T1-weighted and Fluid-attenuated inversion recovery) to regularize the super-resolution process. The accuracy of the method is validated against conventional interpolation techniques using a phantom, as well as simulated and in vivo acquired human brain images of multiple sclerosis subjects. Results: The method preserves tissue contrast and structural information, and matches well with the trend of acquired high resolution MRSI. Conclusions: These results suggest that the method has potential for clinically relevant neuroimaging applications. PMID:28197066

Super-resolution for asymmetric resolution of FIB-SEM 3D imaging using AI with deep learning.

PubMed

Hagita, Katsumi; Higuchi, Takeshi; Jinnai, Hiroshi

2018-04-12

Scanning electron microscopy equipped with a focused ion beam (FIB-SEM) is a promising three-dimensional (3D) imaging technique for nano- and meso-scale morphologies. In FIB-SEM, the specimen surface is stripped by an ion beam and imaged by an SEM installed orthogonally to the FIB. The lateral resolution is governed by the SEM, while the depth resolution, i.e., the FIB milling direction, is determined by the thickness of the stripped thin layer. In most cases, the lateral resolution is superior to the depth resolution; hence, asymmetric resolution is generated in the 3D image. Here, we propose a new approach based on an image-processing or deep-learning-based method for super-resolution of 3D images with such asymmetric resolution, so as to restore the depth resolution to achieve symmetric resolution. The deep-learning-based method learns from high-resolution sub-images obtained via SEM and recovers low-resolution sub-images parallel to the FIB milling direction. The 3D morphologies of polymeric nano-composites are used as test images, which are subjected to the deep-learning-based method as well as conventional methods. We find that the former yields superior restoration, particularly as the asymmetric resolution is increased. Our super-resolution approach for images having asymmetric resolution enables observation time reduction.

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network

PubMed Central

Qu, Xiaobo; He, Yifan

2018-01-01

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods. PMID:29509666

Single Image Super-Resolution Based on Multi-Scale Competitive Convolutional Neural Network.

PubMed

Du, Xiaofeng; Qu, Xiaobo; He, Yifan; Guo, Di

2018-03-06

Deep convolutional neural networks (CNNs) are successful in single-image super-resolution. Traditional CNNs are limited to exploit multi-scale contextual information for image reconstruction due to the fixed convolutional kernel in their building modules. To restore various scales of image details, we enhance the multi-scale inference capability of CNNs by introducing competition among multi-scale convolutional filters, and build up a shallow network under limited computational resources. The proposed network has the following two advantages: (1) the multi-scale convolutional kernel provides the multi-context for image super-resolution, and (2) the maximum competitive strategy adaptively chooses the optimal scale of information for image reconstruction. Our experimental results on image super-resolution show that the performance of the proposed network outperforms the state-of-the-art methods.

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution

PubMed Central

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-01-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images. PMID:29062159

Brain Atlas Fusion from High-Thickness Diagnostic Magnetic Resonance Images by Learning-Based Super-Resolution.

PubMed

Zhang, Jinpeng; Zhang, Lichi; Xiang, Lei; Shao, Yeqin; Wu, Guorong; Zhou, Xiaodong; Shen, Dinggang; Wang, Qian

2017-03-01

It is fundamentally important to fuse the brain atlas from magnetic resonance (MR) images for many imaging-based studies. Most existing works focus on fusing the atlases from high-quality MR images. However, for low-quality diagnostic images (i.e., with high inter-slice thickness), the problem of atlas fusion has not been addressed yet. In this paper, we intend to fuse the brain atlas from the high-thickness diagnostic MR images that are prevalent for clinical routines. The main idea of our works is to extend the conventional groupwise registration by incorporating a novel super-resolution strategy. The contribution of the proposed super-resolution framework is two-fold. First, each high-thickness subject image is reconstructed to be isotropic by the patch-based sparsity learning. Then, the reconstructed isotropic image is enhanced for better quality through the random-forest-based regression model. In this way, the images obtained by the super-resolution strategy can be fused together by applying the groupwise registration method to construct the required atlas. Our experiments have shown that the proposed framework can effectively solve the problem of atlas fusion from the low-quality brain MR images.

Super-resolution imaging based on the temperature-dependent electron-phonon collision frequency effect of metal thin films

NASA Astrophysics Data System (ADS)

Ding, Chenliang; Wei, Jingsong; Xiao, Mufei

2018-05-01

We herein propose a far-field super-resolution imaging with metal thin films based on the temperature-dependent electron-phonon collision frequency effect. In the proposed method, neither fluorescence labeling nor any special properties are required for the samples. The 100 nm lands and 200 nm grooves on the Blu-ray disk substrates were clearly resolved and imaged through a laser scanning microscope of wavelength 405 nm. The spot size was approximately 0.80 μm , and the imaging resolution of 1/8 of the laser spot size was experimentally obtained. This work can be applied to the far-field super-resolution imaging of samples with neither fluorescence labeling nor any special properties.

Super-resolution in a defocused plenoptic camera: a wave-optics-based approach.

PubMed

Sahin, Erdem; Katkovnik, Vladimir; Gotchev, Atanas

2016-03-01

Plenoptic cameras enable the capture of a light field with a single device. However, with traditional light field rendering procedures, they can provide only low-resolution two-dimensional images. Super-resolution is considered to overcome this drawback. In this study, we present a super-resolution method for the defocused plenoptic camera (Plenoptic 1.0), where the imaging system is modeled using wave optics principles and utilizing low-resolution depth information of the scene. We are particularly interested in super-resolution of in-focus and near in-focus scene regions, which constitute the most challenging cases. The simulation results show that the employed wave-optics model makes super-resolution possible for such regions as long as sufficiently accurate depth information is available.

Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

PubMed Central

Hu, Mao-Gui; Wang, Jin-Feng; Ge, Yong

2009-01-01

Satellite remote sensing (RS) is an important contributor to Earth observation, providing various kinds of imagery every day, but low spatial resolution remains a critical bottleneck in a lot of applications, restricting higher spatial resolution analysis (e.g., intra-urban). In this study, a multifractal-based super-resolution reconstruction method is proposed to alleviate this problem. The multifractal characteristic is common in Nature. The self-similarity or self-affinity presented in the image is useful to estimate details at larger and smaller scales than the original. We first look for the presence of multifractal characteristics in the images. Then we estimate parameters of the information transfer function and noise of the low resolution image. Finally, a noise-free, spatial resolution-enhanced image is generated by a fractal coding-based denoising and downscaling method. The empirical case shows that the reconstructed super-resolution image performs well in detail enhancement. This method is not only useful for remote sensing in investigating Earth, but also for other images with multifractal characteristics. PMID:22291530

Super resolution terahertz imaging by subpixel estimation: application to hyperspectral beam profiling

NASA Astrophysics Data System (ADS)

Logofătu, Petre C.; Damian, Victor

2018-05-01

A super-resolution terahertz imaging technique based on subpixel estimation was applied to hyperspectral beam profiling. The topic of hyperspectral beam profiling was chosen because the beam profile and its dependence on wavelength are not well known and are important for imaging applications. Super-resolution is required here to avoid diffraction effects and to provide a stronger signal. Super-resolution usually adds supplementary information to the measurement, but in this case, it is a prerequisite for it. We report that the beam profile is almost Gaussian for many frequencies; the waist of the Gaussian profile increases with frequency while the center wobbles slightly. Knowledge of the beam profile may subsequently be used as reference for imaging.

Single-image super-resolution based on Markov random field and contourlet transform

NASA Astrophysics Data System (ADS)

Wu, Wei; Liu, Zheng; Gueaieb, Wail; He, Xiaohai

2011-04-01

Learning-based methods are well adopted in image super-resolution. In this paper, we propose a new learning-based approach using contourlet transform and Markov random field. The proposed algorithm employs contourlet transform rather than the conventional wavelet to represent image features and takes into account the correlation between adjacent pixels or image patches through the Markov random field (MRF) model. The input low-resolution (LR) image is decomposed with the contourlet transform and fed to the MRF model together with the contourlet transform coefficients from the low- and high-resolution image pairs in the training set. The unknown high-frequency components/coefficients for the input low-resolution image are inferred by a belief propagation algorithm. Finally, the inverse contourlet transform converts the LR input and the inferred high-frequency coefficients into the super-resolved image. The effectiveness of the proposed method is demonstrated with the experiments on facial, vehicle plate, and real scene images. A better visual quality is achieved in terms of peak signal to noise ratio and the image structural similarity measurement.

A Microfluidic Platform for Correlative Live-Cell and Super-Resolution Microscopy

PubMed Central

Tam, Johnny; Cordier, Guillaume Alan; Bálint, Štefan; Sandoval Álvarez, Ángel; Borbely, Joseph Steven; Lakadamyali, Melike

2014-01-01

Recently, super-resolution microscopy methods such as stochastic optical reconstruction microscopy (STORM) have enabled visualization of subcellular structures below the optical resolution limit. Due to the poor temporal resolution, however, these methods have mostly been used to image fixed cells or dynamic processes that evolve on slow time-scales. In particular, fast dynamic processes and their relationship to the underlying ultrastructure or nanoscale protein organization cannot be discerned. To overcome this limitation, we have recently developed a correlative and sequential imaging method that combines live-cell and super-resolution microscopy. This approach adds dynamic background to ultrastructural images providing a new dimension to the interpretation of super-resolution data. However, currently, it suffers from the need to carry out tedious steps of sample preparation manually. To alleviate this problem, we implemented a simple and versatile microfluidic platform that streamlines the sample preparation steps in between live-cell and super-resolution imaging. The platform is based on a microfluidic chip with parallel, miniaturized imaging chambers and an automated fluid-injection device, which delivers a precise amount of a specified reagent to the selected imaging chamber at a specific time within the experiment. We demonstrate that this system can be used for live-cell imaging, automated fixation, and immunostaining of adherent mammalian cells in situ followed by STORM imaging. We further demonstrate an application by correlating mitochondrial dynamics, morphology, and nanoscale mitochondrial protein distribution in live and super-resolution images. PMID:25545548

Fast and efficient molecule detection in localization-based super-resolution microscopy by parallel adaptive histogram equalization.

PubMed

Li, Yiming; Ishitsuka, Yuji; Hedde, Per Niklas; Nienhaus, G Ulrich

2013-06-25

In localization-based super-resolution microscopy, individual fluorescent markers are stochastically photoactivated and subsequently localized within a series of camera frames, yielding a final image with a resolution far beyond the diffraction limit. Yet, before localization can be performed, the subregions within the frames where the individual molecules are present have to be identified-oftentimes in the presence of high background. In this work, we address the importance of reliable molecule identification for the quality of the final reconstructed super-resolution image. We present a fast and robust algorithm (a-livePALM) that vastly improves the molecule detection efficiency while minimizing false assignments that can lead to image artifacts.

Super-resolution optical telescopes with local light diffraction shrinkage

PubMed Central

Wang, Changtao; Tang, Dongliang; Wang, Yanqin; Zhao, Zeyu; Wang, Jiong; Pu, Mingbo; Zhang, Yudong; Yan, Wei; Gao, Ping; Luo, Xiangang

2015-01-01

Suffering from giant size of objective lenses and infeasible manipulations of distant targets, telescopes could not seek helps from present super-resolution imaging, such as scanning near-field optical microscopy, perfect lens and stimulated emission depletion microscopy. In this paper, local light diffraction shrinkage associated with optical super-oscillatory phenomenon is proposed for real-time and optically restoring super-resolution imaging information in a telescope system. It is found that fine target features concealed in diffraction-limited optical images of a telescope could be observed in a small local field of view, benefiting from a relayed metasurface-based super-oscillatory imaging optics in which some local Fourier components beyond the cut-off frequency of telescope could be restored. As experimental examples, a minimal resolution to 0.55 of Rayleigh criterion is obtained, and imaging complex targets and large targets by superimposing multiple local fields of views are demonstrated as well. This investigation provides an access for real-time, incoherent and super-resolution telescopes without the manipulation of distant targets. More importantly, it gives counterintuitive evidence to the common knowledge that relayed optics could not deliver more imaging details than objective systems. PMID:26677820

A super resolution framework for low resolution document image OCR

NASA Astrophysics Data System (ADS)

Ma, Di; Agam, Gady

2013-01-01

Optical character recognition is widely used for converting document images into digital media. Existing OCR algorithms and tools produce good results from high resolution, good quality, document images. In this paper, we propose a machine learning based super resolution framework for low resolution document image OCR. Two main techniques are used in our proposed approach: a document page segmentation algorithm and a modified K-means clustering algorithm. Using this approach, by exploiting coherence in the document, we reconstruct from a low resolution document image a better resolution image and improve OCR results. Experimental results show substantial gain in low resolution documents such as the ones captured from video.

Super-Resolution for Color Imagery

DTIC Science & Technology

2017-09-01

separately; however, it requires performing the super-resolution computation 3 times. We transform images in the default red, green, blue (RGB) color space...chrominance components based on ARL’s alias-free image upsampling using Fourier-based windowing methods. A reverse transformation is performed on... Transformation from sRGB to CIELAB............................................... 3 Fig. 2 YCbCr mathematical coordinate transformation

Example-based super-resolution for single-image analysis from the Chang'e-1 Mission

NASA Astrophysics Data System (ADS)

Wu, Fan-Lu; Wang, Xiang-Jun

2016-11-01

Due to the low spatial resolution of images taken from the Chang'e-1 (CE-1) orbiter, the details of the lunar surface are blurred and lost. Considering the limited spatial resolution of image data obtained by a CCD camera on CE-1, an example-based super-resolution (SR) algorithm is employed to obtain high-resolution (HR) images. SR reconstruction is important for the application of image data to increase the resolution of images. In this article, a novel example-based algorithm is proposed to implement SR reconstruction by single-image analysis, and the computational cost is reduced compared to other example-based SR methods. The results show that this method can enhance the resolution of images using SR and recover detailed information about the lunar surface. Thus it can be used for surveying HR terrain and geological features. Moreover, the algorithm is significant for the HR processing of remotely sensed images obtained by other imaging systems.

Three-Dimensional Orientation of Anisotropic Plasmonic Aggregates at Intracellular Nuclear Indentation Sites by Integrated Light Sheet Super-Resolution Microscopy.

PubMed

Chakkarapani, Suresh Kumar; Sun, Yucheng; Lee, Seungah; Fang, Ning; Kang, Seong Ho

2018-05-22

Three-dimensional (3D) orientations of individual anisotropic plasmonic nanoparticles in aggregates were observed in real time by integrated light sheet super-resolution microscopy ( iLSRM). Asymmetric light scattering of a gold nanorod (AuNR) was used to trigger signals based on the polarizer angle. Controlled photoswitching was achieved by turning the polarizer and obtaining a series of images at different polarization directions. 3D subdiffraction-limited super-resolution images were obtained by superlocalization of scattering signals as a function of the anisotropic optical properties of AuNRs. Varying the polarizer angle allowed resolution of the orientation of individual AuNRs. 3D images of individual nanoparticles were resolved in aggregated regions, resulting in as low as 64 nm axial resolution and 28 nm spatial resolution. The proposed imaging setup and localization approach demonstrates a convenient method for imaging under a noisy environment where the majority of scattering noise comes from cellular components. This integrated 3D iLSRM and localization technique was shown to be reliable and useful in the field of 3D nonfluorescence super-resolution imaging.

An Example-Based Super-Resolution Algorithm for Selfie Images

PubMed Central

William, Jino Hans; Venkateswaran, N.; Narayanan, Srinath; Ramachandran, Sandeep

2016-01-01

A selfie is typically a self-portrait captured using the front camera of a smartphone. Most state-of-the-art smartphones are equipped with a high-resolution (HR) rear camera and a low-resolution (LR) front camera. As selfies are captured by front camera with limited pixel resolution, the fine details in it are explicitly missed. This paper aims to improve the resolution of selfies by exploiting the fine details in HR images captured by rear camera using an example-based super-resolution (SR) algorithm. HR images captured by rear camera carry significant fine details and are used as an exemplar to train an optimal matrix-value regression (MVR) operator. The MVR operator serves as an image-pair priori which learns the correspondence between the LR-HR patch-pairs and is effectively used to super-resolve LR selfie images. The proposed MVR algorithm avoids vectorization of image patch-pairs and preserves image-level information during both learning and recovering process. The proposed algorithm is evaluated for its efficiency and effectiveness both qualitatively and quantitatively with other state-of-the-art SR algorithms. The results validate that the proposed algorithm is efficient as it requires less than 3 seconds to super-resolve LR selfie and is effective as it preserves sharp details without introducing any counterfeit fine details. PMID:27064500

Single image super-resolution reconstruction algorithm based on eage selection

NASA Astrophysics Data System (ADS)

Zhang, Yaolan; Liu, Yijun

2017-05-01

Super-resolution (SR) has become more important, because it can generate high-quality high-resolution (HR) images from low-resolution (LR) input images. At present, there are a lot of work is concentrated on developing sophisticated image priors to improve the image quality, while taking much less attention to estimating and incorporating the blur model that can also impact the reconstruction results. We present a new reconstruction method based on eager selection. This method takes full account of the factors that affect the blur kernel estimation and accurately estimating the blur process. When comparing with the state-of-the-art methods, our method has comparable performance.

Dictionary learning based noisy image super-resolution via distance penalty weight model

PubMed Central

Han, Yulan; Zhao, Yongping; Wang, Qisong

2017-01-01

In this study, we address the problem of noisy image super-resolution. Noisy low resolution (LR) image is always obtained in applications, while most of the existing algorithms assume that the LR image is noise-free. As to this situation, we present an algorithm for noisy image super-resolution which can achieve simultaneously image super-resolution and denoising. And in the training stage of our method, LR example images are noise-free. For different input LR images, even if the noise variance varies, the dictionary pair does not need to be retrained. For the input LR image patch, the corresponding high resolution (HR) image patch is reconstructed through weighted average of similar HR example patches. To reduce computational cost, we use the atoms of learned sparse dictionary as the examples instead of original example patches. We proposed a distance penalty model for calculating the weight, which can complete a second selection on similar atoms at the same time. Moreover, LR example patches removed mean pixel value are also used to learn dictionary rather than just their gradient features. Based on this, we can reconstruct initial estimated HR image and denoised LR image. Combined with iterative back projection, the two reconstructed images are applied to obtain final estimated HR image. We validate our algorithm on natural images and compared with the previously reported algorithms. Experimental results show that our proposed method performs better noise robustness. PMID:28759633

Super-resolution of fluorescence-free plasmonic nanoparticles using enhanced dark-field illumination based on wavelength-modulation

DOE PAGES

Zhang, Peng; Lee, Seungah; Yu, Hyunung; ...

2015-06-15

Super-resolution imaging of fluorescence-free plasmonic nanoparticles (NPs) was achieved using enhanced dark-field (EDF) illumination based on wavelength-modulation. Indistinguishable adjacent EDF images of 103-nm gold nanoparticles (GNPs), 40-nm gold nanorods (GNRs), and 80-nm silver nanoparticles (SNPs) were modulated at their wavelengths of specific localized surface plasmon scattering. The coordinates (x, y) of each NP were resolved by fitting their point spread functions with a two-dimensional Gaussian. The measured localization precisions of GNPs, GNRs, and SNPs were 2.5 nm, 5.0 nm, and 2.9 nm, respectively. From the resolved coordinates of NPs and the corresponding localization precisions, super-resolution images were reconstructed. Depending onmore » the spontaneous polarization of GNR scattering, the orientation angle of GNRs in two-dimensions was resolved and provided more elaborate localization information. This novel fluorescence-free super-resolution method was applied to live HeLa cells to resolve NPs and provided remarkable subdiffraction limit images.« less

Combined multi-plane phase retrieval and super-resolution optical fluctuation imaging for 4D cell microscopy

NASA Astrophysics Data System (ADS)

Descloux, A.; Grußmayer, K. S.; Bostan, E.; Lukes, T.; Bouwens, A.; Sharipov, A.; Geissbuehler, S.; Mahul-Mellier, A.-L.; Lashuel, H. A.; Leutenegger, M.; Lasser, T.

2018-03-01

Super-resolution fluorescence microscopy provides unprecedented insight into cellular and subcellular structures. However, going `beyond the diffraction barrier' comes at a price, since most far-field super-resolution imaging techniques trade temporal for spatial super-resolution. We propose the combination of a novel label-free white light quantitative phase imaging with fluorescence to provide high-speed imaging and spatial super-resolution. The non-iterative phase retrieval relies on the acquisition of single images at each z-location and thus enables straightforward 3D phase imaging using a classical microscope. We realized multi-plane imaging using a customized prism for the simultaneous acquisition of eight planes. This allowed us to not only image live cells in 3D at up to 200 Hz, but also to integrate fluorescence super-resolution optical fluctuation imaging within the same optical instrument. The 4D microscope platform unifies the sensitivity and high temporal resolution of phase imaging with the specificity and high spatial resolution of fluorescence microscopy.

Localization-based super-resolution imaging meets high-content screening.

PubMed

Beghin, Anne; Kechkar, Adel; Butler, Corey; Levet, Florian; Cabillic, Marine; Rossier, Olivier; Giannone, Gregory; Galland, Rémi; Choquet, Daniel; Sibarita, Jean-Baptiste

2017-12-01

Single-molecule localization microscopy techniques have proven to be essential tools for quantitatively monitoring biological processes at unprecedented spatial resolution. However, these techniques are very low throughput and are not yet compatible with fully automated, multiparametric cellular assays. This shortcoming is primarily due to the huge amount of data generated during imaging and the lack of software for automation and dedicated data mining. We describe an automated quantitative single-molecule-based super-resolution methodology that operates in standard multiwell plates and uses analysis based on high-content screening and data-mining software. The workflow is compatible with fixed- and live-cell imaging and allows extraction of quantitative data like fluorophore photophysics, protein clustering or dynamic behavior of biomolecules. We demonstrate that the method is compatible with high-content screening using 3D dSTORM and DNA-PAINT based super-resolution microscopy as well as single-particle tracking.

Multi-dimensional super-resolution imaging enables surface hydrophobicity mapping

NASA Astrophysics Data System (ADS)

Bongiovanni, Marie N.; Godet, Julien; Horrocks, Mathew H.; Tosatto, Laura; Carr, Alexander R.; Wirthensohn, David C.; Ranasinghe, Rohan T.; Lee, Ji-Eun; Ponjavic, Aleks; Fritz, Joelle V.; Dobson, Christopher M.; Klenerman, David; Lee, Steven F.

2016-12-01

Super-resolution microscopy allows biological systems to be studied at the nanoscale, but has been restricted to providing only positional information. Here, we show that it is possible to perform multi-dimensional super-resolution imaging to determine both the position and the environmental properties of single-molecule fluorescent emitters. The method presented here exploits the solvatochromic and fluorogenic properties of nile red to extract both the emission spectrum and the position of each dye molecule simultaneously enabling mapping of the hydrophobicity of biological structures. We validated this by studying synthetic lipid vesicles of known composition. We then applied both to super-resolve the hydrophobicity of amyloid aggregates implicated in neurodegenerative diseases, and the hydrophobic changes in mammalian cell membranes. Our technique is easily implemented by inserting a transmission diffraction grating into the optical path of a localization-based super-resolution microscope, enabling all the information to be extracted simultaneously from a single image plane.

Multi-dimensional super-resolution imaging enables surface hydrophobicity mapping

PubMed Central

Bongiovanni, Marie N.; Godet, Julien; Horrocks, Mathew H.; Tosatto, Laura; Carr, Alexander R.; Wirthensohn, David C.; Ranasinghe, Rohan T.; Lee, Ji-Eun; Ponjavic, Aleks; Fritz, Joelle V.; Dobson, Christopher M.; Klenerman, David; Lee, Steven F.

2016-01-01

Super-resolution microscopy allows biological systems to be studied at the nanoscale, but has been restricted to providing only positional information. Here, we show that it is possible to perform multi-dimensional super-resolution imaging to determine both the position and the environmental properties of single-molecule fluorescent emitters. The method presented here exploits the solvatochromic and fluorogenic properties of nile red to extract both the emission spectrum and the position of each dye molecule simultaneously enabling mapping of the hydrophobicity of biological structures. We validated this by studying synthetic lipid vesicles of known composition. We then applied both to super-resolve the hydrophobicity of amyloid aggregates implicated in neurodegenerative diseases, and the hydrophobic changes in mammalian cell membranes. Our technique is easily implemented by inserting a transmission diffraction grating into the optical path of a localization-based super-resolution microscope, enabling all the information to be extracted simultaneously from a single image plane. PMID:27929085

Simultaneous digital super-resolution and nonuniformity correction for infrared imaging systems.

PubMed

Meza, Pablo; Machuca, Guillermo; Torres, Sergio; Martin, Cesar San; Vera, Esteban

2015-07-20

In this article, we present a novel algorithm to achieve simultaneous digital super-resolution and nonuniformity correction from a sequence of infrared images. We propose to use spatial regularization terms that exploit nonlocal means and the absence of spatial correlation between the scene and the nonuniformity noise sources. We derive an iterative optimization algorithm based on a gradient descent minimization strategy. Results from infrared image sequences corrupted with simulated and real fixed-pattern noise show a competitive performance compared with state-of-the-art methods. A qualitative analysis on the experimental results obtained with images from a variety of infrared cameras indicates that the proposed method provides super-resolution images with significantly less fixed-pattern noise.

Image super-resolution via sparse representation.

PubMed

Yang, Jianchao; Wright, John; Huang, Thomas S; Ma, Yi

2010-11-01

This paper presents a new approach to single-image super-resolution, based on sparse signal representation. Research on image statistics suggests that image patches can be well-represented as a sparse linear combination of elements from an appropriately chosen over-complete dictionary. Inspired by this observation, we seek a sparse representation for each patch of the low-resolution input, and then use the coefficients of this representation to generate the high-resolution output. Theoretical results from compressed sensing suggest that under mild conditions, the sparse representation can be correctly recovered from the downsampled signals. By jointly training two dictionaries for the low- and high-resolution image patches, we can enforce the similarity of sparse representations between the low resolution and high resolution image patch pair with respect to their own dictionaries. Therefore, the sparse representation of a low resolution image patch can be applied with the high resolution image patch dictionary to generate a high resolution image patch. The learned dictionary pair is a more compact representation of the patch pairs, compared to previous approaches, which simply sample a large amount of image patch pairs, reducing the computational cost substantially. The effectiveness of such a sparsity prior is demonstrated for both general image super-resolution and the special case of face hallucination. In both cases, our algorithm generates high-resolution images that are competitive or even superior in quality to images produced by other similar SR methods. In addition, the local sparse modeling of our approach is naturally robust to noise, and therefore the proposed algorithm can handle super-resolution with noisy inputs in a more unified framework.

Plasmonics and metamaterials based super-resolution imaging (Conference Presentation)

NASA Astrophysics Data System (ADS)

Liu, Zhaowei

2017-05-01

In recent years, surface imaging of various biological dynamics and biomechanical phenomena has seen a surge of interest. Imaging of processes such as exocytosis and kinesin motion are most effective when depth is limited to a very thin region of interest at the edge of the cell or specimen. However, many objects and processes of interest are of size scales below the diffraction limit for safe, visible wavelength illumination. Super-resolution imaging methods such as structured illumination microscopy and others have offered various compromises between resolution, imaging speed, and bio-compatibility. In this talk, I will present our most recent progress in plasmonic structured illumination microscopy (PSIM) and localized plasmonic structured illumination microscopy (LPSIM), and their applications in bio-imaging. We have achieved wide-field surface imaging with resolution down to 75 nm while maintaining reasonable speed and compatibility with biological specimens. These plasmonic enhanced super resolution techniques offer unique solutions to obtain 50nm spatial resolution and 50 frames per second wide imaging speed at the same time.

Field-Portable Pixel Super-Resolution Colour Microscope

PubMed Central

Greenbaum, Alon; Akbari, Najva; Feizi, Alborz; Luo, Wei; Ozcan, Aydogan

2013-01-01

Based on partially-coherent digital in-line holography, we report a field-portable microscope that can render lensfree colour images over a wide field-of-view of e.g., >20 mm2. This computational holographic microscope weighs less than 145 grams with dimensions smaller than 17×6×5 cm, making it especially suitable for field settings and point-of-care use. In this lensfree imaging design, we merged a colorization algorithm with a source shifting based multi-height pixel super-resolution technique to mitigate ‘rainbow’ like colour artefacts that are typical in holographic imaging. This image processing scheme is based on transforming the colour components of an RGB image into YUV colour space, which separates colour information from brightness component of an image. The resolution of our super-resolution colour microscope was characterized using a USAF test chart to confirm sub-micron spatial resolution, even for reconstructions that employ multi-height phase recovery to handle dense and connected objects. To further demonstrate the performance of this colour microscope Papanicolaou (Pap) smears were also successfully imaged. This field-portable and wide-field computational colour microscope could be useful for tele-medicine applications in resource poor settings. PMID:24086742

Field-portable pixel super-resolution colour microscope.

PubMed

Greenbaum, Alon; Akbari, Najva; Feizi, Alborz; Luo, Wei; Ozcan, Aydogan

2013-01-01

Based on partially-coherent digital in-line holography, we report a field-portable microscope that can render lensfree colour images over a wide field-of-view of e.g., >20 mm(2). This computational holographic microscope weighs less than 145 grams with dimensions smaller than 17×6×5 cm, making it especially suitable for field settings and point-of-care use. In this lensfree imaging design, we merged a colorization algorithm with a source shifting based multi-height pixel super-resolution technique to mitigate 'rainbow' like colour artefacts that are typical in holographic imaging. This image processing scheme is based on transforming the colour components of an RGB image into YUV colour space, which separates colour information from brightness component of an image. The resolution of our super-resolution colour microscope was characterized using a USAF test chart to confirm sub-micron spatial resolution, even for reconstructions that employ multi-height phase recovery to handle dense and connected objects. To further demonstrate the performance of this colour microscope Papanicolaou (Pap) smears were also successfully imaged. This field-portable and wide-field computational colour microscope could be useful for tele-medicine applications in resource poor settings.

Application of Super-Resolution Convolutional Neural Network for Enhancing Image Resolution in Chest CT.

PubMed

Umehara, Kensuke; Ota, Junko; Ishida, Takayuki

2017-10-18

In this study, the super-resolution convolutional neural network (SRCNN) scheme, which is the emerging deep-learning-based super-resolution method for enhancing image resolution in chest CT images, was applied and evaluated using the post-processing approach. For evaluation, 89 chest CT cases were sampled from The Cancer Imaging Archive. The 89 CT cases were divided randomly into 45 training cases and 44 external test cases. The SRCNN was trained using the training dataset. With the trained SRCNN, a high-resolution image was reconstructed from a low-resolution image, which was down-sampled from an original test image. For quantitative evaluation, two image quality metrics were measured and compared to those of the conventional linear interpolation methods. The image restoration quality of the SRCNN scheme was significantly higher than that of the linear interpolation methods (p < 0.001 or p < 0.05). The high-resolution image reconstructed by the SRCNN scheme was highly restored and comparable to the original reference image, in particular, for a ×2 magnification. These results indicate that the SRCNN scheme significantly outperforms the linear interpolation methods for enhancing image resolution in chest CT images. The results also suggest that SRCNN may become a potential solution for generating high-resolution CT images from standard CT images.

Face sketch recognition based on edge enhancement via deep learning

NASA Astrophysics Data System (ADS)

Xie, Zhenzhu; Yang, Fumeng; Zhang, Yuming; Wu, Congzhong

2017-11-01

In this paper,we address the face sketch recognition problem. Firstly, we utilize the eigenface algorithm to convert a sketch image into a synthesized sketch face image. Subsequently, considering the low-level vision problem in synthesized face sketch image .Super resolution reconstruction algorithm based on CNN(convolutional neural network) is employed to improve the visual effect. To be specific, we uses a lightweight super-resolution structure to learn a residual mapping instead of directly mapping the feature maps from the low-level space to high-level patch representations, which making the networks are easier to optimize and have lower computational complexity. Finally, we adopt LDA(Linear Discriminant Analysis) algorithm to realize face sketch recognition on synthesized face image before super resolution and after respectively. Extensive experiments on the face sketch database(CUFS) from CUHK demonstrate that the recognition rate of SVM(Support Vector Machine) algorithm improves from 65% to 69% and the recognition rate of LDA(Linear Discriminant Analysis) algorithm improves from 69% to 75%.What'more,the synthesized face image after super resolution can not only better describer image details such as hair ,nose and mouth etc, but also improve the recognition accuracy effectively.

Combined self-learning based single-image super-resolution and dual-tree complex wavelet transform denoising for medical images

NASA Astrophysics Data System (ADS)

Yang, Guang; Ye, Xujiong; Slabaugh, Greg; Keegan, Jennifer; Mohiaddin, Raad; Firmin, David

2016-03-01

In this paper, we propose a novel self-learning based single-image super-resolution (SR) method, which is coupled with dual-tree complex wavelet transform (DTCWT) based denoising to better recover high-resolution (HR) medical images. Unlike previous methods, this self-learning based SR approach enables us to reconstruct HR medical images from a single low-resolution (LR) image without extra training on HR image datasets in advance. The relationships between the given image and its scaled down versions are modeled using support vector regression with sparse coding and dictionary learning, without explicitly assuming reoccurrence or self-similarity across image scales. In addition, we perform DTCWT based denoising to initialize the HR images at each scale instead of simple bicubic interpolation. We evaluate our method on a variety of medical images. Both quantitative and qualitative results show that the proposed approach outperforms bicubic interpolation and state-of-the-art single-image SR methods while effectively removing noise.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography).

PubMed

Siegel, Nisan; Storrie, Brian; Bruce, Marc; Brooker, Gary

2015-02-07

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called "CINCH". An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution.

Super-resolved refocusing with a plenoptic camera

NASA Astrophysics Data System (ADS)

Zhou, Zhiliang; Yuan, Yan; Bin, Xiangli; Qian, Lulu

2011-03-01

This paper presents an approach to enhance the resolution of refocused images by super resolution methods. In plenoptic imaging, we demonstrate that the raw sensor image can be divided to a number of low-resolution angular images with sub-pixel shifts between each other. The sub-pixel shift, which defines the super-resolving ability, is mathematically derived by considering the plenoptic camera as equivalent camera arrays. We implement simulation to demonstrate the imaging process of a plenoptic camera. A high-resolution image is then reconstructed using maximum a posteriori (MAP) super resolution algorithms. Without other degradation effects in simulation, the super resolved image achieves a resolution as high as predicted by the proposed model. We also build an experimental setup to acquire light fields. With traditional refocusing methods, the image is rendered at a rather low resolution. In contrast, we implement the super-resolved refocusing methods and recover an image with more spatial details. To evaluate the performance of the proposed method, we finally compare the reconstructed images using image quality metrics like peak signal to noise ratio (PSNR).

Single image super-resolution via regularized extreme learning regression for imagery from microgrid polarimeters

NASA Astrophysics Data System (ADS)

Sargent, Garrett C.; Ratliff, Bradley M.; Asari, Vijayan K.

2017-08-01

The advantage of division of focal plane imaging polarimeters is their ability to obtain temporally synchronized intensity measurements across a scene; however, they sacrifice spatial resolution in doing so due to their spatially modulated arrangement of the pixel-to-pixel polarizers and often result in aliased imagery. Here, we propose a super-resolution method based upon two previously trained extreme learning machines (ELM) that attempt to recover missing high frequency and low frequency content beyond the spatial resolution of the sensor. This method yields a computationally fast and simple way of recovering lost high and low frequency content from demosaicing raw microgrid polarimetric imagery. The proposed method outperforms other state-of-the-art single-image super-resolution algorithms in terms of structural similarity and peak signal-to-noise ratio.

CINCH (confocal incoherent correlation holography) super resolution fluorescence microscopy based upon FINCH (Fresnel incoherent correlation holography)

PubMed Central

Siegel, Nisan; Storrie, Brian; Bruce, Marc

2016-01-01

FINCH holographic fluorescence microscopy creates high resolution super-resolved images with enhanced depth of focus. The simple addition of a real-time Nipkow disk confocal image scanner in a conjugate plane of this incoherent holographic system is shown to reduce the depth of focus, and the combination of both techniques provides a simple way to enhance the axial resolution of FINCH in a combined method called “CINCH”. An important feature of the combined system allows for the simultaneous real-time image capture of widefield and holographic images or confocal and confocal holographic images for ready comparison of each method on the exact same field of view. Additional GPU based complex deconvolution processing of the images further enhances resolution. PMID:26839443

Detecting breast microcalcifications using super-resolution ultrasound imaging: a clinical study

NASA Astrophysics Data System (ADS)

Huang, Lianjie; Labyed, Yassin; Hanson, Kenneth; Sandoval, Daniel; Pohl, Jennifer; Williamson, Michael

2013-03-01

Imaging breast microcalcifications is crucial for early detection and diagnosis of breast cancer. It is challenging for current clinical ultrasound to image breast microcalcifications. However, new imaging techniques using data acquired with a synthetic-aperture ultrasound system have the potential to significantly improve ultrasound imaging. We recently developed a super-resolution ultrasound imaging method termed the phase-coherent multiple-signal classification (PC-MUSIC). This signal subspace method accounts for the phase response of transducer elements to improve image resolution. In this paper, we investigate the clinical feasibility of our super-resolution ultrasound imaging method for detecting breast microcalcifications. We use our custom-built, real-time synthetic-aperture ultrasound system to acquire breast ultrasound data for 40 patients whose mammograms show the presence of breast microcalcifications. We apply our super-resolution ultrasound imaging method to the patient data, and produce clear images of breast calcifications. Our super-resolution ultrasound PC-MUSIC imaging with synthetic-aperture ultrasound data can provide a new imaging modality for detecting breast microcalcifications in clinic without using ionizing radiation.

Super resolution imaging of HER2 gene amplification

NASA Astrophysics Data System (ADS)

Okada, Masaya; Kubo, Takuya; Masumoto, Kanako; Iwanaga, Shigeki

2016-02-01

HER2 positive breast cancer is currently examined by counting HER2 genes using fluorescence in situ hybridization (FISH)-stained breast carcinoma samples. In this research, two-dimensional super resolution fluorescence microscopy based on stochastic optical reconstruction microscopy (STORM), with a spatial resolution of approximately 20 nm in the lateral direction, was used to more precisely distinguish and count HER2 genes in a FISH-stained tissue section. Furthermore, by introducing double-helix point spread function (DH-PSF), an optical phase modulation technique, to super resolution microscopy, three-dimensional images were obtained of HER2 in a breast carcinoma sample approximately 4 μm thick.

Single image super-resolution based on convolutional neural networks

NASA Astrophysics Data System (ADS)

Zou, Lamei; Luo, Ming; Yang, Weidong; Li, Peng; Jin, Liujia

2018-03-01

We present a deep learning method for single image super-resolution (SISR). The proposed approach learns end-to-end mapping between low-resolution (LR) images and high-resolution (HR) images. The mapping is represented as a deep convolutional neural network which inputs the LR image and outputs the HR image. Our network uses 5 convolution layers, which kernels size include 5×5, 3×3 and 1×1. In our proposed network, we use residual-learning and combine different sizes of convolution kernels at the same layer. The experiment results show that our proposed method performs better than the existing methods in reconstructing quality index and human visual effects on benchmarked images.

Controlled power delivery for super-resolution imaging of biological samples using digital micromirror device

NASA Astrophysics Data System (ADS)

Valiya Peedikakkal, Liyana; Cadby, Ashley

2017-02-01

Localization based super resolution images of a biological sample is generally achieved by using high power laser illumination with long exposure time which unfortunately increases photo-toxicity of a sample, making super resolution microscopy, in general, incompatible with live cell imaging. Furthermore, the limitation of photobleaching reduces the ability to acquire time lapse images of live biological cells using fluorescence microscopy. Digital Light Processing (DLP) technology can deliver light at grey scale levels by flickering digital micromirrors at around 290 Hz enabling highly controlled power delivery to samples. In this work, Digital Micromirror Device (DMD) is implemented in an inverse Schiefspiegler telescope setup to control the power and pattern of illumination for super resolution microscopy. We can achieve spatial and temporal patterning of illumination by controlling the DMD pixel by pixel. The DMD allows us to control the power and spatial extent of the laser illumination. We have used this to show that we can reduce the power delivered to the sample to allow for longer time imaging in one area while achieving sub-diffraction STORM imaging in another using higher power densities.

Fast live-cell conventional fluorophore nanoscopy with ImageJ through super-resolution radial fluctuations

PubMed Central

Gustafsson, Nils; Culley, Siân; Ashdown, George; Owen, Dylan M.; Pereira, Pedro Matos; Henriques, Ricardo

2016-01-01

Despite significant progress, high-speed live-cell super-resolution studies remain limited to specialized optical setups, generally requiring intense phototoxic illumination. Here, we describe a new analytical approach, super-resolution radial fluctuations (SRRF), provided as a fast graphics processing unit-enabled ImageJ plugin. In the most challenging data sets for super-resolution, such as those obtained in low-illumination live-cell imaging with GFP, we show that SRRF is generally capable of achieving resolutions better than 150 nm. Meanwhile, for data sets similar to those obtained in PALM or STORM imaging, SRRF achieves resolutions approaching those of standard single-molecule localization analysis. The broad applicability of SRRF and its performance at low signal-to-noise ratios allows super-resolution using modern widefield, confocal or TIRF microscopes with illumination orders of magnitude lower than methods such as PALM, STORM or STED. We demonstrate this by super-resolution live-cell imaging over timescales ranging from minutes to hours. PMID:27514992

Multicolor Super-Resolution Fluorescence Imaging via Multi-Parameter Fluorophore Detection

PubMed Central

Bates, Mark; Dempsey, Graham T; Chen, Kok Hao; Zhuang, Xiaowei

2012-01-01

Understanding the complexity of the cellular environment will benefit from the ability to unambiguously resolve multiple cellular components, simultaneously and with nanometer-scale spatial resolution. Multicolor super-resolution fluorescence microscopy techniques have been developed to achieve this goal, yet challenges remain in terms of the number of targets that can be simultaneously imaged and the crosstalk between color channels. Herein, we demonstrate multicolor stochastic optical reconstruction microscopy (STORM) based on a multi-parameter detection strategy, which uses both the fluorescence activation wavelength and the emission color to discriminate between photo-activatable fluorescent probes. First, we obtained two-color super-resolution images using the near-infrared cyanine dye Alexa 750 in conjunction with a red cyanine dye Alexa 647, and quantified color crosstalk levels and image registration accuracy. Combinatorial pairing of these two switchable dyes with fluorophores which enhance photo-activation enabled multi-parameter detection of six different probes. Using this approach, we obtained six-color super-resolution fluorescence images of a model sample. The combination of multiple fluorescence detection parameters for improved fluorophore discrimination promises to substantially enhance our ability to visualize multiple cellular targets with sub-diffraction-limit resolution. PMID:22213647

Super-resolved all-refocused image with a plenoptic camera

NASA Astrophysics Data System (ADS)

Wang, Xiang; Li, Lin; Hou, Guangqi

2015-12-01

This paper proposes an approach to produce the super-resolution all-refocused images with the plenoptic camera. The plenoptic camera can be produced by putting a micro-lens array between the lens and the sensor in a conventional camera. This kind of camera captures both the angular and spatial information of the scene in one single shot. A sequence of digital refocused images, which are refocused at different depth, can be produced after processing the 4D light field captured by the plenoptic camera. The number of the pixels in the refocused image is the same as that of the micro-lens in the micro-lens array. Limited number of the micro-lens will result in poor low resolution refocused images. Therefore, not enough details will exist in these images. Such lost details, which are often high frequency information, are important for the in-focus part in the refocused image. We decide to super-resolve these in-focus parts. The result of image segmentation method based on random walks, which works on the depth map produced from the 4D light field data, is used to separate the foreground and background in the refocused image. And focusing evaluation function is employed to determine which refocused image owns the clearest foreground part and which one owns the clearest background part. Subsequently, we employ single image super-resolution method based on sparse signal representation to process the focusing parts in these selected refocused images. Eventually, we can obtain the super-resolved all-focus image through merging the focusing background part and the focusing foreground part in the way of digital signal processing. And more spatial details will be kept in these output images. Our method will enhance the resolution of the refocused image, and just the refocused images owning the clearest foreground and background need to be super-resolved.

Reducible dictionaries for single image super-resolution based on patch matching and mean shifting

NASA Astrophysics Data System (ADS)

Rasti, Pejman; Nasrollahi, Kamal; Orlova, Olga; Tamberg, Gert; Moeslund, Thomas B.; Anbarjafari, Gholamreza

2017-03-01

A single-image super-resolution (SR) method is proposed. The proposed method uses a generated dictionary from pairs of high resolution (HR) images and their corresponding low resolution (LR) representations. First, HR images and the corresponding LR ones are divided into patches of HR and LR, respectively, and then they are collected into separate dictionaries. Afterward, when performing SR, the distance between every patch of the input LR image and those of available LR patches in the LR dictionary is calculated. The minimum distance between the input LR patch and those in the LR dictionary is taken, and its counterpart from the HR dictionary is passed through an illumination enhancement process. By this technique, the noticeable change of illumination between neighbor patches in the super-resolved image is significantly reduced. The enhanced HR patch represents the HR patch of the super-resolved image. Finally, to remove the blocking effect caused by merging the patches, an average of the obtained HR image and the interpolated image obtained using bicubic interpolation is calculated. The quantitative and qualitative analyses show the superiority of the proposed technique over the conventional and state-of-art methods.

New developments in super-resolution for GaoFen-4

NASA Astrophysics Data System (ADS)

Li, Feng; Fu, Jie; Xin, Lei; Liu, Yuhong; Liu, Zhijia

2017-10-01

In this paper, the application of super resolution (SR, restoring a high spatial resolution image from a series of low resolution images of the same scene) techniques to GaoFen(GF)-4, which is the most advanced geostationaryorbit earth observing satellite in China, remote sensing images is investigated and tested. SR has been a hot research area for decades, but one of the barriers of applying SR in remote sensing community is the time slot between those low resolution (LR) images acquisition. In general, the longer the time slot, the less reliable the reconstruction. GF-4 has the unique advantage of capturing a sequence of LR of the same region in minutes, i.e. working as a staring camera from the point view of SR. This is the first experiment of applying super resolution to a sequence of low resolution images captured by GF-4 within a short time period. In this paper, we use Maximum a Posteriori (MAP) to solve the ill-conditioned problem of SR. Both the wavelet transform and the curvelet transform are used to setup a sparse prior for remote sensing images. By combining several images of both the BeiJing and DunHuang regions captured by GF-4 our method can improve spatial resolution both visually and numerically. Experimental tests show that lots of detail cannot be observed in the captured LR images, but can be seen in the super resolved high resolution (HR) images. To help the evaluation, Google Earth image can also be referenced. Moreover, our experimental tests also show that the higher the temporal resolution, the better the HR images can be resolved. The study illustrates that the application for SR to geostationary-orbit based earth observation data is very feasible and worthwhile, and it holds the potential application for all other geostationary-orbit based earth observing systems.

Measuring the performance of super-resolution reconstruction algorithms

NASA Astrophysics Data System (ADS)

Dijk, Judith; Schutte, Klamer; van Eekeren, Adam W. M.; Bijl, Piet

2012-06-01

For many military operations situational awareness is of great importance. This situational awareness and related tasks such as Target Acquisition can be acquired using cameras, of which the resolution is an important characteristic. Super resolution reconstruction algorithms can be used to improve the effective sensor resolution. In order to judge these algorithms and the conditions under which they operate best, performance evaluation methods are necessary. This evaluation, however, is not straightforward for several reasons. First of all, frequency-based evaluation techniques alone will not provide a correct answer, due to the fact that they are unable to discriminate between structure-related and noise-related effects. Secondly, most super-resolution packages perform additional image enhancement techniques such as noise reduction and edge enhancement. As these algorithms improve the results they cannot be evaluated separately. Thirdly, a single high-resolution ground truth is rarely available. Therefore, evaluation of the differences in high resolution between the estimated high resolution image and its ground truth is not that straightforward. Fourth, different artifacts can occur due to super-resolution reconstruction, which are not known on forehand and hence are difficult to evaluate. In this paper we present a set of new evaluation techniques to assess super-resolution reconstruction algorithms. Some of these evaluation techniques are derived from processing on dedicated (synthetic) imagery. Other evaluation techniques can be evaluated on both synthetic and natural images (real camera data). The result is a balanced set of evaluation algorithms that can be used to assess the performance of super-resolution reconstruction algorithms.

Depletion-based techniques for super-resolution imaging of NV-diamond

NASA Astrophysics Data System (ADS)

Jaskula, Jean-Christophe; Trifonov, Alexei; Glenn, David; Walsworth, Ronald

2012-06-01

We discuss the development and application of depletion-based techniques for super-resolution imaging of NV centers in diamond: stimulated emission depletion (STED), metastable ground state depletion (GSD), and dark state depletion (DSD). NV centers in diamond do not bleach under optical excitation, are not biotoxic, and have long-lived electronic spin coherence and spin-state-dependent fluorescence. Thus NV-diamond has great potential as a fluorescent biomarker and as a magnetic biosensor.

Cygnus A super-resolved via convex optimization from VLA data

NASA Astrophysics Data System (ADS)

Dabbech, A.; Onose, A.; Abdulaziz, A.; Perley, R. A.; Smirnov, O. M.; Wiaux, Y.

2018-05-01

We leverage the Sparsity Averaging Re-weighted Analysis approach for interferometric imaging, that is based on convex optimization, for the super-resolution of Cyg A from observations at the frequencies 8.422 and 6.678 GHz with the Karl G. Jansky Very Large Array (VLA). The associated average sparsity and positivity priors enable image reconstruction beyond instrumental resolution. An adaptive Preconditioned primal-dual algorithmic structure is developed for imaging in the presence of unknown noise levels and calibration errors. We demonstrate the superior performance of the algorithm with respect to the conventional CLEAN-based methods, reflected in super-resolved images with high fidelity. The high-resolution features of the recovered images are validated by referring to maps of Cyg A at higher frequencies, more precisely 17.324 and 14.252 GHz. We also confirm the recent discovery of a radio transient in Cyg A, revealed in the recovered images of the investigated data sets. Our MATLAB code is available online on GitHub.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

NASA Astrophysics Data System (ADS)

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-04-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics.

FALCON: fast and unbiased reconstruction of high-density super-resolution microscopy data

PubMed Central

Min, Junhong; Vonesch, Cédric; Kirshner, Hagai; Carlini, Lina; Olivier, Nicolas; Holden, Seamus; Manley, Suliana; Ye, Jong Chul; Unser, Michael

2014-01-01

Super resolution microscopy such as STORM and (F)PALM is now a well known method for biological studies at the nanometer scale. However, conventional imaging schemes based on sparse activation of photo-switchable fluorescent probes have inherently slow temporal resolution which is a serious limitation when investigating live-cell dynamics. Here, we present an algorithm for high-density super-resolution microscopy which combines a sparsity-promoting formulation with a Taylor series approximation of the PSF. Our algorithm is designed to provide unbiased localization on continuous space and high recall rates for high-density imaging, and to have orders-of-magnitude shorter run times compared to previous high-density algorithms. We validated our algorithm on both simulated and experimental data, and demonstrated live-cell imaging with temporal resolution of 2.5 seconds by recovering fast ER dynamics. PMID:24694686

Conical diffraction as a versatile building block to implement new imaging modalities for superresolution in fluorescence microscopy

NASA Astrophysics Data System (ADS)

Fallet, Clément; Caron, Julien; Oddos, Stephane; Tinevez, Jean-Yves; Moisan, Lionel; Sirat, Gabriel Y.; Braitbart, Philippe O.; Shorte, Spencer L.

2014-08-01

We present a new technology for super-resolution fluorescence imaging, based on conical diffraction. Conical diffraction is a linear, singular phenomenon taking place when a polarized beam is diffracted through a biaxial crystal. The illumination patterns generated by conical diffraction are more compact than the classical Gaussian beam; we use them to generate a super-resolution imaging modality. Conical Diffraction Microscopy (CODIM) resolution enhancement can be achieved with any type of objective on any kind of sample preparation and standard fluorophores. Conical diffraction can be used in multiple fashion to create new and disruptive technologies for super-resolution microscopy. This paper will focus on the first one that has been implemented and give a glimpse at what the future of microscopy using conical diffraction could be.

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement

PubMed Central

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-01-01

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L0 gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements. PMID:29414893

Spatio-Temporal Super-Resolution Reconstruction of Remote-Sensing Images Based on Adaptive Multi-Scale Detail Enhancement.

PubMed

Zhu, Hong; Tang, Xinming; Xie, Junfeng; Song, Weidong; Mo, Fan; Gao, Xiaoming

2018-02-07

There are many problems in existing reconstruction-based super-resolution algorithms, such as the lack of texture-feature representation and of high-frequency details. Multi-scale detail enhancement can produce more texture information and high-frequency information. Therefore, super-resolution reconstruction of remote-sensing images based on adaptive multi-scale detail enhancement (AMDE-SR) is proposed in this paper. First, the information entropy of each remote-sensing image is calculated, and the image with the maximum entropy value is regarded as the reference image. Subsequently, spatio-temporal remote-sensing images are processed using phase normalization, which is to reduce the time phase difference of image data and enhance the complementarity of information. The multi-scale image information is then decomposed using the L ₀ gradient minimization model, and the non-redundant information is processed by difference calculation and expanding non-redundant layers and the redundant layer by the iterative back-projection (IBP) technique. The different-scale non-redundant information is adaptive-weighted and fused using cross-entropy. Finally, a nonlinear texture-detail-enhancement function is built to improve the scope of small details, and the peak signal-to-noise ratio (PSNR) is used as an iterative constraint. Ultimately, high-resolution remote-sensing images with abundant texture information are obtained by iterative optimization. Real results show an average gain in entropy of up to 0.42 dB for an up-scaling of 2 and a significant promotion gain in enhancement measure evaluation for an up-scaling of 2. The experimental results show that the performance of the AMED-SR method is better than existing super-resolution reconstruction methods in terms of visual and accuracy improvements.

Underwater video enhancement using multi-camera super-resolution

NASA Astrophysics Data System (ADS)

Quevedo, E.; Delory, E.; Callicó, G. M.; Tobajas, F.; Sarmiento, R.

2017-12-01

Image spatial resolution is critical in several fields such as medicine, communications or satellite, and underwater applications. While a large variety of techniques for image restoration and enhancement has been proposed in the literature, this paper focuses on a novel Super-Resolution fusion algorithm based on a Multi-Camera environment that permits to enhance the quality of underwater video sequences without significantly increasing computation. In order to compare the quality enhancement, two objective quality metrics have been used: PSNR (Peak Signal-to-Noise Ratio) and the SSIM (Structural SIMilarity) index. Results have shown that the proposed method enhances the objective quality of several underwater sequences, avoiding the appearance of undesirable artifacts, with respect to basic fusion Super-Resolution algorithms.

Color image guided depth image super resolution using fusion filter

NASA Astrophysics Data System (ADS)

He, Jin; Liang, Bin; He, Ying; Yang, Jun

2018-04-01

Depth cameras are currently playing an important role in many areas. However, most of them can only obtain lowresolution (LR) depth images. Color cameras can easily provide high-resolution (HR) color images. Using color image as a guide image is an efficient way to get a HR depth image. In this paper, we propose a depth image super resolution (SR) algorithm, which uses a HR color image as a guide image and a LR depth image as input. We use the fusion filter of guided filter and edge based joint bilateral filter to get HR depth image. Our experimental results on Middlebury 2005 datasets show that our method can provide better quality in HR depth images both numerically and visually.

Fast, label-free super-resolution live-cell imaging using rotating coherent scattering (ROCS) microscopy

NASA Astrophysics Data System (ADS)

Jünger, Felix; Olshausen, Philipp V.; Rohrbach, Alexander

2016-07-01

Living cells are highly dynamic systems with cellular structures being often below the optical resolution limit. Super-resolution microscopes, usually based on fluorescence cell labelling, are usually too slow to resolve small, dynamic structures. We present a label-free microscopy technique, which can generate thousands of super-resolved, high contrast images at a frame rate of 100 Hertz and without any post-processing. The technique is based on oblique sample illumination with coherent light, an approach believed to be not applicable in life sciences because of too many interference artefacts. However, by circulating an incident laser beam by 360° during one image acquisition, relevant image information is amplified. By combining total internal reflection illumination with dark-field detection, structures as small as 150 nm become separable through local destructive interferences. The technique images local changes in refractive index through scattered laser light and is applied to living mouse macrophages and helical bacteria revealing unexpected dynamic processes.

Fast, label-free super-resolution live-cell imaging using rotating coherent scattering (ROCS) microscopy

PubMed Central

Jünger, Felix; Olshausen, Philipp v.; Rohrbach, Alexander

2016-01-01

Living cells are highly dynamic systems with cellular structures being often below the optical resolution limit. Super-resolution microscopes, usually based on fluorescence cell labelling, are usually too slow to resolve small, dynamic structures. We present a label-free microscopy technique, which can generate thousands of super-resolved, high contrast images at a frame rate of 100 Hertz and without any post-processing. The technique is based on oblique sample illumination with coherent light, an approach believed to be not applicable in life sciences because of too many interference artefacts. However, by circulating an incident laser beam by 360° during one image acquisition, relevant image information is amplified. By combining total internal reflection illumination with dark-field detection, structures as small as 150 nm become separable through local destructive interferences. The technique images local changes in refractive index through scattered laser light and is applied to living mouse macrophages and helical bacteria revealing unexpected dynamic processes. PMID:27465033

Lensfree on-chip microscopy over a wide field-of-view using pixel super-resolution

PubMed Central

Bishara, Waheb; Su, Ting-Wei; Coskun, Ahmet F.; Ozcan, Aydogan

2010-01-01

We demonstrate lensfree holographic microscopy on a chip to achieve ~0.6 µm spatial resolution corresponding to a numerical aperture of ~0.5 over a large field-of-view of ~24 mm2. By using partially coherent illumination from a large aperture (~50 µm), we acquire lower resolution lensfree in-line holograms of the objects with unit fringe magnification. For each lensfree hologram, the pixel size at the sensor chip limits the spatial resolution of the reconstructed image. To circumvent this limitation, we implement a sub-pixel shifting based super-resolution algorithm to effectively recover much higher resolution digital holograms of the objects, permitting sub-micron spatial resolution to be achieved across the entire sensor chip active area, which is also equivalent to the imaging field-of-view (24 mm2) due to unit magnification. We demonstrate the success of this pixel super-resolution approach by imaging patterned transparent substrates, blood smear samples, as well as Caenoharbditis Elegans. PMID:20588977

Super-Resolution Scanning Laser Microscopy Based on Virtually Structured Detection

PubMed Central

Zhi, Yanan; Wang, Benquan; Yao, Xincheng

2016-01-01

Light microscopy plays a key role in biological studies and medical diagnosis. The spatial resolution of conventional optical microscopes is limited to approximately half the wavelength of the illumination light as a result of the diffraction limit. Several approaches—including confocal microscopy, stimulated emission depletion microscopy, stochastic optical reconstruction microscopy, photoactivated localization microscopy, and structured illumination microscopy—have been established to achieve super-resolution imaging. However, none of these methods is suitable for the super-resolution ophthalmoscopy of retinal structures because of laser safety issues and inevitable eye movements. We recently experimentally validated virtually structured detection (VSD) as an alternative strategy to extend the diffraction limit. Without the complexity of structured illumination, VSD provides an easy, low-cost, and phase artifact–free strategy to achieve super-resolution in scanning laser microscopy. In this article we summarize the basic principles of the VSD method, review our demonstrated single-point and line-scan super-resolution systems, and discuss both technical challenges and the potential of VSD-based instrumentation for super-resolution ophthalmoscopy of the retina. PMID:27480461

Three-dimensional nanometre localization of nanoparticles to enhance super-resolution microscopy

NASA Astrophysics Data System (ADS)

Bon, Pierre; Bourg, Nicolas; Lécart, Sandrine; Monneret, Serge; Fort, Emmanuel; Wenger, Jérôme; Lévêque-Fort, Sandrine

2015-07-01

Meeting the nanometre resolution promised by super-resolution microscopy techniques (pointillist: PALM, STORM, scanning: STED) requires stabilizing the sample drifts in real time during the whole acquisition process. Metal nanoparticles are excellent probes to track the lateral drifts as they provide crisp and photostable information. However, achieving nanometre axial super-localization is still a major challenge, as diffraction imposes large depths-of-fields. Here we demonstrate fast full three-dimensional nanometre super-localization of gold nanoparticles through simultaneous intensity and phase imaging with a wavefront-sensing camera based on quadriwave lateral shearing interferometry. We show how to combine the intensity and phase information to provide the key to the third axial dimension. Presently, we demonstrate even in the occurrence of large three-dimensional fluctuations of several microns, unprecedented sub-nanometre localization accuracies down to 0.7 nm in lateral and 2.7 nm in axial directions at 50 frames per second. We demonstrate that nanoscale stabilization greatly enhances the image quality and resolution in direct stochastic optical reconstruction microscopy imaging.

Under the Microscope: Single-Domain Antibodies for Live-Cell Imaging and Super-Resolution Microscopy.

PubMed

Traenkle, Bjoern; Rothbauer, Ulrich

2017-01-01

Single-domain antibodies (sdAbs) have substantially expanded the possibilities of advanced cellular imaging such as live-cell or super-resolution microscopy to visualize cellular antigens and their dynamics. In addition to their unique properties including small size, high stability, and solubility in many environments, sdAbs can be efficiently functionalized according to the needs of the respective imaging approach. Genetically encoded intrabodies fused to fluorescent proteins (chromobodies) have become versatile tools to study dynamics of endogenous proteins in living cells. Additionally, sdAbs conjugated to organic dyes were shown to label cellular structures with high density and minimal fluorophore displacement making them highly attractive probes for super-resolution microscopy. Here, we review recent advances of the chromobody technology to visualize localization and dynamics of cellular targets and the application of chromobody-based cell models for compound screening. Acknowledging the emerging importance of super-resolution microscopy in cell biology, we further discuss advantages and challenges of sdAbs for this technology.

Sub-pixel mapping of hyperspectral imagery using super-resolution

NASA Astrophysics Data System (ADS)

Sharma, Shreya; Sharma, Shakti; Buddhiraju, Krishna M.

2016-04-01

With the development of remote sensing technologies, it has become possible to obtain an overview of landscape elements which helps in studying the changes on earth's surface due to climate, geological, geomorphological and human activities. Remote sensing measures the electromagnetic radiations from the earth's surface and match the spectral similarity between the observed signature and the known standard signatures of the various targets. However, problem lies when image classification techniques assume pixels to be pure. In hyperspectral imagery, images have high spectral resolution but poor spatial resolution. Therefore, the spectra obtained is often contaminated due to the presence of mixed pixels and causes misclassification. To utilise this high spectral information, spatial resolution has to be enhanced. Many factors make the spatial resolution one of the most expensive and hardest to improve in imaging systems. To solve this problem, post-processing of hyperspectral images is done to retrieve more information from the already acquired images. The algorithm to enhance spatial resolution of the images by dividing them into sub-pixels is known as super-resolution and several researches have been done in this domain.In this paper, we propose a new method for super-resolution based on ant colony optimization and review the popular methods of sub-pixel mapping of hyperspectral images along with their comparative analysis.

Microsphere-aided optical microscopy and its applications for super-resolution imaging

NASA Astrophysics Data System (ADS)

Upputuri, Paul Kumar; Pramanik, Manojit

2017-12-01

The spatial resolution of a standard optical microscope (SOM) is limited by diffraction. In visible spectrum, SOM can provide ∼ 200 nm resolution. To break the diffraction limit several approaches were developed including scanning near field microscopy, metamaterial super-lenses, nanoscale solid immersion lenses, super-oscillatory lenses, confocal fluorescence microscopy, techniques that exploit non-linear response of fluorophores like stimulated emission depletion microscopy, stochastic optical reconstruction microscopy, etc. Recently, photonic nanojet generated by a dielectric microsphere was used to break the diffraction limit. The microsphere-approach is simple, cost-effective and can be implemented under a standard microscope, hence it has gained enormous attention for super-resolution imaging. In this article, we briefly review the microsphere approach and its applications for super-resolution imaging in various optical imaging modalities.

Measuring true localization accuracy in super resolution microscopy with DNA-origami nanostructures

NASA Astrophysics Data System (ADS)

Reuss, Matthias; Fördős, Ferenc; Blom, Hans; Öktem, Ozan; Högberg, Björn; Brismar, Hjalmar

2017-02-01

A common method to assess the performance of (super resolution) microscopes is to use the localization precision of emitters as an estimate for the achieved resolution. Naturally, this is widely used in super resolution methods based on single molecule stochastic switching. This concept suffers from the fact that it is hard to calibrate measures against a real sample (a phantom), because true absolute positions of emitters are almost always unknown. For this reason, resolution estimates are potentially biased in an image since one is blind to true position accuracy, i.e. deviation in position measurement from true positions. We have solved this issue by imaging nanorods fabricated with DNA-origami. The nanorods used are designed to have emitters attached at each end in a well-defined and highly conserved distance. These structures are widely used to gauge localization precision. Here, we additionally determined the true achievable localization accuracy and compared this figure of merit to localization precision values for two common super resolution microscope methods STED and STORM.

Bayesian Deconvolution for Angular Super-Resolution in Forward-Looking Scanning Radar

PubMed Central

Zha, Yuebo; Huang, Yulin; Sun, Zhichao; Wang, Yue; Yang, Jianyu

2015-01-01

Scanning radar is of notable importance for ground surveillance, terrain mapping and disaster rescue. However, the angular resolution of a scanning radar image is poor compared to the achievable range resolution. This paper presents a deconvolution algorithm for angular super-resolution in scanning radar based on Bayesian theory, which states that the angular super-resolution can be realized by solving the corresponding deconvolution problem with the maximum a posteriori (MAP) criterion. The algorithm considers that the noise is composed of two mutually independent parts, i.e., a Gaussian signal-independent component and a Poisson signal-dependent component. In addition, the Laplace distribution is used to represent the prior information about the targets under the assumption that the radar image of interest can be represented by the dominant scatters in the scene. Experimental results demonstrate that the proposed deconvolution algorithm has higher precision for angular super-resolution compared with the conventional algorithms, such as the Tikhonov regularization algorithm, the Wiener filter and the Richardson–Lucy algorithm. PMID:25806871

Demosaiced pixel super-resolution in digital holography for multiplexed computational color imaging on-a-chip (Conference Presentation)

NASA Astrophysics Data System (ADS)

Wu, Yichen; Zhang, Yibo; Luo, Wei; Ozcan, Aydogan

2017-03-01

Digital holographic on-chip microscopy achieves large space-bandwidth-products (e.g., >1 billion) by making use of pixel super-resolution techniques. To synthesize a digital holographic color image, one can take three sets of holograms representing the red (R), green (G) and blue (B) parts of the spectrum and digitally combine them to synthesize a color image. The data acquisition efficiency of this sequential illumination process can be improved by 3-fold using wavelength-multiplexed R, G and B illumination that simultaneously illuminates the sample, and using a Bayer color image sensor with known or calibrated transmission spectra to digitally demultiplex these three wavelength channels. This demultiplexing step is conventionally used with interpolation-based Bayer demosaicing methods. However, because the pixels of different color channels on a Bayer image sensor chip are not at the same physical location, conventional interpolation-based demosaicing process generates strong color artifacts, especially at rapidly oscillating hologram fringes, which become even more pronounced through digital wave propagation and phase retrieval processes. Here, we demonstrate that by merging the pixel super-resolution framework into the demultiplexing process, such color artifacts can be greatly suppressed. This novel technique, termed demosaiced pixel super-resolution (D-PSR) for digital holographic imaging, achieves very similar color imaging performance compared to conventional sequential R,G,B illumination, with 3-fold improvement in image acquisition time and data-efficiency. We successfully demonstrated the color imaging performance of this approach by imaging stained Pap smears. The D-PSR technique is broadly applicable to high-throughput, high-resolution digital holographic color microscopy techniques that can be used in resource-limited-settings and point-of-care offices.

Single image super-resolution via an iterative reproducing kernel Hilbert space method.

PubMed

Deng, Liang-Jian; Guo, Weihong; Huang, Ting-Zhu

2016-11-01

Image super-resolution, a process to enhance image resolution, has important applications in satellite imaging, high definition television, medical imaging, etc. Many existing approaches use multiple low-resolution images to recover one high-resolution image. In this paper, we present an iterative scheme to solve single image super-resolution problems. It recovers a high quality high-resolution image from solely one low-resolution image without using a training data set. We solve the problem from image intensity function estimation perspective and assume the image contains smooth and edge components. We model the smooth components of an image using a thin-plate reproducing kernel Hilbert space (RKHS) and the edges using approximated Heaviside functions. The proposed method is applied to image patches, aiming to reduce computation and storage. Visual and quantitative comparisons with some competitive approaches show the effectiveness of the proposed method.

Super-resolution method for face recognition using nonlinear mappings on coherent features.

PubMed

Huang, Hua; He, Huiting

2011-01-01

Low-resolution (LR) of face images significantly decreases the performance of face recognition. To address this problem, we present a super-resolution method that uses nonlinear mappings to infer coherent features that favor higher recognition of the nearest neighbor (NN) classifiers for recognition of single LR face image. Canonical correlation analysis is applied to establish the coherent subspaces between the principal component analysis (PCA) based features of high-resolution (HR) and LR face images. Then, a nonlinear mapping between HR/LR features can be built by radial basis functions (RBFs) with lower regression errors in the coherent feature space than in the PCA feature space. Thus, we can compute super-resolved coherent features corresponding to an input LR image according to the trained RBF model efficiently and accurately. And, face identity can be obtained by feeding these super-resolved features to a simple NN classifier. Extensive experiments on the Facial Recognition Technology, University of Manchester Institute of Science and Technology, and Olivetti Research Laboratory databases show that the proposed method outperforms the state-of-the-art face recognition algorithms for single LR image in terms of both recognition rate and robustness to facial variations of pose and expression.

Super-Resolution Optical Fluctuation Bio-Imaging with Dual-Color Carbon Nanodots.

PubMed

Chizhik, Anna M; Stein, Simon; Dekaliuk, Mariia O; Battle, Christopher; Li, Weixing; Huss, Anja; Platen, Mitja; Schaap, Iwan A T; Gregor, Ingo; Demchenko, Alexander P; Schmidt, Christoph F; Enderlein, Jörg; Chizhik, Alexey I

2016-01-13

Success in super-resolution imaging relies on a proper choice of fluorescent probes. Here, we suggest novel easily produced and biocompatible nanoparticles-carbon nanodots-for super-resolution optical fluctuation bioimaging (SOFI). The particles revealed an intrinsic dual-color fluorescence, which corresponds to two subpopulations of particles of different electric charges. The neutral nanoparticles localize to cellular nuclei suggesting their potential use as an inexpensive, easily produced nucleus-specific label. The single particle study revealed that the carbon nanodots possess a unique hybrid combination of fluorescence properties exhibiting characteristics of both dye molecules and semiconductor nanocrystals. The results suggest that charge trapping and redistribution on the surface of the particles triggers their transitions between emissive and dark states. These findings open up new possibilities for the utilization of carbon nanodots in the various super-resolution microscopy methods based on stochastic optical switching.

Super-resolution links vinculin localization to function in focal adhesions.

PubMed

Giannone, Grégory

2015-07-01

Integrin-based focal adhesions integrate biochemical and biomechanical signals from the extracellular matrix and the actin cytoskeleton. The combination of three-dimensional super-resolution imaging and loss- or gain-of-function protein mutants now links the nanoscale dynamic localization of proteins to their activation and function within focal adhesions.

Super-Resolution Imaging Strategies for Cell Biologists Using a Spinning Disk Microscope

PubMed Central

Hosny, Neveen A.; Song, Mingying; Connelly, John T.; Ameer-Beg, Simon; Knight, Martin M.; Wheeler, Ann P.

2013-01-01

In this study we use a spinning disk confocal microscope (SD) to generate super-resolution images of multiple cellular features from any plane in the cell. We obtain super-resolution images by using stochastic intensity fluctuations of biological probes, combining Photoactivation Light-Microscopy (PALM)/Stochastic Optical Reconstruction Microscopy (STORM) methodologies. We compared different image analysis algorithms for processing super-resolution data to identify the most suitable for analysis of particular cell structures. SOFI was chosen for X and Y and was able to achieve a resolution of ca. 80 nm; however higher resolution was possible >30 nm, dependant on the super-resolution image analysis algorithm used. Our method uses low laser power and fluorescent probes which are available either commercially or through the scientific community, and therefore it is gentle enough for biological imaging. Through comparative studies with structured illumination microscopy (SIM) and widefield epifluorescence imaging we identified that our methodology was advantageous for imaging cellular structures which are not immediately at the cell-substrate interface, which include the nuclear architecture and mitochondria. We have shown that it was possible to obtain two coloured images, which highlights the potential this technique has for high-content screening, imaging of multiple epitopes and live cell imaging. PMID:24130668

Low-light-level image super-resolution reconstruction based on iterative projection photon localization algorithm

NASA Astrophysics Data System (ADS)

Ying, Changsheng; Zhao, Peng; Li, Ye

2018-01-01

The intensified charge-coupled device (ICCD) is widely used in the field of low-light-level (LLL) imaging. The LLL images captured by ICCD suffer from low spatial resolution and contrast, and the target details can hardly be recognized. Super-resolution (SR) reconstruction of LLL images captured by ICCDs is a challenging issue. The dispersion in the double-proximity-focused image intensifier is the main factor that leads to a reduction in image resolution and contrast. We divide the integration time into subintervals that are short enough to get photon images, so the overlapping effect and overstacking effect of dispersion can be eliminated. We propose an SR reconstruction algorithm based on iterative projection photon localization. In the iterative process, the photon image is sliced by projection planes, and photons are screened under the constraints of regularity. The accurate position information of the incident photons in the reconstructed SR image is obtained by the weighted centroids calculation. The experimental results show that the spatial resolution and contrast of our SR image are significantly improved.

Machine Learning Based Single-Frame Super-Resolution Processing for Lensless Blood Cell Counting

PubMed Central

Huang, Xiwei; Jiang, Yu; Liu, Xu; Xu, Hang; Han, Zhi; Rong, Hailong; Yang, Haiping; Yan, Mei; Yu, Hao

2016-01-01

A lensless blood cell counting system integrating microfluidic channel and a complementary metal oxide semiconductor (CMOS) image sensor is a promising technique to miniaturize the conventional optical lens based imaging system for point-of-care testing (POCT). However, such a system has limited resolution, making it imperative to improve resolution from the system-level using super-resolution (SR) processing. Yet, how to improve resolution towards better cell detection and recognition with low cost of processing resources and without degrading system throughput is still a challenge. In this article, two machine learning based single-frame SR processing types are proposed and compared for lensless blood cell counting, namely the Extreme Learning Machine based SR (ELMSR) and Convolutional Neural Network based SR (CNNSR). Moreover, lensless blood cell counting prototypes using commercial CMOS image sensors and custom designed backside-illuminated CMOS image sensors are demonstrated with ELMSR and CNNSR. When one captured low-resolution lensless cell image is input, an improved high-resolution cell image will be output. The experimental results show that the cell resolution is improved by 4×, and CNNSR has 9.5% improvement over the ELMSR on resolution enhancing performance. The cell counting results also match well with a commercial flow cytometer. Such ELMSR and CNNSR therefore have the potential for efficient resolution improvement in lensless blood cell counting systems towards POCT applications. PMID:27827837

SRRF: Universal live-cell super-resolution microscopy.

PubMed

Culley, Siân; Tosheva, Kalina L; Matos Pereira, Pedro; Henriques, Ricardo

2018-08-01

Super-resolution microscopy techniques break the diffraction limit of conventional optical microscopy to achieve resolutions approaching tens of nanometres. The major advantage of such techniques is that they provide resolutions close to those obtainable with electron microscopy while maintaining the benefits of light microscopy such as a wide palette of high specificity molecular labels, straightforward sample preparation and live-cell compatibility. Despite this, the application of super-resolution microscopy to dynamic, living samples has thus far been limited and often requires specialised, complex hardware. Here we demonstrate how a novel analytical approach, Super-Resolution Radial Fluctuations (SRRF), is able to make live-cell super-resolution microscopy accessible to a wider range of researchers. We show its applicability to live samples expressing GFP using commercial confocal as well as laser- and LED-based widefield microscopes, with the latter achieving long-term timelapse imaging with minimal photobleaching. Copyright © 2018 The Authors. Published by Elsevier Ltd.. All rights reserved.

Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

NASA Astrophysics Data System (ADS)

Zou, Zhenzhen; Luo, Xinghong; Yu, Qiang

2018-02-01

Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to measure the changes of sample temperature, morphology and volume. Then, the specific heat, surface tension, viscosity changes and sample density can be obtained. Considering that the falling speed of the material sample droplet is approximately 31.3 m/s when it reaches the bottom of a 50-meter-high drop tube, a high-speed camera with a collection rate of up to 106 frames/s is required to image the falling droplet. However, at the high-speed mode, very few pixels, approximately 48-120, will be obtained in each exposure time, which results in low image quality. Super-resolution image reconstruction is an algorithm that provides finer details than the sampling grid of a given imaging device by increasing the number of pixels per unit area in the image. In this work, we demonstrate the application of single image-resolution reconstruction in the microgravity and electrostatic levitation for the first time. Here, using the image super-resolution method based on sparse representation, a low-resolution droplet image can be reconstructed. Employed Yang's related dictionary model, high- and low-resolution image patches were combined with dictionary training, and high- and low-resolution-related dictionaries were obtained. The online double-sparse dictionary training algorithm was used in the study of related dictionaries and overcome the shortcomings of the traditional training algorithm with small image patch. During the stage of image reconstruction, the algorithm of kernel regression is added, which effectively overcomes the shortcomings of the Yang image's edge blurs.

Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

NASA Astrophysics Data System (ADS)

Zou, Zhenzhen; Luo, Xinghong; Yu, Qiang

2018-05-01

Microgravity and containerless conditions, which are produced via electrostatic levitation combined with a drop tube, are important when studying the intrinsic properties of new metastable materials. Generally, temperature and image sensors can be used to measure the changes of sample temperature, morphology and volume. Then, the specific heat, surface tension, viscosity changes and sample density can be obtained. Considering that the falling speed of the material sample droplet is approximately 31.3 m/s when it reaches the bottom of a 50-meter-high drop tube, a high-speed camera with a collection rate of up to 106 frames/s is required to image the falling droplet. However, at the high-speed mode, very few pixels, approximately 48-120, will be obtained in each exposure time, which results in low image quality. Super-resolution image reconstruction is an algorithm that provides finer details than the sampling grid of a given imaging device by increasing the number of pixels per unit area in the image. In this work, we demonstrate the application of single image-resolution reconstruction in the microgravity and electrostatic levitation for the first time. Here, using the image super-resolution method based on sparse representation, a low-resolution droplet image can be reconstructed. Employed Yang's related dictionary model, high- and low-resolution image patches were combined with dictionary training, and high- and low-resolution-related dictionaries were obtained. The online double-sparse dictionary training algorithm was used in the study of related dictionaries and overcome the shortcomings of the traditional training algorithm with small image patch. During the stage of image reconstruction, the algorithm of kernel regression is added, which effectively overcomes the shortcomings of the Yang image's edge blurs.

Super-resolution using a light inception layer in convolutional neural network

NASA Astrophysics Data System (ADS)

Mou, Qinyang; Guo, Jun

2018-04-01

Recently, several models based on CNN architecture have achieved great result on Single Image Super-Resolution (SISR) problem. In this paper, we propose an image super-resolution method (SR) using a light inception layer in convolutional network (LICN). Due to the strong representation ability of our well-designed inception layer that can learn richer representation with less parameters, we can build our model with shallow architecture that can reduce the effect of vanishing gradients problem and save computational costs. Our model strike a balance between computational speed and the quality of the result. Compared with state-of-the-art result, we produce comparable or better results with faster computational speed.

Super Resolution Imaging Applied to Scientific Images

DTIC Science & Technology

2007-05-01

norm has found favor in the image restoration community because it allows discontinuities in its solution. As opposed to the L2 norm it does not...Oxford University Press. 31) Malay Kumar Nema , S.Rakshit and S.Chaudhuri,”Edge Model Based High Resolution Image Genration”Indian Conference on...Society of America, vol. 11, no. 2, pp. 572- 579, February 1994 37) M. Nema , S. Rakshit and S. Chaudhuri, ``Edge Model Based High Resolution Image

Super-Resolution Enhancement From Multiple Overlapping Images: A Fractional Area Technique

NASA Astrophysics Data System (ADS)

Michaels, Joshua A.

With the availability of large quantities of relatively low-resolution data from several decades of space borne imaging, methods of creating an accurate, higher-resolution image from the multiple lower-resolution images (i.e. super-resolution), have been developed almost since such imagery has been around. The fractional-area super-resolution technique developed in this thesis has never before been documented. Satellite orbits, like Landsat, have a quantifiable variation, which means each image is not centered on the exact same spot more than once and the overlapping information from these multiple images may be used for super-resolution enhancement. By splitting a single initial pixel into many smaller, desired pixels, a relationship can be created between them using the ratio of the area within the initial pixel. The ideal goal for this technique is to obtain smaller pixels with exact values and no error, yielding a better potential result than those methods that yield interpolated pixel values with consequential loss of spatial resolution. A Fortran 95 program was developed to perform all calculations associated with the fractional-area super-resolution technique. The fractional areas are calculated using traditional trigonometry and coordinate geometry and Linear Algebra Package (LAPACK; Anderson et al., 1999) is used to solve for the higher-resolution pixel values. In order to demonstrate proof-of-concept, a synthetic dataset was created using the intrinsic Fortran random number generator and Adobe Illustrator CS4 (for geometry). To test the real-life application, digital pictures from a Sony DSC-S600 digital point-and-shoot camera with a tripod were taken of a large US geological map under fluorescent lighting. While the fractional-area super-resolution technique works in perfect synthetic conditions, it did not successfully produce a reasonable or consistent solution in the digital photograph enhancement test. The prohibitive amount of processing time (up to 60 days for a relatively small enhancement area) severely limits the practical usefulness of fraction-area super-resolution. Fractional-area super-resolution is very sensitive to relative input image co-registration, which must be accurate to a sub-pixel degree. However, use of this technique, if input conditions permit, could be applied as a "pinpoint" super-resolution technique. Such an application could be possible by only applying it to only very small areas with very good input image co-registration.

3D super resolution range-gated imaging for canopy reconstruction and measurement

NASA Astrophysics Data System (ADS)

Huang, Hantao; Wang, Xinwei; Sun, Liang; Lei, Pingshun; Fan, Songtao; Zhou, Yan

2018-01-01

In this paper, we proposed a method of canopy reconstruction and measurement based on 3D super resolution range-gated imaging. In this method, high resolution 2D intensity images are grasped by active gate imaging, and 3D images of canopy are reconstructed by triangular-range-intensity correlation algorithm at the same time. A range-gated laser imaging system(RGLIS) is established based on 808 nm diode laser and gated intensified charge-coupled device (ICCD) camera with 1392´1040 pixels. The proof experiments have been performed for potted plants located 75m away and trees located 165m away. The experiments show it that can acquire more than 1 million points per frame, and 3D imaging has the spatial resolution about 0.3mm at the distance of 75m and the distance accuracy about 10 cm. This research is beneficial for high speed acquisition of canopy structure and non-destructive canopy measurement.

Resolution enhancement of tri-stereo remote sensing images by super resolution methods

NASA Astrophysics Data System (ADS)

Tuna, Caglayan; Akoguz, Alper; Unal, Gozde; Sertel, Elif

2016-10-01

Super resolution (SR) refers to generation of a High Resolution (HR) image from a decimated, blurred, low-resolution (LR) image set, which can be either a single frame or multi-frame that contains a collection of several images acquired from slightly different views of the same observation area. In this study, we propose a novel application of tri-stereo Remote Sensing (RS) satellite images to the super resolution problem. Since the tri-stereo RS images of the same observation area are acquired from three different viewing angles along the flight path of the satellite, these RS images are properly suited to a SR application. We first estimate registration between the chosen reference LR image and other LR images to calculate the sub pixel shifts among the LR images. Then, the warping, blurring and down sampling matrix operators are created as sparse matrices to avoid high memory and computational requirements, which would otherwise make the RS-SR solution impractical. Finally, the overall system matrix, which is constructed based on the obtained operator matrices is used to obtain the estimate HR image in one step in each iteration of the SR algorithm. Both the Laplacian and total variation regularizers are incorporated separately into our algorithm and the results are presented to demonstrate an improved quantitative performance against the standard interpolation method as well as improved qualitative results due expert evaluations.

TH-EF-BRA-11: Feasibility of Super-Resolution Time-Resolved 4DMRI for Multi-Breath Volumetric Motion Simulation in Radiotherapy Planning

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, G; Zakian, K; Deasy, J

Purpose: To develop a novel super-resolution time-resolved 4DMRI technique to evaluate multi-breath, irregular and complex organ motion without respiratory surrogate for radiotherapy planning. Methods: The super-resolution time-resolved (TR) 4DMRI approach combines a series of low-resolution 3D cine MRI images acquired during free breathing (FB) with a high-resolution breath-hold (BH) 3DMRI via deformable image registration (DIR). Five volunteers participated in the study under an IRB-approved protocol. The 3D cine images with voxel size of 5×5×5 mm{sup 3} at two volumes per second (2Hz) were acquired coronally using a T1 fast field echo sequence, half-scan (0.8) acceleration, and SENSE (3) parallel imaging.more » Phase-encoding was set in the lateral direction to minimize motion artifacts. The BH image with voxel size of 2×2×2 mm{sup 3} was acquired using the same sequence within 10 seconds. A demons-based DIR program was employed to produce super-resolution 2Hz 4DMRI. Registration quality was visually assessed using difference images between TR 4DMRI and 3D cine and quantitatively assessed using average voxel correlation. The fidelity of the 3D cine images was assessed using a gel phantom and a 1D motion platform by comparing mobile and static images. Results: Owing to voxel intensity similarity using the same MRI scanning sequence, accurate DIR between FB and BH images is achieved. The voxel correlations between 3D cine and TR 4DMRI are greater than 0.92 in all cases and the difference images illustrate minimal residual error with little systematic patterns. The 3D cine images of the mobile gel phantom preserve object geometry with minimal scanning artifacts. Conclusion: The super-resolution time-resolved 4DMRI technique has been achieved via DIR, providing a potential solution for multi-breath motion assessment. Accurate DIR mapping has been achieved to map high-resolution BH images to low-resolution FB images, producing 2Hz volumetric high-resolution 4DMRI. Further validation and improvement are still required prior to clinical applications. This study is in part supported by the NIH (U54CA137788/U54CA132378).« less

Light-sheet Bayesian microscopy enables deep-cell super-resolution imaging of heterochromatin in live human embryonic stem cells.

PubMed

Hu, Ying S; Zhu, Quan; Elkins, Keri; Tse, Kevin; Li, Yu; Fitzpatrick, James A J; Verma, Inder M; Cang, Hu

2013-01-01

Heterochromatin in the nucleus of human embryonic cells plays an important role in the epigenetic regulation of gene expression. The architecture of heterochromatin and its dynamic organization remain elusive because of the lack of fast and high-resolution deep-cell imaging tools. We enable this task by advancing instrumental and algorithmic implementation of the localization-based super-resolution technique. We present light-sheet Bayesian super-resolution microscopy (LSBM). We adapt light-sheet illumination for super-resolution imaging by using a novel prism-coupled condenser design to illuminate a thin slice of the nucleus with high signal-to-noise ratio. Coupled with a Bayesian algorithm that resolves overlapping fluorophores from high-density areas, we show, for the first time, nanoscopic features of the heterochromatin structure in both fixed and live human embryonic stem cells. The enhanced temporal resolution allows capturing the dynamic change of heterochromatin with a lateral resolution of 50-60 nm on a time scale of 2.3 s. Light-sheet Bayesian microscopy opens up broad new possibilities of probing nanometer-scale nuclear structures and real-time sub-cellular processes and other previously difficult-to-access intracellular regions of living cells at the single-molecule, and single cell level.

Light-sheet Bayesian microscopy enables deep-cell super-resolution imaging of heterochromatin in live human embryonic stem cells

PubMed Central

Hu, Ying S; Zhu, Quan; Elkins, Keri; Tse, Kevin; Li, Yu; Fitzpatrick, James A J; Verma, Inder M; Cang, Hu

2016-01-01

Background Heterochromatin in the nucleus of human embryonic cells plays an important role in the epigenetic regulation of gene expression. The architecture of heterochromatin and its dynamic organization remain elusive because of the lack of fast and high-resolution deep-cell imaging tools. We enable this task by advancing instrumental and algorithmic implementation of the localization-based super-resolution technique. Results We present light-sheet Bayesian super-resolution microscopy (LSBM). We adapt light-sheet illumination for super-resolution imaging by using a novel prism-coupled condenser design to illuminate a thin slice of the nucleus with high signal-to-noise ratio. Coupled with a Bayesian algorithm that resolves overlapping fluorophores from high-density areas, we show, for the first time, nanoscopic features of the heterochromatin structure in both fixed and live human embryonic stem cells. The enhanced temporal resolution allows capturing the dynamic change of heterochromatin with a lateral resolution of 50–60 nm on a time scale of 2.3 s. Conclusion Light-sheet Bayesian microscopy opens up broad new possibilities of probing nanometer-scale nuclear structures and real-time sub-cellular processes and other previously difficult-to-access intracellular regions of living cells at the single-molecule, and single cell level. PMID:27795878

Super-resolution and super-localization microscopy: A novel tool for imaging chemical and biological processes

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dong, Bin

2015-01-01

Optical microscopy imaging of single molecules and single particles is an essential method for studying fundamental biological and chemical processes at the molecular and nanometer scale. The best spatial resolution (~ λ/2) achievable in traditional optical microscopy is governed by the diffraction of light. However, single molecule-based super-localization and super-resolution microscopy imaging techniques have emerged in the past decade. Individual molecules can be localized with nanometer scale accuracy and precision for studying of biological and chemical processes.This work uncovered the heterogeneous properties of the pore structures. In this dissertation, the coupling of molecular transport and catalytic reaction at the singlemore » molecule and single particle level in multilayer mesoporous nanocatalysts was elucidated. Most previous studies dealt with these two important phenomena separately. A fluorogenic oxidation reaction of non-fluorescent amplex red to highly fluorescent resorufin was tested. The diffusion behavior of single resorufin molecules in aligned nanopores was studied using total internal reflection fluorescence microscopy (TIRFM).« less

Nanoscopy for nanoscience: how super-resolution microscopy extends imaging for nanotechnology.

PubMed

Johnson, Sam A

2015-01-01

Imaging methods have presented scientists with powerful means of investigation for centuries. The ability to resolve structures using light microscopes is though limited to around 200 nm. Fluorescence-based super-resolution light microscopy techniques of several principles and methods have emerged in recent years and offer great potential to extend the capabilities of microscopy. This resolution improvement is especially promising for nanoscience where the imaging of nanoscale structures is inherently restricted by the resolution limit of standard forms of light microscopy. Resolution can be improved by several distinct approaches including structured illumination microscopy, stimulated emission depletion, and single-molecule positioning methods such as photoactivated localization microscopy and stochastic optical reconstruction microscopy and several derivative variations of each of these. These methods involve substantial differences in the resolutions achievable in the different axes, speed of acquisition, compatibility with different labels, ease of use, hardware complexity, and compatibility with live biological samples. The field of super-resolution imaging and its application to nanotechnology is relatively new and still rapidly developing. An overview of how these methods may be used with nanomaterials is presented with some examples of pioneering uses of these approaches. © 2014 Wiley Periodicals, Inc.

Correlative super-resolution fluorescence microscopy combined with optical coherence microscopy

NASA Astrophysics Data System (ADS)

Kim, Sungho; Kim, Gyeong Tae; Jang, Soohyun; Shim, Sang-Hee; Bae, Sung Chul

2015-03-01

Recent development of super-resolution fluorescence imaging technique such as stochastic optical reconstruction microscopy (STORM) and photoactived localization microscope (PALM) has brought us beyond the diffraction limits. It allows numerous opportunities in biology because vast amount of formerly obscured molecular structures, due to lack of spatial resolution, now can be directly observed. A drawback of fluorescence imaging, however, is that it lacks complete structural information. For this reason, we have developed a super-resolution multimodal imaging system based on STORM and full-field optical coherence microscopy (FF-OCM). FF-OCM is a type of interferometry systems based on a broadband light source and a bulk Michelson interferometer, which provides label-free and non-invasive visualization of biological samples. The integration between the two systems is simple because both systems use a wide-field illumination scheme and a conventional microscope. This combined imaging system gives us both functional information at a molecular level (~20nm) and structural information at the sub-cellular level (~1μm). For thick samples such as tissue slices, while FF-OCM is readily capable of imaging the 3D architecture, STORM suffer from aberrations and high background fluorescence that substantially degrade the resolution. In order to correct the aberrations in thick tissues, we employed an adaptive optics system in the detection path of the STORM microscope. We used our multimodal system to obtain images on brain tissue samples with structural and functional information.

Introduction to the virtual special issue on super-resolution imaging techniques

NASA Astrophysics Data System (ADS)

Cao, Liangcai; Liu, Zhengjun

2017-12-01

Until quite recently, the resolution of optical imaging instruments, including telescopes, cameras and microscopes, was considered to be limited by the diffraction of light and by image sensors. In the past few years, many exciting super-resolution approaches have emerged that demonstrate intriguing ways to bypass the classical limit in optics and detectors. More and more research groups are engaged in the study of advanced super-resolution schemes, devices, algorithms, systems, and applications [1-6]. Super-resolution techniques involve new methods in science and engineering of optics [7,8], measurements [9,10], chemistry [11,12] and information [13,14]. Promising applications, particularly in biomedical research and semiconductor industry, have been successfully demonstrated.

Super-resolution optical imaging and magnetometry using NV centers in diamond

NASA Astrophysics Data System (ADS)

Jaskula, Jean-Christophe; Trifonov, Alexei; Glenn, David; Bar-Gill, Nir; Walsworth, Ronald

2013-05-01

We report progress done on the development and application of depletion-based techniques for super-resolution (nanoscale) optical imaging and magnetometry using NV centers in diamond. In particulare we are integrating stimulated emission depletion (STED) and ground state depletion (GSD) imaging techniques with advanced pulsed sequences for AC magnetometry. NV centers in diamond do not bleach under optical excitation, have long-lived electronic spin coherence and spin-state-dependent fluorescence, and are not biotoxic. Thus NV-diamond has great potential in quantum science and as a nanoscale magnetic biosensor.

3D high- and super-resolution imaging using single-objective SPIM.

PubMed

Galland, Remi; Grenci, Gianluca; Aravind, Ajay; Viasnoff, Virgile; Studer, Vincent; Sibarita, Jean-Baptiste

2015-07-01

Single-objective selective-plane illumination microscopy (soSPIM) is achieved with micromirrored cavities combined with a laser beam-steering unit installed on a standard inverted microscope. The illumination and detection are done through the same objective. soSPIM can be used with standard sample preparations and features high background rejection and efficient photon collection, allowing for 3D single-molecule-based super-resolution imaging of whole cells or cell aggregates. Using larger mirrors enabled us to broaden the capabilities of our system to image Drosophila embryos.

All-passive pixel super-resolution of time-stretch imaging

PubMed Central

Chan, Antony C. S.; Ng, Ho-Cheung; Bogaraju, Sharat C. V.; So, Hayden K. H.; Lam, Edmund Y.; Tsia, Kevin K.

2017-01-01

Based on image encoding in a serial-temporal format, optical time-stretch imaging entails a stringent requirement of state-of-the-art fast data acquisition unit in order to preserve high image resolution at an ultrahigh frame rate — hampering the widespread utilities of such technology. Here, we propose a pixel super-resolution (pixel-SR) technique tailored for time-stretch imaging that preserves pixel resolution at a relaxed sampling rate. It harnesses the subpixel shifts between image frames inherently introduced by asynchronous digital sampling of the continuous time-stretch imaging process. Precise pixel registration is thus accomplished without any active opto-mechanical subpixel-shift control or other additional hardware. Here, we present the experimental pixel-SR image reconstruction pipeline that restores high-resolution time-stretch images of microparticles and biological cells (phytoplankton) at a relaxed sampling rate (≈2–5 GSa/s)—more than four times lower than the originally required readout rate (20 GSa/s) — is thus effective for high-throughput label-free, morphology-based cellular classification down to single-cell precision. Upon integration with the high-throughput image processing technology, this pixel-SR time-stretch imaging technique represents a cost-effective and practical solution for large scale cell-based phenotypic screening in biomedical diagnosis and machine vision for quality control in manufacturing. PMID:28303936

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI)

PubMed Central

Hainsworth, A. H.; Lee, S.; Patel, A.; Poon, W. W.; Knight, A. E.

2018-01-01

Aims The spatial resolution of light microscopy is limited by the wavelength of visible light (the ‘diffraction limit’, approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Methods Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8–32 nm) and for SOFI (effective pixel size 80 nm). Results In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Conclusions Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. PMID:28696566

Super-resolution imaging of subcortical white matter using stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI).

PubMed

Hainsworth, A H; Lee, S; Foot, P; Patel, A; Poon, W W; Knight, A E

2018-06-01

The spatial resolution of light microscopy is limited by the wavelength of visible light (the 'diffraction limit', approximately 250 nm). Resolution of sub-cellular structures, smaller than this limit, is possible with super resolution methods such as stochastic optical reconstruction microscopy (STORM) and super-resolution optical fluctuation imaging (SOFI). We aimed to resolve subcellular structures (axons, myelin sheaths and astrocytic processes) within intact white matter, using STORM and SOFI. Standard cryostat-cut sections of subcortical white matter from donated human brain tissue and from adult rat and mouse brain were labelled, using standard immunohistochemical markers (neurofilament-H, myelin-associated glycoprotein, glial fibrillary acidic protein, GFAP). Image sequences were processed for STORM (effective pixel size 8-32 nm) and for SOFI (effective pixel size 80 nm). In human, rat and mouse, subcortical white matter high-quality images for axonal neurofilaments, myelin sheaths and filamentous astrocytic processes were obtained. In quantitative measurements, STORM consistently underestimated width of axons and astrocyte processes (compared with electron microscopy measurements). SOFI provided more accurate width measurements, though with somewhat lower spatial resolution than STORM. Super resolution imaging of intact cryo-cut human brain tissue is feasible. For quantitation, STORM can under-estimate diameters of thin fluorescent objects. SOFI is more robust. The greatest limitation for super-resolution imaging in brain sections is imposed by sample preparation. We anticipate that improved strategies to reduce autofluorescence and to enhance fluorophore performance will enable rapid expansion of this approach. © 2017 British Neuropathological Society.

Super-resolution reconstruction of hyperspectral images.

PubMed

Akgun, Toygar; Altunbasak, Yucel; Mersereau, Russell M

2005-11-01

Hyperspectral images are used for aerial and space imagery applications, including target detection, tracking, agricultural, and natural resource exploration. Unfortunately, atmospheric scattering, secondary illumination, changing viewing angles, and sensor noise degrade the quality of these images. Improving their resolution has a high payoff, but applying super-resolution techniques separately to every spectral band is problematic for two main reasons. First, the number of spectral bands can be in the hundreds, which increases the computational load excessively. Second, considering the bands separately does not make use of the information that is present across them. Furthermore, separate band super-resolution does not make use of the inherent low dimensionality of the spectral data, which can effectively be used to improve the robustness against noise. In this paper, we introduce a novel super-resolution method for hyperspectral images. An integral part of our work is to model the hyperspectral image acquisition process. We propose a model that enables us to represent the hyperspectral observations from different wavelengths as weighted linear combinations of a small number of basis image planes. Then, a method for applying super resolution to hyperspectral images using this model is presented. The method fuses information from multiple observations and spectral bands to improve spatial resolution and reconstruct the spectrum of the observed scene as a combination of a small number of spectral basis functions.

Wavelet Filter Banks for Super-Resolution SAR Imaging

NASA Technical Reports Server (NTRS)

Sheybani, Ehsan O.; Deshpande, Manohar; Memarsadeghi, Nargess

2011-01-01

This paper discusses Innovative wavelet-based filter banks designed to enhance the analysis of super resolution Synthetic Aperture Radar (SAR) images using parametric spectral methods and signal classification algorithms, SAR finds applications In many of NASA's earth science fields such as deformation, ecosystem structure, and dynamics of Ice, snow and cold land processes, and surface water and ocean topography. Traditionally, standard methods such as Fast-Fourier Transform (FFT) and Inverse Fast-Fourier Transform (IFFT) have been used to extract Images from SAR radar data, Due to non-parametric features of these methods and their resolution limitations and observation time dependence, use of spectral estimation and signal pre- and post-processing techniques based on wavelets to process SAR radar data has been proposed. Multi-resolution wavelet transforms and advanced spectral estimation techniques have proven to offer efficient solutions to this problem.

Optimized multiple linear mappings for single image super-resolution

NASA Astrophysics Data System (ADS)

Zhang, Kaibing; Li, Jie; Xiong, Zenggang; Liu, Xiuping; Gao, Xinbo

2017-12-01

Learning piecewise linear regression has been recognized as an effective way for example learning-based single image super-resolution (SR) in literature. In this paper, we employ an expectation-maximization (EM) algorithm to further improve the SR performance of our previous multiple linear mappings (MLM) based SR method. In the training stage, the proposed method starts with a set of linear regressors obtained by the MLM-based method, and then jointly optimizes the clustering results and the low- and high-resolution subdictionary pairs for regression functions by using the metric of the reconstruction errors. In the test stage, we select the optimal regressor for SR reconstruction by accumulating the reconstruction errors of m-nearest neighbors in the training set. Thorough experimental results carried on six publicly available datasets demonstrate that the proposed SR method can yield high-quality images with finer details and sharper edges in terms of both quantitative and perceptual image quality assessments.

Super-resolution reconstruction of MR image with a novel residual learning network algorithm

NASA Astrophysics Data System (ADS)

Shi, Jun; Liu, Qingping; Wang, Chaofeng; Zhang, Qi; Ying, Shihui; Xu, Haoyu

2018-04-01

Spatial resolution is one of the key parameters of magnetic resonance imaging (MRI). The image super-resolution (SR) technique offers an alternative approach to improve the spatial resolution of MRI due to its simplicity. Convolutional neural networks (CNN)-based SR algorithms have achieved state-of-the-art performance, in which the global residual learning (GRL) strategy is now commonly used due to its effectiveness for learning image details for SR. However, the partial loss of image details usually happens in a very deep network due to the degradation problem. In this work, we propose a novel residual learning-based SR algorithm for MRI, which combines both multi-scale GRL and shallow network block-based local residual learning (LRL). The proposed LRL module works effectively in capturing high-frequency details by learning local residuals. One simulated MRI dataset and two real MRI datasets have been used to evaluate our algorithm. The experimental results show that the proposed SR algorithm achieves superior performance to all of the other compared CNN-based SR algorithms in this work.

Resolution enhancement in deep-tissue nanoparticle imaging based on plasmonic saturated excitation microscopy

NASA Astrophysics Data System (ADS)

Deka, Gitanjal; Nishida, Kentaro; Mochizuki, Kentaro; Ding, Hou-Xian; Fujita, Katsumasa; Chu, Shi-Wei

2018-03-01

Recently, many resolution enhancing techniques are demonstrated, but most of them are severely limited for deep tissue applications. For example, wide-field based localization techniques lack the ability of optical sectioning, and structured light based techniques are susceptible to beam distortion due to scattering/aberration. Saturated excitation (SAX) microscopy, which relies on temporal modulation that is less affected when penetrating into tissues, should be the best candidate for deep-tissue resolution enhancement. Nevertheless, although fluorescence saturation has been successfully adopted in SAX, it is limited by photobleaching, and its practical resolution enhancement is less than two-fold. Recently, we demonstrated plasmonic SAX which provides bleaching-free imaging with three-fold resolution enhancement. Here we show that the three-fold resolution enhancement is sustained throughout the whole working distance of an objective, i.e., 200 μm, which is the deepest super-resolution record to our knowledge, and is expected to extend into deeper tissues. In addition, SAX offers the advantage of background-free imaging by rejecting unwanted scattering background from biological tissues. This study provides an inspirational direction toward deep-tissue super-resolution imaging and has the potential in tumor monitoring and beyond.

Multi-frame super-resolution with quality self-assessment for retinal fundus videos.

PubMed

Köhler, Thomas; Brost, Alexander; Mogalle, Katja; Zhang, Qianyi; Köhler, Christiane; Michelson, Georg; Hornegger, Joachim; Tornow, Ralf P

2014-01-01

This paper proposes a novel super-resolution framework to reconstruct high-resolution fundus images from multiple low-resolution video frames in retinal fundus imaging. Natural eye movements during an examination are used as a cue for super-resolution in a robust maximum a-posteriori scheme. In order to compensate heterogeneous illumination on the fundus, we integrate retrospective illumination correction for photometric registration to the underlying imaging model. Our method utilizes quality self-assessment to provide objective quality scores for reconstructed images as well as to select regularization parameters automatically. In our evaluation on real data acquired from six human subjects with a low-cost video camera, the proposed method achieved considerable enhancements of low-resolution frames and improved noise and sharpness characteristics by 74%. In terms of image analysis, we demonstrate the importance of our method for the improvement of automatic blood vessel segmentation as an example application, where the sensitivity was increased by 13% using super-resolution reconstruction.

Scene-based nonuniformity correction and enhancement: pixel statistics and subpixel motion.

PubMed

Zhao, Wenyi; Zhang, Chao

2008-07-01

We propose a framework for scene-based nonuniformity correction (NUC) and nonuniformity correction and enhancement (NUCE) that is required for focal-plane array-like sensors to obtain clean and enhanced-quality images. The core of the proposed framework is a novel registration-based nonuniformity correction super-resolution (NUCSR) method that is bootstrapped by statistical scene-based NUC methods. Based on a comprehensive imaging model and an accurate parametric motion estimation, we are able to remove severe/structured nonuniformity and in the presence of subpixel motion to simultaneously improve image resolution. One important feature of our NUCSR method is the adoption of a parametric motion model that allows us to (1) handle many practical scenarios where parametric motions are present and (2) carry out perfect super-resolution in principle by exploring available subpixel motions. Experiments with real data demonstrate the efficiency of the proposed NUCE framework and the effectiveness of the NUCSR method.

A Microfluidic Cytometer for Complete Blood Count With a 3.2-Megapixel, 1.1- μm-Pitch Super-Resolution Image Sensor in 65-nm BSI CMOS.

PubMed

Liu, Xu; Huang, Xiwei; Jiang, Yu; Xu, Hang; Guo, Jing; Hou, Han Wei; Yan, Mei; Yu, Hao

2017-08-01

Based on a 3.2-Megapixel 1.1- μm-pitch super-resolution (SR) CMOS image sensor in a 65-nm backside-illumination process, a lens-free microfluidic cytometer for complete blood count (CBC) is demonstrated in this paper. Backside-illumination improves resolution and contrast at the device level with elimination of surface treatment when integrated with microfluidic channels. A single-frame machine-learning-based SR processing is further realized at system level for resolution correction with minimum hardware resources. The demonstrated microfluidic cytometer can detect the platelet cells (< 2 μm) required in CBC, hence is promising for point-of-care diagnostics.

High Resolution Bathymetry Estimation Improvement with Single Image Super-Resolution Algorithm Super-Resolution Forests

DTIC Science & Technology

2017-01-26

Naval Research Laboratory Washington, DC 20375-5320 NRL/MR/5514--17-9692 High Resolution Bathymetry Estimation Improvement with Single Image Super...collection of information is estimated to average 1 hour per response, including the time for reviewing instructions, searching existing data sources...gathering and maintaining the data needed, and completing and reviewing this collection of information. Send comments regarding this burden estimate

Development of bimolecular fluorescence complementation using rsEGFP2 for detection and super-resolution imaging of protein-protein interactions in live cells

PubMed Central

Wang, Sheng; Ding, Miao; Chen, Xuanze; Chang, Lei; Sun, Yujie

2017-01-01

Direct visualization of protein-protein interactions (PPIs) at high spatial and temporal resolution in live cells is crucial for understanding the intricate and dynamic behaviors of signaling protein complexes. Recently, bimolecular fluorescence complementation (BiFC) assays have been combined with super-resolution imaging techniques including PALM and SOFI to visualize PPIs at the nanometer spatial resolution. RESOLFT nanoscopy has been proven as a powerful live-cell super-resolution imaging technique. With regard to the detection and visualization of PPIs in live cells with high temporal and spatial resolution, here we developed a BiFC assay using split rsEGFP2, a highly photostable and reversibly photoswitchable fluorescent protein previously developed for RESOLFT nanoscopy. Combined with parallelized RESOLFT microscopy, we demonstrated the high spatiotemporal resolving capability of a rsEGFP2-based BiFC assay by detecting and visualizing specifically the heterodimerization interactions between Bcl-xL and Bak as well as the dynamics of the complex on mitochondria membrane in live cells. PMID:28663931

Portable lensless wide-field microscopy imaging platform based on digital inline holography and multi-frame pixel super-resolution

PubMed Central

Sobieranski, Antonio C; Inci, Fatih; Tekin, H Cumhur; Yuksekkaya, Mehmet; Comunello, Eros; Cobra, Daniel; von Wangenheim, Aldo; Demirci, Utkan

2017-01-01

In this paper, an irregular displacement-based lensless wide-field microscopy imaging platform is presented by combining digital in-line holography and computational pixel super-resolution using multi-frame processing. The samples are illuminated by a nearly coherent illumination system, where the hologram shadows are projected into a complementary metal-oxide semiconductor-based imaging sensor. To increase the resolution, a multi-frame pixel resolution approach is employed to produce a single holographic image from multiple frame observations of the scene, with small planar displacements. Displacements are resolved by a hybrid approach: (i) alignment of the LR images by a fast feature-based registration method, and (ii) fine adjustment of the sub-pixel information using a continuous optimization approach designed to find the global optimum solution. Numerical method for phase-retrieval is applied to decode the signal and reconstruct the morphological details of the analyzed sample. The presented approach was evaluated with various biological samples including sperm and platelets, whose dimensions are in the order of a few microns. The obtained results demonstrate a spatial resolution of 1.55 µm on a field-of-view of ≈30 mm2. PMID:29657866

In vivo super-resolution imaging of transient retinal phototropism evoked by oblique light stimulation.

PubMed

Lu, Yiming; Liu, Changgeng; Yao, Xincheng

2018-05-01

Rod-dominated transient retinal phototropism (TRP) has been observed in freshly isolated retinas, promising a noninvasive biomarker for objective assessment of retinal physiology. However, in vivo mapping of TRP is challenging due to its subcellular signal magnitude and fast time course. We report here a virtually structured detection-based super-resolution ophthalmoscope to achieve subcellular spatial resolution and millisecond temporal resolution for in vivo imaging of TRP. Spatiotemporal properties of in vivo TRP were characterized corresponding to variable light intensity stimuli, confirming that TRP is tightly correlated with early stages of phototransduction. (2018) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE).

Multi-pulse pumping for far-field super-resolution imaging

NASA Astrophysics Data System (ADS)

Requena, Sebastian; Raut, Sangram; Doan, Hung; Kimball, Joe; Fudala, Rafal; Borejdo, Julian; Gryczynski, Ignacy; Strzhemechny, Yuri; Gryczynski, Zygmunt

2016-02-01

Recently, far-field optical imaging with a resolution significantly beyond diffraction limit has attracted tremendous attention allowing for high resolution imaging in living objects. Various methods have been proposed that are divided in to two basic approaches; deterministic super-resolution like STED or RESOLFT and stochastic super-resolution like PALM or STORM. We propose to achieve super-resolution in far-field fluorescence imaging by the use of controllable (on-demand) bursts of pulses that can change the fluorescence signal of long-lived component over one order of magnitude. We demonstrate that two beads, one labeled with a long-lived dye and another with a short-lived dye, separated by a distance lower than 100 nm can be easily resolved in a single experiment. The proposed method can be used to separate two biological structures in a cell by targeting them with two antibodies labeled with long-lived and short-lived fluorophores.

Tilted Light Sheet Microscopy with 3D Point Spread Functions for Single-Molecule Super-Resolution Imaging in Mammalian Cells.

PubMed

Gustavsson, Anna-Karin; Petrov, Petar N; Lee, Maurice Y; Shechtman, Yoav; Moerner, W E

2018-02-01

To obtain a complete picture of subcellular nanostructures, cells must be imaged with high resolution in all three dimensions (3D). Here, we present tilted light sheet microscopy with 3D point spread functions (TILT3D), an imaging platform that combines a novel, tilted light sheet illumination strategy with engineered long axial range point spread functions (PSFs) for low-background, 3D super localization of single molecules as well as 3D super-resolution imaging in thick cells. TILT3D is built upon a standard inverted microscope and has minimal custom parts. The axial positions of the single molecules are encoded in the shape of the PSF rather than in the position or thickness of the light sheet, and the light sheet can therefore be formed using simple optics. The result is flexible and user-friendly 3D super-resolution imaging with tens of nm localization precision throughout thick mammalian cells. We validated TILT3D for 3D super-resolution imaging in mammalian cells by imaging mitochondria and the full nuclear lamina using the double-helix PSF for single-molecule detection and the recently developed Tetrapod PSF for fiducial bead tracking and live axial drift correction. We envision TILT3D to become an important tool not only for 3D super-resolution imaging, but also for live whole-cell single-particle and single-molecule tracking.

Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images

NASA Astrophysics Data System (ADS)

Ardila, Juan P.; Tolpekin, Valentyn A.; Bijker, Wietske; Stein, Alfred

2011-11-01

Identification of tree crowns from remote sensing requires detailed spectral information and submeter spatial resolution imagery. Traditional pixel-based classification techniques do not fully exploit the spatial and spectral characteristics of remote sensing datasets. We propose a contextual and probabilistic method for detection of tree crowns in urban areas using a Markov random field based super resolution mapping (SRM) approach in very high resolution images. Our method defines an objective energy function in terms of the conditional probabilities of panchromatic and multispectral images and it locally optimizes the labeling of tree crown pixels. Energy and model parameter values are estimated from multiple implementations of SRM in tuning areas and the method is applied in QuickBird images to produce a 0.6 m tree crown map in a city of The Netherlands. The SRM output shows an identification rate of 66% and commission and omission errors in small trees and shrub areas. The method outperforms tree crown identification results obtained with maximum likelihood, support vector machines and SRM at nominal resolution (2.4 m) approaches.

Time multiplexing based extended depth of focus imaging.

PubMed

Ilovitsh, Asaf; Zalevsky, Zeev

2016-01-01

We propose to utilize the time multiplexing super resolution method to extend the depth of focus of an imaging system. In standard time multiplexing, the super resolution is achieved by generating duplication of the optical transfer function in the spectrum domain, by the use of moving gratings. While this improves the spatial resolution, it does not increase the depth of focus. By changing the gratings frequency and, by that changing the duplication positions, it is possible to obtain an extended depth of focus. The proposed method is presented analytically, demonstrated via numerical simulations and validated by a laboratory experiment.

Single-Image Super-Resolution Based on Rational Fractal Interpolation.

PubMed

Zhang, Yunfeng; Fan, Qinglan; Bao, Fangxun; Liu, Yifang; Zhang, Caiming

2018-08-01

This paper presents a novel single-image super-resolution (SR) procedure, which upscales a given low-resolution (LR) input image to a high-resolution image while preserving the textural and structural information. First, we construct a new type of bivariate rational fractal interpolation model and investigate its analytical properties. This model has different forms of expression with various values of the scaling factors and shape parameters; thus, it can be employed to better describe image features than current interpolation schemes. Furthermore, this model combines the advantages of rational interpolation and fractal interpolation, and its effectiveness is validated through theoretical analysis. Second, we develop a single-image SR algorithm based on the proposed model. The LR input image is divided into texture and non-texture regions, and then, the image is interpolated according to the characteristics of the local structure. Specifically, in the texture region, the scaling factor calculation is the critical step. We present a method to accurately calculate scaling factors based on local fractal analysis. Extensive experiments and comparisons with the other state-of-the-art methods show that our algorithm achieves competitive performance, with finer details and sharper edges.

Image inpainting and super-resolution using non-local recursive deep convolutional network with skip connections

NASA Astrophysics Data System (ADS)

Liu, Miaofeng

2017-07-01

In recent years, deep convolutional neural networks come into use in image inpainting and super-resolution in many fields. Distinct to most of the former methods requiring to know beforehand the local information for corrupted pixels, we propose a 20-depth fully convolutional network to learn an end-to-end mapping a dataset of damaged/ground truth subimage pairs realizing non-local blind inpainting and super-resolution. As there often exist image with huge corruptions or inpainting on a low-resolution image that the existing approaches unable to perform well, we also share parameters in local area of layers to achieve spatial recursion and enlarge the receptive field. To avoid the difficulty of training this deep neural network, skip-connections between symmetric convolutional layers are designed. Experimental results shows that the proposed method outperforms state-of-the-art methods for diverse corrupting and low-resolution conditions, it works excellently when realizing super-resolution and image inpainting simultaneously

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images

PubMed Central

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-01-01

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures. PMID:26007744

Multisensor Super Resolution Using Directionally-Adaptive Regularization for UAV Images.

PubMed

Kang, Wonseok; Yu, Soohwan; Ko, Seungyong; Paik, Joonki

2015-05-22

In various unmanned aerial vehicle (UAV) imaging applications, the multisensor super-resolution (SR) technique has become a chronic problem and attracted increasing attention. Multisensor SR algorithms utilize multispectral low-resolution (LR) images to make a higher resolution (HR) image to improve the performance of the UAV imaging system. The primary objective of the paper is to develop a multisensor SR method based on the existing multispectral imaging framework instead of using additional sensors. In order to restore image details without noise amplification or unnatural post-processing artifacts, this paper presents an improved regularized SR algorithm by combining the directionally-adaptive constraints and multiscale non-local means (NLM) filter. As a result, the proposed method can overcome the physical limitation of multispectral sensors by estimating the color HR image from a set of multispectral LR images using intensity-hue-saturation (IHS) image fusion. Experimental results show that the proposed method provides better SR results than existing state-of-the-art SR methods in the sense of objective measures.

3D single-molecule super-resolution microscopy with a tilted light sheet.

PubMed

Gustavsson, Anna-Karin; Petrov, Petar N; Lee, Maurice Y; Shechtman, Yoav; Moerner, W E

2018-01-09

Tilted light sheet microscopy with 3D point spread functions (TILT3D) combines a novel, tilted light sheet illumination strategy with long axial range point spread functions (PSFs) for low-background, 3D super-localization of single molecules as well as 3D super-resolution imaging in thick cells. Because the axial positions of the single emitters are encoded in the shape of each single-molecule image rather than in the position or thickness of the light sheet, the light sheet need not be extremely thin. TILT3D is built upon a standard inverted microscope and has minimal custom parts. The result is simple and flexible 3D super-resolution imaging with tens of nm localization precision throughout thick mammalian cells. We validate TILT3D for 3D super-resolution imaging in mammalian cells by imaging mitochondria and the full nuclear lamina using the double-helix PSF for single-molecule detection and the recently developed tetrapod PSFs for fiducial bead tracking and live axial drift correction.

Large scale superres 3D imaging: light-sheet single-molecule localization microscopy (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lu, Chieh Han; Chen, Peilin; Chen, Bi-Chang

2017-02-01

Optical imaging techniques provide much important information in understanding life science especially cellular structure and morphology because "seeing is believing". However, the resolution of optical imaging is limited by the diffraction limit, which is discovered by Ernst Abbe, i.e. λ/2(NA) (NA is the numerical aperture of the objective lens). Fluorescence super-resolution microscopic techniques such as Stimulated emission depletion microscopy (STED), Photoactivated localization microscopy (PALM), and Stochastic optical reconstruction microscopy (STORM) are invented to have the capability of seeing biological entities down to molecular level that are smaller than the diffraction limit (around 200-nm in lateral resolution). These techniques do not physically violate the Abbe limit of resolution but exploit the photoluminescence properties and labelling specificity of fluorescence molecules to achieve super-resolution imaging. However, these super-resolution techniques limit most of their applications to the 2D imaging of fixed or dead samples due to the high laser power needed or slow speed for the localization process. Extended from 2D imaging, light sheet microscopy has been proven to have a lot of applications on 3D imaging at much better spatiotemporal resolutions due to its intrinsic optical sectioning and high imaging speed. Herein, we combine the advantage of localization microscopy and light-sheet microscopy to have super-resolved cellular imaging in 3D across large field of view. With high-density labeled spontaneous blinking fluorophore and wide-field detection of light-sheet microscopy, these allow us to construct 3D super-resolution multi-cellular imaging at high speed ( minutes) by light-sheet single-molecule localization microscopy.

Super-resolution convolutional neural network for the improvement of the image quality of magnified images in chest radiographs

NASA Astrophysics Data System (ADS)

Umehara, Kensuke; Ota, Junko; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

2017-02-01

Single image super-resolution (SR) method can generate a high-resolution (HR) image from a low-resolution (LR) image by enhancing image resolution. In medical imaging, HR images are expected to have a potential to provide a more accurate diagnosis with the practical application of HR displays. In recent years, the super-resolution convolutional neural network (SRCNN), which is one of the state-of-the-art deep learning based SR methods, has proposed in computer vision. In this study, we applied and evaluated the SRCNN scheme to improve the image quality of magnified images in chest radiographs. For evaluation, a total of 247 chest X-rays were sampled from the JSRT database. The 247 chest X-rays were divided into 93 training cases with non-nodules and 152 test cases with lung nodules. The SRCNN was trained using the training dataset. With the trained SRCNN, the HR image was reconstructed from the LR one. We compared the image quality of the SRCNN and conventional image interpolation methods, nearest neighbor, bilinear and bicubic interpolations. For quantitative evaluation, we measured two image quality metrics, peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). In the SRCNN scheme, PSNR and SSIM were significantly higher than those of three interpolation methods (p<0.001). Visual assessment confirmed that the SRCNN produced much sharper edge than conventional interpolation methods without any obvious artifacts. These preliminary results indicate that the SRCNN scheme significantly outperforms conventional interpolation algorithms for enhancing image resolution and that the use of the SRCNN can yield substantial improvement of the image quality of magnified images in chest radiographs.

TestSTORM: Simulator for optimizing sample labeling and image acquisition in localization based super-resolution microscopy

PubMed Central

Sinkó, József; Kákonyi, Róbert; Rees, Eric; Metcalf, Daniel; Knight, Alex E.; Kaminski, Clemens F.; Szabó, Gábor; Erdélyi, Miklós

2014-01-01

Localization-based super-resolution microscopy image quality depends on several factors such as dye choice and labeling strategy, microscope quality and user-defined parameters such as frame rate and number as well as the image processing algorithm. Experimental optimization of these parameters can be time-consuming and expensive so we present TestSTORM, a simulator that can be used to optimize these steps. TestSTORM users can select from among four different structures with specific patterns, dye and acquisition parameters. Example results are shown and the results of the vesicle pattern are compared with experimental data. Moreover, image stacks can be generated for further evaluation using localization algorithms, offering a tool for further software developments. PMID:24688813

Projections onto Convex Sets Super-Resolution Reconstruction Based on Point Spread Function Estimation of Low-Resolution Remote Sensing Images

PubMed Central

Fan, Chong; Wu, Chaoyun; Li, Grand; Ma, Jun

2017-01-01

To solve the problem on inaccuracy when estimating the point spread function (PSF) of the ideal original image in traditional projection onto convex set (POCS) super-resolution (SR) reconstruction, this paper presents an improved POCS SR algorithm based on PSF estimation of low-resolution (LR) remote sensing images. The proposed algorithm can improve the spatial resolution of the image and benefit agricultural crop visual interpolation. The PSF of the high-resolution (HR) image is unknown in reality. Therefore, analysis of the relationship between the PSF of the HR image and the PSF of the LR image is important to estimate the PSF of the HR image by using multiple LR images. In this study, the linear relationship between the PSFs of the HR and LR images can be proven. In addition, the novel slant knife-edge method is employed, which can improve the accuracy of the PSF estimation of LR images. Finally, the proposed method is applied to reconstruct airborne digital sensor 40 (ADS40) three-line array images and the overlapped areas of two adjacent GF-2 images by embedding the estimated PSF of the HR image to the original POCS SR algorithm. Experimental results show that the proposed method yields higher quality of reconstructed images than that produced by the blind SR method and the bicubic interpolation method. PMID:28208837

Novel Super-Resolution Approach to Time-Resolved Volumetric 4-Dimensional Magnetic Resonance Imaging With High Spatiotemporal Resolution for Multi-Breathing Cycle Motion Assessment

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Guang, E-mail: lig2@mskcc.org; Wei, Jie; Kadbi, Mo

Purpose: To develop and evaluate a super-resolution approach to reconstruct time-resolved 4-dimensional magnetic resonance imaging (TR-4DMRI) with a high spatiotemporal resolution for multi-breathing cycle motion assessment. Methods and Materials: A super-resolution approach was developed to combine fast 3-dimensional (3D) cine MRI with low resolution during free breathing (FB) and high-resolution 3D static MRI during breath hold (BH) using deformable image registration. A T1-weighted, turbo field echo sequence, coronal 3D cine acquisition, partial Fourier approximation, and SENSitivity Encoding parallel acceleration were used. The same MRI pulse sequence, field of view, and acceleration techniques were applied in both FB and BH acquisitions;more » the intensity-based Demons deformable image registration method was used. Under an institutional review board–approved protocol, 7 volunteers were studied with 3D cine FB scan (voxel size: 5 × 5 × 5 mm{sup 3}) at 2 Hz for 40 seconds and a 3D static BH scan (2 × 2 × 2 mm{sup 3}). To examine the image fidelity of 3D cine and super-resolution TR-4DMRI, a mobile gel phantom with multi-internal targets was scanned at 3 speeds and compared with the 3D static image. Image similarity among 3D cine, 4DMRI, and 3D static was evaluated visually using difference image and quantitatively using voxel intensity correlation and Dice index (phantom only). Multi-breathing-cycle waveforms were extracted and compared in both phantom and volunteer images using the 3D cine as the references. Results: Mild imaging artifacts were found in the 3D cine and TR-4DMRI of the mobile gel phantom with a Dice index of >0.95. Among 7 volunteers, the super-resolution TR-4DMRI yielded high voxel-intensity correlation (0.92 ± 0.05) and low voxel-intensity difference (<0.05). The detected motion differences between TR-4DMRI and 3D cine were −0.2 ± 0.5 mm (phantom) and −0.2 ± 1.9 mm (diaphragms). Conclusion: Super-resolution TR-4DMRI has been reconstructed with adequate temporal (2 Hz) and spatial (2 × 2 × 2 mm{sup 3}) resolutions. Further TR-4DMRI characterization and improvement are necessary before clinical applications. Multi-breathing cycles can be examined, providing patient-specific breathing irregularities and motion statistics for future 4D radiation therapy.« less

Single image super-resolution based on compressive sensing and improved TV minimization sparse recovery

NASA Astrophysics Data System (ADS)

Vishnukumar, S.; Wilscy, M.

2017-12-01

In this paper, we propose a single image Super-Resolution (SR) method based on Compressive Sensing (CS) and Improved Total Variation (TV) Minimization Sparse Recovery. In the CS framework, low-resolution (LR) image is treated as the compressed version of high-resolution (HR) image. Dictionary Training and Sparse Recovery are the two phases of the method. K-Singular Value Decomposition (K-SVD) method is used for dictionary training and the dictionary represents HR image patches in a sparse manner. Here, only the interpolated version of the LR image is used for training purpose and thereby the structural self similarity inherent in the LR image is exploited. In the sparse recovery phase the sparse representation coefficients with respect to the trained dictionary for LR image patches are derived using Improved TV Minimization method. HR image can be reconstructed by the linear combination of the dictionary and the sparse coefficients. The experimental results show that the proposed method gives better results quantitatively as well as qualitatively on both natural and remote sensing images. The reconstructed images have better visual quality since edges and other sharp details are preserved.

Evanescent-Wave Filtering in Images Using Remote Terahertz Structured Illumination

NASA Astrophysics Data System (ADS)

Flammini, M.; Pontecorvo, E.; Giliberti, V.; Rizza, C.; Ciattoni, A.; Ortolani, M.; DelRe, E.

2017-11-01

Imaging with structured illumination allows for the retrieval of subwavelength features of an object by conversion of evanescent waves into propagating waves. In conditions in which the object plane and the structured-illumination plane do not coincide, this conversion process is subject to progressive filtering of the components with high spatial frequency when the distance between the two planes increases, until the diffraction-limited lateral resolution is restored when the distance exceeds the extension of evanescent waves. We study the progressive filtering of evanescent waves by developing a remote super-resolution terahertz imaging system operating at a wavelength λ =1.00 mm , based on a freestanding knife edge and a reflective confocal terahertz microscope. In the images recorded with increasing knife-edge-to-object-plane distance, we observe the transition from a super-resolution of λ /17 ≃60 μ m to the diffraction-limited lateral resolution of Δ x ≃λ expected for our confocal microscope. The extreme nonparaxial conditions are analyzed in detail, exploiting the fact that, in the terahertz frequency range, the knife edge can be positioned at a variable subwavelength distance from the object plane. Electromagnetic simulations of radiation scattering by the knife edge reproduce the experimental super-resolution achieved.

Sparse coded image super-resolution using K-SVD trained dictionary based on regularized orthogonal matching pursuit.

PubMed

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2015-01-01

Image super-resolution (SR) plays a vital role in medical imaging that allows a more efficient and effective diagnosis process. Usually, diagnosing is difficult and inaccurate from low-resolution (LR) and noisy images. Resolution enhancement through conventional interpolation methods strongly affects the precision of consequent processing steps, such as segmentation and registration. Therefore, we propose an efficient sparse coded image SR reconstruction technique using a trained dictionary. We apply a simple and efficient regularized version of orthogonal matching pursuit (ROMP) to seek the coefficients of sparse representation. ROMP has the transparency and greediness of OMP and the robustness of the L1-minization that enhance the dictionary learning process to capture feature descriptors such as oriented edges and contours from complex images like brain MRIs. The sparse coding part of the K-SVD dictionary training procedure is modified by substituting OMP with ROMP. The dictionary update stage allows simultaneously updating an arbitrary number of atoms and vectors of sparse coefficients. In SR reconstruction, ROMP is used to determine the vector of sparse coefficients for the underlying patch. The recovered representations are then applied to the trained dictionary, and finally, an optimization leads to high-resolution output of high-quality. Experimental results demonstrate that the super-resolution reconstruction quality of the proposed scheme is comparatively better than other state-of-the-art schemes.

Super-Chelators for Advanced Protein Labeling in Living Cells.

PubMed

Gatterdam, Karl; Joest, Eike F; Dietz, Marina S; Heilemann, Mike; Tampé, Robert

2018-05-14

Live-cell labeling, super-resolution microscopy, single-molecule applications, protein localization, or chemically induced assembly are emerging approaches, which require specific and very small interaction pairs. The minimal disturbance of protein function is essential to derive unbiased insights into cellular processes. Herein, we define a new class of hexavalent N-nitrilotriacetic acid (hexaNTA) chelators, displaying the highest affinity and stability of all NTA-based small interaction pairs described so far. Coupled to bright organic fluorophores with fine-tuned photophysical properties, the super-chelator probes were delivered into human cells by chemically gated nanopores. These super-chelators permit kinetic profiling, multiplexed labeling of His 6 - and His 12 -tagged proteins as well as single-molecule-based super-resolution imaging. © 2018 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Improved vocal tract reconstruction and modeling using an image super-resolution technique.

PubMed

Zhou, Xinhui; Woo, Jonghye; Stone, Maureen; Prince, Jerry L; Espy-Wilson, Carol Y

2013-06-01

Magnetic resonance imaging has been widely used in speech production research. Often only one image stack (sagittal, axial, or coronal) is used for vocal tract modeling. As a result, complementary information from other available stacks is not utilized. To overcome this, a recently developed super-resolution technique was applied to integrate three orthogonal low-resolution stacks into one isotropic volume. The results on vowels show that the super-resolution volume produces better vocal tract visualization than any of the low-resolution stacks. Its derived area functions generally produce formant predictions closer to the ground truth, particularly for those formants sensitive to area perturbations at constrictions.

Super-resolution Microscopy in Plant Cell Imaging.

PubMed

Komis, George; Šamajová, Olga; Ovečka, Miroslav; Šamaj, Jozef

2015-12-01

Although the development of super-resolution microscopy methods dates back to 1994, relevant applications in plant cell imaging only started to emerge in 2010. Since then, the principal super-resolution methods, including structured-illumination microscopy (SIM), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), and stimulated emission depletion microscopy (STED), have been implemented in plant cell research. However, progress has been limited due to the challenging properties of plant material. Here we summarize the basic principles of existing super-resolution methods and provide examples of applications in plant science. The limitations imposed by the nature of plant material are reviewed and the potential for future applications in plant cell imaging is highlighted. Copyright © 2015 Elsevier Ltd. All rights reserved.

Joint estimation of high resolution images and depth maps from light field cameras

NASA Astrophysics Data System (ADS)

Ohashi, Kazuki; Takahashi, Keita; Fujii, Toshiaki

2014-03-01

Light field cameras are attracting much attention as tools for acquiring 3D information of a scene through a single camera. The main drawback of typical lenselet-based light field cameras is the limited resolution. This limitation comes from the structure where a microlens array is inserted between the sensor and the main lens. The microlens array projects 4D light field on a single 2D image sensor at the sacrifice of the resolution; the angular resolution and the position resolution trade-off under the fixed resolution of the image sensor. This fundamental trade-off remains after the raw light field image is converted to a set of sub-aperture images. The purpose of our study is to estimate a higher resolution image from low resolution sub-aperture images using a framework of super-resolution reconstruction. In this reconstruction, these sub-aperture images should be registered as accurately as possible. This registration is equivalent to depth estimation. Therefore, we propose a method where super-resolution and depth refinement are performed alternatively. Most of the process of our method is implemented by image processing operations. We present several experimental results using a Lytro camera, where we increased the resolution of a sub-aperture image by three times horizontally and vertically. Our method can produce clearer images compared to the original sub-aperture images and the case without depth refinement.

Development and Characterization of a Dither-Based Super-Resolution Reconstruction Method for Fiber Imaging Arrays

NASA Astrophysics Data System (ADS)

Languirand, Eric Robert

Chemical imaging is an important tool for providing insight into function, role, and spatial distribution of analytes. This thesis describes the use of imaging fiber bundles (IFB) for super-resolution reconstruction using surface enhanced Raman scattering (SERS) showing improvement in resolution with arrayed bundles for the first time. Additionally this thesis describes characteristics of the IFB with regards to cross-talk as a function of aperture size. The first part of this thesis characterizes the IFB for both tapered and untapered bundles in terms of cross-talk. Cross-talk is defined as the amount of light leaking from a central fiber element in the imaging fiber bundle to surrounding fiber elements. To make this measurement ubiquitous for all imaging bundles, quantum dots were employed. Untapered and tapered IFB possess cross-talk of 2% or less, with fiber elements down to 32nm. The second part of this thesis employs a super resolution reconstruction algorithm using projection onto convex sets for resolution improvement. When using IFB arrays, the point spread function (PSF) of the array can be known accurately if the fiber elements over fill the pixel detector array. Therefore, the use of the known PSF compared to a general blurring kernel was evaluated. Relative increases in resolution of 12% and 2% at the 95% confidence level are found, when compared to a reference image, for the general blurring kernel and PSF, respectively. The third part of this thesis shows for the first time the use of SERS with a dithered IFB array coupled with super-resolution reconstruction. The resolution improvement across a step-edge is shown to be approximately 20% when compared to a reference image. This provides an additional means of increasing the resolution of fiber bundles beyond that of just tapering. Furthermore, this provides a new avenue for nanoscale imaging using these bundles. Lastly, synthetic data with varying degrees of signal-to-noise (S/N) were employed to explore the relationship S/N has with the reconstruction process. It is generally shown that increasing the number images used in the reconstruction process and increasing the S/N will improve the reconstruction providing larger increases in resolution.

Pixel-super-resolved lensfree holography using adaptive relaxation factor and positional error correction

NASA Astrophysics Data System (ADS)

Zhang, Jialin; Chen, Qian; Sun, Jiasong; Li, Jiaji; Zuo, Chao

2018-01-01

Lensfree holography provides a new way to effectively bypass the intrinsical trade-off between the spatial resolution and field-of-view (FOV) of conventional lens-based microscopes. Unfortunately, due to the limited sensor pixel-size, unpredictable disturbance during image acquisition, and sub-optimum solution to the phase retrieval problem, typical lensfree microscopes only produce compromised imaging quality in terms of lateral resolution and signal-to-noise ratio (SNR). In this paper, we propose an adaptive pixel-super-resolved lensfree imaging (APLI) method to address the pixel aliasing problem by Z-scanning only, without resorting to subpixel shifting or beam-angle manipulation. Furthermore, an automatic positional error correction algorithm and adaptive relaxation strategy are introduced to enhance the robustness and SNR of reconstruction significantly. Based on APLI, we perform full-FOV reconstruction of a USAF resolution target across a wide imaging area of {29.85 mm2 and achieve half-pitch lateral resolution of 770 nm, surpassing 2.17 times of the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel-size (1.67 μm). Full-FOV imaging result of a typical dicot root is also provided to demonstrate its promising potential applications in biologic imaging.

Watching entangled circular DNA in real time with super-resolution

NASA Astrophysics Data System (ADS)

Jee, Ah-Young; Kim, Hyeongju; Granick, Steve

In this talk, we will show how we unraveled the conformational dynamics of entangled ring-shaped polymers in network, which is one of the most well-known problems in polymer physics, using deep imaging based on super-resolution fluorescence imaging, stimulated emission depletion (STED) microscopy. By using home-written software, we obtained the statistics of each of the hundreds of molecules, mapping out a large statistical distribution. Through inspection we not only found some aspects of the classic understanding of polymers, but some surprising aspects as well.

Point target detection utilizing super-resolution strategy for infrared scanning oversampling system

NASA Astrophysics Data System (ADS)

Wang, Longguang; Lin, Zaiping; Deng, Xinpu; An, Wei

2017-11-01

To improve the resolution of remote sensing infrared images, infrared scanning oversampling system is employed with information amount quadrupled, which contributes to the target detection. Generally the image data from double-line detector of infrared scanning oversampling system is shuffled to a whole oversampled image to be post-processed, whereas the aliasing between neighboring pixels leads to image degradation with a great impact on target detection. This paper formulates a point target detection method utilizing super-resolution (SR) strategy concerning infrared scanning oversampling system, with an accelerated SR strategy proposed to realize fast de-aliasing of the oversampled image and an adaptive MRF-based regularization designed to achieve the preserving and aggregation of target energy. Extensive experiments demonstrate the superior detection performance, robustness and efficiency of the proposed method compared with other state-of-the-art approaches.

Time multiplexing super-resolution nanoscopy based on the Brownian motion of gold nanoparticles

NASA Astrophysics Data System (ADS)

Ilovitsh, Tali; Ilovitsh, Asaf; Wagner, Omer; Zalevsky, Zeev

2017-02-01

Super-resolution localization microscopy can overcome the diffraction limit and achieve a tens of order improvement in resolution. It requires labeling the sample with fluorescent probes followed with their repeated cycles of activation and photobleaching. This work presents an alternative approach that is free from direct labeling and does not require the activation and photobleaching cycles. Fluorescently labeled gold nanoparticles in a solution are distributed on top of the sample. The nanoparticles move in a random Brownian motion, and interact with the sample. By obscuring different areas in the sample, the nanoparticles encode the sub-wavelength features. A sequence of images of the sample is captured and decoded by digital post processing to create the super-resolution image. The achievable resolution is limited by the additive noise and the size of the nanoparticles. Regular nanoparticles with diameter smaller than 100nm are barely seen in a conventional bright field microscope, thus fluorescently labeled gold nanoparticles were used, with proper

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy (iPALM).

PubMed

Wang, Yilin; Kanchanawong, Pakorn

2016-12-01

Fluorescence microscopy enables direct visualization of specific biomolecules within cells. However, for conventional fluorescence microscopy, the spatial resolution is restricted by diffraction to ~ 200 nm within the image plane and > 500 nm along the optical axis. As a result, fluorescence microscopy has long been severely limited in the observation of ultrastructural features within cells. The recent development of super resolution microscopy methods has overcome this limitation. In particular, the advent of photoswitchable fluorophores enables localization-based super resolution microscopy, which provides resolving power approaching the molecular-length scale. Here, we describe the application of a three-dimensional super resolution microscopy method based on single-molecule localization microscopy and multiphase interferometry, called interferometric PhotoActivated Localization Microscopy (iPALM). This method provides nearly isotropic resolution on the order of 20 nm in all three dimensions. Protocols for visualizing the filamentous actin cytoskeleton, including specimen preparation and operation of the iPALM instrument, are described here. These protocols are also readily adaptable and instructive for the study of other ultrastructural features in cells.

Supporting lander and rover operation: a novel super-resolution restoration technique

NASA Astrophysics Data System (ADS)

Tao, Yu; Muller, Jan-Peter

2015-04-01

Higher resolution imaging data is always desirable to critical rover engineering operations, such as landing site selection, path planning, and optical localisation. For current Mars missions, 25cm HiRISE images have been widely used by the MER & MSL engineering team for rover path planning and location registration/adjustment. However, 25cm is not high enough resolution to be able to view individual rocks (≤2m in size) or visualise the types of sedimentary features that rover onboard cameras might observe. Nevertheless, due to various physical constraints (e.g. telescope size and mass) from the imaging instruments themselves, one needs to be able to tradeoff spatial resolution and bandwidth. This means that future imaging systems are likely to be limited to resolve features larger than 25cm. We have developed a novel super-resolution algorithm/pipeline to be able to restore higher resolution image from the non-redundant sub-pixel information contained in multiple lower resolution raw images [Tao & Muller 2015]. We will demonstrate with experiments performed using 5-10 overlapped 25cm HiRISE images for MER-A, MER-B & MSL to resolve 5-10cm super resolution images that can be directly compared to rover imagery at a range of 5 metres from the rover cameras but in our case can be used to visualise features many kilometres away from the actual rover traverse. We will demonstrate how these super-resolution images together with image understanding software can be used to quantify rock size-frequency distributions as well as measure sedimentary rock layers for several critical sites for comparison with rover orthorectified image mosaic to demonstrate optimality of using our super-resolution resolved image to better support future lander and rover operation in future. We present the potential of super-resolution for virtual exploration to the ˜400 HiRISE areas which have been viewed 5 or more times and the potential application of this technique to all of the ESA ExoMars Trace Gas orbiter CaSSiS stereo, multi-angle and colour camera images from 2017 onwards. Acknowledgements: The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement No.312377 PRoViDE.

Parsing Stem Cell Lineage Development Using High Content Image Analysis of Epigenetic Spatial Markers.

PubMed

Kim, Joseph J; Moghe, Prabhas V

2018-06-14

This unit describes a protocol for acquiring and analyzing high-content super-resolution images of human stem cell nuclei for the characterization and classification of the cell differentiation paths based on distinct patterns of epigenetic mark organization. Here, we describe the cell culture, immunocytochemical labeling, super-resolution imaging parameters, and MATLAB-based quantitative image analysis approaches for monitoring human mesenchymal stem cells (hMSCs) and human induced pluripotent stem cells (hiPSCs) as the cells differentiate towards various lineages. Although this protocol uses specific cell types as examples, this approach could be easily extended to a variety of cell types and nuclear epigenetic and mechanosensitive biomarkers that are relevant to specific cell developmental scenarios. © 2018 by John Wiley & Sons, Inc. Copyright © 2018 John Wiley & Sons, Inc.

Breast Microcalcification Detection Using Super-Resolution Ultrasound Image Reconstruction

DTIC Science & Technology

2010-09-01

microcalcifications often occur as one of two types: calcium oxalate dihydrate or calcium hydroxyapatite. Their sizes range approximately from 0.1 mm to 0.5 mm...super-resolution imaging, ultrasound imaging, wave equation. 1. INTRODUCTION Microcalcifications, tiny specks of mineral deposits ( calcium ), are the

A user's guide to localization-based super-resolution fluorescence imaging.

PubMed

Dempsey, Graham T

2013-01-01

Advances in far-field fluorescence microscopy over the past decade have led to the development of super-resolution imaging techniques that provide more than an order of magnitude improvement in spatial resolution compared to conventional light microscopy. One such approach, called Stochastic Optical Reconstruction Microscopy (STORM) uses the sequential, nanometer-scale localization of individual fluorophores to reconstruct a high-resolution image of a structure of interest. This is an attractive method for biological investigation at the nanoscale due to its relative simplicity, both conceptually and practically in the laboratory. Like most research tools, however, the devil is in the details. The aim of this chapter is to serve as a guide for applying STORM to the study of biological samples. This chapter will discuss considerations for choosing a photoswitchable fluorescent probe, preparing a sample, selecting hardware for data acquisition, and collecting and analyzing data for image reconstruction. Copyright © 2013 Elsevier Inc. All rights reserved.

Compact three-dimensional super-resolution system based on fluorescence emission difference microscopy

NASA Astrophysics Data System (ADS)

Zhu, Dazhao; Chen, Youhua; Fang, Yue; Hussain, Anwar; Kuang, Cuifang; Zhou, Xiaoxu; Xu, Yingke; Liu, Xu

2017-12-01

A compact microscope system for three-dimensional (3-D) super-resolution imaging is presented. The super-resolution capability of the system is based on a size-reduced effective 3-D point spread function generated through the fluorescence emission difference (FED) method. The appropriate polarization direction distribution and manipulation allows the panel active area of the spatial light modulator to be fully utilized. This allows simultaneous modulation of the incident light by two kinds of phase masks to be performed with a single spatial light modulator in order to generate a 3-D negative spot. The system is more compact than standard 3-D FED systems while maintaining all the advantages of 3-D FED microscopy. The experimental results demonstrated the improvement in 3-D resolution by nearly 1.7 times and 1.6 times compared to the classic confocal resolution in the lateral and axial directions, respectively.

Tilted light sheet microscopy with 3D point spread functions for single-molecule super-resolution imaging in mammalian cells

NASA Astrophysics Data System (ADS)

Gustavsson, Anna-Karin; Petrov, Petar N.; Lee, Maurice Y.; Shechtman, Yoav; Moerner, W. E.

2018-02-01

To obtain a complete picture of subcellular nanostructures, cells must be imaged with high resolution in all three dimensions (3D). Here, we present tilted light sheet microscopy with 3D point spread functions (TILT3D), an imaging platform that combines a novel, tilted light sheet illumination strategy with engineered long axial range point spread functions (PSFs) for low-background, 3D super localization of single molecules as well as 3D super-resolution imaging in thick cells. TILT3D is built upon a standard inverted microscope and has minimal custom parts. The axial positions of the single molecules are encoded in the shape of the PSF rather than in the position or thickness of the light sheet, and the light sheet can therefore be formed using simple optics. The result is flexible and user-friendly 3D super-resolution imaging with tens of nm localization precision throughout thick mammalian cells. We validated TILT3D for 3D superresolution imaging in mammalian cells by imaging mitochondria and the full nuclear lamina using the double-helix PSF for single-molecule detection and the recently developed Tetrapod PSF for fiducial bead tracking and live axial drift correction. We envision TILT3D to become an important tool not only for 3D super-resolution imaging, but also for live whole-cell single-particle and single-molecule tracking.

Experimental assessment and analysis of super-resolution in fluorescence microscopy based on multiple-point spread function fitting of spectrally demultiplexed images

NASA Astrophysics Data System (ADS)

Nishimura, Takahiro; Kimura, Hitoshi; Ogura, Yusuke; Tanida, Jun

2018-06-01

This paper presents an experimental assessment and analysis of super-resolution microscopy based on multiple-point spread function fitting of spectrally demultiplexed images using a designed DNA structure as a test target. For the purpose, a DNA structure was designed to have binding sites at a certain interval that is smaller than the diffraction limit. The structure was labeled with several types of quantum dots (QDs) to acquire their spatial information as spectrally encoded images. The obtained images are analyzed with a point spread function multifitting algorithm to determine the QD locations that indicate the binding site positions. The experimental results show that the labeled locations can be observed beyond the diffraction-limited resolution using three-colored fluorescence images that were obtained with a confocal fluorescence microscope. Numerical simulations show that labeling with eight types of QDs enables the positions aligned at 27.2-nm pitches on the DNA structure to be resolved with high accuracy.

Single image super-resolution based on approximated Heaviside functions and iterative refinement

PubMed Central

Wang, Xin-Yu; Huang, Ting-Zhu; Deng, Liang-Jian

2018-01-01

One method of solving the single-image super-resolution problem is to use Heaviside functions. This has been done previously by making a binary classification of image components as “smooth” and “non-smooth”, describing these with approximated Heaviside functions (AHFs), and iteration including l1 regularization. We now introduce a new method in which the binary classification of image components is extended to different degrees of smoothness and non-smoothness, these components being represented by various classes of AHFs. Taking into account the sparsity of the non-smooth components, their coefficients are l1 regularized. In addition, to pick up more image details, the new method uses an iterative refinement for the residuals between the original low-resolution input and the downsampled resulting image. Experimental results showed that the new method is superior to the original AHF method and to four other published methods. PMID:29329298

Complementarity of PALM and SOFI for super-resolution live-cell imaging of focal adhesions

PubMed Central

Deschout, Hendrik; Lukes, Tomas; Sharipov, Azat; Szlag, Daniel; Feletti, Lely; Vandenberg, Wim; Dedecker, Peter; Hofkens, Johan; Leutenegger, Marcel; Lasser, Theo; Radenovic, Aleksandra

2016-01-01

Live-cell imaging of focal adhesions requires a sufficiently high temporal resolution, which remains a challenge for super-resolution microscopy. Here we address this important issue by combining photoactivated localization microscopy (PALM) with super-resolution optical fluctuation imaging (SOFI). Using simulations and fixed-cell focal adhesion images, we investigate the complementarity between PALM and SOFI in terms of spatial and temporal resolution. This PALM-SOFI framework is used to image focal adhesions in living cells, while obtaining a temporal resolution below 10 s. We visualize the dynamics of focal adhesions, and reveal local mean velocities around 190 nm min−1. The complementarity of PALM and SOFI is assessed in detail with a methodology that integrates a resolution and signal-to-noise metric. This PALM and SOFI concept provides an enlarged quantitative imaging framework, allowing unprecedented functional exploration of focal adhesions through the estimation of molecular parameters such as fluorophore densities and photoactivation or photoswitching kinetics. PMID:27991512

Complementarity of PALM and SOFI for super-resolution live-cell imaging of focal adhesions

NASA Astrophysics Data System (ADS)

Deschout, Hendrik; Lukes, Tomas; Sharipov, Azat; Szlag, Daniel; Feletti, Lely; Vandenberg, Wim; Dedecker, Peter; Hofkens, Johan; Leutenegger, Marcel; Lasser, Theo; Radenovic, Aleksandra

2016-12-01

Live-cell imaging of focal adhesions requires a sufficiently high temporal resolution, which remains a challenge for super-resolution microscopy. Here we address this important issue by combining photoactivated localization microscopy (PALM) with super-resolution optical fluctuation imaging (SOFI). Using simulations and fixed-cell focal adhesion images, we investigate the complementarity between PALM and SOFI in terms of spatial and temporal resolution. This PALM-SOFI framework is used to image focal adhesions in living cells, while obtaining a temporal resolution below 10 s. We visualize the dynamics of focal adhesions, and reveal local mean velocities around 190 nm min-1. The complementarity of PALM and SOFI is assessed in detail with a methodology that integrates a resolution and signal-to-noise metric. This PALM and SOFI concept provides an enlarged quantitative imaging framework, allowing unprecedented functional exploration of focal adhesions through the estimation of molecular parameters such as fluorophore densities and photoactivation or photoswitching kinetics.

Complementarity of PALM and SOFI for super-resolution live-cell imaging of focal adhesions.

PubMed

Deschout, Hendrik; Lukes, Tomas; Sharipov, Azat; Szlag, Daniel; Feletti, Lely; Vandenberg, Wim; Dedecker, Peter; Hofkens, Johan; Leutenegger, Marcel; Lasser, Theo; Radenovic, Aleksandra

2016-12-19

Live-cell imaging of focal adhesions requires a sufficiently high temporal resolution, which remains a challenge for super-resolution microscopy. Here we address this important issue by combining photoactivated localization microscopy (PALM) with super-resolution optical fluctuation imaging (SOFI). Using simulations and fixed-cell focal adhesion images, we investigate the complementarity between PALM and SOFI in terms of spatial and temporal resolution. This PALM-SOFI framework is used to image focal adhesions in living cells, while obtaining a temporal resolution below 10 s. We visualize the dynamics of focal adhesions, and reveal local mean velocities around 190 nm min -1 . The complementarity of PALM and SOFI is assessed in detail with a methodology that integrates a resolution and signal-to-noise metric. This PALM and SOFI concept provides an enlarged quantitative imaging framework, allowing unprecedented functional exploration of focal adhesions through the estimation of molecular parameters such as fluorophore densities and photoactivation or photoswitching kinetics.

Fast, long-term, super-resolution imaging with Hessian structured illumination microscopy.

PubMed

Huang, Xiaoshuai; Fan, Junchao; Li, Liuju; Liu, Haosen; Wu, Runlong; Wu, Yi; Wei, Lisi; Mao, Heng; Lal, Amit; Xi, Peng; Tang, Liqiang; Zhang, Yunfeng; Liu, Yanmei; Tan, Shan; Chen, Liangyi

2018-06-01

To increase the temporal resolution and maximal imaging time of super-resolution (SR) microscopy, we have developed a deconvolution algorithm for structured illumination microscopy based on Hessian matrixes (Hessian-SIM). It uses the continuity of biological structures in multiple dimensions as a priori knowledge to guide image reconstruction and attains artifact-minimized SR images with less than 10% of the photon dose used by conventional SIM while substantially outperforming current algorithms at low signal intensities. Hessian-SIM enables rapid imaging of moving vesicles or loops in the endoplasmic reticulum without motion artifacts and with a spatiotemporal resolution of 88 nm and 188 Hz. Its high sensitivity allows the use of sub-millisecond excitation pulses followed by dark recovery times to reduce photobleaching of fluorescent proteins, enabling hour-long time-lapse SR imaging of actin filaments in live cells. Finally, we observed the structural dynamics of mitochondrial cristae and structures that, to our knowledge, have not been observed previously, such as enlarged fusion pores during vesicle exocytosis.

Super-resolution for scanning light stimulation systems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bitzer, L. A.; Neumann, K.; Benson, N., E-mail: niels.benson@uni-due.de

Super-resolution (SR) is a technique used in digital image processing to overcome the resolution limitation of imaging systems. In this process, a single high resolution image is reconstructed from multiple low resolution images. SR is commonly used for CCD and CMOS (Complementary Metal-Oxide-Semiconductor) sensor images, as well as for medical applications, e.g., magnetic resonance imaging. Here, we demonstrate that super-resolution can be applied with scanning light stimulation (LS) systems, which are common to obtain space-resolved electro-optical parameters of a sample. For our purposes, the Projection Onto Convex Sets (POCS) was chosen and modified to suit the needs of LS systems.more » To demonstrate the SR adaption, an Optical Beam Induced Current (OBIC) LS system was used. The POCS algorithm was optimized by means of OBIC short circuit current measurements on a multicrystalline solar cell, resulting in a mean square error reduction of up to 61% and improved image quality.« less

Polarization sensitive localization based super-resolution microscopy with a birefringent wedge

NASA Astrophysics Data System (ADS)

Sinkó, József; Gajdos, Tamás; Czvik, Elvira; Szabó, Gábor; Erdélyi, Miklós

2017-03-01

A practical method has been presented for polarization sensitive localization based super-resolution microscopy using a birefringent dual wedge. The measurement of the polarization degree at the single molecule level can reveal the chemical and physical properties of the local environment of the fluorescent dye molecule and can hence provide information about the sub-diffraction sized structure of biological samples. Polarization sensitive STORM imaging of the F-Actins proved correlation between the orientation of fluorescent dipoles and the axis of the fibril.

Sparse representation based image interpolation with nonlocal autoregressive modeling.

PubMed

Dong, Weisheng; Zhang, Lei; Lukac, Rastislav; Shi, Guangming

2013-04-01

Sparse representation is proven to be a promising approach to image super-resolution, where the low-resolution (LR) image is usually modeled as the down-sampled version of its high-resolution (HR) counterpart after blurring. When the blurring kernel is the Dirac delta function, i.e., the LR image is directly down-sampled from its HR counterpart without blurring, the super-resolution problem becomes an image interpolation problem. In such cases, however, the conventional sparse representation models (SRM) become less effective, because the data fidelity term fails to constrain the image local structures. In natural images, fortunately, many nonlocal similar patches to a given patch could provide nonlocal constraint to the local structure. In this paper, we incorporate the image nonlocal self-similarity into SRM for image interpolation. More specifically, a nonlocal autoregressive model (NARM) is proposed and taken as the data fidelity term in SRM. We show that the NARM-induced sampling matrix is less coherent with the representation dictionary, and consequently makes SRM more effective for image interpolation. Our extensive experimental results demonstrate that the proposed NARM-based image interpolation method can effectively reconstruct the edge structures and suppress the jaggy/ringing artifacts, achieving the best image interpolation results so far in terms of PSNR as well as perceptual quality metrics such as SSIM and FSIM.

Repurposing a photosynthetic antenna protein as a super-resolution microscopy label.

PubMed

Barnett, Samuel F H; Hitchcock, Andrew; Mandal, Amit K; Vasilev, Cvetelin; Yuen, Jonathan M; Morby, James; Brindley, Amanda A; Niedzwiedzki, Dariusz M; Bryant, Donald A; Cadby, Ashley J; Holten, Dewey; Hunter, C Neil

2017-12-01

Techniques such as Stochastic Optical Reconstruction Microscopy (STORM) and Structured Illumination Microscopy (SIM) have increased the achievable resolution of optical imaging, but few fluorescent proteins are suitable for super-resolution microscopy, particularly in the far-red and near-infrared emission range. Here we demonstrate the applicability of CpcA, a subunit of the photosynthetic antenna complex in cyanobacteria, for STORM and SIM imaging. The periodicity and width of fabricated nanoarrays of CpcA, with a covalently attached phycoerythrobilin (PEB) or phycocyanobilin (PCB) chromophore, matched the lines in reconstructed STORM images. SIM and STORM reconstructions of Escherichia coli cells harbouring CpcA-labelled cytochrome bd 1 ubiquinol oxidase in the cytoplasmic membrane show that CpcA-PEB and CpcA-PCB are suitable for super-resolution imaging in vivo. The stability, ease of production, small size and brightness of CpcA-PEB and CpcA-PCB demonstrate the potential of this largely unexplored protein family as novel probes for super-resolution microscopy.

Multiple-image hiding using super resolution reconstruction in high-frequency domains

NASA Astrophysics Data System (ADS)

Li, Xiao-Wei; Zhao, Wu-Xiang; Wang, Jun; Wang, Qiong-Hua

2017-12-01

In this paper, a robust multiple-image hiding method using the computer-generated integral imaging and the modified super-resolution reconstruction algorithm is proposed. In our work, the host image is first transformed into frequency domains by cellular automata (CA), to assure the quality of the stego-image, the secret images are embedded into the CA high-frequency domains. The proposed method has the following advantages: (1) robustness to geometric attacks because of the memory-distributed property of elemental images, (2) increasing quality of the reconstructed secret images as the scheme utilizes the modified super-resolution reconstruction algorithm. The simulation results show that the proposed multiple-image hiding method outperforms other similar hiding methods and is robust to some geometric attacks, e.g., Gaussian noise and JPEG compression attacks.

Towards breaking the spatial resolution barriers: An optical flow and super-resolution approach for sea ice motion estimation

NASA Astrophysics Data System (ADS)

Petrou, Zisis I.; Xian, Yang; Tian, YingLi

2018-04-01

Estimation of sea ice motion at fine scales is important for a number of regional and local level applications, including modeling of sea ice distribution, ocean-atmosphere and climate dynamics, as well as safe navigation and sea operations. In this study, we propose an optical flow and super-resolution approach to accurately estimate motion from remote sensing images at a higher spatial resolution than the original data. First, an external example learning-based super-resolution method is applied on the original images to generate higher resolution versions. Then, an optical flow approach is applied on the higher resolution images, identifying sparse correspondences and interpolating them to extract a dense motion vector field with continuous values and subpixel accuracies. Our proposed approach is successfully evaluated on passive microwave, optical, and Synthetic Aperture Radar data, proving appropriate for multi-sensor applications and different spatial resolutions. The approach estimates motion with similar or higher accuracy than the original data, while increasing the spatial resolution of up to eight times. In addition, the adopted optical flow component outperforms a state-of-the-art pattern matching method. Overall, the proposed approach results in accurate motion vectors with unprecedented spatial resolutions of up to 1.5 km for passive microwave data covering the entire Arctic and 20 m for radar data, and proves promising for numerous scientific and operational applications.

Modeling super-resolution SERS using a T-matrix method to elucidate molecule-nanoparticle coupling and the origins of localization errors

NASA Astrophysics Data System (ADS)

Heaps, Charles W.; Schatz, George C.

2017-06-01

A computational method to model diffraction-limited images from super-resolution surface-enhanced Raman scattering microscopy is introduced. Despite significant experimental progress in plasmon-based super-resolution imaging, theoretical predictions of the diffraction limited images remain a challenge. The method is used to calculate localization errors and image intensities for a single spherical gold nanoparticle-molecule system. The light scattering is calculated using a modification of generalized Mie (T-matrix) theory with a point dipole source and diffraction limited images are calculated using vectorial diffraction theory. The calculation produces the multipole expansion for each emitter and the coherent superposition of all fields. Imaging the constituent fields in addition to the total field provides new insight into the strong coupling between the molecule and the nanoparticle. Regardless of whether the molecular dipole moment is oriented parallel or perpendicular to the nanoparticle surface, the anisotropic excitation distorts the center of the nanoparticle as measured by the point spread function by approximately fifty percent of the particle radius toward to the molecule. Inspection of the nanoparticle multipoles reveals that distortion arises from a weak quadrupole resonance interfering with the dipole field in the nanoparticle. When the nanoparticle-molecule fields are in-phase, the distorted nanoparticle field dominates the observed image. When out-of-phase, the nanoparticle and molecule are of comparable intensity and interference between the two emitters dominates the observed image. The method is also applied to different wavelengths and particle radii. At off-resonant wavelengths, the method predicts images closer to the molecule not because of relative intensities but because of greater distortion in the nanoparticle. The method is a promising approach to improving the understanding of plasmon-enhanced super-resolution experiments.

SNSMIL, a real-time single molecule identification and localization algorithm for super-resolution fluorescence microscopy

PubMed Central

Tang, Yunqing; Dai, Luru; Zhang, Xiaoming; Li, Junbai; Hendriks, Johnny; Fan, Xiaoming; Gruteser, Nadine; Meisenberg, Annika; Baumann, Arnd; Katranidis, Alexandros; Gensch, Thomas

2015-01-01

Single molecule localization based super-resolution fluorescence microscopy offers significantly higher spatial resolution than predicted by Abbe’s resolution limit for far field optical microscopy. Such super-resolution images are reconstructed from wide-field or total internal reflection single molecule fluorescence recordings. Discrimination between emission of single fluorescent molecules and background noise fluctuations remains a great challenge in current data analysis. Here we present a real-time, and robust single molecule identification and localization algorithm, SNSMIL (Shot Noise based Single Molecule Identification and Localization). This algorithm is based on the intrinsic nature of noise, i.e., its Poisson or shot noise characteristics and a new identification criterion, QSNSMIL, is defined. SNSMIL improves the identification accuracy of single fluorescent molecules in experimental or simulated datasets with high and inhomogeneous background. The implementation of SNSMIL relies on a graphics processing unit (GPU), making real-time analysis feasible as shown for real experimental and simulated datasets. PMID:26098742

Fast myopic 2D-SIM super resolution microscopy with joint modulation pattern estimation

NASA Astrophysics Data System (ADS)

Orieux, François; Loriette, Vincent; Olivo-Marin, Jean-Christophe; Sepulveda, Eduardo; Fragola, Alexandra

2017-12-01

Super-resolution in structured illumination microscopy (SIM) is obtained through de-aliasing of modulated raw images, in which high frequencies are measured indirectly inside the optical transfer function. Usual approaches that use 9 or 15 images are often too slow for dynamic studies. Moreover, as experimental conditions change with time, modulation parameters must be estimated within the images. This paper tackles the problem of image reconstruction for fast super resolution in SIM, where the number of available raw images is reduced to four instead of nine or fifteen. Within an optimization framework, the solution is inferred via a joint myopic criterion for image and modulation (or acquisition) parameters, leading to what is frequently called a myopic or semi-blind inversion problem. The estimate is chosen as the minimizer of the nonlinear criterion, numerically calculated by means of a block coordinate optimization algorithm. The effectiveness of the proposed method is demonstrated for simulated and experimental examples. The results show precise estimation of the modulation parameters jointly with the reconstruction of the super resolution image. The method also shows its effectiveness for thick biological samples.

Super-Resolution Imaging of a Dielectric Microsphere Is Governed by the Waist of Its Photonic Nanojet.

PubMed

Yang, Hui; Trouillon, Raphaël; Huszka, Gergely; Gijs, Martin A M

2016-08-10

Dielectric microspheres with appropriate refractive index can image objects with super-resolution, that is, with a precision well beyond the classical diffraction limit. A microsphere is also known to generate upon illumination a photonic nanojet, which is a scattered beam of light with a high-intensity main lobe and very narrow waist. Here, we report a systematic study of the imaging of water-immersed nanostructures by barium titanate glass microspheres of different size. A numerical study of the light propagation through a microsphere points out the light focusing capability of microspheres of different size and the waist of their photonic nanojet. The former correlates to the magnification factor of the virtual images obtained from linear test nanostructures, the biggest magnification being obtained with microspheres of ∼6-7 μm in size. Analyzing the light intensity distribution of microscopy images allows determining analytically the point spread function of the optical system and thereby quantifies its resolution. We find that the super-resolution imaging of a microsphere is dependent on the waist of its photonic nanojet, the best resolution being obtained with a 6 μm Ø microsphere, which generates the nanojet with the minimum waist. This comparison allows elucidating the super-resolution imaging mechanism.

Inferring Biological Structures from Super-Resolution Single Molecule Images Using Generative Models

PubMed Central

Maji, Suvrajit; Bruchez, Marcel P.

2012-01-01

Localization-based super resolution imaging is presently limited by sampling requirements for dynamic measurements of biological structures. Generating an image requires serial acquisition of individual molecular positions at sufficient density to define a biological structure, increasing the acquisition time. Efficient analysis of biological structures from sparse localization data could substantially improve the dynamic imaging capabilities of these methods. Using a feature extraction technique called the Hough Transform simple biological structures are identified from both simulated and real localization data. We demonstrate that these generative models can efficiently infer biological structures in the data from far fewer localizations than are required for complete spatial sampling. Analysis at partial data densities revealed efficient recovery of clathrin vesicle size distributions and microtubule orientation angles with as little as 10% of the localization data. This approach significantly increases the temporal resolution for dynamic imaging and provides quantitatively useful biological information. PMID:22629348

Super resolution for astronomical observations

NASA Astrophysics Data System (ADS)

Li, Zhan; Peng, Qingyu; Bhanu, Bir; Zhang, Qingfeng; He, Haifeng

2018-05-01

In order to obtain detailed information from multiple telescope observations a general blind super-resolution (SR) reconstruction approach for astronomical images is proposed in this paper. A pixel-reliability-based SR reconstruction algorithm is described and implemented, where the developed process incorporates flat field correction, automatic star searching and centering, iterative star matching, and sub-pixel image registration. Images captured by the 1-m telescope at Yunnan Observatory are used to test the proposed technique. The results of these experiments indicate that, following SR reconstruction, faint stars are more distinct, bright stars have sharper profiles, and the backgrounds have higher details; thus these results benefit from the high-precision star centering and image registration provided by the developed method. Application of the proposed approach not only provides more opportunities for new discoveries from astronomical image sequences, but will also contribute to enhancing the capabilities of most spatial or ground-based telescopes.

A super-resolution ultrasound method for brain vascular mapping

PubMed Central

O'Reilly, Meaghan A.; Hynynen, Kullervo

2013-01-01

Purpose: High-resolution vascular imaging has not been achieved in the brain due to limitations of current clinical imaging modalities. The authors present a method for transcranial ultrasound imaging of single micrometer-size bubbles within a tube phantom. Methods: Emissions from single bubbles within a tube phantom were mapped through an ex vivo human skull using a sparse hemispherical receiver array and a passive beamforming algorithm. Noninvasive phase and amplitude correction techniques were applied to compensate for the aberrating effects of the skull bone. The positions of the individual bubbles were estimated beyond the diffraction limit of ultrasound to produce a super-resolution image of the tube phantom, which was compared with microcomputed tomography (micro-CT). Results: The resulting super-resolution ultrasound image is comparable to results obtained via the micro-CT for small tissue specimen imaging. Conclusions: This method provides superior resolution to deep-tissue contrast ultrasound and has the potential to be extended to provide complete vascular network imaging in the brain. PMID:24320408

Super-resolution Doppler beam sharpening method using fast iterative adaptive approach-based spectral estimation

NASA Astrophysics Data System (ADS)

Mao, Deqing; Zhang, Yin; Zhang, Yongchao; Huang, Yulin; Yang, Jianyu

2018-01-01

Doppler beam sharpening (DBS) is a critical technology for airborne radar ground mapping in forward-squint region. In conventional DBS technology, the narrow-band Doppler filter groups formed by fast Fourier transform (FFT) method suffer from low spectral resolution and high side lobe levels. The iterative adaptive approach (IAA), based on the weighted least squares (WLS), is applied to the DBS imaging applications, forming narrower Doppler filter groups than the FFT with lower side lobe levels. Regrettably, the IAA is iterative, and requires matrix multiplication and inverse operation when forming the covariance matrix, its inverse and traversing the WLS estimate for each sampling point, resulting in a notably high computational complexity for cubic time. We propose a fast IAA (FIAA)-based super-resolution DBS imaging method, taking advantage of the rich matrix structures of the classical narrow-band filtering. First, we formulate the covariance matrix via the FFT instead of the conventional matrix multiplication operation, based on the typical Fourier structure of the steering matrix. Then, by exploiting the Gohberg-Semencul representation, the inverse of the Toeplitz covariance matrix is computed by the celebrated Levinson-Durbin (LD) and Toeplitz-vector algorithm. Finally, the FFT and fast Toeplitz-vector algorithm are further used to traverse the WLS estimates based on the data-dependent trigonometric polynomials. The method uses the Hermitian feature of the echo autocorrelation matrix R to achieve its fast solution and uses the Toeplitz structure of R to realize its fast inversion. The proposed method enjoys a lower computational complexity without performance loss compared with the conventional IAA-based super-resolution DBS imaging method. The results based on simulations and measured data verify the imaging performance and the operational efficiency.

Single Image Super-Resolution Using Global Regression Based on Multiple Local Linear Mappings.

PubMed

Choi, Jae-Seok; Kim, Munchurl

2017-03-01

Super-resolution (SR) has become more vital, because of its capability to generate high-quality ultra-high definition (UHD) high-resolution (HR) images from low-resolution (LR) input images. Conventional SR methods entail high computational complexity, which makes them difficult to be implemented for up-scaling of full-high-definition input images into UHD-resolution images. Nevertheless, our previous super-interpolation (SI) method showed a good compromise between Peak-Signal-to-Noise Ratio (PSNR) performances and computational complexity. However, since SI only utilizes simple linear mappings, it may fail to precisely reconstruct HR patches with complex texture. In this paper, we present a novel SR method, which inherits the large-to-small patch conversion scheme from SI but uses global regression based on local linear mappings (GLM). Thus, our new SR method is called GLM-SI. In GLM-SI, each LR input patch is divided into 25 overlapped subpatches. Next, based on the local properties of these subpatches, 25 different local linear mappings are applied to the current LR input patch to generate 25 HR patch candidates, which are then regressed into one final HR patch using a global regressor. The local linear mappings are learned cluster-wise in our off-line training phase. The main contribution of this paper is as follows: Previously, linear-mapping-based conventional SR methods, including SI only used one simple yet coarse linear mapping to each patch to reconstruct its HR version. On the contrary, for each LR input patch, our GLM-SI is the first to apply a combination of multiple local linear mappings, where each local linear mapping is found according to local properties of the current LR patch. Therefore, it can better approximate nonlinear LR-to-HR mappings for HR patches with complex texture. Experiment results show that the proposed GLM-SI method outperforms most of the state-of-the-art methods, and shows comparable PSNR performance with much lower computational complexity when compared with a super-resolution method based on convolutional neural nets (SRCNN15). Compared with the previous SI method that is limited with a scale factor of 2, GLM-SI shows superior performance with average 0.79 dB higher in PSNR, and can be used for scale factors of 3 or higher.

Computational-optical microscopy for 3D biological imaging beyond the diffraction limit

NASA Astrophysics Data System (ADS)

Grover, Ginni

In recent years, super-resolution imaging has become an important fluorescent microscopy tool. It has enabled imaging of structures smaller than the optical diffraction limit with resolution less than 50 nm. Extension to high-resolution volume imaging has been achieved by integration with various optical techniques. In this thesis, development of a fluorescent microscope to enable high resolution, extended depth, three dimensional (3D) imaging is discussed; which is achieved by integration of computational methods with optical systems. In the first part of the thesis, point spread function (PSF) engineering for volume imaging is discussed. A class of PSFs, referred to as double-helix (DH) PSFs, is generated. The PSFs exhibit two focused spots in the image plane which rotate about the optical axis, encoding depth in rotation of the image. These PSFs extend the depth-of-field up to a factor of ˜5. Precision performance of the DH-PSFs, based on an information theoretical analysis, is compared with other 3D methods with conclusion that the DH-PSFs provide the best precision and the longest depth-of-field. Out of various possible DH-PSFs, a suitable PSF is obtained for super-resolution microscopy. The DH-PSFs are implemented in imaging systems, such as a microscope, with a special phase modulation at the pupil plane. Surface-relief elements which are polarization-insensitive and ˜90% light efficient are developed for phase modulation. The photon-efficient DH-PSF microscopes thus developed are used, along with optimal position estimation algorithms, for tracking and super-resolution imaging in 3D. Imaging at depths-of-field of up to 2.5 microm is achieved without focus scanning. Microtubules were imaged with 3D resolution of (6, 9, 39) nm, which is in close agreement with the theoretical limit. A quantitative study of co-localization of two proteins in volume was conducted in live bacteria. In the last part of the thesis practical aspects of the DH-PSF microscope are discussed. A method to stabilize it, for extended periods of time, with 3-4 nm precision in 3D is developed. 3D Super-resolution is demonstrated without drift. A PSF correction algorithm is demonstrated to improve characteristics of the DH-PSF in an experiment, where it is implemented with a polarization-insensitive liquid crystal spatial light modulator.

North Twin Peak in super resolution

NASA Technical Reports Server (NTRS)

1997-01-01

This pair of images shows the result of taking a sequence of 25 identical exposures from the Imager for Mars Pathfinder (IMP) of the northern Twin Peak, with small camera motions, and processing them with the Super-Resolution algorithm developed at NASA's Ames Research Center.

The upper image is a representative input image, scaled up by a factor of five, with the pixel edges smoothed out for a fair comparison. The lower image allows significantly finer detail to be resolved.

Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is an operating division of the California Institute of Technology (Caltech). The Imager for Mars Pathfinder (IMP) was developed by the University of Arizona Lunar and Planetary Laboratory under contract to JPL. Peter Smith is the Principal Investigator.

The super-resolution research was conducted by Peter Cheeseman, Bob Kanefsky, Robin Hanson, and John Stutz of NASA's Ames Research Center, Mountain View, CA. More information on this technology is available on the Ames Super Resolution home page at

http://ic-www.arc.nasa.gov/ic/projects/bayes-group/ group/super-res/

Photon-efficient super-resolution laser radar

NASA Astrophysics Data System (ADS)

Shin, Dongeek; Shapiro, Jeffrey H.; Goyal, Vivek K.

2017-08-01

The resolution achieved in photon-efficient active optical range imaging systems can be low due to non-idealities such as propagation through a diffuse scattering medium. We propose a constrained optimization-based frame- work to address extremes in scarcity of photons and blurring by a forward imaging kernel. We provide two algorithms for the resulting inverse problem: a greedy algorithm, inspired by sparse pursuit algorithms; and a convex optimization heuristic that incorporates image total variation regularization. We demonstrate that our framework outperforms existing deconvolution imaging techniques in terms of peak signal-to-noise ratio. Since our proposed method is able to super-resolve depth features using small numbers of photon counts, it can be useful for observing fine-scale phenomena in remote sensing through a scattering medium and through-the-skin biomedical imaging applications.

Three-Dimensional Localization of Single Molecules for Super-Resolution Imaging and Single-Particle Tracking

PubMed Central

von Diezmann, Alex; Shechtman, Yoav; Moerner, W. E.

2017-01-01

Single-molecule super-resolution fluorescence microscopy and single-particle tracking are two imaging modalities that illuminate the properties of cells and materials on spatial scales down to tens of nanometers, or with dynamical information about nanoscale particle motion in the millisecond range, respectively. These methods generally use wide-field microscopes and two-dimensional camera detectors to localize molecules to much higher precision than the diffraction limit. Given the limited total photons available from each single-molecule label, both modalities require careful mathematical analysis and image processing. Much more information can be obtained about the system under study by extending to three-dimensional (3D) single-molecule localization: without this capability, visualization of structures or motions extending in the axial direction can easily be missed or confused, compromising scientific understanding. A variety of methods for obtaining both 3D super-resolution images and 3D tracking information have been devised, each with their own strengths and weaknesses. These include imaging of multiple focal planes, point-spread-function engineering, and interferometric detection. These methods may be compared based on their ability to provide accurate and precise position information of single-molecule emitters with limited photons. To successfully apply and further develop these methods, it is essential to consider many practical concerns, including the effects of optical aberrations, field-dependence in the imaging system, fluorophore labeling density, and registration between different color channels. Selected examples of 3D super-resolution imaging and tracking are described for illustration from a variety of biological contexts and with a variety of methods, demonstrating the power of 3D localization for understanding complex systems. PMID:28151646

Super-resolved terahertz microscopy by knife-edge scan

NASA Astrophysics Data System (ADS)

Giliberti, V.; Flammini, M.; Ciano, C.; Pontecorvo, E.; Del Re, E.; Ortolani, M.

2017-08-01

We present a compact, all solid-state THz confocal microscope operating at 0.30 THz that achieves super-resolution by using the knife-edge scan approach. In the final reconstructed image, a lateral resolution of 60 μm ≍ λ/17 is demonstrated when the knife-edge is deep in the near-field of the sample surface. When the knife-edge is lifted up to λ/4 from the sample surface, a certain degree of super-resolution is maintained with a resolution of 0.4 mm, i.e. more than a factor 2 if compared to the diffraction-limited scheme. The present results open an interesting path towards super-resolved imaging with in-depth information that would be peculiar to THz microscopy systems.

Analyzing Protein Clusters on the Plasma Membrane: Application of Spatial Statistical Analysis Methods on Super-Resolution Microscopy Images.

PubMed

Paparelli, Laura; Corthout, Nikky; Pavie, Benjamin; Annaert, Wim; Munck, Sebastian

2016-01-01

The spatial distribution of proteins within the cell affects their capability to interact with other molecules and directly influences cellular processes and signaling. At the plasma membrane, multiple factors drive protein compartmentalization into specialized functional domains, leading to the formation of clusters in which intermolecule interactions are facilitated. Therefore, quantifying protein distributions is a necessity for understanding their regulation and function. The recent advent of super-resolution microscopy has opened up the possibility of imaging protein distributions at the nanometer scale. In parallel, new spatial analysis methods have been developed to quantify distribution patterns in super-resolution images. In this chapter, we provide an overview of super-resolution microscopy and summarize the factors influencing protein arrangements on the plasma membrane. Finally, we highlight methods for analyzing clusterization of plasma membrane proteins, including examples of their applications.

Effective deep learning training for single-image super-resolution in endomicroscopy exploiting video-registration-based reconstruction.

PubMed

Ravì, Daniele; Szczotka, Agnieszka Barbara; Shakir, Dzhoshkun Ismail; Pereira, Stephen P; Vercauteren, Tom

2018-06-01

Probe-based confocal laser endomicroscopy (pCLE) is a recent imaging modality that allows performing in vivo optical biopsies. The design of pCLE hardware, and its reliance on an optical fibre bundle, fundamentally limits the image quality with a few tens of thousands fibres, each acting as the equivalent of a single-pixel detector, assembled into a single fibre bundle. Video registration techniques can be used to estimate high-resolution (HR) images by exploiting the temporal information contained in a sequence of low-resolution (LR) images. However, the alignment of LR frames, required for the fusion, is computationally demanding and prone to artefacts. In this work, we propose a novel synthetic data generation approach to train exemplar-based Deep Neural Networks (DNNs). HR pCLE images with enhanced quality are recovered by the models trained on pairs of estimated HR images (generated by the video registration algorithm) and realistic synthetic LR images. Performance of three different state-of-the-art DNNs techniques were analysed on a Smart Atlas database of 8806 images from 238 pCLE video sequences. The results were validated through an extensive image quality assessment that takes into account different quality scores, including a Mean Opinion Score (MOS). Results indicate that the proposed solution produces an effective improvement in the quality of the obtained reconstructed image. The proposed training strategy and associated DNNs allows us to perform convincing super-resolution of pCLE images.

A general strategy for developing cell-permeable photo-modulatable organic fluorescent probes for live-cell super-resolution imaging.

PubMed

Pan, Deng; Hu, Zhe; Qiu, Fengwu; Huang, Zhen-Li; Ma, Yilong; Wang, Yina; Qin, Lingsong; Zhang, Zhihong; Zeng, Shaoqun; Zhang, Yu-Hui

2014-11-20

Single-molecule localization microscopy (SMLM) achieves super-resolution imaging beyond the diffraction limit but critically relies on the use of photo-modulatable fluorescent probes. Here we report a general strategy for constructing cell-permeable photo-modulatable organic fluorescent probes for live-cell SMLM by exploiting the remarkable cytosolic delivery ability of a cell-penetrating peptide (rR)3R2. We develop photo-modulatable organic fluorescent probes consisting of a (rR)3R2 peptide coupled to a cell-impermeable organic fluorophore and a recognition unit. Our results indicate that these organic probes are not only cell permeable but can also specifically and directly label endogenous targeted proteins. Using the probes, we obtain super-resolution images of lysosomes and endogenous F-actin under physiological conditions. We resolve the dynamics of F-actin with 10 s temporal resolution in live cells and discern fine F-actin structures with diameters of ~80 nm. These results open up new avenues in the design of fluorescent probes for live-cell super-resolution imaging.

Adaptive pixel-super-resolved lensfree in-line digital holography for wide-field on-chip microscopy.

PubMed

Zhang, Jialin; Sun, Jiasong; Chen, Qian; Li, Jiaji; Zuo, Chao

2017-09-18

High-resolution wide field-of-view (FOV) microscopic imaging plays an essential role in various fields of biomedicine, engineering, and physical sciences. As an alternative to conventional lens-based scanning techniques, lensfree holography provides a new way to effectively bypass the intrinsical trade-off between the spatial resolution and FOV of conventional microscopes. Unfortunately, due to the limited sensor pixel-size, unpredictable disturbance during image acquisition, and sub-optimum solution to the phase retrieval problem, typical lensfree microscopes only produce compromised imaging quality in terms of lateral resolution and signal-to-noise ratio (SNR). Here, we propose an adaptive pixel-super-resolved lensfree imaging (APLI) method which can solve, or at least partially alleviate these limitations. Our approach addresses the pixel aliasing problem by Z-scanning only, without resorting to subpixel shifting or beam-angle manipulation. Automatic positional error correction algorithm and adaptive relaxation strategy are introduced to enhance the robustness and SNR of reconstruction significantly. Based on APLI, we perform full-FOV reconstruction of a USAF resolution target (~29.85 mm 2 ) and achieve half-pitch lateral resolution of 770 nm, surpassing 2.17 times of the theoretical Nyquist-Shannon sampling resolution limit imposed by the sensor pixel-size (1.67µm). Full-FOV imaging result of a typical dicot root is also provided to demonstrate its promising potential applications in biologic imaging.

A Bayesian Nonparametric Approach to Image Super-Resolution.

PubMed

Polatkan, Gungor; Zhou, Mingyuan; Carin, Lawrence; Blei, David; Daubechies, Ingrid

2015-02-01

Super-resolution methods form high-resolution images from low-resolution images. In this paper, we develop a new Bayesian nonparametric model for super-resolution. Our method uses a beta-Bernoulli process to learn a set of recurring visual patterns, called dictionary elements, from the data. Because it is nonparametric, the number of elements found is also determined from the data. We test the results on both benchmark and natural images, comparing with several other models from the research literature. We perform large-scale human evaluation experiments to assess the visual quality of the results. In a first implementation, we use Gibbs sampling to approximate the posterior. However, this algorithm is not feasible for large-scale data. To circumvent this, we then develop an online variational Bayes (VB) algorithm. This algorithm finds high quality dictionaries in a fraction of the time needed by the Gibbs sampler.

Understanding Super-Resolution Nanoscopy and Its Biological Applications in Cell Imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Dehong; Zhao, Baoming; Xie, Yumei

2013-01-01

Optical microscopy has been an ideal tool to study phenomena in live cells because visible light at reasonable intensity does not perturb much of the normal biological functions. However, optical resolution using visible light is significantly limited by the wavelength. Overcoming this diffraction-limit barrier will reveal biological mechanisms, cellular structures, and physiological processes at nanometer scale, orders of magnitude lower than current optical microscopy. Although this appears to be a daunting task, recently developed photoswitchable probes enable reconstruction of individual images into a super-resolution image, thus the emergence of nanoscopy. Harnessing the resolution power of nanoscopy, we report here nano-resolutionmore » fluorescence imaging of microtubules and their network structures in biological cells. The super-resolution nanoscopy successfully resolved nanostructures of microtubule network—a daunting task that cannot be completed using conventional wide-field microscopy.« less

DMD-based LED-illumination super-resolution and optical sectioning microscopy.

PubMed

Dan, Dan; Lei, Ming; Yao, Baoli; Wang, Wen; Winterhalder, Martin; Zumbusch, Andreas; Qi, Yujiao; Xia, Liang; Yan, Shaohui; Yang, Yanlong; Gao, Peng; Ye, Tong; Zhao, Wei

2013-01-01

Super-resolution three-dimensional (3D) optical microscopy has incomparable advantages over other high-resolution microscopic technologies, such as electron microscopy and atomic force microscopy, in the study of biological molecules, pathways and events in live cells and tissues. We present a novel approach of structured illumination microscopy (SIM) by using a digital micromirror device (DMD) for fringe projection and a low-coherence LED light for illumination. The lateral resolution of 90 nm and the optical sectioning depth of 120 μm were achieved. The maximum acquisition speed for 3D imaging in the optical sectioning mode was 1.6×10(7) pixels/second, which was mainly limited by the sensitivity and speed of the CCD camera. In contrast to other SIM techniques, the DMD-based LED-illumination SIM is cost-effective, ease of multi-wavelength switchable and speckle-noise-free. The 2D super-resolution and 3D optical sectioning modalities can be easily switched and applied to either fluorescent or non-fluorescent specimens.

DMD-based LED-illumination Super-resolution and optical sectioning microscopy

PubMed Central

Dan, Dan; Lei, Ming; Yao, Baoli; Wang, Wen; Winterhalder, Martin; Zumbusch, Andreas; Qi, Yujiao; Xia, Liang; Yan, Shaohui; Yang, Yanlong; Gao, Peng; Ye, Tong; Zhao, Wei

2013-01-01

Super-resolution three-dimensional (3D) optical microscopy has incomparable advantages over other high-resolution microscopic technologies, such as electron microscopy and atomic force microscopy, in the study of biological molecules, pathways and events in live cells and tissues. We present a novel approach of structured illumination microscopy (SIM) by using a digital micromirror device (DMD) for fringe projection and a low-coherence LED light for illumination. The lateral resolution of 90 nm and the optical sectioning depth of 120 μm were achieved. The maximum acquisition speed for 3D imaging in the optical sectioning mode was 1.6×107 pixels/second, which was mainly limited by the sensitivity and speed of the CCD camera. In contrast to other SIM techniques, the DMD-based LED-illumination SIM is cost-effective, ease of multi-wavelength switchable and speckle-noise-free. The 2D super-resolution and 3D optical sectioning modalities can be easily switched and applied to either fluorescent or non-fluorescent specimens. PMID:23346373

Effect of probe diffusion on the SOFI imaging accuracy.

PubMed

Vandenberg, Wim; Dedecker, Peter

2017-03-23

Live-cell super-resolution fluorescence imaging is becoming commonplace for exploring biological systems, though sample dynamics can affect the imaging quality. In this work we evaluate the effect of probe diffusion on super-resolution optical fluctuation imaging (SOFI), using a theoretical model and numerical simulations based on the imaging of live cells labelled with photochromic fluorescent proteins. We find that, over a range of physiological conditions, fluorophore diffusion results in a change in the amplitude of the SOFI signal. The magnitude of this change is approximately proportional to the on-time ratio of the fluorophores. However, for photochromic fluorescent proteins this effect is unlikely to present a significant distortion in practical experiments in biological systems. Due to this lack of distortions, probe diffusion strongly enhances the SOFI imaging by avoiding spatial undersampling caused by the limited labeling density.

Quantum correlation enhanced super-resolution localization microscopy enabled by a fibre bundle camera

PubMed Central

Israel, Yonatan; Tenne, Ron; Oron, Dan; Silberberg, Yaron

2017-01-01

Despite advances in low-light-level detection, single-photon methods such as photon correlation have rarely been used in the context of imaging. The few demonstrations, for example of subdiffraction-limited imaging utilizing quantum statistics of photons, have remained in the realm of proof-of-principle demonstrations. This is primarily due to a combination of low values of fill factors, quantum efficiencies, frame rates and signal-to-noise characteristic of most available single-photon sensitive imaging detectors. Here we describe an imaging device based on a fibre bundle coupled to single-photon avalanche detectors that combines a large fill factor, a high quantum efficiency, a low noise and scalable architecture. Our device enables localization-based super-resolution microscopy in a non-sparse non-stationary scene, utilizing information on the number of active emitters, as gathered from non-classical photon statistics. PMID:28287167

Super-resolution photoacoustic microscopy using a localized near-field of a plasmonic nanoaperture: a three-dimensional simulation study

NASA Astrophysics Data System (ADS)

Park, Byullee; Lee, Hongki; Upputuri, Paul Kumar; Pramanik, Manojit; Kim, Donghyun; Kim, Chulhong

2018-02-01

Super-resolution microscopy has been increasingly important to delineate nanoscale biological structures or nanoparticles. With these increasing demands, several imaging modalities, including super-resolution fluorescence microscope (SRFM) and electron microscope (EM), have been developed and commercialized. These modalities achieve nanoscale resolution, however, SRFM cannot image without fluorescence, and sample preparation of EM is not suitable for biological specimens. To overcome those disadvantages, we have numerically studied the possibility of superresolution photoacoustic microscopy (SR-PAM) based on near-field localization of light. Photoacoustic (PA) signal is generally acquired based on optical absorption contrast; thus it requires no agents or pre-processing for the samples. The lateral resolution of the conventional photoacoustic microscopy is limited to 200 nm by diffraction limit, therefore reducing the lateral resolution is a major research impetus. Our approach to breaking resolution limit is to use laser pulses of extremely small spot size as a light source. In this research, we simulated the PA signal by constructing the three dimensional SR-PAM system environment using the k-Wave toolbox. As the light source, we simulated ultrashort light pulses using geometrical nanoaperture with near-field localization of surface plasmons. Through the PA simulation, we have successfully distinguish cuboids spaced 3 nm apart. In the near future, we will develop the SR-PAM and it will contribute to biomedical and material sciences.

Diverse protocols for correlative super-resolution fluorescence imaging and electron microscopy of chemically fixed samples

PubMed Central

Kopek, Benjamin G.; Paez-Segala, Maria G.; Shtengel, Gleb; Sochacki, Kem A.; Sun, Mei G.; Wang, Yalin; Xu, C. Shan; van Engelenburg, Schuyler B.; Taraska, Justin W.; Looger, Loren L.; Hess, Harald F.

2017-01-01

Our groups have recently developed related approaches for sample preparation for super-resolution imaging within endogenous cellular environments using correlative light and electron microscopy (CLEM). Four distinct techniques for preparing and acquiring super-resolution CLEM datasets on aldehyde-fixed specimens are provided, including Tokuyasu cryosectioning, whole-cell mount, cell unroofing and platinum replication, and resin embedding and sectioning. Choice of the best protocol for a given application depends on a number of criteria that are discussed in detail. Tokuyasu cryosectioning is relatively rapid but is limited to small, delicate specimens. Whole-cell mount has the simplest sample preparation but is restricted to surface structures. Cell unroofing and platinum replica creates high-contrast, 3-dimensional images of the cytoplasmic surface of the plasma membrane, but is more challenging than whole-cell mount. Resin embedding permits serial sectioning of large samples, but is limited to osmium-resistant probes, and is technically difficult. Expected results from these protocols include super-resolution localization (~10–50 nm) of fluorescent targets within the context of electron microscopy ultrastructure, which can help address cell biological questions. These protocols can be completed in 2–7 days, are compatible with a number of super-resolution imaging protocols, and are broadly applicable across biology. PMID:28384138

Robust video super-resolution with registration efficiency adaptation

NASA Astrophysics Data System (ADS)

Zhang, Xinfeng; Xiong, Ruiqin; Ma, Siwei; Zhang, Li; Gao, Wen

2010-07-01

Super-Resolution (SR) is a technique to construct a high-resolution (HR) frame by fusing a group of low-resolution (LR) frames describing the same scene. The effectiveness of the conventional super-resolution techniques, when applied on video sequences, strongly relies on the efficiency of motion alignment achieved by image registration. Unfortunately, such efficiency is limited by the motion complexity in the video and the capability of adopted motion model. In image regions with severe registration errors, annoying artifacts usually appear in the produced super-resolution video. This paper proposes a robust video super-resolution technique that adapts itself to the spatially-varying registration efficiency. The reliability of each reference pixel is measured by the corresponding registration error and incorporated into the optimization objective function of SR reconstruction. This makes the SR reconstruction highly immune to the registration errors, as outliers with higher registration errors are assigned lower weights in the objective function. In particular, we carefully design a mechanism to assign weights according to registration errors. The proposed superresolution scheme has been tested with various video sequences and experimental results clearly demonstrate the effectiveness of the proposed method.

Advanced Topics in Space Situational Awareness

DTIC Science & Technology

2007-11-07

34super-resolution." Such optical superresolution is characteristic of many model-based image processing algorithms, and reflects the incorporation of...Sampling Theorem," J. Opt. Soc. Am. A, vol. 24, 311-325 (2007). [39] S. Prasad, "Digital and Optical Superresolution of Low-Resolution Image Sequences," Un...wavefront coding for the specific application of extension of image depth well beyond what is possible in a standard imaging system. The problem of optical

Live-cell super-resolution imaging of intrinsically fast moving flagellates

NASA Astrophysics Data System (ADS)

Glogger, M.; Stichler, S.; Subota, I.; Bertlein, S.; Spindler, M.-C.; Teßmar, J.; Groll, J.; Engstler, M.; Fenz, S. F.

2017-02-01

Recent developments in super-resolution microscopy make it possible to resolve structures in biological cells at a spatial resolution of a few nm and observe dynamical processes with a temporal resolution of ms to μs. However, the optimal structural resolution requires repeated illumination cycles and is thus limited to chemically fixed cells. For live cell applications substantial improvement over classical Abbe-limited imaging can already be obtained in adherent or slow moving cells. Nonetheless, a large group of cells are fast moving and thus could not yet be addressed with live cell super-resolution microscopy. These include flagellate pathogens like African trypanosomes, the causative agents of sleeping sickness in humans and nagana in livestock. Here, we present an embedding method based on a in situ forming cytocompatible UV-crosslinked hydrogel. The fast cross-linking hydrogel immobilizes trypanosomes efficiently to allow microscopy on the nanoscale. We characterized both the trypanosomes and the hydrogel with respect to their autofluorescence properties and found them suitable for single-molecule fluorescence microscopy (SMFM). As a proof of principle, SMFM was applied to super-resolve a structure inside the living trypanosome. We present an image of a flagellar axoneme component recorded by using the intrinsic blinking behavior of eYFP. , which features invited work from the best early-career researchers working within the scope of J Phys D. This project is part of the Journal of Physics series’ 50th anniversary celebrations in 2017. Susanne Fenz was selected by the Editorial Board of J Phys D as an Emerging Talent/Leader.

Super-achromatic microprobe for ultrahigh-resolution endoscopic OCT imaging at 800 nm (Conference Presentation)

NASA Astrophysics Data System (ADS)

Yuan, Wu; Alemohammad, Milad; Yu, Xiaoyun; Yu, Shaoyong; Li, Xingde

2016-03-01

In this paper, we report a super-achromatic microprobe made with fiber-optic ball lens to enable ultrahigh-resolution endoscopic OCT imaging. An axial resolution of ~2.4 µm (in air) can be achieved with a 7-fs Ti:Sapphire laser. The microprobe has minimal astigmatism which affords a high transverse resolution of ~5.6 µm. The miniaturized microprobe has an outer diameter of ~520 µm including the encasing metal guard and can be used to image small luminal organs. The performance of the ultrahigh-resolution OCT microprobe was demonstrated by imaging rat esophagus, guinea pig esophagus, and mouse rectum in vivo.

Accelerating cross-validation with total variation and its application to super-resolution imaging

NASA Astrophysics Data System (ADS)

Obuchi, Tomoyuki; Ikeda, Shiro; Akiyama, Kazunori; Kabashima, Yoshiyuki

2017-12-01

We develop an approximation formula for the cross-validation error (CVE) of a sparse linear regression penalized by ℓ_1-norm and total variation terms, which is based on a perturbative expansion utilizing the largeness of both the data dimensionality and the model. The developed formula allows us to reduce the necessary computational cost of the CVE evaluation significantly. The practicality of the formula is tested through application to simulated black-hole image reconstruction on the event-horizon scale with super resolution. The results demonstrate that our approximation reproduces the CVE values obtained via literally conducted cross-validation with reasonably good precision.

SuperSegger: robust image segmentation, analysis and lineage tracking of bacterial cells.

PubMed

Stylianidou, Stella; Brennan, Connor; Nissen, Silas B; Kuwada, Nathan J; Wiggins, Paul A

2016-11-01

Many quantitative cell biology questions require fast yet reliable automated image segmentation to identify and link cells from frame-to-frame, and characterize the cell morphology and fluorescence. We present SuperSegger, an automated MATLAB-based image processing package well-suited to quantitative analysis of high-throughput live-cell fluorescence microscopy of bacterial cells. SuperSegger incorporates machine-learning algorithms to optimize cellular boundaries and automated error resolution to reliably link cells from frame-to-frame. Unlike existing packages, it can reliably segment microcolonies with many cells, facilitating the analysis of cell-cycle dynamics in bacteria as well as cell-contact mediated phenomena. This package has a range of built-in capabilities for characterizing bacterial cells, including the identification of cell division events, mother, daughter and neighbouring cells, and computing statistics on cellular fluorescence, the location and intensity of fluorescent foci. SuperSegger provides a variety of postprocessing data visualization tools for single cell and population level analysis, such as histograms, kymographs, frame mosaics, movies and consensus images. Finally, we demonstrate the power of the package by analyzing lag phase growth with single cell resolution. © 2016 John Wiley & Sons Ltd.

Open-source image reconstruction of super-resolution structured illumination microscopy data in ImageJ

PubMed Central

Müller, Marcel; Mönkemöller, Viola; Hennig, Simon; Hübner, Wolfgang; Huser, Thomas

2016-01-01

Super-resolved structured illumination microscopy (SR-SIM) is an important tool for fluorescence microscopy. SR-SIM microscopes perform multiple image acquisitions with varying illumination patterns, and reconstruct them to a super-resolved image. In its most frequent, linear implementation, SR-SIM doubles the spatial resolution. The reconstruction is performed numerically on the acquired wide-field image data, and thus relies on a software implementation of specific SR-SIM image reconstruction algorithms. We present fairSIM, an easy-to-use plugin that provides SR-SIM reconstructions for a wide range of SR-SIM platforms directly within ImageJ. For research groups developing their own implementations of super-resolution structured illumination microscopy, fairSIM takes away the hurdle of generating yet another implementation of the reconstruction algorithm. For users of commercial microscopes, it offers an additional, in-depth analysis option for their data independent of specific operating systems. As a modular, open-source solution, fairSIM can easily be adapted, automated and extended as the field of SR-SIM progresses. PMID:26996201

Sparse representation-based volumetric super-resolution algorithm for 3D CT images of reservoir rocks

NASA Astrophysics Data System (ADS)

Li, Zhengji; Teng, Qizhi; He, Xiaohai; Yue, Guihua; Wang, Zhengyong

2017-09-01

The parameter evaluation of reservoir rocks can help us to identify components and calculate the permeability and other parameters, and it plays an important role in the petroleum industry. Until now, computed tomography (CT) has remained an irreplaceable way to acquire the microstructure of reservoir rocks. During the evaluation and analysis, large samples and high-resolution images are required in order to obtain accurate results. Owing to the inherent limitations of CT, however, a large field of view results in low-resolution images, and high-resolution images entail a smaller field of view. Our method is a promising solution to these data collection limitations. In this study, a framework for sparse representation-based 3D volumetric super-resolution is proposed to enhance the resolution of 3D voxel images of reservoirs scanned with CT. A single reservoir structure and its downgraded model are divided into a large number of 3D cubes of voxel pairs and these cube pairs are used to calculate two overcomplete dictionaries and the sparse-representation coefficients in order to estimate the high frequency component. Future more, to better result, a new feature extract method with combine BM4D together with Laplacian filter are introduced. In addition, we conducted a visual evaluation of the method, and used the PSNR and FSIM to evaluate it qualitatively.

Enhanced labeling density and whole-cell 3D dSTORM imaging by repetitive labeling of target proteins.

PubMed

Venkataramani, Varun; Kardorff, Markus; Herrmannsdörfer, Frank; Wieneke, Ralph; Klein, Alina; Tampé, Robert; Heilemann, Mike; Kuner, Thomas

2018-04-03

With continuing advances in the resolving power of super-resolution microscopy, the inefficient labeling of proteins with suitable fluorophores becomes a limiting factor. For example, the low labeling density achieved with antibodies or small molecule tags limits attempts to reveal local protein nano-architecture of cellular compartments. On the other hand, high laser intensities cause photobleaching within and nearby an imaged region, thereby further reducing labeling density and impairing multi-plane whole-cell 3D super-resolution imaging. Here, we show that both labeling density and photobleaching can be addressed by repetitive application of trisNTA-fluorophore conjugates reversibly binding to a histidine-tagged protein by a novel approach called single-epitope repetitive imaging (SERI). For single-plane super-resolution microscopy, we demonstrate that, after multiple rounds of labeling and imaging, the signal density is increased. Using the same approach of repetitive imaging, washing and re-labeling, we demonstrate whole-cell 3D super-resolution imaging compensated for photobleaching above or below the imaging plane. This proof-of-principle study demonstrates that repetitive labeling of histidine-tagged proteins provides a versatile solution to break the 'labeling barrier' and to bypass photobleaching in multi-plane, whole-cell 3D experiments.

Super resolution reconstruction of infrared images based on classified dictionary learning

NASA Astrophysics Data System (ADS)

Liu, Fei; Han, Pingli; Wang, Yi; Li, Xuan; Bai, Lu; Shao, Xiaopeng

2018-05-01

Infrared images always suffer from low-resolution problems resulting from limitations of imaging devices. An economical approach to combat this problem involves reconstructing high-resolution images by reasonable methods without updating devices. Inspired by compressed sensing theory, this study presents and demonstrates a Classified Dictionary Learning method to reconstruct high-resolution infrared images. It classifies features of the samples into several reasonable clusters and trained a dictionary pair for each cluster. The optimal pair of dictionaries is chosen for each image reconstruction and therefore, more satisfactory results is achieved without the increase in computational complexity and time cost. Experiments and results demonstrated that it is a viable method for infrared images reconstruction since it improves image resolution and recovers detailed information of targets.

Super-resolution with a positive epsilon multi-quantum-well super-lens

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bak, A. O.; Giannini, V.; Maier, S. A.

2013-12-23

We design an anisotropic and dichroic quantum metamaterial that is able to achieve super-resolution without the need for a negative permittivity. When exploring the parameters of the structure, we take into account the limits of semiconductor fabrication technology based on quantum well stacks. By heavily doping the structure with free electrons, we infer an anisotropic effective medium with a prolate ellipsoid dispersion curve which allows for near-diffractionless propagation of light (similar to an epsilon-near-zero hyperbolic lens). This, coupled with low absorption, allows us to resolve images at the sub-wavelength scale at distances 6 times greater than equivalent natural materials.

Oblique reconstructions in tomosynthesis. II. Super-resolution

PubMed Central

Acciavatti, Raymond J.; Maidment, Andrew D. A.

2013-01-01

Purpose: In tomosynthesis, super-resolution has been demonstrated using reconstruction planes parallel to the detector. Super-resolution allows for subpixel resolution relative to the detector. The purpose of this work is to develop an analytical model that generalizes super-resolution to oblique reconstruction planes. Methods: In a digital tomosynthesis system, a sinusoidal test object is modeled along oblique angles (i.e., “pitches”) relative to the plane of the detector in a 3D divergent-beam acquisition geometry. To investigate the potential for super-resolution, the input frequency is specified to be greater than the alias frequency of the detector. Reconstructions are evaluated in an oblique plane along the extent of the object using simple backprojection (SBP) and filtered backprojection (FBP). By comparing the amplitude of the reconstruction against the attenuation coefficient of the object at various frequencies, the modulation transfer function (MTF) is calculated to determine whether modulation is within detectable limits for super-resolution. For experimental validation of super-resolution, a goniometry stand was used to orient a bar pattern phantom along various pitches relative to the breast support in a commercial digital breast tomosynthesis system. Results: Using theoretical modeling, it is shown that a single projection image cannot resolve a sine input whose frequency exceeds the detector alias frequency. The high frequency input is correctly visualized in SBP or FBP reconstruction using a slice along the pitch of the object. The Fourier transform of this reconstructed slice is maximized at the input frequency as proof that the object is resolved. Consistent with the theoretical results, experimental images of a bar pattern phantom showed super-resolution in oblique reconstructions. At various pitches, the highest frequency with detectable modulation was determined by visual inspection of the bar patterns. The dependency of the highest detectable frequency on pitch followed the same trend as the analytical model. It was demonstrated that super-resolution is not achievable if the pitch of the object approaches 90°, corresponding to the case in which the test frequency is perpendicular to the breast support. Only low frequency objects are detectable at pitches close to 90°. Conclusions: This work provides a platform for investigating super-resolution in oblique reconstructions for tomosynthesis. In breast imaging, this study should have applications in visualizing microcalcifications and other subtle signs of cancer. PMID:24320445

Dances with Membranes: Breakthroughs from Super-resolution Imaging

PubMed Central

Curthoys, Nikki M.; Parent, Matthew; Mlodzianoski, Michael; Nelson, Andrew J.; Lilieholm, Jennifer; Butler, Michael B.; Valles, Matthew; Hess, Samuel T.

2017-01-01

Biological membrane organization mediates numerous cellular functions and has also been connected with an immense number of human diseases. However, until recently, experimental methodologies have been unable to directly visualize the nanoscale details of biological membranes, particularly in intact living cells. Numerous models explaining membrane organization have been proposed, but testing those models has required indirect methods; the desire to directly image proteins and lipids in living cell membranes is a strong motivation for the advancement of technology. The development of super-resolution microscopy has provided powerful tools for quantification of membrane organization at the level of individual proteins and lipids, and many of these tools are compatible with living cells. Previously inaccessible questions are now being addressed, and the field of membrane biology is developing rapidly. This chapter discusses how the development of super-resolution microscopy has led to fundamental advances in the field of biological membrane organization. We summarize the history and some models explaining how proteins are organized in cell membranes, and give an overview of various super-resolution techniques and methods of quantifying super-resolution data. We discuss the application of super-resolution techniques to membrane biology in general, and also with specific reference to the fields of actin and actin-binding proteins, virus infection, mitochondria, immune cell biology, and phosphoinositide signaling. Finally, we present our hopes and expectations for the future of super-resolution microscopy in the field of membrane biology. PMID:26015281

Correlative Stochastic Optical Reconstruction Microscopy and Electron Microscopy

PubMed Central

Kim, Doory; Deerinck, Thomas J.; Sigal, Yaron M.; Babcock, Hazen P.; Ellisman, Mark H.; Zhuang, Xiaowei

2015-01-01

Correlative fluorescence light microscopy and electron microscopy allows the imaging of spatial distributions of specific biomolecules in the context of cellular ultrastructure. Recent development of super-resolution fluorescence microscopy allows the location of molecules to be determined with nanometer-scale spatial resolution. However, correlative super-resolution fluorescence microscopy and electron microscopy (EM) still remains challenging because the optimal specimen preparation and imaging conditions for super-resolution fluorescence microscopy and EM are often not compatible. Here, we have developed several experiment protocols for correlative stochastic optical reconstruction microscopy (STORM) and EM methods, both for un-embedded samples by applying EM-specific sample preparations after STORM imaging and for embedded and sectioned samples by optimizing the fluorescence under EM fixation, staining and embedding conditions. We demonstrated these methods using a variety of cellular targets. PMID:25874453

Nanoscale Photoacoustic Tomography (nPAT) for label-free super-resolution 3D imaging of red blood cells

NASA Astrophysics Data System (ADS)

Samant, Pratik; Hernandez, Armando; Conklin, Shelby; Xiang, Liangzhong

2017-08-01

We present our results in developing nanoscale photoacoustic tomography (nPAT) for label-free super-resolution imaging in 3D. We have made progress in the development of nPAT, and have acquired our first signal. We have also performed simulations that demonstrate that nPAT is a viable imaging modality for the visualization of malaria infected red blood cells (RBCs). Our results demonstrate that nPAT is both feasible and powerful for the high resolution labelfree imaging of RBCs.

Super-Joule heating in graphene and silver nanowire network

DOE Office of Scientific and Technical Information (OSTI.GOV)

Maize, Kerry; Das, Suprem R.; Sadeque, Sajia

Transistors, sensors, and transparent conductors based on randomly assembled nanowire networks rely on multi-component percolation for unique and distinctive applications in flexible electronics, biochemical sensing, and solar cells. While conduction models for 1-D and 1-D/2-D networks have been developed, typically assuming linear electronic transport and self-heating, the model has not been validated by direct high-resolution characterization of coupled electronic pathways and thermal response. In this letter, we show the occurrence of nonlinear “super-Joule” self-heating at the transport bottlenecks in networks of silver nanowires and silver nanowire/single layer graphene hybrid using high resolution thermoreflectance (TR) imaging. TR images at the microscopicmore » self-heating hotspots within nanowire network and nanowire/graphene hybrid network devices with submicron spatial resolution are used to infer electrical current pathways. The results encourage a fundamental reevaluation of transport models for network-based percolating conductors.« less

Particle tracking and extended object imaging by interferometric super resolution microscopy

NASA Astrophysics Data System (ADS)

Gdor, Itay; Yoo, Seunghwan; Wang, Xiaolei; Daddysman, Matthew; Wilton, Rosemarie; Ferrier, Nicola; Hereld, Mark; Cossairt, Oliver (Ollie); Katsaggelos, Aggelos; Scherer, Norbert F.

2018-02-01

An interferometric fluorescent microscope and a novel theoretic image reconstruction approach were developed and used to obtain super-resolution images of live biological samples and to enable dynamic real time tracking. The tracking utilizes the information stored in the interference pattern of both the illuminating incoherent light and the emitted light. By periodically shifting the interferometer phase and a phase retrieval algorithm we obtain information that allow localization with sub-2 nm axial resolution at 5 Hz.

Super long viewing distance light homogeneous emitting three-dimensional display

NASA Astrophysics Data System (ADS)

Liao, Hongen

2015-04-01

Three-dimensional (3D) display technology has continuously been attracting public attention with the progress in today's 3D television and mature display technologies. The primary characteristics of conventional glasses-free autostereoscopic displays, such as spatial resolution, image depths, and viewing angle, are often limited due to the use of optical lenses or optical gratings. We present a 3D display using MEMS-scanning-mechanism-based light homogeneous emitting (LHE) approach and demonstrate that the display can directly generate an autostereoscopic 3D image without the need for optical lenses or gratings. The generated 3D image has the advantages of non-aberration and a high-definition spatial resolution, making it the first to exhibit animated 3D images with image depth of six meters. Our LHE 3D display approach can be used to generate a natural flat-panel 3D display with super long viewing distance and alternative real-time image update.

Fast super-resolution with affine motion using an adaptive Wiener filter and its application to airborne imaging.

PubMed

Hardie, Russell C; Barnard, Kenneth J; Ordonez, Raul

2011-12-19

Fast nonuniform interpolation based super-resolution (SR) has traditionally been limited to applications with translational interframe motion. This is in part because such methods are based on an underlying assumption that the warping and blurring components in the observation model commute. For translational motion this is the case, but it is not true in general. This presents a problem for applications such as airborne imaging where translation may be insufficient. Here we present a new Fourier domain analysis to show that, for many image systems, an affine warping model with limited zoom and shear approximately commutes with the point spread function when diffraction effects are modeled. Based on this important result, we present a new fast adaptive Wiener filter (AWF) SR algorithm for non-translational motion and study its performance with affine motion. The fast AWF SR method employs a new smart observation window that allows us to precompute all the needed filter weights for any type of motion without sacrificing much of the full performance of the AWF. We evaluate the proposed algorithm using simulated data and real infrared airborne imagery that contains a thermal resolution target allowing for objective resolution analysis.

Super-resolution from single photon emission: toward biological application

NASA Astrophysics Data System (ADS)

Moreva, E.; Traina, P.; Forneris, J.; Ditalia Tchernij, S.; Guarina, L.; Franchino, C.; Picollo, F.; Ruo Berchera, I.; Brida, G.; Degiovanni, I. P.; Carabelli, V.; Olivero, P.; Genovese, M.

2017-08-01

Properties of quantum light represent a tool for overcoming limits of classical optics. Several experiments have demonstrated this advantage ranging from quantum enhanced imaging to quantum illumination. In this work, experimental demonstration of quantum-enhanced resolution in confocal fluorescence microscopy will be presented. This is achieved by exploiting the non-classical photon statistics of fluorescence emission of single nitrogen-vacancy (NV) color centers in diamond. By developing a general model of super-resolution based on the direct sampling of the kth-order autocorrelation function of the photoluminescence signal, we show the possibility to resolve, in principle, arbitrarily close emitting centers. Finally, possible applications of NV-based fluorescent nanodiamonds in biosensing and future developments will be presented.

Super-resolution photon-efficient imaging by nanometric double-helix point spread function localization of emitters (SPINDLE)

PubMed Central

Grover, Ginni; DeLuca, Keith; Quirin, Sean; DeLuca, Jennifer; Piestun, Rafael

2012-01-01

Super-resolution imaging with photo-activatable or photo-switchable probes is a promising tool in biological applications to reveal previously unresolved intra-cellular details with visible light. This field benefits from developments in the areas of molecular probes, optical systems, and computational post-processing of the data. The joint design of optics and reconstruction processes using double-helix point spread functions (DH-PSF) provides high resolution three-dimensional (3D) imaging over a long depth-of-field. We demonstrate for the first time a method integrating a Fisher information efficient DH-PSF design, a surface relief optical phase mask, and an optimal 3D localization estimator. 3D super-resolution imaging using photo-switchable dyes reveals the 3D microtubule network in mammalian cells with localization precision approaching the information theoretical limit over a depth of 1.2 µm. PMID:23187521

Evaluation of the sparse coding super-resolution method for improving image quality of up-sampled images in computed tomography

NASA Astrophysics Data System (ADS)

Ota, Junko; Umehara, Kensuke; Ishimaru, Naoki; Ohno, Shunsuke; Okamoto, Kentaro; Suzuki, Takanori; Shirai, Naoki; Ishida, Takayuki

2017-02-01

As the capability of high-resolution displays grows, high-resolution images are often required in Computed Tomography (CT). However, acquiring high-resolution images takes a higher radiation dose and a longer scanning time. In this study, we applied the Sparse-coding-based Super-Resolution (ScSR) method to generate high-resolution images without increasing the radiation dose. We prepared the over-complete dictionary learned the mapping between low- and highresolution patches and seek a sparse representation of each patch of the low-resolution input. These coefficients were used to generate the high-resolution output. For evaluation, 44 CT cases were used as the test dataset. We up-sampled images up to 2 or 4 times and compared the image quality of the ScSR scheme and bilinear and bicubic interpolations, which are the traditional interpolation schemes. We also compared the image quality of three learning datasets. A total of 45 CT images, 91 non-medical images, and 93 chest radiographs were used for dictionary preparation respectively. The image quality was evaluated by measuring peak signal-to-noise ratio (PSNR) and structure similarity (SSIM). The differences of PSNRs and SSIMs between the ScSR method and interpolation methods were statistically significant. Visual assessment confirmed that the ScSR method generated a high-resolution image with sharpness, whereas conventional interpolation methods generated over-smoothed images. To compare three different training datasets, there were no significance between the CT, the CXR and non-medical datasets. These results suggest that the ScSR provides a robust approach for application of up-sampling CT images and yields substantial high image quality of extended images in CT.

Windowed time-reversal music technique for super-resolution ultrasound imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Lianjie; Labyed, Yassin

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements.

Super-resolved microsphere-assisted Mirau digital holography by oblique illumination

NASA Astrophysics Data System (ADS)

Abbasian, Vahid; Ganjkhani, Yasaman; Akhlaghi, Ehsan A.; Anand, Arun; Javidi, Bahram; Moradi, Ali-Reza

2018-06-01

In this paper, oblique illumination is used to improve the lateral resolution and edge sharpness in microsphere (MS)-assisted Mirau digital holographic microscopy (Mirau-DHM). Abbe showed that tilting the illumination light allows entrance of higher spatial frequencies into the imaging system thus increasing the resolution power. We extended the idea to common-path DHM, based on Mirau objective, toward super-resolved 3D imaging. High magnification Mirau objectives are very expensive and low-magnification ones suffer from low resolution, therefore, any attempt to increase the effective resolution of the system may be of a great interest. We have already demonstrated the effective resolution increasing of a Mirau-DHM system by incorporating a transparent MS within the working distance of the objective. Here, we show that by integrating a MS-assisted Mirau-DHM with the oblique illumination even higher resolutions can be achieved. We have applied the technique for various samples and have shown the increase in the lateral resolution for the both cases of Mirau-DHM with and without the MS.

Identification and super-resolution imaging of ligand-activated receptor dimers in live cells

NASA Astrophysics Data System (ADS)

Winckler, Pascale; Lartigue, Lydia; Giannone, Gregory; de Giorgi, Francesca; Ichas, François; Sibarita, Jean-Baptiste; Lounis, Brahim; Cognet, Laurent

2013-08-01

Molecular interactions are key to many chemical and biological processes like protein function. In many signaling processes they occur in sub-cellular areas displaying nanoscale organizations and involving molecular assemblies. The nanometric dimensions and the dynamic nature of the interactions make their investigations complex in live cells. While super-resolution fluorescence microscopies offer live-cell molecular imaging with sub-wavelength resolutions, they lack specificity for distinguishing interacting molecule populations. Here we combine super-resolution microscopy and single-molecule Förster Resonance Energy Transfer (FRET) to identify dimers of receptors induced by ligand binding and provide super-resolved images of their membrane distribution in live cells. By developing a two-color universal-Point-Accumulation-In-the-Nanoscale-Topography (uPAINT) method, dimers of epidermal growth factor receptors (EGFR) activated by EGF are studied at ultra-high densities, revealing preferential cell-edge sub-localization. This methodology which is specifically devoted to the study of molecules in interaction, may find other applications in biological systems where understanding of molecular organization is crucial.

Large-area super-resolution optical imaging by using core-shell microfibers

NASA Astrophysics Data System (ADS)

Liu, Cheng-Yang; Lo, Wei-Chieh

2017-09-01

We first numerically and experimentally report large-area super-resolution optical imaging achieved by using core-shell microfibers. The particular spatial electromagnetic waves for different core-shell microfibers are studied by using finite-difference time-domain and ray tracing calculations. The focusing properties of photonic nanojets are evaluated in terms of intensity profile and full width at half-maximum along propagation and transversal directions. In experiment, the general optical fiber is chemically etched down to 6 μm diameter and coated with different metallic thin films by using glancing angle deposition. The direct imaging of photonic nanojets for different core-shell microfibers is performed with a scanning optical microscope system. We show that the intensity distribution of a photonic nanojet is highly related to the metallic shell due to the surface plasmon polaritons. Furthermore, large-area super-resolution optical imaging is performed by using different core-shell microfibers placed over the nano-scale grating with 150 nm line width. The core-shell microfiber-assisted imaging is achieved with super-resolution and hundreds of times the field-of-view in contrast to microspheres. The possible applications of these core-shell optical microfibers include real-time large-area micro-fluidics and nano-structure inspections.

Imaging live cells at high spatiotemporal resolution for lab-on-a-chip applications.

PubMed

Chin, Lip Ket; Lee, Chau-Hwang; Chen, Bi-Chang

2016-05-24

Conventional optical imaging techniques are limited by the diffraction limit and difficult-to-image biomolecular and sub-cellular processes in living specimens. Novel optical imaging techniques are constantly evolving with the desire to innovate an imaging tool that is capable of seeing sub-cellular processes in a biological system, especially in three dimensions (3D) over time, i.e. 4D imaging. For fluorescence imaging on live cells, the trade-offs among imaging depth, spatial resolution, temporal resolution and photo-damage are constrained based on the limited photons of the emitters. The fundamental solution to solve this dilemma is to enlarge the photon bank such as the development of photostable and bright fluorophores, leading to the innovation in optical imaging techniques such as super-resolution microscopy and light sheet microscopy. With the synergy of microfluidic technology that is capable of manipulating biological cells and controlling their microenvironments to mimic in vivo physiological environments, studies of sub-cellular processes in various biological systems can be simplified and investigated systematically. In this review, we provide an overview of current state-of-the-art super-resolution and 3D live cell imaging techniques and their lab-on-a-chip applications, and finally discuss future research trends in new and breakthrough research areas of live specimen 4D imaging in controlled 3D microenvironments.

Effects of whispering gallery mode in microsphere super-resolution imaging

NASA Astrophysics Data System (ADS)

Zhou, Song; Deng, Yongbo; Zhou, Wenchao; Yu, Muxin; Urbach, H. P.; Wu, Yihui

2017-09-01

Whispering Gallery modes have been presented in microscopic glass spheres or toruses with many applications. In this paper, the possible approaches to enhance the imaging resolution by Whispering Gallery modes are discussed, including evanescent waves coupling, transformed and illustration by Whispering Gallery modes. It shows that the high-order scattering modes play the dominant role in the reconstructed virtual image when the Whispering Gallery modes exist. Furthermore, we find that the high image resolution of electric dipoles can be achieved, when the out-of-phase components exist from the illustration of Whispering Gallery modes. Those results of our simulation could contribute to the knowledge of microsphere-assisted super-resolution imaging and its potential applications.

Interrogating Surface Functional Group Heterogeneity of Activated Thermoplastics Using Super-Resolution Fluorescence Microscopy.

PubMed

ONeil, Colleen E; Jackson, Joshua M; Shim, Sang-Hee; Soper, Steven A

2016-04-05

We present a novel approach for characterizing surfaces utilizing super-resolution fluorescence microscopy with subdiffraction limit spatial resolution. Thermoplastic surfaces were activated by UV/O3 or O2 plasma treatment under various conditions to generate pendant surface-confined carboxylic acids (-COOH). These surface functional groups were then labeled with a photoswitchable dye and interrogated using single-molecule, localization-based, super-resolution fluorescence microscopy to elucidate the surface heterogeneity of these functional groups across the activated surface. Data indicated nonuniform distributions of these functional groups for both COC and PMMA thermoplastics with the degree of heterogeneity being dose dependent. In addition, COC demonstrated relative higher surface density of functional groups compared to PMMA for both UV/O3 and O2 plasma treatment. The spatial distribution of -COOH groups secured from super-resolution imaging were used to simulate nonuniform patterns of electroosmotic flow in thermoplastic nanochannels. Simulations were compared to single-particle tracking of fluorescent nanoparticles within thermoplastic nanoslits to demonstrate the effects of surface functional group heterogeneity on the electrokinetic transport process.

Super-resolution algorithm based on sparse representation and wavelet preprocessing for remote sensing imagery

NASA Astrophysics Data System (ADS)

Ren, Ruizhi; Gu, Lingjia; Fu, Haoyang; Sun, Chenglin

2017-04-01

An effective super-resolution (SR) algorithm is proposed for actual spectral remote sensing images based on sparse representation and wavelet preprocessing. The proposed SR algorithm mainly consists of dictionary training and image reconstruction. Wavelet preprocessing is used to establish four subbands, i.e., low frequency, horizontal, vertical, and diagonal high frequency, for an input image. As compared to the traditional approaches involving the direct training of image patches, the proposed approach focuses on the training of features derived from these four subbands. The proposed algorithm is verified using different spectral remote sensing images, e.g., moderate-resolution imaging spectroradiometer (MODIS) images with different bands, and the latest Chinese Jilin-1 satellite images with high spatial resolution. According to the visual experimental results obtained from the MODIS remote sensing data, the SR images using the proposed SR algorithm are superior to those using a conventional bicubic interpolation algorithm or traditional SR algorithms without preprocessing. Fusion algorithms, e.g., standard intensity-hue-saturation, principal component analysis, wavelet transform, and the proposed SR algorithms are utilized to merge the multispectral and panchromatic images acquired by the Jilin-1 satellite. The effectiveness of the proposed SR algorithm is assessed by parameters such as peak signal-to-noise ratio, structural similarity index, correlation coefficient, root-mean-square error, relative dimensionless global error in synthesis, relative average spectral error, spectral angle mapper, and the quality index Q4, and its performance is better than that of the standard image fusion algorithms.

Periodic diffraction correlation imaging without a beam-splitter.

PubMed

Li, Hu; Chen, Zhipeng; Xiong, Jin; Zeng, Guihua

2012-01-30

In this paper, we proposed and demonstrated a new correlation imaging mechanism based on the periodic diffraction effect. In this effect, a periodic intensity pattern is generated at the output surface of a periodic point source array. This novel correlation imaging mechanism can realize super-resolution imaging, Nth-order ghost imaging without a beam-splitter and correlation microscopy.

Super-resolution with an SLM and two intensity images

NASA Astrophysics Data System (ADS)

Alcalá Ochoa, Noé; de León, Y. Ponce

2018-06-01

It is reported a method which may simplify the optical setups used to achieve super-resolution through the amplitude multiplication of two waves. For this end we decompose a super-resolving pupil into two complex masks and with the aid of a Spatial Light Modulator (LCoS) we obtain two intensity images that are subtracted. With this proposal, the traditional experimental optical setups are considerably simplified, with the additional benefit that different masks can be utilized without needing to perform the setup alignment each time.

Super-Resolution Imaging of the Golgi in Live Cells with a Bio-orthogonal Ceramide Probe**

PubMed Central

Erdmann, Roman S.; Takakura, Hideo; Thompson, Alexander D.; Rivera-Molina, Felix; Allgeyer, Edward S.; Bewersdorf, Joerg; Toomre, Derek K.; Schepartz, Alanna

2014-01-01

We report a lipid-based strategy to visualize Golgi structure and dynamics at super-resolution in live cells. The method is based on two novel reagents: a trans-cyclooctene-containing ceramide lipid (Cer-TCO) and a highly reactive, tetrazine-tagged near-IR dye (SiR-Tz). These reagents assemble via an extremely rapid ‘tetrazine-click’ reaction into Cer-SiR, a highly photostable ‘vital dye’ that enables prolonged live cell imaging of the Golgi apparatus by 3D confocal and STED microscopy. Cer-SiR is non-toxic at concentrations as high as 2 μM and does not perturb the mobility of Golgi-resident enzymes or the traffic of cargo from the endoplasmic reticulum through the Golgi and to the plasma membrane. PMID:25081303

Custom Super-Resolution Microscope for the Structural Analysis of Nanostructures

DTIC Science & Technology

2018-05-29

research community. As part of our validation of the new design approach, we performed two - color imaging of pairs of adjacent oligo probes hybridized...nanostructures and biological targets. Our microscope features a large field of view and custom optics that facilitate 3D imaging and enhanced contrast in...our imaging throughput by creating two microscopy platforms for high-throughput, super-resolution materials characterization, with the AO set-up being

Resolution enhancement using simultaneous couple illumination

NASA Astrophysics Data System (ADS)

Hussain, Anwar; Martínez Fuentes, José Luis

2016-10-01

A super-resolution technique based on structured illumination created by a liquid crystal on silicon spatial light modulator (LCOS-SLM) is presented. Single and simultaneous pairs of tilted beams are generated to illuminate a target object. Resolution enhancement of an optical 4f system is demonstrated by using numerical simulations. The resulting intensity images are recorded at a charged couple device (CCD) and stored in the computer memory for further processing. One dimension enhancement can be performed with only 15 images. Two dimensional complete improvement requires 153 different images. The resolution of the optical system is extended three times compared to the band limited system.

Long-distance super-resolution imaging assisted by enhanced spatial Fourier transform.

PubMed

Tang, Heng-He; Liu, Pu-Kun

2015-09-07

A new gradient-index (GRIN) lens that can realize enhanced spatial Fourier transform (FT) over optically long distances is demonstrated. By using an anisotropic GRIN metamaterial with hyperbolic dispersion, evanescent wave in free space can be transformed into propagating wave in the metamaterial and then focused outside due to negative-refraction. Both the results based on the ray tracing and the finite element simulation show that the spatial frequency bandwidth of the spatial FT can be extended to 2.7k(0) (k(0) is the wave vector in free space). Furthermore, assisted by the enhanced spatial FT, a new long-distance (in the optical far-field region) super-resolution imaging scheme is also proposed and the super resolved capability of λ/5 (λ is the wavelength in free space) is verified. The work may provide technical support for designing new-type high-speed microscopes with long working distances.

Lateral resolution improvement in scanning nonlinear dielectric microscopy by measuring super-higher-order nonlinear dielectric constants

NASA Astrophysics Data System (ADS)

Chinone, N.; Yamasue, K.; Hiranaga, Y.; Honda, K.; Cho, Y.

2012-11-01

Scanning nonlinear dielectric microscopy (SNDM) can be used to visualize polarization distributions in ferroelectric materials and dopant profiles in semiconductor devices. Without using a special sharp tip, we achieved an improved lateral resolution in SNDM through the measurement of super-higher-order nonlinearity up to the fourth order. We observed a multidomain single crystal congruent LiTaO3 (CLT) sample, and a cross section of a metal-oxide-semiconductor (MOS) field-effect-transistor (FET). The imaged domain boundaries of the CLT were narrower in the super-higher-order images than in the conventional image. Compared to the conventional method, the super-higher-order method resolved the more detailed structure of the MOSFET.

Super-Resolution Image Reconstruction by Nonlocal Means Applied to High-Angle Annular Darkfield Scanning Transmission Electron Microscopy (HAADF-STEM)

DTIC Science & Technology

2009-10-06

When talking about superresolution we always mean to recover the level of resolution set by the microscope, but by using a time series of low...on low resolution possibly very noisy data, is not feasible. Thus, standard superresolution concepts as described above that are based on registration

Demonstration of nanoimprinted hyperlens array for high-throughput sub-diffraction imaging

NASA Astrophysics Data System (ADS)

Byun, Minsueop; Lee, Dasol; Kim, Minkyung; Kim, Yangdoo; Kim, Kwan; Ok, Jong G.; Rho, Junsuk; Lee, Heon

2017-04-01

Overcoming the resolution limit of conventional optics is regarded as the most important issue in optical imaging science and technology. Although hyperlenses, super-resolution imaging devices based on highly anisotropic dispersion relations that allow the access of high-wavevector components, have recently achieved far-field sub-diffraction imaging in real-time, the previously demonstrated devices have suffered from the extreme difficulties of both the fabrication process and the non-artificial objects placement. This results in restrictions on the practical applications of the hyperlens devices. While implementing large-scale hyperlens arrays in conventional microscopy is desirable to solve such issues, it has not been feasible to fabricate such large-scale hyperlens array with the previously used nanofabrication methods. Here, we suggest a scalable and reliable fabrication process of a large-scale hyperlens device based on direct pattern transfer techniques. We fabricate a 5 cm × 5 cm size hyperlenses array and experimentally demonstrate that it can resolve sub-diffraction features down to 160 nm under 410 nm wavelength visible light. The array-based hyperlens device will provide a simple solution for much more practical far-field and real-time super-resolution imaging which can be widely used in optics, biology, medical science, nanotechnology and other closely related interdisciplinary fields.

Portable and cost-effective pixel super-resolution on-chip microscope for telemedicine applications.

PubMed

Bishara, Waheb; Sikora, Uzair; Mudanyali, Onur; Su, Ting-Wei; Yaglidere, Oguzhan; Luckhart, Shirley; Ozcan, Aydogan

2011-01-01

We report a field-portable lensless on-chip microscope with a lateral resolution of <1 μm and a large field-of-view of ~24 mm(2). This microscope is based on digital in-line holography and a pixel super-resolution algorithm to process multiple lensfree holograms and obtain a single high-resolution hologram. In its compact and cost-effective design, we utilize 23 light emitting diodes butt-coupled to 23 multi-mode optical fibers, and a simple optical filter, with no moving parts. Weighing only ~95 grams, we demonstrate the performance of this field-portable microscope by imaging various objects including human malaria parasites in thin blood smears.

Video Super-Resolution via Bidirectional Recurrent Convolutional Networks.

PubMed

Huang, Yan; Wang, Wei; Wang, Liang

2018-04-01

Super resolving a low-resolution video, namely video super-resolution (SR), is usually handled by either single-image SR or multi-frame SR. Single-Image SR deals with each video frame independently, and ignores intrinsic temporal dependency of video frames which actually plays a very important role in video SR. Multi-Frame SR generally extracts motion information, e.g., optical flow, to model the temporal dependency, but often shows high computational cost. Considering that recurrent neural networks (RNNs) can model long-term temporal dependency of video sequences well, we propose a fully convolutional RNN named bidirectional recurrent convolutional network for efficient multi-frame SR. Different from vanilla RNNs, 1) the commonly-used full feedforward and recurrent connections are replaced with weight-sharing convolutional connections. So they can greatly reduce the large number of network parameters and well model the temporal dependency in a finer level, i.e., patch-based rather than frame-based, and 2) connections from input layers at previous timesteps to the current hidden layer are added by 3D feedforward convolutions, which aim to capture discriminate spatio-temporal patterns for short-term fast-varying motions in local adjacent frames. Due to the cheap convolutional operations, our model has a low computational complexity and runs orders of magnitude faster than other multi-frame SR methods. With the powerful temporal dependency modeling, our model can super resolve videos with complex motions and achieve well performance.

Contact microspherical nanoscopy: from fundamentals to biomedical applications

NASA Astrophysics Data System (ADS)

Astratov, V. N.; Maslov, A. V.; Brettin, A.; Blanchette, K. F.; Nesmelov, Y. E.; Limberopoulos, N. I.; Walker, D. E.; Urbas, A. M.

2017-02-01

The mechanisms of super-resolution imaging by contact microspherical or microcylindrical nanoscopy remain an enigmatic question since these lenses neither have an ability to amplify the near-fields like in the case of far-field superlens, nor they have a hyperbolic dispersion similar to hyperlenses. In this work, we present results along two lines. First, we performed numerical modeling of super-resolution properties of two-dimensional (2-D) circular lens in the limit of wavelength-scale diameters, λ <= D <= 2λ, and relatively high indices of refraction, n=2. Our preliminary results on imaging point dipoles indicate that the resolution is generally close to λ/4 however on resonance with whispering gallery modes it may be slightly higher. Second, experimentally, we used actin protein filaments for the resolution quantification in microspherical nanoscopy. The critical feature of our approach is based on using arrayed cladding layer with strong localized surface plasmon resonances. This layer is used for enhancing plasmonic near-field illumination of our objects. In combination with the magnification of virtual image, this technique resulted in the lateral resolution of actin protein filaments on the order of λ/7.

Holographic pixel super-resolution in portable lensless on-chip microscopy using a fiber-optic array.

PubMed

Bishara, Waheb; Sikora, Uzair; Mudanyali, Onur; Su, Ting-Wei; Yaglidere, Oguzhan; Luckhart, Shirley; Ozcan, Aydogan

2011-04-07

We report a portable lensless on-chip microscope that can achieve <1 µm resolution over a wide field-of-view of ∼ 24 mm(2) without the use of any mechanical scanning. This compact on-chip microscope weighs ∼ 95 g and is based on partially coherent digital in-line holography. Multiple fiber-optic waveguides are butt-coupled to light emitting diodes, which are controlled by a low-cost micro-controller to sequentially illuminate the sample. The resulting lensfree holograms are then captured by a digital sensor-array and are rapidly processed using a pixel super-resolution algorithm to generate much higher resolution holographic images (both phase and amplitude) of the objects. This wide-field and high-resolution on-chip microscope, being compact and light-weight, would be important for global health problems such as diagnosis of infectious diseases in remote locations. Toward this end, we validate the performance of this field-portable microscope by imaging human malaria parasites (Plasmodium falciparum) in thin blood smears. Our results constitute the first-time that a lensfree on-chip microscope has successfully imaged malaria parasites.

Microsphere-assisted super-resolution imaging with enlarged numerical aperture by semi-immersion

NASA Astrophysics Data System (ADS)

Wang, Fengge; Yang, Songlin; Ma, Huifeng; Shen, Ping; Wei, Nan; Wang, Meng; Xia, Yang; Deng, Yun; Ye, Yong-Hong

2018-01-01

Microsphere-assisted imaging is an extraordinary simple technology that can obtain optical super-resolution under white-light illumination. Here, we introduce a method to improve the resolution of a microsphere lens by increasing its numerical aperture. In our proposed structure, BaTiO3 glass (BTG) microsphere lenses are semi-immersed in a S1805 layer with a refractive index of 1.65, and then, the semi-immersed microspheres are fully embedded in an elastomer with an index of 1.4. We experimentally demonstrate that this structure, in combination with a conventional optical microscope, can clearly resolve a two-dimensional 200-nm-diameter hexagonally close-packed (hcp) silica microsphere array. On the contrary, the widely used structure where BTG microsphere lenses are fully immersed in a liquid or elastomer cannot even resolve a 250-nm-diameter hcp silica microsphere array. The improvement in resolution through the proposed structure is due to an increase in the effective numerical aperture by semi-immersing BTG microsphere lenses in a high-refractive-index S1805 layer. Our results will inform on the design of microsphere-based high-resolution imaging systems.

High resolution laboratory grating-based x-ray phase-contrast CT

NASA Astrophysics Data System (ADS)

Viermetz, Manuel P.; Birnbacher, Lorenz J. B.; Fehringer, Andreas; Willner, Marian; Noel, Peter B.; Pfeiffer, Franz; Herzen, Julia

2017-03-01

Grating-based phase-contrast computed tomography (gbPC-CT) is a promising imaging method for imaging of soft tissue contrast without the need of any contrast agent. The focus of this study is the increase in spatial resolution without loss in sensitivity to allow visualization of pathologies comparable to the convincing results obtained at the synchrotron. To improve the effective pixel size a super-resolution reconstruction based on subpixel shifts involving a deconvolution of the image is applied on differential phase-contrast data. In our study we could achieve an effective pixel sizes of 28mm without any drawback in terms of sensitivity or the ability to measure quantitative data.

Adaptive Wiener filter super-resolution of color filter array images.

PubMed

Karch, Barry K; Hardie, Russell C

2013-08-12

Digital color cameras using a single detector array with a Bayer color filter array (CFA) require interpolation or demosaicing to estimate missing color information and provide full-color images. However, demosaicing does not specifically address fundamental undersampling and aliasing inherent in typical camera designs. Fast non-uniform interpolation based super-resolution (SR) is an attractive approach to reduce or eliminate aliasing and its relatively low computational load is amenable to real-time applications. The adaptive Wiener filter (AWF) SR algorithm was initially developed for grayscale imaging and has not previously been applied to color SR demosaicing. Here, we develop a novel fast SR method for CFA cameras that is based on the AWF SR algorithm and uses global channel-to-channel statistical models. We apply this new method as a stand-alone algorithm and also as an initialization image for a variational SR algorithm. This paper presents the theoretical development of the color AWF SR approach and applies it in performance comparisons to other SR techniques for both simulated and real data.

Super-Resolution for “Jilin-1” Satellite Video Imagery via a Convolutional Network

PubMed Central

Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-01-01

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method’s practicality. Experimental results on “Jilin-1” satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods. PMID:29652838

Super-Resolution for "Jilin-1" Satellite Video Imagery via a Convolutional Network.

PubMed

Xiao, Aoran; Wang, Zhongyuan; Wang, Lei; Ren, Yexian

2018-04-13

Super-resolution for satellite video attaches much significance to earth observation accuracy, and the special imaging and transmission conditions on the video satellite pose great challenges to this task. The existing deep convolutional neural-network-based methods require pre-processing or post-processing to be adapted to a high-resolution size or pixel format, leading to reduced performance and extra complexity. To this end, this paper proposes a five-layer end-to-end network structure without any pre-processing and post-processing, but imposes a reshape or deconvolution layer at the end of the network to retain the distribution of ground objects within the image. Meanwhile, we formulate a joint loss function by combining the output and high-dimensional features of a non-linear mapping network to precisely learn the desirable mapping relationship between low-resolution images and their high-resolution counterparts. Also, we use satellite video data itself as a training set, which favors consistency between training and testing images and promotes the method's practicality. Experimental results on "Jilin-1" satellite video imagery show that this method demonstrates a superior performance in terms of both visual effects and measure metrics over competing methods.

A stochastically fully connected conditional random field framework for super resolution OCT

NASA Astrophysics Data System (ADS)

Boroomand, A.; Tan, B.; Wong, A.; Bizheva, K.

2017-02-01

A number of factors can degrade the resolution and contrast of OCT images, such as: (1) changes of the OCT pointspread function (PSF) resulting from wavelength dependent scattering and absorption of light along the imaging depth (2) speckle noise, as well as (3) motion artifacts. We propose a new Super Resolution OCT (SR OCT) imaging framework that takes advantage of a Stochastically Fully Connected Conditional Random Field (SF-CRF) model to generate a Super Resolved OCT (SR OCT) image of higher quality from a set of Low-Resolution OCT (LR OCT) images. The proposed SF-CRF SR OCT imaging is able to simultaneously compensate for all of the factors mentioned above, that degrade the OCT image quality, using a unified computational framework. The proposed SF-CRF SR OCT imaging framework was tested on a set of simulated LR human retinal OCT images generated from a high resolution, high contrast retinal image, and on a set of in-vivo, high resolution, high contrast rat retinal OCT images. The reconstructed SR OCT images show considerably higher spatial resolution, less speckle noise and higher contrast compared to other tested methods. Visual assessment of the results demonstrated the usefulness of the proposed approach in better preservation of fine details and structures of the imaged sample, retaining biological tissue boundaries while reducing speckle noise using a unified computational framework. Quantitative evaluation using both Contrast to Noise Ratio (CNR) and Edge Preservation (EP) parameter also showed superior performance of the proposed SF-CRF SR OCT approach compared to other image processing approaches.

Saliency-Guided Change Detection of Remotely Sensed Images Using Random Forest

NASA Astrophysics Data System (ADS)

Feng, W.; Sui, H.; Chen, X.

2018-04-01

Studies based on object-based image analysis (OBIA) representing the paradigm shift in change detection (CD) have achieved remarkable progress in the last decade. Their aim has been developing more intelligent interpretation analysis methods in the future. The prediction effect and performance stability of random forest (RF), as a new kind of machine learning algorithm, are better than many single predictors and integrated forecasting method. In this paper, we present a novel CD approach for high-resolution remote sensing images, which incorporates visual saliency and RF. First, highly homogeneous and compact image super-pixels are generated using super-pixel segmentation, and the optimal segmentation result is obtained through image superimposition and principal component analysis (PCA). Second, saliency detection is used to guide the search of interest regions in the initial difference image obtained via the improved robust change vector analysis (RCVA) algorithm. The salient regions within the difference image that correspond to the binarized saliency map are extracted, and the regions are subject to the fuzzy c-means (FCM) clustering to obtain the pixel-level pre-classification result, which can be used as a prerequisite for superpixel-based analysis. Third, on the basis of the optimal segmentation and pixel-level pre-classification results, different super-pixel change possibilities are calculated. Furthermore, the changed and unchanged super-pixels that serve as the training samples are automatically selected. The spectral features and Gabor features of each super-pixel are extracted. Finally, superpixel-based CD is implemented by applying RF based on these samples. Experimental results on Ziyuan 3 (ZY3) multi-spectral images show that the proposed method outperforms the compared methods in the accuracy of CD, and also confirm the feasibility and effectiveness of the proposed approach.

Location and Geologic Setting for the Three U.S. Mars Landers

NASA Technical Reports Server (NTRS)

Parker, T. J.; Kirk, R. L.

1999-01-01

Super resolution of the horizon at both Viking landing sites has revealed "new" features we use for triangulation, similar to the approach used during the Mars Pathfinder Mission. We propose alternative landing site locations for both landers for which we believe the confidence is very high. Super resolution of VL-1 images also reveals some of the drift material at the site to consist of gravel-size deposits. Since our proposed location for VL-2 is NOT on the Mie ejecta blanket, the blocky surface around the lander may represent the meter-scale texture of "smooth palins" in the region. The Viking Lander panchromatic images typically offer more repeat coverage than does the IMP on Mars Pathfinder, due to the longer duration of these landed missions. Sub-pixel offsets, necessary for super resolution to work, appear to be attributable to thermal effects on the lander and settling of the lander over time. Due to the greater repeat coverage (particularly in the near and mid-fields) and all-panchromatic images, the gain in resolution by super resolution processing is better for Viking than it is with most IMP image sequences. This enhances the study of textural details near the lander and enables the identification rock and surface textures at greater distances from the lander. Discernment of stereo in super resolution im-ages is possible to great distances from the lander, but is limited by the non-rotating baseline between the two cameras and the shorter height of the cameras above the ground compared to IMP. With super resolution, details of horizon features, such as blockiness and crater rim shapes, may be better correlated with Orbiter images. A number of horizon features - craters and ridges - were identified at VL-1 during the misison, and a few hils and subtle ridges were identified at VL-2. We have added a few "new" horizon features for triangulation at the VL-2 landing site in Utopia Planitia. These features were used for independent triangulation with features visible in Viking Orbiter and MGS MOC images, though the actual location of VL-1 lies in a data dropout in the MOC image of the area. Additional information is contained in the original extended abstract.

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI.

PubMed

Gholipour, Ali; Afacan, Onur; Aganj, Iman; Scherrer, Benoit; Prabhu, Sanjay P; Sahin, Mustafa; Warfield, Simon K

2015-12-01

To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans.

Super-resolution depth information from a short-wave infrared laser gated-viewing system by using correlated double sampling

NASA Astrophysics Data System (ADS)

Göhler, Benjamin; Lutzmann, Peter

2017-10-01

Primarily, a laser gated-viewing (GV) system provides range-gated 2D images without any range resolution within the range gate. By combining two GV images with slightly different gate positions, 3D information within a part of the range gate can be obtained. The depth resolution is higher (super-resolution) than the minimal gate shift step size in a tomographic sequence of the scene. For a state-of-the-art system with a typical frame rate of 20 Hz, the time difference between the two required GV images is 50 ms which may be too long in a dynamic scenario with moving objects. Therefore, we have applied this approach to the reset and signal level images of a new short-wave infrared (SWIR) GV camera whose read-out integrated circuit supports correlated double sampling (CDS) actually intended for the reduction of kTC noise (reset noise). These images are extracted from only one single laser pulse with a marginal time difference in between. The SWIR GV camera consists of 640 x 512 avalanche photodiodes based on mercury cadmium telluride with a pixel pitch of 15 μm. A Q-switched, flash lamp pumped solid-state laser with 1.57 μm wavelength (OPO), 52 mJ pulse energy after beam shaping, 7 ns pulse length and 20 Hz pulse repetition frequency is used for flash illumination. In this paper, the experimental set-up is described and the operating principle of CDS is explained. The method of deriving super-resolution depth information from a GV system by using CDS is introduced and optimized. Further, the range accuracy is estimated from measured image data.

Multiple signal classification algorithm for super-resolution fluorescence microscopy

PubMed Central

Agarwal, Krishna; Macháň, Radek

2016-01-01

Single-molecule localization techniques are restricted by long acquisition and computational times, or the need of special fluorophores or biologically toxic photochemical environments. Here we propose a statistical super-resolution technique of wide-field fluorescence microscopy we call the multiple signal classification algorithm which has several advantages. It provides resolution down to at least 50 nm, requires fewer frames and lower excitation power and works even at high fluorophore concentrations. Further, it works with any fluorophore that exhibits blinking on the timescale of the recording. The multiple signal classification algorithm shows comparable or better performance in comparison with single-molecule localization techniques and four contemporary statistical super-resolution methods for experiments of in vitro actin filaments and other independently acquired experimental data sets. We also demonstrate super-resolution at timescales of 245 ms (using 49 frames acquired at 200 frames per second) in samples of live-cell microtubules and live-cell actin filaments imaged without imaging buffers. PMID:27934858

Propagation phasor approach for holographic image reconstruction

PubMed Central

Luo, Wei; Zhang, Yibo; Göröcs, Zoltán; Feizi, Alborz; Ozcan, Aydogan

2016-01-01

To achieve high-resolution and wide field-of-view, digital holographic imaging techniques need to tackle two major challenges: phase recovery and spatial undersampling. Previously, these challenges were separately addressed using phase retrieval and pixel super-resolution algorithms, which utilize the diversity of different imaging parameters. Although existing holographic imaging methods can achieve large space-bandwidth-products by performing pixel super-resolution and phase retrieval sequentially, they require large amounts of data, which might be a limitation in high-speed or cost-effective imaging applications. Here we report a propagation phasor approach, which for the first time combines phase retrieval and pixel super-resolution into a unified mathematical framework and enables the synthesis of new holographic image reconstruction methods with significantly improved data efficiency. In this approach, twin image and spatial aliasing signals, along with other digital artifacts, are interpreted as noise terms that are modulated by phasors that analytically depend on the lateral displacement between hologram and sensor planes, sample-to-sensor distance, wavelength, and the illumination angle. Compared to previous holographic reconstruction techniques, this new framework results in five- to seven-fold reduced number of raw measurements, while still achieving a competitive resolution and space-bandwidth-product. We also demonstrated the success of this approach by imaging biological specimens including Papanicolaou and blood smears. PMID:26964671

Micelle-templated composite quantum dots for super-resolution imaging.

PubMed

Xu, Jianquan; Fan, Qirui; Mahajan, Kalpesh D; Ruan, Gang; Herrington, Andrew; Tehrani, Kayvan F; Kner, Peter; Winter, Jessica O

2014-05-16

Quantum dots (QDs) have tremendous potential for biomedical imaging, including super-resolution techniques that permit imaging below the diffraction limit. However, most QDs are produced via organic methods, and hence require surface treatment to render them water-soluble for biological applications. Previously, we reported a micelle-templating method that yields nanocomposites containing multiple core/shell ZnS-CdSe QDs within the same nanocarrier, increasing overall particle brightness and virtually eliminating QD blinking. Here, this technique is extended to the encapsulation of Mn-doped ZnSe QDs (Mn-ZnSe QDs), which have potential applications in super-resolution imaging as a result of the introduction of Mn(2+) dopant energy levels. The size, shape and fluorescence characteristics of these doped QD-micelles were compared to those of micelles created using core/shell ZnS-CdSe QDs (ZnS-CdSe QD-micelles). Additionally, the stability of both types of particles to photo-oxidation was investigated. Compared to commercial QDs, micelle-templated QDs demonstrated superior fluorescence intensity, higher signal-to-noise ratios, and greater stability against photo-oxidization,while reducing blinking. Additionally, the fluorescence of doped QD-micelles could be modulated from a bright 'on' state to a dark 'off' state, with a modulation depth of up to 76%, suggesting the potential of doped QD-micelles for applications in super-resolution imaging.

Demosaiced pixel super-resolution for multiplexed holographic color imaging

PubMed Central

Wu, Yichen; Zhang, Yibo; Luo, Wei; Ozcan, Aydogan

2016-01-01

To synthesize a holographic color image, one can sequentially take three holograms at different wavelengths, e.g., at red (R), green (G) and blue (B) parts of the spectrum, and digitally merge them. To speed up the imaging process by a factor of three, a Bayer color sensor-chip can also be used to demultiplex three wavelengths that simultaneously illuminate the sample and digitally retrieve individual set of holograms using the known transmission spectra of the Bayer color filters. However, because the pixels of different channels (R, G, B) on a Bayer color sensor are not at the same physical location, conventional demosaicing techniques generate color artifacts in holographic imaging using simultaneous multi-wavelength illumination. Here we demonstrate that pixel super-resolution can be merged into the color de-multiplexing process to significantly suppress the artifacts in wavelength-multiplexed holographic color imaging. This new approach, termed Demosaiced Pixel Super-Resolution (D-PSR), generates color images that are similar in performance to sequential illumination at three wavelengths, and therefore improves the speed of holographic color imaging by 3-fold. D-PSR method is broadly applicable to holographic microscopy applications, where high-resolution imaging and multi-wavelength illumination are desired. PMID:27353242

Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue

PubMed Central

Spühler, Isabelle A.; Conley, Gaurasundar M.; Scheffold, Frank; Sprecher, Simon G.

2016-01-01

Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation. PMID:27303270

Super Resolution Imaging of Genetically Labeled Synapses in Drosophila Brain Tissue.

PubMed

Spühler, Isabelle A; Conley, Gaurasundar M; Scheffold, Frank; Sprecher, Simon G

2016-01-01

Understanding synaptic connectivity and plasticity within brain circuits and their relationship to learning and behavior is a fundamental quest in neuroscience. Visualizing the fine details of synapses using optical microscopy remains however a major technical challenge. Super resolution microscopy opens the possibility to reveal molecular features of synapses beyond the diffraction limit. With direct stochastic optical reconstruction microscopy, dSTORM, we image synaptic proteins in the brain tissue of the fruit fly, Drosophila melanogaster. Super resolution imaging of brain tissue harbors difficulties due to light scattering and the density of signals. In order to reduce out of focus signal, we take advantage of the genetic tools available in the Drosophila and have fluorescently tagged synaptic proteins expressed in only a small number of neurons. These neurons form synapses within the calyx of the mushroom body, a distinct brain region involved in associative memory formation. Our results show that super resolution microscopy, in combination with genetically labeled synaptic proteins, is a powerful tool to investigate synapses in a quantitative fashion providing an entry point for studies on synaptic plasticity during learning and memory formation.

Label-free photoacoustic nanoscopy

PubMed Central

Danielli, Amos; Maslov, Konstantin; Garcia-Uribe, Alejandro; Winkler, Amy M.; Li, Chiye; Wang, Lidai; Chen, Yun; Dorn, Gerald W.; Wang, Lihong V.

2014-01-01

Abstract. Super-resolution microscopy techniques—capable of overcoming the diffraction limit of light—have opened new opportunities to explore subcellular structures and dynamics not resolvable in conventional far-field microscopy. However, relying on staining with exogenous fluorescent markers, these techniques can sometimes introduce undesired artifacts to the image, mainly due to large tagging agent sizes and insufficient or variable labeling densities. By contrast, the use of endogenous pigments allows imaging of the intrinsic structures of biological samples with unaltered molecular constituents. Here, we report label-free photoacoustic (PA) nanoscopy, which is exquisitely sensitive to optical absorption, with an 88 nm resolution. At each scanning position, multiple PA signals are successively excited with increasing laser pulse energy. Because of optical saturation or nonlinear thermal expansion, the PA amplitude depends on the nonlinear incident optical fluence. The high-order dependence, quantified by polynomial fitting, provides super-resolution imaging with optical sectioning. PA nanoscopy is capable of super-resolution imaging of either fluorescent or nonfluorescent molecules. PMID:25104412

Full-field dual-color 100-nm super-resolution imaging reveals organization and dynamics of mitochondrial and ER networks.

PubMed

Brunstein, Maia; Wicker, Kai; Hérault, Karine; Heintzmann, Rainer; Oheim, Martin

2013-11-04

Most structured illumination microscopes use a physical or synthetic grating that is projected into the sample plane to generate a periodic illumination pattern. Albeit simple and cost-effective, this arrangement hampers fast or multi-color acquisition, which is a critical requirement for time-lapse imaging of cellular and sub-cellular dynamics. In this study, we designed and implemented an interferometric approach allowing large-field, fast, dual-color imaging at an isotropic 100-nm resolution based on a sub-diffraction fringe pattern generated by the interference of two colliding evanescent waves. Our all-mirror-based system generates illumination pat-terns of arbitrary orientation and period, limited only by the illumination aperture (NA = 1.45), the response time of a fast, piezo-driven tip-tilt mirror (10 ms) and the available fluorescence signal. At low µW laser powers suitable for long-period observation of life cells and with a camera exposure time of 20 ms, our system permits the acquisition of super-resolved 50 µm by 50 µm images at 3.3 Hz. The possibility it offers for rapidly adjusting the pattern between images is particularly advantageous for experiments that require multi-scale and multi-color information. We demonstrate the performance of our instrument by imaging mitochondrial dynamics in cultured cortical astrocytes. As an illustration of dual-color excitation dual-color detection, we also resolve interaction sites between near-membrane mitochondria and the endoplasmic reticulum. Our TIRF-SIM microscope provides a versatile, compact and cost-effective arrangement for super-resolution imaging, allowing the investigation of co-localization and dynamic interactions between organelles--important questions in both cell biology and neurophysiology.

Fast range estimation based on active range-gated imaging for coastal surveillance

NASA Astrophysics Data System (ADS)

Kong, Qingshan; Cao, Yinan; Wang, Xinwei; Tong, Youwan; Zhou, Yan; Liu, Yuliang

2012-11-01

Coastal surveillance is very important because it is useful for search and rescue, illegal immigration, or harbor security and so on. Furthermore, range estimation is critical for precisely detecting the target. Range-gated laser imaging sensor is suitable for high accuracy range especially in night and no moonlight. Generally, before detecting the target, it is necessary to change delay time till the target is captured. There are two operating mode for range-gated imaging sensor, one is passive imaging mode, and the other is gate viewing mode. Firstly, the sensor is passive mode, only capturing scenes by ICCD, once the object appears in the range of monitoring area, we can obtain the course range of the target according to the imaging geometry/projecting transform. Then, the sensor is gate viewing mode, applying micro second laser pulses and sensor gate width, we can get the range of targets by at least two continuous images with trapezoid-shaped range intensity profile. This technique enables super-resolution depth mapping with a reduction of imaging data processing. Based on the first step, we can calculate the rough value and quickly fix delay time which the target is detected. This technique has overcome the depth resolution limitation for 3D active imaging and enables super-resolution depth mapping with a reduction of imaging data processing. By the two steps, we can quickly obtain the distance between the object and sensor.

Single-Image Super Resolution for Multispectral Remote Sensing Data Using Convolutional Neural Networks

NASA Astrophysics Data System (ADS)

Liebel, L.; Körner, M.

2016-06-01

In optical remote sensing, spatial resolution of images is crucial for numerous applications. Space-borne systems are most likely to be affected by a lack of spatial resolution, due to their natural disadvantage of a large distance between the sensor and the sensed object. Thus, methods for single-image super resolution are desirable to exceed the limits of the sensor. Apart from assisting visual inspection of datasets, post-processing operations—e.g., segmentation or feature extraction—can benefit from detailed and distinguishable structures. In this paper, we show that recently introduced state-of-the-art approaches for single-image super resolution of conventional photographs, making use of deep learning techniques, such as convolutional neural networks (CNN), can successfully be applied to remote sensing data. With a huge amount of training data available, end-to-end learning is reasonably easy to apply and can achieve results unattainable using conventional handcrafted algorithms. We trained our CNN on a specifically designed, domain-specific dataset, in order to take into account the special characteristics of multispectral remote sensing data. This dataset consists of publicly available SENTINEL-2 images featuring 13 spectral bands, a ground resolution of up to 10m, and a high radiometric resolution and thus satisfying our requirements in terms of quality and quantity. In experiments, we obtained results superior compared to competing approaches trained on generic image sets, which failed to reasonably scale satellite images with a high radiometric resolution, as well as conventional interpolation methods.

Super-resolution imaging and tracking of protein-protein interactions in sub-diffraction cellular space

NASA Astrophysics Data System (ADS)

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-07-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein-protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB-EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB-EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB-EF-Tu interactions.

Super-resolution imaging and tracking of protein–protein interactions in sub-diffraction cellular space

PubMed Central

Liu, Zhen; Xing, Dong; Su, Qian Peter; Zhu, Yun; Zhang, Jiamei; Kong, Xinyu; Xue, Boxin; Wang, Sheng; Sun, Hao; Tao, Yile; Sun, Yujie

2014-01-01

Imaging the location and dynamics of individual interacting protein pairs is essential but often difficult because of the fluorescent background from other paired and non-paired molecules, particularly in the sub-diffraction cellular space. Here we develop a new method combining bimolecular fluorescence complementation and photoactivated localization microscopy for super-resolution imaging and single-molecule tracking of specific protein–protein interactions. The method is used to study the interaction of two abundant proteins, MreB and EF-Tu, in Escherichia coli cells. The super-resolution imaging shows interesting distribution and domain sizes of interacting MreB–EF-Tu pairs as a subpopulation of total EF-Tu. The single-molecule tracking of MreB, EF-Tu and MreB–EF-Tu pairs reveals intriguing localization-dependent heterogonous dynamics and provides valuable insights to understanding the roles of MreB–EF-Tu interactions. PMID:25030837

Improved Wallis Dodging Algorithm for Large-Scale Super-Resolution Reconstruction Remote Sensing Images.

PubMed

Fan, Chong; Chen, Xushuai; Zhong, Lei; Zhou, Min; Shi, Yun; Duan, Yulin

2017-03-18

A sub-block algorithm is usually applied in the super-resolution (SR) reconstruction of images because of limitations in computer memory. However, the sub-block SR images can hardly achieve a seamless image mosaicking because of the uneven distribution of brightness and contrast among these sub-blocks. An effectively improved weighted Wallis dodging algorithm is proposed, aiming at the characteristic that SR reconstructed images are gray images with the same size and overlapping region. This algorithm can achieve consistency of image brightness and contrast. Meanwhile, a weighted adjustment sequence is presented to avoid the spatial propagation and accumulation of errors and the loss of image information caused by excessive computation. A seam line elimination method can share the partial dislocation in the seam line to the entire overlapping region with a smooth transition effect. Subsequently, the improved method is employed to remove the uneven illumination for 900 SR reconstructed images of ZY-3. Then, the overlapping image mosaic method is adopted to accomplish a seamless image mosaic based on the optimal seam line.

Super-resolution mapping using multi-viewing CHRIS/PROBA data

NASA Astrophysics Data System (ADS)

Dwivedi, Manish; Kumar, Vinay

2016-04-01

High-spatial resolution Remote Sensing (RS) data provides detailed information which ensures high-definition visual image analysis of earth surface features. These data sets also support improved information extraction capabilities at a fine scale. In order to improve the spatial resolution of coarser resolution RS data, the Super Resolution Reconstruction (SRR) technique has become widely acknowledged which focused on multi-angular image sequences. In this study multi-angle CHRIS/PROBA data of Kutch area is used for SR image reconstruction to enhance the spatial resolution from 18 m to 6m in the hope to obtain a better land cover classification. Various SR approaches like Projection onto Convex Sets (POCS), Robust, Iterative Back Projection (IBP), Non-Uniform Interpolation and Structure-Adaptive Normalized Convolution (SANC) chosen for this study. Subjective assessment through visual interpretation shows substantial improvement in land cover details. Quantitative measures including peak signal to noise ratio and structural similarity are used for the evaluation of the image quality. It was observed that SANC SR technique using Vandewalle algorithm for the low resolution image registration outperformed the other techniques. After that SVM based classifier is used for the classification of SRR and data resampled to 6m spatial resolution using bi-cubic interpolation. A comparative analysis is carried out between classified data of bicubic interpolated and SR derived images of CHRIS/PROBA and SR derived classified data have shown a significant improvement of 10-12% in the overall accuracy. The results demonstrated that SR methods is able to improve spatial detail of multi-angle images as well as the classification accuracy.

Quantitative super-resolution single molecule microscopy dataset of YFP-tagged growth factor receptors.

PubMed

Lukeš, Tomáš; Pospíšil, Jakub; Fliegel, Karel; Lasser, Theo; Hagen, Guy M

2018-03-01

Super-resolution single molecule localization microscopy (SMLM) is a method for achieving resolution beyond the classical limit in optical microscopes (approx. 200 nm laterally). Yellow fluorescent protein (YFP) has been used for super-resolution single molecule localization microscopy, but less frequently than other fluorescent probes. Working with YFP in SMLM is a challenge because a lower number of photons are emitted per molecule compared with organic dyes, which are more commonly used. Publically available experimental data can facilitate development of new data analysis algorithms. Four complete, freely available single molecule super-resolution microscopy datasets on YFP-tagged growth factor receptors expressed in a human cell line are presented, including both raw and analyzed data. We report methods for sample preparation, for data acquisition, and for data analysis, as well as examples of the acquired images. We also analyzed the SMLM datasets using a different method: super-resolution optical fluctuation imaging (SOFI). The 2 modes of analysis offer complementary information about the sample. A fifth single molecule super-resolution microscopy dataset acquired with the dye Alexa 532 is included for comparison purposes. This dataset has potential for extensive reuse. Complete raw data from SMLM experiments have typically not been published. The YFP data exhibit low signal-to-noise ratios, making data analysis a challenge. These datasets will be useful to investigators developing their own algorithms for SMLM, SOFI, and related methods. The data will also be useful for researchers investigating growth factor receptors such as ErbB3.

Nano-scale measurement of biomolecules by optical microscopy and semiconductor nanoparticles

PubMed Central

Ichimura, Taro; Jin, Takashi; Fujita, Hideaki; Higuchi, Hideo; Watanabe, Tomonobu M.

2014-01-01

Over the past decade, great developments in optical microscopy have made this technology increasingly compatible with biological studies. Fluorescence microscopy has especially contributed to investigating the dynamic behaviors of live specimens and can now resolve objects with nanometer precision and resolution due to super-resolution imaging. Additionally, single particle tracking provides information on the dynamics of individual proteins at the nanometer scale both in vitro and in cells. Complementing advances in microscopy technologies has been the development of fluorescent probes. The quantum dot, a semi-conductor fluorescent nanoparticle, is particularly suitable for single particle tracking and super-resolution imaging. This article overviews the principles of single particle tracking and super resolution along with describing their application to the nanometer measurement/observation of biological systems when combined with quantum dot technologies. PMID:25120488

From single-molecule spectroscopy to super-resolution imaging of the neuron: a review

PubMed Central

Laine, Romain F; Kaminski Schierle, Gabriele S; van de Linde, Sebastian; Kaminski, Clemens F

2016-01-01

Abstract For more than 20 years, single-molecule spectroscopy has been providing invaluable insights into nature at the molecular level. The field has received a powerful boost with the development of the technique into super-resolution imaging methods, ca. 10 years ago, which overcome the limitations imposed by optical diffraction. Today, single molecule super-resolution imaging is routinely used in the study of macromolecular function and structure in the cell. Concomitantly, computational methods have been developed that provide information on numbers and positions of molecules at the nanometer-scale. In this overview, we outline the technical developments that have led to the emergence of localization microscopy techniques from single-molecule spectroscopy. We then provide a comprehensive review on the application of the technique in the field of neuroscience research. PMID:28809165

Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

PubMed Central

Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; Edwards, Thayne L.; James, Conrad D.; Lidke, Keith A.

2016-01-01

We have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single molecule super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet. PMID:27375939

Assessing resolution in live cell structured illumination microscopy

NASA Astrophysics Data System (ADS)

Pospíšil, Jakub; Fliegel, Karel; Klíma, Miloš

2017-12-01

Structured Illumination Microscopy (SIM) is a powerful super-resolution technique, which is able to enhance the resolution of optical microscope beyond the Abbe diffraction limit. In the last decade, numerous SIM methods that achieve the resolution of 100 nm in the lateral dimension have been developed. The SIM setups with new high-speed cameras and illumination pattern generators allow rapid acquisition of the live specimen. Therefore, SIM is widely used for investigation of the live structures in molecular and live cell biology. Quantitative evaluation of resolution enhancement in a real sample is essential to describe the efficiency of super-resolution microscopy technique. However, measuring the resolution of a live cell sample is a challenging task. Based on our experimental findings, the widely used Fourier ring correlation (FRC) method does not seem to be well suited for measuring the resolution of SIM live cell video sequences. Therefore, the resolution assessing methods based on Fourier spectrum analysis are often used. We introduce a measure based on circular average power spectral density (PSDca) estimated from a single SIM image (one video frame). PSDca describes the distribution of the power of a signal with respect to its spatial frequency. Spatial resolution corresponds to the cut-off frequency in Fourier space. In order to estimate the cut-off frequency from a noisy signal, we use a spectral subtraction method for noise suppression. In the future, this resolution assessment approach might prove useful also for single-molecule localization microscopy (SMLM) live cell imaging.

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gholipour, Ali, E-mail: ali.gholipour@childrens.harvard.edu; Afacan, Onur; Scherrer, Benoit

Purpose: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. Methods: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) ofmore » image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Results: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. Conclusions: Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans.« less

Super-resolution reconstruction in frequency, image, and wavelet domains to reduce through-plane partial voluming in MRI

PubMed Central

Gholipour, Ali; Afacan, Onur; Aganj, Iman; Scherrer, Benoit; Prabhu, Sanjay P.; Sahin, Mustafa; Warfield, Simon K.

2015-01-01

Purpose: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. Methods: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Results: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in resampled out-of-plane views consistently showed the superiority of SRR compared to original axial and coronal image acquisitions. Conclusions: Thick-slice 2D T2-weighted MRI scans are part of many routine clinical protocols due to their high signal-to-noise ratio, but are often severely affected by through-plane partial voluming effects. This study shows that while radiologic assessment is performed in 2D on thick-slice scans, super-resolution MRI reconstruction techniques can be used to fuse those scans to generate a high-resolution image with reduced partial voluming for improved postacquisition processing. Qualitative and quantitative evaluation showed the efficacy of all SRR techniques with the best results obtained from SRR in the image domain. The limitations of SRR techniques are uncertainties in modeling the slice profile, density compensation, quantization in resampling, and uncompensated motion between scans. PMID:26632048

Three-Dimensional Super-Resolution: Theory, Modeling, and Field Tests Results

NASA Technical Reports Server (NTRS)

Bulyshev, Alexander; Amzajerdian, Farzin; Roback, Vincent E.; Hines, Glenn; Pierrottet, Diego; Reisse, Robert

2014-01-01

Many flash lidar applications continue to demand higher three-dimensional image resolution beyond the current state-of-the-art technology of the detector arrays and their associated readout circuits. Even with the available number of focal plane pixels, the required number of photons for illuminating all the pixels may impose impractical requirements on the laser pulse energy or the receiver aperture size. Therefore, image resolution enhancement by means of a super-resolution algorithm in near real time presents a very attractive solution for a wide range of flash lidar applications. This paper describes a superresolution technique and illustrates its performance and merits for generating three-dimensional image frames at a video rate.

Long Time-lapse Nanoscopy with Spontaneously Blinking Membrane Probes

PubMed Central

Takakura, Hideo; Zhang, Yongdeng; Erdmann, Roman S.; Thompson, Alexander D.; Lin, Yu; McNellis, Brian; Rivera-Molina, Felix; Uno, Shin-nosuke; Kamiya, Mako; Urano, Yasuteru; Rothman, James E.; Bewersdorf, Joerg; Schepartz, Alanna; Toomre, Derek

2017-01-01

Long time-lapse, diffraction-unlimited super-resolution imaging of cellular structures and organelles in living cells is highly challenging, as it requires dense labeling, bright, highly photostable dyes, and non-toxic conditions. We developed a set of high-density, environment-sensitive (HIDE) membrane probes based on HMSiR that assemble in situ and enable long time-lapse, live cell nanoscopy of discrete cellular structures and organelles with high spatio-temporal resolution. HIDE-enabled nanoscopy movies are up to 50x longer than movies obtained with labeled proteins, reveal the 2D dynamics of the mitochondria, plasma membrane, and filopodia, and the 2D and 3D dynamics of the endoplasmic reticulum in living cells. These new HIDE probes also facilitate the acquisition of live cell, two-color, super-resolution images, greatly expanding the utility of nanoscopy to visualize processes and structures in living cells. PMID:28671662

Structural analysis of herpes simplex virus by optical super-resolution imaging

NASA Astrophysics Data System (ADS)

Laine, Romain F.; Albecka, Anna; van de Linde, Sebastian; Rees, Eric J.; Crump, Colin M.; Kaminski, Clemens F.

2015-01-01

Herpes simplex virus type-1 (HSV-1) is one of the most widespread pathogens among humans. Although the structure of HSV-1 has been extensively investigated, the precise organization of tegument and envelope proteins remains elusive. Here we use super-resolution imaging by direct stochastic optical reconstruction microscopy (dSTORM) in combination with a model-based analysis of single-molecule localization data, to determine the position of protein layers within virus particles. We resolve different protein layers within individual HSV-1 particles using multi-colour dSTORM imaging and discriminate envelope-anchored glycoproteins from tegument proteins, both in purified virions and in virions present in infected cells. Precise characterization of HSV-1 structure was achieved by particle averaging of purified viruses and model-based analysis of the radial distribution of the tegument proteins VP16, VP1/2 and pUL37, and envelope protein gD. From this data, we propose a model of the protein organization inside the tegument.

Cape Verde

NASA Technical Reports Server (NTRS)

2007-01-01

This Mars Exploration Rover Opportunity Pancam 'super resolution' mosaic of the approximately 6 m (20 foot) high cliff face of the Cape Verde promontory was taken by the rover from inside Victoria Crater, during the rover's descent into Duck Bay. Super-resolution is an imaging technique which utilizes information from multiple pictures of the same target in order to generate an image with a higher resolution than any of the individual images. Cape Verde is a geologically rich outcrop and is teaching scientists about how rocks at Victoria crater were modified since they were deposited long ago. This image complements super resolution mosaics obtained at Cape St. Mary and Cape St. Vincent and is consistent with the hypothesis that Victoria crater is located in the middle of what used to be an ancient sand dune field. Many rover team scientists are hoping to be able to eventually drive the rover closer to these layered rocks in the hopes of measuring their chemistry and mineralogy.

This is a Mars Exploration Rover Opportunity Panoramic Camera image mosaic acquired on sols 1342 and 1356 (November 2 and 17, 2007), and was constructed from a mathematical combination of 64 different blue filter (480 nm) images.

Super-resolution for imagery from integrated microgrid polarimeters.

PubMed

Hardie, Russell C; LeMaster, Daniel A; Ratliff, Bradley M

2011-07-04

Imagery from microgrid polarimeters is obtained by using a mosaic of pixel-wise micropolarizers on a focal plane array (FPA). Each distinct polarization image is obtained by subsampling the full FPA image. Thus, the effective pixel pitch for each polarization channel is increased and the sampling frequency is decreased. As a result, aliasing artifacts from such undersampling can corrupt the true polarization content of the scene. Here we present the first multi-channel multi-frame super-resolution (SR) algorithms designed specifically for the problem of image restoration in microgrid polarization imagers. These SR algorithms can be used to address aliasing and other degradations, without sacrificing field of view or compromising optical resolution with an anti-aliasing filter. The new SR methods are designed to exploit correlation between the polarimetric channels. One of the new SR algorithms uses a form of regularized least squares and has an iterative solution. The other is based on the faster adaptive Wiener filter SR method. We demonstrate that the new multi-channel SR algorithms are capable of providing significant enhancement of polarimetric imagery and that they outperform their independent channel counterparts.

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media

NASA Astrophysics Data System (ADS)

Edrei, Eitan; Scarcelli, Giuliano

2016-09-01

High-resolution imaging through turbid media is a fundamental challenge of optical sciences that has attracted a lot of attention in recent years for its wide range of potential applications. Here, we demonstrate that the resolution of imaging systems looking behind a highly scattering medium can be improved below the diffraction-limit. To achieve this, we demonstrate a novel microscopy technique enabled by the optical memory effect that uses a deconvolution image processing and thus it does not require iterative focusing, scanning or phase retrieval procedures. We show that this newly established ability of direct imaging through turbid media provides fundamental and practical advantages such as three-dimensional refocusing and unambiguous object reconstruction.

Memory-effect based deconvolution microscopy for super-resolution imaging through scattering media.

PubMed

Edrei, Eitan; Scarcelli, Giuliano

2016-09-16

High-resolution imaging through turbid media is a fundamental challenge of optical sciences that has attracted a lot of attention in recent years for its wide range of potential applications. Here, we demonstrate that the resolution of imaging systems looking behind a highly scattering medium can be improved below the diffraction-limit. To achieve this, we demonstrate a novel microscopy technique enabled by the optical memory effect that uses a deconvolution image processing and thus it does not require iterative focusing, scanning or phase retrieval procedures. We show that this newly established ability of direct imaging through turbid media provides fundamental and practical advantages such as three-dimensional refocusing and unambiguous object reconstruction.

Recent advances in the field of super resolved imaging and sensing

NASA Astrophysics Data System (ADS)

Zalevsky, Zeev; Borkowski, Amikam; Marom, Emanuel; Javidi, Bahram; Beiderman, Yevgeny; Micó, Vicente; García, Javier

2011-05-01

In this paper we start by presenting one recent development in the field of geometric super resolution. The new approach overcomes the reduction of resolution caused by the non ideal sampling of the image done by the spatial averaging of each pixel of the sampling array. Right after, we demonstrate a remote super sensing technique allowing monitoring, from a distance, the heart beats, blood pulse pressure and the glucose level in the blood stream of a patient by tracking the trajectory of secondary speckle patterns reflected from the skin of the wrist or from the sclera.

Enhancing Deep-Water Low-Resolution Gridded Bathymetry Using Single Image Super-Resolution

NASA Astrophysics Data System (ADS)

Elmore, P. A.; Nock, K.; Bonanno, D.; Smith, L.; Ferrini, V. L.; Petry, F. E.

2017-12-01

We present research to employ single-image super-resolution (SISR) algorithms to enhance knowledge of the seafloor using the 1-minute GEBCO 2014 grid when 100m grids from high-resolution sonar systems are available for training. Our numerical upscaling experiments of x15 upscaling of the GEBCO grid along three areas of the Eastern Pacific Ocean along mid-ocean ridge systems where we have these 100m gridded bathymetry data sets, which we accept as ground-truth. We show that four SISR algorithms can enhance this low-resolution knowledge of bathymetry versus bicubic or Spline-In-Tension algorithms through upscaling under these conditions: 1) rough topography is present in both training and testing areas and 2) the range of depths and features in the training area contains the range of depths in the enhancement area. We quantitatively judged successful SISR enhancement versus bicubic interpolation when Student's hypothesis testing show significant improvement of the root-mean squared error (RMSE) between upscaled bathymetry and 100m gridded ground-truth bathymetry at p < 0.05. In addition, we found evidence that random forest based SISR methods may provide more robust enhancements versus non-forest based SISR algorithms.

SIL-STED microscopy technique enhancing super-resolution of fluorescence microscopy

NASA Astrophysics Data System (ADS)

Park, No-Cheol; Lim, Geon; Lee, Won-sup; Moon, Hyungbae; Choi, Guk-Jong; Park, Young-Pil

2017-08-01

We have characterized a new type STED microscope which combines a high numerical aperture (NA) optical head with a solid immersion lens (SIL), and we call it as SIL-STED microscope. The advantage of a SIL-STED microscope is that its high NA of the SIL makes it superior to a general STED microscope in lateral resolution, thus overcoming the optical diffraction limit at the macromolecular level and enabling advanced super-resolution imaging of cell surface or cell membrane structure and function Do. This study presents the first implementation of higher NA illumination in a STED microscope limiting the fluorescence lateral resolution to about 40 nm. The refractive index of the SIL which is made of material KTaO3 is about 2.23 and 2.20 at a wavelength of 633 nm and 780 nm which are used for excitation and depletion in STED imaging, respectively. Based on the vector diffraction theory, the electric field focused by the SILSTED microscope is numerically calculated so that the numerical results of the point dispersion function of the microscope and the expected resolution could be analyzed. For further investigation, fluorescence imaging of nano size fluorescent beads is fulfilled to show improved performance of the technique.

Re-scan confocal microscopy: scanning twice for better resolution.

PubMed

De Luca, Giulia M R; Breedijk, Ronald M P; Brandt, Rick A J; Zeelenberg, Christiaan H C; de Jong, Babette E; Timmermans, Wendy; Azar, Leila Nahidi; Hoebe, Ron A; Stallinga, Sjoerd; Manders, Erik M M

2013-01-01

We present a new super-resolution technique, Re-scan Confocal Microscopy (RCM), based on standard confocal microscopy extended with an optical (re-scanning) unit that projects the image directly on a CCD-camera. This new microscope has improved lateral resolution and strongly improved sensitivity while maintaining the sectioning capability of a standard confocal microscope. This simple technology is typically useful for biological applications where the combination high-resolution and high-sensitivity is required.

Super-resolution fusion of complementary panoramic images based on cross-selection kernel regression interpolation.

PubMed

Chen, Lidong; Basu, Anup; Zhang, Maojun; Wang, Wei; Liu, Yu

2014-03-20

A complementary catadioptric imaging technique was proposed to solve the problem of low and nonuniform resolution in omnidirectional imaging. To enhance this research, our paper focuses on how to generate a high-resolution panoramic image from the captured omnidirectional image. To avoid the interference between the inner and outer images while fusing the two complementary views, a cross-selection kernel regression method is proposed. First, in view of the complementarity of sampling resolution in the tangential and radial directions between the inner and the outer images, respectively, the horizontal gradients in the expected panoramic image are estimated based on the scattered neighboring pixels mapped from the outer, while the vertical gradients are estimated using the inner image. Then, the size and shape of the regression kernel are adaptively steered based on the local gradients. Furthermore, the neighboring pixels in the next interpolation step of kernel regression are also selected based on the comparison between the horizontal and vertical gradients. In simulation and real-image experiments, the proposed method outperforms existing kernel regression methods and our previous wavelet-based fusion method in terms of both visual quality and objective evaluation.

Robust isotropic super-resolution by maximizing a Laplace posterior for MRI volumes

NASA Astrophysics Data System (ADS)

Han, Xian-Hua; Iwamoto, Yutaro; Shiino, Akihiko; Chen, Yen-Wei

2014-03-01

Magnetic resonance imaging can only acquire volume data with finite resolution due to various factors. In particular, the resolution in one direction (such as the slice direction) is much lower than others (such as the in-plane direction), yielding un-realistic visualizations. This study explores to reconstruct MRI isotropic resolution volumes from three orthogonal scans. This proposed super- resolution reconstruction is formulated as a maximum a posterior (MAP) problem, which relies on the generation model of the acquired scans from the unknown high-resolution volumes. Generally, the deviation ensemble of the reconstructed high-resolution (HR) volume from the available LR ones in the MAP is represented as a Gaussian distribution, which usually results in some noise and artifacts in the reconstructed HR volume. Therefore, this paper investigates a robust super-resolution by formulating the deviation set as a Laplace distribution, which assumes sparsity in the deviation ensemble based on the possible insight of the appeared large values only around some unexpected regions. In addition, in order to achieve reliable HR MRI volume, we integrates the priors such as bilateral total variation (BTV) and non-local mean (NLM) into the proposed MAP framework for suppressing artifacts and enriching visual detail. We validate the proposed robust SR strategy using MRI mouse data with high-definition resolution in two direction and low-resolution in one direction, which are imaged in three orthogonal scans: axial, coronal and sagittal planes. Experiments verifies that the proposed strategy can achieve much better HR MRI volumes than the conventional MAP method even with very high-magnification factor: 10.

Far-field optical imaging with subdiffraction resolution enabled by nonlinear saturation absorption

NASA Astrophysics Data System (ADS)

Ding, Chenliang; Wei, Jingsong

2016-01-01

The resolution of far-field optical imaging is required to improve beyond the Abbe limit to the subdiffraction or even the nanoscale. In this work, inspired by scanning electronic microscopy (SEM) imaging, in which carbon (or Au) thin films are usually required to be coated on the sample surface before imaging to remove the charging effect while imaging by electrons. We propose a saturation-absorption-induced far-field super-resolution optical imaging method (SAI-SRIM). In the SAI-SRIM, the carbon (or Au) layers in SEM imaging are replaced by nonlinear-saturation-absorption (NSA) thin films, which are directly coated onto the sample surfaces using advanced thin film deposition techniques. The surface fluctuant morphologies are replicated to the NSA thin films, accordingly. The coated sample surfaces are then imaged using conventional laser scanning microscopy. Consequently, the imaging resolution is greatly improved, and subdiffraction-resolved optical images are obtained theoretically and experimentally. The SAI-SRIM provides an effective and easy way to achieve far-field super-resolution optical imaging for sample surfaces with geometric fluctuant morphology characteristics.

Filling the gap: adding super-resolution to array tomography for correlated ultrastructural and molecular identification of electrical synapses at the C. elegans connectome.

PubMed

Markert, Sebastian Matthias; Britz, Sebastian; Proppert, Sven; Lang, Marietta; Witvliet, Daniel; Mulcahy, Ben; Sauer, Markus; Zhen, Mei; Bessereau, Jean-Louis; Stigloher, Christian

2016-10-01

Correlating molecular labeling at the ultrastructural level with high confidence remains challenging. Array tomography (AT) allows for a combination of fluorescence and electron microscopy (EM) to visualize subcellular protein localization on serial EM sections. Here, we describe an application for AT that combines near-native tissue preservation via high-pressure freezing and freeze substitution with super-resolution light microscopy and high-resolution scanning electron microscopy (SEM) analysis on the same section. We established protocols that combine SEM with structured illumination microscopy (SIM) and direct stochastic optical reconstruction microscopy (dSTORM). We devised a method for easy, precise, and unbiased correlation of EM images and super-resolution imaging data using endogenous cellular landmarks and freely available image processing software. We demonstrate that these methods allow us to identify and label gap junctions in Caenorhabditis elegans with precision and confidence, and imaging of even smaller structures is feasible. With the emergence of connectomics, these methods will allow us to fill in the gap-acquiring the correlated ultrastructural and molecular identity of electrical synapses.

"Supertrap" at Work: Extremely Efficient Nonradiative Recombination Channels in MAPbI3 Perovskites Revealed by Luminescence Super-Resolution Imaging and Spectroscopy.

PubMed

Merdasa, Aboma; Tian, Yuxi; Camacho, Rafael; Dobrovolsky, Alexander; Debroye, Elke; Unger, Eva L; Hofkens, Johan; Sundström, Villy; Scheblykin, Ivan G

2017-06-27

Organo-metal halide perovskites are some of the most promising materials for the new generation of low-cost photovoltaic and light-emitting devices. Their solution processability is a beneficial trait, although it leads to a spatial inhomogeneity of perovskite films with a variation of the trap state density at the nanoscale. Comprehending their properties using traditional spectroscopy therefore becomes difficult, calling for a combination with microscopy in order to see beyond the ensemble-averaged response. We studied photoluminescence (PL) blinking of micrometer-sized individual methylammonium lead iodide (MAPbI 3 ) perovskite polycrystals, as well as monocrystalline microrods up to 10 μm long. We correlated their PL dynamics with structure employing scanning electron and optical super-resolution microscopy. Combining super-resolution localization imaging and super-resolution optical fluctuation imaging (SOFI), we could detect and quantify preferential emitting regions in polycrystals exhibiting different types of blinking. We propose that blinking in MAPbI 3 occurs by the activation/passivation of a "supertrap" which presumably is a donor-acceptor pair able to trap both electrons and holes. As such, nonradiative recombination via supertraps, in spite being present at a rather low concentrations (10 12 -10 15 cm -3 ), is much more efficient than via all other defect states present in the material at higher concentrations (10 16 -10 18 cm -3 ). We speculate that activation/deactivation of a supertrap occurs by its temporary dissociation into free donor and acceptor impurities. We found that supertraps are most efficient in structurally homogeneous and large MAPbI 3 crystals where carrier diffusion is efficient, which may therefore pose limitations on the efficiency of perovskite-based devices.

Single objective light-sheet microscopy for high-speed whole-cell 3D super-resolution

DOE PAGES

Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.; ...

2016-01-01

Here, we have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single moleculemore » super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.« less

Dynamic placement of plasmonic hotspots for super-resolution surface-enhanced Raman scattering.

PubMed

Ertsgaard, Christopher T; McKoskey, Rachel M; Rich, Isabel S; Lindquist, Nathan C

2014-10-28

In this paper, we demonstrate dynamic placement of locally enhanced plasmonic fields using holographic laser illumination of a silver nanohole array. To visualize these focused "hotspots", the silver surface was coated with various biological samples for surface-enhanced Raman spectroscopy (SERS) imaging. Due to the large field enhancements, blinking behavior of the SERS hotspots was observed and processed using a stochastic optical reconstruction microscopy algorithm enabling super-resolution localization of the hotspots to within 10 nm. These hotspots were then shifted across the surface in subwavelength (<100 nm for a wavelength of 660 nm) steps using holographic illumination from a spatial light modulator. This created a dynamic imaging and sensing surface, whereas static illumination would only have produced stationary hotspots. Using this technique, we also show that such subwavelength shifting and localization of plasmonic hotspots has potential for imaging applications. Interestingly, illuminating the surface with randomly shifting SERS hotspots was sufficient to completely fill in a wide field of view for super-resolution chemical imaging.

Time reversal and phase coherent music techniques for super-resolution ultrasound imaging

DOE Office of Scientific and Technical Information (OSTI.GOV)

Huang, Lianjie; Labyed, Yassin

Systems and methods for super-resolution ultrasound imaging using a windowed and generalized TR-MUSIC algorithm that divides the imaging region into overlapping sub-regions and applies the TR-MUSIC algorithm to the windowed backscattered ultrasound signals corresponding to each sub-region. The algorithm is also structured to account for the ultrasound attenuation in the medium and the finite-size effects of ultrasound transducer elements. A modified TR-MUSIC imaging algorithm is used to account for ultrasound scattering from both density and compressibility contrasts. The phase response of ultrasound transducer elements is accounted for in a PC-MUSIC system.

Imaging cellular structures in super-resolution with SIM, STED and Localisation Microscopy: A practical comparison.

PubMed

Wegel, Eva; Göhler, Antonia; Lagerholm, B Christoffer; Wainman, Alan; Uphoff, Stephan; Kaufmann, Rainer; Dobbie, Ian M

2016-06-06

Many biological questions require fluorescence microscopy with a resolution beyond the diffraction limit of light. Super-resolution methods such as Structured Illumination Microscopy (SIM), STimulated Emission Depletion (STED) microscopy and Single Molecule Localisation Microscopy (SMLM) enable an increase in image resolution beyond the classical diffraction-limit. Here, we compare the individual strengths and weaknesses of each technique by imaging a variety of different subcellular structures in fixed cells. We chose examples ranging from well separated vesicles to densely packed three dimensional filaments. We used quantitative and correlative analyses to assess the performance of SIM, STED and SMLM with the aim of establishing a rough guideline regarding the suitability for typical applications and to highlight pitfalls associated with the different techniques.

Fluorescent Nano-Probes to Image Plant Cell Walls by Super-Resolution STED Microscopy

PubMed Central

Paës, Gabriel; Habrant, Anouck; Terryn, Christine

2018-01-01

Lignocellulosic biomass is a complex network of polymers making up the cell walls of plants. It represents a feedstock of sustainable resources to be converted into fuels, chemicals, and materials. Because of its complex architecture, lignocellulose is a recalcitrant material that requires some pretreatments and several types of catalysts to be transformed efficiently. Gaining more knowledge in the architecture of plant cell walls is therefore important to understand and optimize transformation processes. For the first time, super-resolution imaging of poplar wood samples has been performed using the Stimulated Emission Depletion (STED) technique. In comparison to standard confocal images, STED reveals new details in cell wall structure, allowing the identification of secondary walls and middle lamella with fine details, while keeping open the possibility to perform topochemistry by the use of relevant fluorescent nano-probes. In particular, the deconvolution of STED images increases the signal-to-noise ratio so that images become very well defined. The obtained results show that the STED super-resolution technique can be easily implemented by using cheap commercial fluorescent rhodamine-PEG nano-probes which outline the architecture of plant cell walls due to their interaction with lignin. Moreover, the sample preparation only requires easily-prepared plant sections of a few tens of micrometers, in addition to an easily-implemented post-treatment of images. Overall, the STED super-resolution technique in combination with a variety of nano-probes can provide a new vision of plant cell wall imaging by filling in the gap between classical photon microscopy and electron microscopy. PMID:29415498

Fluorescent Nano-Probes to Image Plant Cell Walls by Super-Resolution STED Microscopy.

PubMed

Paës, Gabriel; Habrant, Anouck; Terryn, Christine

2018-02-06

Lignocellulosic biomass is a complex network of polymers making up the cell walls of plants. It represents a feedstock of sustainable resources to be converted into fuels, chemicals, and materials. Because of its complex architecture, lignocellulose is a recalcitrant material that requires some pretreatments and several types of catalysts to be transformed efficiently. Gaining more knowledge in the architecture of plant cell walls is therefore important to understand and optimize transformation processes. For the first time, super-resolution imaging of poplar wood samples has been performed using the Stimulated Emission Depletion (STED) technique. In comparison to standard confocal images, STED reveals new details in cell wall structure, allowing the identification of secondary walls and middle lamella with fine details, while keeping open the possibility to perform topochemistry by the use of relevant fluorescent nano-probes. In particular, the deconvolution of STED images increases the signal-to-noise ratio so that images become very well defined. The obtained results show that the STED super-resolution technique can be easily implemented by using cheap commercial fluorescent rhodamine-PEG nano-probes which outline the architecture of plant cell walls due to their interaction with lignin. Moreover, the sample preparation only requires easily-prepared plant sections of a few tens of micrometers, in addition to an easily-implemented post-treatment of images. Overall, the STED super-resolution technique in combination with a variety of nano-probes can provide a new vision of plant cell wall imaging by filling in the gap between classical photon microscopy and electron microscopy.

Stochastic Optical Reconstruction Microscopy (STORM).

PubMed

Xu, Jianquan; Ma, Hongqiang; Liu, Yang

2017-07-05

Super-resolution (SR) fluorescence microscopy, a class of optical microscopy techniques at a spatial resolution below the diffraction limit, has revolutionized the way we study biology, as recognized by the Nobel Prize in Chemistry in 2014. Stochastic optical reconstruction microscopy (STORM), a widely used SR technique, is based on the principle of single molecule localization. STORM routinely achieves a spatial resolution of 20 to 30 nm, a ten-fold improvement compared to conventional optical microscopy. Among all SR techniques, STORM offers a high spatial resolution with simple optical instrumentation and standard organic fluorescent dyes, but it is also prone to image artifacts and degraded image resolution due to improper sample preparation or imaging conditions. It requires careful optimization of all three aspects-sample preparation, image acquisition, and image reconstruction-to ensure a high-quality STORM image, which will be extensively discussed in this unit. © 2017 by John Wiley & Sons, Inc. Copyright © 2017 John Wiley & Sons, Inc.

Wide field of view 3D label-free super-resolution imaging

NASA Astrophysics Data System (ADS)

Nolvi, Anton; Laidmäe, Ivo; Maconi, Göran; Heinämäki, Jyrki; Hæggström, Edward; Kassamakov, Ivan

2018-02-01

Recently, 3D label-free super-resolution profilers based on microsphere-assisted scanning white light interferometry were introduced having vertical resolution of few angstroms (Å) and a lateral resolution approaching 100 nm. However, the use of a single microsphere to generate the photonic nanojet (PNJ) limits their field of view. We overcome this limitation by using polymer microfibers to generate the PNJ. This increases the field of view by order of magnitude in comparison to the previously developed solutions while still resolving sub 100 nm features laterally and keeping the vertical resolution in 1nm range. To validate the capabilities of our system we used a recordable Blu-ray disc as a sample. It features a grooved surface topology with heights in the range of 20 nm and with distinguishable sub 100 nm lateral features that are unresolvable by diffraction limited optics. We achieved agreement between all three measurement devices across lateral and vertical dimensions. The field of view of our instrument was 110 μm by 2 μm and the imaging time was a couple of seconds.

Three-dimensional super-resolved live cell imaging through polarized multi-angle TIRF.

PubMed

Zheng, Cheng; Zhao, Guangyuan; Liu, Wenjie; Chen, Youhua; Zhang, Zhimin; Jin, Luhong; Xu, Yingke; Kuang, Cuifang; Liu, Xu

2018-04-01

Measuring three-dimensional nanoscale cellular structures is challenging, especially when the structure is dynamic. Owing to the informative total internal reflection fluorescence (TIRF) imaging under varied illumination angles, multi-angle (MA) TIRF has been examined to offer a nanoscale axial and a subsecond temporal resolution. However, conventional MA-TIRF still performs badly in lateral resolution and fails to characterize the depth image in densely distributed regions. Here, we emphasize the lateral super-resolution in the MA-TIRF, exampled by simply introducing polarization modulation into the illumination procedure. Equipped with a sparsity and accelerated proximal algorithm, we examine a more precise 3D sample structure compared with previous methods, enabling live cell imaging with a temporal resolution of 2 s and recovering high-resolution mitochondria fission and fusion processes. We also shared the recovery program, which is the first open-source recovery code for MA-TIRF, to the best of our knowledge.

Structured illumination microscopy for dual-modality 3D sub-diffraction resolution fluorescence and refractive-index reconstruction

PubMed Central

Chowdhury, Shwetadwip; Eldridge, Will J.; Wax, Adam; Izatt, Joseph A.

2017-01-01

Though structured illumination (SI) microscopy is a popular imaging technique conventionally associated with fluorescent super-resolution, recent works have suggested its applicability towards sub-diffraction resolution coherent imaging with quantitative endogenous biological contrast. Here, we demonstrate that SI can efficiently integrate together the principles of fluorescent super-resolution and coherent synthetic aperture to achieve 3D dual-modality sub-diffraction resolution, fluorescence and refractive-index (RI) visualizations of biological samples. We experimentally demonstrate this framework by introducing a SI microscope capable of 3D sub-diffraction resolution fluorescence and RI imaging, and verify its biological visualization capabilities by experimentally reconstructing 3D RI/fluorescence visualizations of fluorescent calibration microspheres as well as alveolar basal epithelial adenocarcinoma (A549) and human colorectal adenocarcinmoa (HT-29) cells, fluorescently stained for F-actin. This demonstration may suggest SI as an especially promising imaging technique to enable future biological studies that explore synergistically operating biophysical/biochemical and molecular mechanisms at sub-diffraction resolutions. PMID:29296504

Re-scan confocal microscopy: scanning twice for better resolution

PubMed Central

De Luca, Giulia M.R.; Breedijk, Ronald M.P.; Brandt, Rick A.J.; Zeelenberg, Christiaan H.C.; de Jong, Babette E.; Timmermans, Wendy; Azar, Leila Nahidi; Hoebe, Ron A.; Stallinga, Sjoerd; Manders, Erik M.M.

2013-01-01

We present a new super-resolution technique, Re-scan Confocal Microscopy (RCM), based on standard confocal microscopy extended with an optical (re-scanning) unit that projects the image directly on a CCD-camera. This new microscope has improved lateral resolution and strongly improved sensitivity while maintaining the sectioning capability of a standard confocal microscope. This simple technology is typically useful for biological applications where the combination high-resolution and high-sensitivity is required. PMID:24298422

Interactive local super-resolution reconstruction of whole-body MRI mouse data: a pilot study with applications to bone and kidney metastases.

PubMed

Dzyubachyk, Oleh; Khmelinskii, Artem; Plenge, Esben; Kok, Peter; Snoeks, Thomas J A; Poot, Dirk H J; Löwik, Clemens W G M; Botha, Charl P; Niessen, Wiro J; van der Weerd, Louise; Meijering, Erik; Lelieveldt, Boudewijn P F

2014-01-01

In small animal imaging studies, when the locations of the micro-structures of interest are unknown a priori, there is a simultaneous need for full-body coverage and high resolution. In MRI, additional requirements to image contrast and acquisition time will often make it impossible to acquire such images directly. Recently, a resolution enhancing post-processing technique called super-resolution reconstruction (SRR) has been demonstrated to improve visualization and localization of micro-structures in small animal MRI by combining multiple low-resolution acquisitions. However, when the field-of-view is large relative to the desired voxel size, solving the SRR problem becomes very expensive, in terms of both memory requirements and computation time. In this paper we introduce a novel local approach to SRR that aims to overcome the computational problems and allow researchers to efficiently explore both global and local characteristics in whole-body small animal MRI. The method integrates state-of-the-art image processing techniques from the areas of articulated atlas-based segmentation, planar reformation, and SRR. A proof-of-concept is provided with two case studies involving CT, BLI, and MRI data of bone and kidney tumors in a mouse model. We show that local SRR-MRI is a computationally efficient complementary imaging modality for the precise characterization of tumor metastases, and that the method provides a feasible high-resolution alternative to conventional MRI.

Multiplexed and scalable super-resolution imaging of three-dimensional protein localization in size-adjustable tissues.

PubMed

Ku, Taeyun; Swaney, Justin; Park, Jeong-Yoon; Albanese, Alexandre; Murray, Evan; Cho, Jae Hun; Park, Young-Gyun; Mangena, Vamsi; Chen, Jiapei; Chung, Kwanghun

2016-09-01

The biology of multicellular organisms is coordinated across multiple size scales, from the subnanoscale of molecules to the macroscale, tissue-wide interconnectivity of cell populations. Here we introduce a method for super-resolution imaging of the multiscale organization of intact tissues. The method, called magnified analysis of the proteome (MAP), linearly expands entire organs fourfold while preserving their overall architecture and three-dimensional proteome organization. MAP is based on the observation that preventing crosslinking within and between endogenous proteins during hydrogel-tissue hybridization allows for natural expansion upon protein denaturation and dissociation. The expanded tissue preserves its protein content, its fine subcellular details, and its organ-scale intercellular connectivity. We use off-the-shelf antibodies for multiple rounds of immunolabeling and imaging of a tissue's magnified proteome, and our experiments demonstrate a success rate of 82% (100/122 antibodies tested). We show that specimen size can be reversibly modulated to image both inter-regional connections and fine synaptic architectures in the mouse brain.

Hyperspectral imagery super-resolution by compressive sensing inspired dictionary learning and spatial-spectral regularization.

PubMed

Huang, Wei; Xiao, Liang; Liu, Hongyi; Wei, Zhihui

2015-01-19

Due to the instrumental and imaging optics limitations, it is difficult to acquire high spatial resolution hyperspectral imagery (HSI). Super-resolution (SR) imagery aims at inferring high quality images of a given scene from degraded versions of the same scene. This paper proposes a novel hyperspectral imagery super-resolution (HSI-SR) method via dictionary learning and spatial-spectral regularization. The main contributions of this paper are twofold. First, inspired by the compressive sensing (CS) framework, for learning the high resolution dictionary, we encourage stronger sparsity on image patches and promote smaller coherence between the learned dictionary and sensing matrix. Thus, a sparsity and incoherence restricted dictionary learning method is proposed to achieve higher efficiency sparse representation. Second, a variational regularization model combing a spatial sparsity regularization term and a new local spectral similarity preserving term is proposed to integrate the spectral and spatial-contextual information of the HSI. Experimental results show that the proposed method can effectively recover spatial information and better preserve spectral information. The high spatial resolution HSI reconstructed by the proposed method outperforms reconstructed results by other well-known methods in terms of both objective measurements and visual evaluation.

The internal architecture of dendritic spines revealed by super-resolution imaging: What did we learn so far?

DOE Office of Scientific and Technical Information (OSTI.GOV)

MacGillavry, Harold D., E-mail: h.d.macgillavry@uu.nl; Hoogenraad, Casper C., E-mail: c.hoogenraad@uu.nl

2015-07-15

The molecular architecture of dendritic spines defines the efficiency of signal transmission across excitatory synapses. It is therefore critical to understand the mechanisms that control the dynamic localization of the molecular constituents within spines. However, because of the small scale at which most processes within spines take place, conventional light microscopy techniques are not adequate to provide the necessary level of resolution. Recently, super-resolution imaging techniques have overcome the classical barrier imposed by the diffraction of light, and can now resolve the localization and dynamic behavior of proteins within small compartments with nanometer precision, revolutionizing the study of dendritic spinemore » architecture. Here, we highlight exciting new findings from recent super-resolution studies on neuronal spines, and discuss how these studies revealed important new insights into how protein complexes are assembled and how their dynamic behavior shapes the efficiency of synaptic transmission.« less

Lensfree super-resolution holographic microscopy using wetting films on a chip

NASA Astrophysics Data System (ADS)

Mudanyali, Onur; Bishara, Waheb; Ozcan, Aydogan

2011-08-01

We investigate the use of wetting films to significantly improve the imaging performance of lensfree pixel super-resolution on-chip microscopy, achieving < 1 μm spatial resolution over a large imaging area of ~24 mm2. Formation of an ultra-thin wetting film over the specimen effectively creates a micro-lens effect over each object, which significantly improves the signal-to-noise-ratio and therefore the resolution of our lensfree images. We validate the performance of this approach through lensfree on-chip imaging of various objects having fine morphological features (with dimensions of e.g., ≤0.5 μm) such as Escherichia coli (E. coli), human sperm, Giardia lamblia trophozoites, polystyrene micro beads as well as red blood cells. These results are especially important for the development of highly sensitive field-portable microscopic analysis tools for resource limited settings.

Passive Standoff Super Resolution Imaging using Spatial-Spectral Multiplexing

DTIC Science & Technology

2017-08-14

94 5.0 Four -Dimensional Object-Space Data Reconstruction Using Spatial...103 5.3 Four -dimensional scene reconstruction using SSM...transitioning to systems based on spectrally resolved longitudinal spatial coherence interferometry. This document also includes research related to four

Resolution enhancement of low-quality videos using a high-resolution frame

NASA Astrophysics Data System (ADS)

Pham, Tuan Q.; van Vliet, Lucas J.; Schutte, Klamer

2006-01-01

This paper proposes an example-based Super-Resolution (SR) algorithm of compressed videos in the Discrete Cosine Transform (DCT) domain. Input to the system is a Low-Resolution (LR) compressed video together with a High-Resolution (HR) still image of similar content. Using a training set of corresponding LR-HR pairs of image patches from the HR still image, high-frequency details are transferred from the HR source to the LR video. The DCT-domain algorithm is much faster than example-based SR in spatial domain 6 because of a reduction in search dimensionality, which is a direct result of the compact and uncorrelated DCT representation. Fast searching techniques like tree-structure vector quantization 16 and coherence search1 are also key to the improved efficiency. Preliminary results on MJPEG sequence show promising result of the DCT-domain SR synthesis approach.

Barnacle Bill in Super Resolution from Super Panorama

NASA Image and Video Library

1998-07-03

"Barnacle Bill" is a small rock immediately west-northwest of the Mars Pathfinder lander and was the first rock visited by the Sojourner Rover's alpha proton X-ray spectrometer (APXS) instrument. This image shows super resolution techniques applied to the first APXS target rock, which was never imaged with the rover's forward cameras. Super resolution was applied to help to address questions about the texture of this rock and what it might tell us about its mode of origin. This view of Barnacle Bill was produced by combining the "Super Panorama" frames from the IMP camera. Super resolution was applied to help to address questions about the texture of these rocks and what it might tell us about their mode of origin. The composite color frames that make up this anaglyph were produced for both the right and left eye of the IMP. The composites consist of 7 frames in the right eye and 8 frames in the left eye, taken with different color filters that were enlarged by 500% and then co-added using Adobe Photoshop to produce, in effect, a super-resolution panchromatic frame that is sharper than an individual frame would be. These panchromatic frames were then colorized with the red, green, and blue filtered images from the same sequence. The color balance was adjusted to approximate the true color of Mars. The anaglyph view was produced by combining the left with the right eye color composite frames by assigning the left eye composite view to the red color plane and the right eye composite view to the green and blue color planes (cyan), to produce a stereo anaglyph mosaic. This mosaic can be viewed in 3-D on your computer monitor or in color print form by wearing red-blue 3-D glasses. http://photojournal.jpl.nasa.gov/catalog/PIA01409

Super resolution PLIF demonstrated in turbulent jet flows seeded with I2

NASA Astrophysics Data System (ADS)

Xu, Wenjiang; Liu, Ning; Ma, Lin

2018-05-01

Planar laser induced fluorescence (PLIF) represents an indispensable tool for flow and flame imaging. However, the PLIF technique suffers from limited spatial resolution or blurring in many situations, which restricts its applicability and capability. This work describes a new method, named SR-PLIF (super-resolution PLIF), to overcome these limitations and enhance the capability of PLIF. The method uses PLIF images captured simultaneously from two (or more) orientations to reconstruct a final PLIF image with resolution enhanced or blurring removed. This paper reports the development of the reconstruction algorithm, and the experimental demonstration of the SR-PLIF method both with controlled samples and with turbulent flows seeded with iodine vapor. Using controlled samples with two cameras, the spatial resolution in the best case was improved from 0.06 mm in the projections to 0.03 mm in the SR image, in terms of the spreading width of a sharp edge. With turbulent flows, an image sharpness measure was developed to quantify the spatial resolution, and SR reconstruction with two cameras can effectively improve the spatial resolution compared to the projections in terms of the sharpness measure.

Resolution enhancement in a double-helix phase engineered scanning microscope (RESCH microscope) (Presentation Recording)

NASA Astrophysics Data System (ADS)

Jesacher, Alexander; Ritsch-Marte, Monika; Piestun, Rafael

2015-08-01

Recently we introduced RESCH microscopy [1] - a scanning microscope that allows slightly refocusing the sample after the acquisition has been performed, solely by performing appropriate data post-processing. The microscope features a double-helix phase-engineered emission point spread function in combination with camera-based detection. Based on the principle of transverse resolution enhancement in Image Scanning Microscopy [2,3], we demonstrate similar resolution improvement in RESCH. Furthermore, we outline a pathway for how the collected 3D sample information can be used to construct sharper optical sections. [1] A. Jesacher, M. Ritsch-Marte and R. Piestun, accepted for Optica. [2] C.J.R. Sheppard, "Super-resolution in Confocal imaging," Optik, 80, 53-54 (1988). [3] C.B. Müller and J. Enderlein "Image Scanning Microscopy," Phys. Rev. Lett. 104, 198101 (2010).

Breaking the diffraction barrier using coherent anti-Stokes Raman scattering difference microscopy.

PubMed

Wang, Dong; Liu, Shuanglong; Chen, Yue; Song, Jun; Liu, Wei; Xiong, Maozhen; Wang, Guangsheng; Peng, Xiao; Qu, Junle

2017-05-01

We propose a method to improve the resolution of coherent anti-Stokes Raman scattering microscopy (CARS), and present a theoretical model. The proposed method, coherent anti-Stokes Raman scattering difference microscopy (CARS-D), is based on the intensity difference between two differently acquired images. One being the conventional CARS image, and the other obtained when the sample is illuminated by a doughnut shaped spot. The final super-resolution CARS-D image is constructed by intensity subtraction of these two images. However, there is a subtractive factor between them, and the theoretical model sets this factor to obtain the best imaging effect.

Sparsity-Based Super Resolution for SEM Images.

PubMed

Tsiper, Shahar; Dicker, Or; Kaizerman, Idan; Zohar, Zeev; Segev, Mordechai; Eldar, Yonina C

2017-09-13

The scanning electron microscope (SEM) is an electron microscope that produces an image of a sample by scanning it with a focused beam of electrons. The electrons interact with the atoms in the sample, which emit secondary electrons that contain information about the surface topography and composition. The sample is scanned by the electron beam point by point, until an image of the surface is formed. Since its invention in 1942, the capabilities of SEMs have become paramount in the discovery and understanding of the nanometer world, and today it is extensively used for both research and in industry. In principle, SEMs can achieve resolution better than one nanometer. However, for many applications, working at subnanometer resolution implies an exceedingly large number of scanning points. For exactly this reason, the SEM diagnostics of microelectronic chips is performed either at high resolution (HR) over a small area or at low resolution (LR) while capturing a larger portion of the chip. Here, we employ sparse coding and dictionary learning to algorithmically enhance low-resolution SEM images of microelectronic chips-up to the level of the HR images acquired by slow SEM scans, while considerably reducing the noise. Our methodology consists of two steps: an offline stage of learning a joint dictionary from a sequence of LR and HR images of the same region in the chip, followed by a fast-online super-resolution step where the resolution of a new LR image is enhanced. We provide several examples with typical chips used in the microelectronics industry, as well as a statistical study on arbitrary images with characteristic structural features. Conceptually, our method works well when the images have similar characteristics, as microelectronics chips do. This work demonstrates that employing sparsity concepts can greatly improve the performance of SEM, thereby considerably increasing the scanning throughput without compromising on analysis quality and resolution.

LFNet: A Novel Bidirectional Recurrent Convolutional Neural Network for Light-Field Image Super-Resolution.

PubMed

Wang, Yunlong; Liu, Fei; Zhang, Kunbo; Hou, Guangqi; Sun, Zhenan; Tan, Tieniu

2018-09-01

The low spatial resolution of light-field image poses significant difficulties in exploiting its advantage. To mitigate the dependency of accurate depth or disparity information as priors for light-field image super-resolution, we propose an implicitly multi-scale fusion scheme to accumulate contextual information from multiple scales for super-resolution reconstruction. The implicitly multi-scale fusion scheme is then incorporated into bidirectional recurrent convolutional neural network, which aims to iteratively model spatial relations between horizontally or vertically adjacent sub-aperture images of light-field data. Within the network, the recurrent convolutions are modified to be more effective and flexible in modeling the spatial correlations between neighboring views. A horizontal sub-network and a vertical sub-network of the same network structure are ensembled for final outputs via stacked generalization. Experimental results on synthetic and real-world data sets demonstrate that the proposed method outperforms other state-of-the-art methods by a large margin in peak signal-to-noise ratio and gray-scale structural similarity indexes, which also achieves superior quality for human visual systems. Furthermore, the proposed method can enhance the performance of light field applications such as depth estimation.

Two-color CW STED nanoscopy

NASA Astrophysics Data System (ADS)

Chen, Xuanze; Liu, Yujia; Yang, Xusan; Wang, Tingting; Alonas, Eric; Santangelo, Philip J.; Ren, Qiushi; Xi, Peng

2013-02-01

Fluorescent microscopy has become an essential tool to study biological molecules, pathways and events in living cells, tissues and animals. Meanwhile even the most advanced confocal microscopy can only yield optical resolution approaching Abbe diffraction limit of 200 nm. This is still larger than many subcellular structures, which are too small to be resolved in detail. These limitations have driven the development of super-resolution optical imaging methodologies over the past decade. In stimulated emission depletion (STED) microscopy, the excitation focus is overlapped by an intense doughnut-shaped spot to instantly de-excite markers from their fluorescent state to the ground state by stimulated emission. This effectively eliminates the periphery of the Point Spread Function (PSF), resulting in a narrower focal region, or super-resolution. Scanning a sharpened spot through the specimen renders images with sub-diffraction resolution. Multi-color STED imaging can present important structural and functional information for protein-protein interaction. In this work, we presented a two-color, synchronization-free STED microscopy with a Ti:Sapphire oscillator. The excitation wavelengths were 532nm and 635nm, respectively. With pump power of 4.6 W and sample irradiance of 310 mW, we achieved super-resolution as high as 71 nm. Human respiratory syncytial virus (hRSV) proteins were imaged with our two-color CW STED for co-localization analysis.

Tracking and Predicting Fine Scale Sea Ice Motion by Constructing Super-Resolution Images and Fusing Multiple Satellite Sensors

DTIC Science & Technology

2013-09-30

COVERED 00-00-2013 to 00-00-2013 4. TITLE AND SUBTITLE Tracking and Predicting Fine Scale Sea Ice Motion by Constructing Super-Resolution Images...limited, but potentially provide more detailed data. Initial assessments have been made on MODIS data in terms of its suitability. While clouds obscure...estimates. 2 Data from Aqua, Terra, and Suomi NPP satellites were investigated. Aqua and Terra are older satellites that fly the MODIS instrument

Parallel detecting super-resolution microscopy using correlation based image restoration

NASA Astrophysics Data System (ADS)

Yu, Zhongzhi; Liu, Shaocong; Zhu, Dazhao; Kuang, Cuifang; Liu, Xu

2017-12-01

A novel approach to achieve the image restoration is proposed in which each detector's relative position in the detector array is no longer a necessity. We can identify each detector's relative location by extracting a certain area from one of the detector's image and scanning it on other detectors' images. According to this location, we can generate the point spread functions (PSF) for each detector and perform deconvolution for image restoration. Equipped with this method, the microscope with discretionally designed detector array can be easily constructed without the concern of exact relative locations of detectors. The simulated results and experimental results show the total improvement in resolution with a factor of 1.7 compared to conventional confocal fluorescence microscopy. With the significant enhancement in resolution and easiness for application of this method, this novel method should have potential for a wide range of application in fluorescence microscopy based on parallel detecting.

High Resolution Image Reconstruction from Projection of Low Resolution Images DIffering in Subpixel Shifts

NASA Technical Reports Server (NTRS)

Mareboyana, Manohar; Le Moigne-Stewart, Jacqueline; Bennett, Jerome

2016-01-01

In this paper, we demonstrate a simple algorithm that projects low resolution (LR) images differing in subpixel shifts on a high resolution (HR) also called super resolution (SR) grid. The algorithm is very effective in accuracy as well as time efficiency. A number of spatial interpolation techniques using nearest neighbor, inverse-distance weighted averages, Radial Basis Functions (RBF) etc. used in projection yield comparable results. For best accuracy of reconstructing SR image by a factor of two requires four LR images differing in four independent subpixel shifts. The algorithm has two steps: i) registration of low resolution images and (ii) shifting the low resolution images to align with reference image and projecting them on high resolution grid based on the shifts of each low resolution image using different interpolation techniques. Experiments are conducted by simulating low resolution images by subpixel shifts and subsampling of original high resolution image and the reconstructing the high resolution images from the simulated low resolution images. The results of accuracy of reconstruction are compared by using mean squared error measure between original high resolution image and reconstructed image. The algorithm was tested on remote sensing images and found to outperform previously proposed techniques such as Iterative Back Projection algorithm (IBP), Maximum Likelihood (ML), and Maximum a posterior (MAP) algorithms. The algorithm is robust and is not overly sensitive to the registration inaccuracies.

Super-resolution pupil filtering for visual performance enhancement using adaptive optics

NASA Astrophysics Data System (ADS)

Zhao, Lina; Dai, Yun; Zhao, Junlei; Zhou, Xiaojun

2018-05-01

Ocular aberration correction can significantly improve visual function of the human eye. However, even under ideal aberration correction conditions, pupil diffraction restricts the resolution of retinal images. Pupil filtering is a simple super-resolution (SR) method that can overcome this diffraction barrier. In this study, a 145-element piezoelectric deformable mirror was used as a pupil phase filter because of its programmability and high fitting accuracy. Continuous phase-only filters were designed based on Zernike polynomial series and fitted through closed-loop adaptive optics. SR results were validated using double-pass point spread function images. Contrast sensitivity was further assessed to verify the SR effect on visual function. An F-test was conducted for nested models to statistically compare different CSFs. These results indicated CSFs for the proposed SR filter were significantly higher than the diffraction correction (p < 0.05). As such, the proposed filter design could provide useful guidance for supernormal vision optical correction of the human eye.

Super-Resolution Imaging of Molecular Emission Spectra and Single Molecule Spectral Fluctuations

PubMed Central

Mlodzianoski, Michael J.; Curthoys, Nikki M.; Gunewardene, Mudalige S.; Carter, Sean; Hess, Samuel T.

2016-01-01

Localization microscopy can image nanoscale cellular details. To address biological questions, the ability to distinguish multiple molecular species simultaneously is invaluable. Here, we present a new version of fluorescence photoactivation localization microscopy (FPALM) which detects the emission spectrum of each localized molecule, and can quantify changes in emission spectrum of individual molecules over time. This information can allow for a dramatic increase in the number of different species simultaneously imaged in a sample, and can create super-resolution maps showing how single molecule emission spectra vary with position and time in a sample. PMID:27002724

Single cell systems biology by super-resolution imaging and combinatorial labeling

PubMed Central

Lubeck, Eric; Cai, Long

2012-01-01

Fluorescence microscopy is a powerful quantitative tool for exploring regulatory networks in single cells. However, the number of molecular species that can be measured simultaneously is limited by the spectral separability of fluorophores. Here we demonstrate a simple but general strategy to drastically increase the capacity for multiplex detection of molecules in single cells by using optical super-resolution microscopy (SRM) and combinatorial labeling. As a proof of principle, we labeled mRNAs with unique combinations of fluorophores using Fluorescence in situ Hybridization (FISH), and resolved the sequences and combinations of fluorophores with SRM. We measured the mRNA levels of 32 genes simultaneously in single S. cerevisiae cells. These experiments demonstrate that combinatorial labeling and super-resolution imaging of single cells provides a natural approach to bring systems biology into single cells. PMID:22660740

Achieving high-efficiency emission depletion nanoscopy by employing cross relaxation in upconversion nanoparticles.

PubMed

Zhan, Qiuqiang; Liu, Haichun; Wang, Baoju; Wu, Qiusheng; Pu, Rui; Zhou, Chao; Huang, Bingru; Peng, Xingyun; Ågren, Hans; He, Sailing

2017-10-20

Stimulated emission depletion microscopy provides a powerful sub-diffraction imaging modality for life science studies. Conventionally, stimulated emission depletion requires a relatively high light intensity to obtain an adequate depletion efficiency through only light-matter interaction. Here we show efficient emission depletion for a class of lanthanide-doped upconversion nanoparticles with the assistance of interionic cross relaxation, which significantly lowers the laser intensity requirements of optical depletion. We demonstrate two-color super-resolution imaging using upconversion nanoparticles (resolution ~ 66 nm) with a single pair of excitation/depletion beams. In addition, we show super-resolution imaging of immunostained cytoskeleton structures of fixed cells (resolution ~ 82 nm) using upconversion nanoparticles. These achievements provide a new perspective for the development of photoswitchable luminescent probes and will broaden the applications of lanthanide-doped nanoparticles for sub-diffraction microscopic imaging.

Fundamental techniques for resolution enhancement of average subsampled images

NASA Astrophysics Data System (ADS)

Shen, Day-Fann; Chiu, Chui-Wen

2012-07-01

Although single image resolution enhancement, otherwise known as super-resolution, is widely regarded as an ill-posed inverse problem, we re-examine the fundamental relationship between a high-resolution (HR) image acquisition module and its low-resolution (LR) counterpart. Analysis shows that partial HR information is attenuated but still exists, in its LR version, through the fundamental averaging-and-subsampling process. As a result, we propose a modified Laplacian filter (MLF) and an intensity correction process (ICP) as the pre and post process, respectively, with an interpolation algorithm to partially restore the attenuated information in a super-resolution (SR) enhanced image image. Experiments show that the proposed MLF and ICP provide significant and consistent quality improvements on all 10 test images with three well known interpolation methods including bilinear, bi-cubic, and the SR graphical user interface program provided by Ecole Polytechnique Federale de Lausanne. The proposed MLF and ICP are simple in implementation and generally applicable to all average-subsampled LR images. MLF and ICP, separately or together, can be integrated into most interpolation methods that attempt to restore the original HR contents. Finally, the idea of MLF and ICP can also be applied for average, subsampled one-dimensional signal.

MIiSR: Molecular Interactions in Super-Resolution Imaging Enables the Analysis of Protein Interactions, Dynamics and Formation of Multi-protein Structures.

PubMed

Caetano, Fabiana A; Dirk, Brennan S; Tam, Joshua H K; Cavanagh, P Craig; Goiko, Maria; Ferguson, Stephen S G; Pasternak, Stephen H; Dikeakos, Jimmy D; de Bruyn, John R; Heit, Bryan

2015-12-01

Our current understanding of the molecular mechanisms which regulate cellular processes such as vesicular trafficking has been enabled by conventional biochemical and microscopy techniques. However, these methods often obscure the heterogeneity of the cellular environment, thus precluding a quantitative assessment of the molecular interactions regulating these processes. Herein, we present Molecular Interactions in Super Resolution (MIiSR) software which provides quantitative analysis tools for use with super-resolution images. MIiSR combines multiple tools for analyzing intermolecular interactions, molecular clustering and image segmentation. These tools enable quantification, in the native environment of the cell, of molecular interactions and the formation of higher-order molecular complexes. The capabilities and limitations of these analytical tools are demonstrated using both modeled data and examples derived from the vesicular trafficking system, thereby providing an established and validated experimental workflow capable of quantitatively assessing molecular interactions and molecular complex formation within the heterogeneous environment of the cell.

The 2015 super-resolution microscopy roadmap

NASA Astrophysics Data System (ADS)

Hell, Stefan W.; Sahl, Steffen J.; Bates, Mark; Zhuang, Xiaowei; Heintzmann, Rainer; Booth, Martin J.; Bewersdorf, Joerg; Shtengel, Gleb; Hess, Harald; Tinnefeld, Philip; Honigmann, Alf; Jakobs, Stefan; Testa, Ilaria; Cognet, Laurent; Lounis, Brahim; Ewers, Helge; Davis, Simon J.; Eggeling, Christian; Klenerman, David; Willig, Katrin I.; Vicidomini, Giuseppe; Castello, Marco; Diaspro, Alberto; Cordes, Thorben

2015-11-01

Far-field optical microscopy using focused light is an important tool in a number of scientific disciplines including chemical, (bio)physical and biomedical research, particularly with respect to the study of living cells and organisms. Unfortunately, the applicability of the optical microscope is limited, since the diffraction of light imposes limitations on the spatial resolution of the image. Consequently the details of, for example, cellular protein distributions, can be visualized only to a certain extent. Fortunately, recent years have witnessed the development of ‘super-resolution’ far-field optical microscopy (nanoscopy) techniques such as stimulated emission depletion (STED), ground state depletion (GSD), reversible saturated optical (fluorescence) transitions (RESOLFT), photoactivation localization microscopy (PALM), stochastic optical reconstruction microscopy (STORM), structured illumination microscopy (SIM) or saturated structured illumination microscopy (SSIM), all in one way or another addressing the problem of the limited spatial resolution of far-field optical microscopy. While SIM achieves a two-fold improvement in spatial resolution compared to conventional optical microscopy, STED, RESOLFT, PALM/STORM, or SSIM have all gone beyond, pushing the limits of optical image resolution to the nanometer scale. Consequently, all super-resolution techniques open new avenues of biomedical research. Because the field is so young, the potential capabilities of different super-resolution microscopy approaches have yet to be fully explored, and uncertainties remain when considering the best choice of methodology. Thus, even for experts, the road to the future is sometimes shrouded in mist. The super-resolution optical microscopy roadmap of Journal of Physics D: Applied Physics addresses this need for clarity. It provides guidance to the outstanding questions through a collection of short review articles from experts in the field, giving a thorough discussion on the concepts underlying super-resolution optical microscopy, the potential of different approaches, the importance of label optimization (such as reversible photoswitchable proteins) and applications in which these methods will have a significant impact. Mark Bates, Christian Eggeling

Research on compression performance of ultrahigh-definition videos

NASA Astrophysics Data System (ADS)

Li, Xiangqun; He, Xiaohai; Qing, Linbo; Tao, Qingchuan; Wu, Di

2017-11-01

With the popularization of high-definition (HD) images and videos (1920×1080 pixels and above), there are even 4K (3840×2160) television signals and 8 K (8192×4320) ultrahigh-definition videos. The demand for HD images and videos is increasing continuously, along with the increasing data volume. The storage and transmission cannot be properly solved only by virtue of the expansion capacity of hard disks and the update and improvement of transmission devices. Based on the full use of the coding standard high-efficiency video coding (HEVC), super-resolution reconstruction technology, and the correlation between the intra- and the interprediction, we first put forward a "division-compensation"-based strategy to further improve the compression performance of a single image and frame I. Then, by making use of the above thought and HEVC encoder and decoder, a video compression coding frame is designed. HEVC is used inside the frame. Last, with the super-resolution reconstruction technology, the reconstructed video quality is further improved. The experiment shows that by the proposed compression method for a single image (frame I) and video sequence here, the performance is superior to that of HEVC in a low bit rate environment.

Improved localization accuracy in stochastic super-resolution fluorescence microscopy by K-factor image deshadowing

PubMed Central

Ilovitsh, Tali; Meiri, Amihai; Ebeling, Carl G.; Menon, Rajesh; Gerton, Jordan M.; Jorgensen, Erik M.; Zalevsky, Zeev

2013-01-01

Localization of a single fluorescent particle with sub-diffraction-limit accuracy is a key merit in localization microscopy. Existing methods such as photoactivated localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM) achieve localization accuracies of single emitters that can reach an order of magnitude lower than the conventional resolving capabilities of optical microscopy. However, these techniques require a sparse distribution of simultaneously activated fluorophores in the field of view, resulting in larger time needed for the construction of the full image. In this paper we present the use of a nonlinear image decomposition algorithm termed K-factor, which reduces an image into a nonlinear set of contrast-ordered decompositions whose joint product reassembles the original image. The K-factor technique, when implemented on raw data prior to localization, can improve the localization accuracy of standard existing methods, and also enable the localization of overlapping particles, allowing the use of increased fluorophore activation density, and thereby increased data collection speed. Numerical simulations of fluorescence data with random probe positions, and especially at high densities of activated fluorophores, demonstrate an improvement of up to 85% in the localization precision compared to single fitting techniques. Implementing the proposed concept on experimental data of cellular structures yielded a 37% improvement in resolution for the same super-resolution image acquisition time, and a decrease of 42% in the collection time of super-resolution data with the same resolution. PMID:24466491

Subpixel target detection and enhancement in hyperspectral images

NASA Astrophysics Data System (ADS)

Tiwari, K. C.; Arora, M.; Singh, D.

2011-06-01

Hyperspectral data due to its higher information content afforded by higher spectral resolution is increasingly being used for various remote sensing applications including information extraction at subpixel level. There is however usually a lack of matching fine spatial resolution data particularly for target detection applications. Thus, there always exists a tradeoff between the spectral and spatial resolutions due to considerations of type of application, its cost and other associated analytical and computational complexities. Typically whenever an object, either manmade, natural or any ground cover class (called target, endmembers, components or class) gets spectrally resolved but not spatially, mixed pixels in the image result. Thus, numerous manmade and/or natural disparate substances may occur inside such mixed pixels giving rise to mixed pixel classification or subpixel target detection problems. Various spectral unmixing models such as Linear Mixture Modeling (LMM) are in vogue to recover components of a mixed pixel. Spectral unmixing outputs both the endmember spectrum and their corresponding abundance fractions inside the pixel. It, however, does not provide spatial distribution of these abundance fractions within a pixel. This limits the applicability of hyperspectral data for subpixel target detection. In this paper, a new inverse Euclidean distance based super-resolution mapping method has been presented that achieves subpixel target detection in hyperspectral images by adjusting spatial distribution of abundance fraction within a pixel. Results obtained at different resolutions indicate that super-resolution mapping may effectively aid subpixel target detection.

Comparison of DSMs acquired by terrestrial laser scanning, UAV-based aerial images and ground-based optical images at the Super-Sauze landslide

NASA Astrophysics Data System (ADS)

Rothmund, Sabrina; Niethammer, Uwe; Walter, Marco; Joswig, Manfred

2013-04-01

In recent years, the high-resolution and multi-temporal 3D mapping of the Earth's surface using terrestrial laser scanning (TLS), ground-based optical images and especially low-cost UAV-based aerial images (Unmanned Aerial Vehicle) has grown in importance. This development resulted from the progressive technical improvement of the imaging systems and the freely available multi-view stereo (MVS) software packages. These different methods of data acquisition for the generation of accurate, high-resolution digital surface models (DSMs) were applied as part of an eight-week field campaign at the Super-Sauze landslide (South French Alps). An area of approximately 10,000 m² with long-term average displacement rates greater than 0.01 m/day has been investigated. The TLS-based point clouds were acquired at different viewpoints with an average point spacing between 10 to 40 mm and at different dates. On these days, more than 50 optical images were taken on points along a predefined line on the side part of the landslide by a low-cost digital compact camera. Additionally, aerial images were taken by a radio-controlled mini quad-rotor UAV equipped with another low-cost digital compact camera. The flight altitude ranged between 20 m and 250 m and produced a corresponding ground resolution between 0.6 cm and 7 cm. DGPS measurements were carried out as well in order to geo-reference and validate the point cloud data. To generate unscaled photogrammetric 3D point clouds from a disordered and tilted image set, we use the widespread open-source software package Bundler and PMVS2 (University of Washington). These multi-temporal DSMs are required on the one hand to determine the three-dimensional surface deformations and on the other hand it will be required for differential correction for orthophoto production. Drawing on the example of the acquired data at the Super-Sauze landslide, we demonstrate the potential but also the limitations of the photogrammetric point clouds. To determine the quality of the photogrammetric point cloud, these point clouds are compared with the TLS-based DSMs. The comparison shows that photogrammetric points accuracies are in the range of cm to dm, therefore don't reach the quality of the high-resolution TLS-based DSMs. Further, the validation of the photogrammetric point clouds reveals that some of them have internal curvature effects. The advantage of the photogrammetric 3D data acquisition is the use of low-cost equipment and less time-consuming data collection in the field. While the accuracy of the photogrammetric point clouds is not as high as TLS-based DSMs, the advantages of the former method are seen when applied in areas where dm-range is sufficient.

Multispectral image enhancement processing for microsat-borne imager

NASA Astrophysics Data System (ADS)

Sun, Jianying; Tan, Zheng; Lv, Qunbo; Pei, Linlin

2017-10-01

With the rapid development of remote sensing imaging technology, the micro satellite, one kind of tiny spacecraft, appears during the past few years. A good many studies contribute to dwarfing satellites for imaging purpose. Generally speaking, micro satellites weigh less than 100 kilograms, even less than 50 kilograms, which are slightly larger or smaller than the common miniature refrigerators. However, the optical system design is hard to be perfect due to the satellite room and weight limitation. In most cases, the unprocessed data captured by the imager on the microsatellite cannot meet the application need. Spatial resolution is the key problem. As for remote sensing applications, the higher spatial resolution of images we gain, the wider fields we can apply them. Consequently, how to utilize super resolution (SR) and image fusion to enhance the quality of imagery deserves studying. Our team, the Key Laboratory of Computational Optical Imaging Technology, Academy Opto-Electronics, is devoted to designing high-performance microsat-borne imagers and high-efficiency image processing algorithms. This paper addresses a multispectral image enhancement framework for space-borne imagery, jointing the pan-sharpening and super resolution techniques to deal with the spatial resolution shortcoming of microsatellites. We test the remote sensing images acquired by CX6-02 satellite and give the SR performance. The experiments illustrate the proposed approach provides high-quality images.

Image superresolution of cytology images using wavelet based patch search

NASA Astrophysics Data System (ADS)

Vargas, Carlos; García-Arteaga, Juan D.; Romero, Eduardo

2015-01-01

Telecytology is a new research area that holds the potential of significantly reducing the number of deaths due to cervical cancer in developing countries. This work presents a novel super-resolution technique that couples high and low frequency information in order to reduce the bandwidth consumption of cervical image transmission. The proposed approach starts by decomposing into wavelets the high resolution images and transmitting only the lower frequency coefficients. The transmitted coefficients are used to reconstruct an image of the original size. Additional details are added by iteratively replacing patches of the wavelet reconstructed image with equivalent high resolution patches from a previously acquired image database. Finally, the original transmitted low frequency coefficients are used to correct the final image. Results show a higher signal to noise ratio in the proposed method over simply discarding high frequency wavelet coefficients or replacing directly down-sampled patches from the image-database.

Super Resolution and Interference Suppression Technique applied to SHARAD Radar Data

NASA Astrophysics Data System (ADS)

Raguso, M. C.; Mastrogiuseppe, M.; Seu, R.; Piazzo, L.

2017-12-01

We will present a super resolution and interference suppression technique applied to the data acquired by the SHAllow RADar (SHARAD) on board the NASA's 2005 Mars Reconnaissance Orbiter (MRO) mission, currently operating around Mars [1]. The algorithms allow to improve the range resolution roughly by a factor of 3 and the Signal to Noise Ratio (SNR) by a several decibels. Range compression algorithms usually adopt conventional Fourier transform techniques, which are limited in the resolution by the transmitted signal bandwidth, analogous to the Rayleigh's criterion in optics. In this work, we investigate a super resolution method based on autoregressive models and linear prediction techniques [2]. Starting from the estimation of the linear prediction coefficients from the spectral data, the algorithm performs the radar bandwidth extrapolation (BWE), thereby improving the range resolution of the pulse-compressed coherent radar data. Moreover, the EMIs (ElectroMagnetic Interferences) are detected and the spectra is interpolated in order to reconstruct an interference free spectrum, thereby improving the SNR. The algorithm can be applied to the single complex look image after synthetic aperture processing (SAR). We apply the proposed algorithm to simulated as well as to real radar data. We will demonstrate the effective enhancement on vertical resolution with respect to the classical spectral estimator. We will show that the imaging of the subsurface layered structures observed in radargrams is improved, allowing additional insights for the scientific community in the interpretation of the SHARAD radar data, which will help to further our understanding of the formation and evolution of known geological features on Mars. References: [1] Seu et al. 2007, Science, 2007, 317, 1715-1718 [2] K.M. Cuomo, "A Bandwidth Extrapolation Technique for Improved Range Resolution of Coherent Radar Data", Project Report CJP-60, Revision 1, MIT Lincoln Laboratory (4 Dec. 1992).

Synthesis of a Far-Red Photoactivatable Silicon-Containing Rhodamine for Super-Resolution Microscopy.

PubMed

Grimm, Jonathan B; Klein, Teresa; Kopek, Benjamin G; Shtengel, Gleb; Hess, Harald F; Sauer, Markus; Lavis, Luke D

2016-01-26

The rhodamine system is a flexible framework for building small-molecule fluorescent probes. Changing N-substitution patterns and replacing the xanthene oxygen with a dimethylsilicon moiety can shift the absorption and fluorescence emission maxima of rhodamine dyes to longer wavelengths. Acylation of the rhodamine nitrogen atoms forces the molecule to adopt a nonfluorescent lactone form, providing a convenient method to make fluorogenic compounds. Herein, we take advantage of all of these structural manipulations and describe a novel photoactivatable fluorophore based on a Si-containing analogue of Q-rhodamine. This probe is the first example of a "caged" Si-rhodamine, exhibits higher photon counts compared to established localization microscopy dyes, and is sufficiently red-shifted to allow multicolor imaging. The dye is a useful label for super-resolution imaging and constitutes a new scaffold for far-red fluorogenic molecules. © 2015 The Authors. Published by Wiley-VCH Verlag GmbH & Co. KGaA.

DURIP: Super-Resolution Module for Confocal Microscopy of Reconfigurable Matter

DTIC Science & Technology

2014-09-28

Research Office P.O. Box 12211 Research Triangle Park, NC 27709-2211 superresolution microscopy, colloidal particles, self-assembly REPORT...previously have been resolved by optical microscopy. Results of Super Resolution Technique Evaluation Commercially available superresolution imaging...Weaknesses of the method are that is fundamentally a measurement that can only be deployed for fixed samples. Because superresolution is obtained by

A weighted optimization approach to time-of-flight sensor fusion.

PubMed

Schwarz, Sebastian; Sjostrom, Marten; Olsson, Roger

2014-01-01

Acquiring scenery depth is a fundamental task in computer vision, with many applications in manufacturing, surveillance, or robotics relying on accurate scenery information. Time-of-flight cameras can provide depth information in real-time and overcome short-comings of traditional stereo analysis. However, they provide limited spatial resolution and sophisticated upscaling algorithms are sought after. In this paper, we present a sensor fusion approach to time-of-flight super resolution, based on the combination of depth and texture sources. Unlike other texture guided approaches, we interpret the depth upscaling process as a weighted energy optimization problem. Three different weights are introduced, employing different available sensor data. The individual weights address object boundaries in depth, depth sensor noise, and temporal consistency. Applied in consecutive order, they form three weighting strategies for time-of-flight super resolution. Objective evaluations show advantages in depth accuracy and for depth image based rendering compared with state-of-the-art depth upscaling. Subjective view synthesis evaluation shows a significant increase in viewer preference by a factor of four in stereoscopic viewing conditions. To the best of our knowledge, this is the first extensive subjective test performed on time-of-flight depth upscaling. Objective and subjective results proof the suitability of our approach to time-of-flight super resolution approach for depth scenery capture.

Super-resolved thickness maps of thin film phantoms and in vivo visualization of tear film lipid layer using OCT

PubMed Central

dos Santos, Valentin Aranha; Schmetterer, Leopold; Triggs, Graham J.; Leitgeb, Rainer A.; Gröschl, Martin; Messner, Alina; Schmidl, Doreen; Garhofer, Gerhard; Aschinger, Gerold; Werkmeister, René M.

2016-01-01

In optical coherence tomography (OCT), the axial resolution is directly linked to the coherence length of the employed light source. It is currently unclear if OCT allows measuring thicknesses below its axial resolution value. To investigate spectral-domain OCT imaging in the super-resolution regime, we derived a signal model and compared it with the experiment. Several island thin film samples of known refractive indices and thicknesses in the range 46 – 163 nm were fabricated and imaged. Reference thickness measurements were performed using a commercial atomic force microscope. In vivo measurements of the tear film were performed in 4 healthy subjects. Our results show that quantitative super-resolved thickness measurement can be performed using OCT. In addition, we report repeatable tear film lipid layer visualization. Our results provide a novel interpretation of the OCT axial resolution limit and open a perspective to deeper extraction of the information hidden in the coherence volume. PMID:27446696

Stimulated emission depletion microscopy resolves individual nitrogen vacancy centers in diamond nanocrystals.

PubMed

Arroyo-Camejo, Silvia; Adam, Marie-Pierre; Besbes, Mondher; Hugonin, Jean-Paul; Jacques, Vincent; Greffet, Jean-Jacques; Roch, Jean-François; Hell, Stefan W; Treussart, François

2013-12-23

Nitrogen-vacancy (NV) color centers in nanodiamonds are highly promising for bioimaging and sensing. However, resolving individual NV centers within nanodiamond particles and the controlled addressing and readout of their spin state has remained a major challenge. Spatially stochastic super-resolution techniques cannot provide this capability in principle, whereas coordinate-controlled super-resolution imaging methods, like stimulated emission depletion (STED) microscopy, have been predicted to fail in nanodiamonds. Here we show that, contrary to these predictions, STED can resolve single NV centers in 40-250 nm sized nanodiamonds with a resolution of ≈10 nm. Even multiple adjacent NVs located in single nanodiamonds can be imaged individually down to relative distances of ≈15 nm. Far-field optical super-resolution of NVs inside nanodiamonds is highly relevant for bioimaging applications of these fluorescent nanolabels. The targeted addressing and readout of individual NV(-) spins inside nanodiamonds by STED should also be of high significance for quantum sensing and information applications.

Super-resolution Imaging of Chemical Synapses in the Brain

PubMed Central

Dani, Adish; Huang, Bo; Bergan, Joseph; Dulac, Catherine; Zhuang, Xiaowei

2010-01-01

Determination of the molecular architecture of synapses requires nanoscopic image resolution and specific molecular recognition, a task that has so far defied many conventional imaging approaches. Here we present a super-resolution fluorescence imaging method to visualize the molecular architecture of synapses in the brain. Using multicolor, three-dimensional stochastic optical reconstruction microscopy, the distributions of synaptic proteins can be measured with nanometer precision. Furthermore, the wide-field, volumetric imaging method enables high-throughput, quantitative analysis of a large number of synapses from different brain regions. To demonstrate the capabilities of this approach, we have determined the organization of ten protein components of the presynaptic active zone and the postsynaptic density. Variations in synapse morphology, neurotransmitter receptor composition, and receptor distribution were observed both among synapses and across different brain regions. Combination with optogenetics further allowed molecular events associated with synaptic plasticity to be resolved at the single-synapse level. PMID:21144999

Gallium nitride light sources for optical coherence tomography

NASA Astrophysics Data System (ADS)

Goldberg, Graham R.; Ivanov, Pavlo; Ozaki, Nobuhiko; Childs, David T. D.; Groom, Kristian M.; Kennedy, Kenneth L.; Hogg, Richard A.

2017-02-01

The advent of optical coherence tomography (OCT) has permitted high-resolution, non-invasive, in vivo imaging of the eye, skin and other biological tissue. The axial resolution is limited by source bandwidth and central wavelength. With the growing demand for short wavelength imaging, super-continuum sources and non-linear fibre-based light sources have been demonstrated in tissue imaging applications exploiting the near-UV and visible spectrum. Whilst the potential has been identified of using gallium nitride devices due to relative maturity of laser technology, there have been limited reports on using such low cost, robust devices in imaging systems. A GaN super-luminescent light emitting diode (SLED) was first reported in 2009, using tilted facets to suppress lasing, with the focus since on high power, low speckle and relatively low bandwidth applications. In this paper we discuss a method of producing a GaN based broadband source, including a passive absorber to suppress lasing. The merits of this passive absorber are then discussed with regards to broad-bandwidth applications, rather than power applications. For the first time in GaN devices, the performance of the light sources developed are assessed though the point spread function (PSF) (which describes an imaging systems response to a point source), calculated from the emission spectra. We show a sub-7μm resolution is possible without the use of special epitaxial techniques, ultimately outlining the suitability of these short wavelength, broadband, GaN devices for use in OCT applications.

Super-resolution reconstruction of diffusion parameters from diffusion-weighted images with different slice orientations.

PubMed

Van Steenkiste, Gwendolyn; Jeurissen, Ben; Veraart, Jelle; den Dekker, Arnold J; Parizel, Paul M; Poot, Dirk H J; Sijbers, Jan

2016-01-01

Diffusion MRI is hampered by long acquisition times, low spatial resolution, and a low signal-to-noise ratio. Recently, methods have been proposed to improve the trade-off between spatial resolution, signal-to-noise ratio, and acquisition time of diffusion-weighted images via super-resolution reconstruction (SRR) techniques. However, during the reconstruction, these SRR methods neglect the q-space relation between the different diffusion-weighted images. An SRR method that includes a diffusion model and directly reconstructs high resolution diffusion parameters from a set of low resolution diffusion-weighted images was proposed. Our method allows an arbitrary combination of diffusion gradient directions and slice orientations for the low resolution diffusion-weighted images, optimally samples the q- and k-space, and performs motion correction with b-matrix rotation. Experiments with synthetic data and in vivo human brain data show an increase of spatial resolution of the diffusion parameters, while preserving a high signal-to-noise ratio and low scan time. Moreover, the proposed SRR method outperforms the previous methods in terms of the root-mean-square error. The proposed SRR method substantially increases the spatial resolution of MRI that can be obtained in a clinically feasible scan time. © 2015 Wiley Periodicals, Inc.

Chip-based wide field-of-view nanoscopy

NASA Astrophysics Data System (ADS)

Diekmann, Robin; Helle, Øystein I.; Øie, Cristina I.; McCourt, Peter; Huser, Thomas R.; Schüttpelz, Mark; Ahluwalia, Balpreet S.

2017-04-01

Present optical nanoscopy techniques use a complex microscope for imaging and a simple glass slide to hold the sample. Here, we demonstrate the inverse: the use of a complex, but mass-producible optical chip, which hosts the sample and provides a waveguide for the illumination source, and a standard low-cost microscope to acquire super-resolved images via two different approaches. Waveguides composed of a material with high refractive-index contrast provide a strong evanescent field that is used for single-molecule switching and fluorescence excitation, thus enabling chip-based single-molecule localization microscopy. Additionally, multimode interference patterns induce spatial fluorescence intensity variations that enable fluctuation-based super-resolution imaging. As chip-based nanoscopy separates the illumination and detection light paths, total-internal-reflection fluorescence excitation is possible over a large field of view, with up to 0.5 mm × 0.5 mm being demonstrated. Using multicolour chip-based nanoscopy, we visualize fenestrations in liver sinusoidal endothelial cells.

Sparse Representations-Based Super-Resolution of Key-Frames Extracted from Frames-Sequences Generated by a Visual Sensor Network

PubMed Central

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2014-01-01

Visual sensor networks (VSNs) usually generate a low-resolution (LR) frame-sequence due to energy and processing constraints. These LR-frames are not very appropriate for use in certain surveillance applications. It is very important to enhance the resolution of the captured LR-frames using resolution enhancement schemes. In this paper, an effective framework for a super-resolution (SR) scheme is proposed that enhances the resolution of LR key-frames extracted from frame-sequences captured by visual-sensors. In a VSN, a visual processing hub (VPH) collects a huge amount of visual data from camera sensors. In the proposed framework, at the VPH, key-frames are extracted using our recent key-frame extraction technique and are streamed to the base station (BS) after compression. A novel effective SR scheme is applied at BS to produce a high-resolution (HR) output from the received key-frames. The proposed SR scheme uses optimized orthogonal matching pursuit (OOMP) for sparse-representation recovery in SR. OOMP does better in terms of detecting true sparsity than orthogonal matching pursuit (OMP). This property of the OOMP helps produce a HR image which is closer to the original image. The K-SVD dictionary learning procedure is incorporated for dictionary learning. Batch-OMP improves the dictionary learning process by removing the limitation in handling a large set of observed signals. Experimental results validate the effectiveness of the proposed scheme and show its superiority over other state-of-the-art schemes. PMID:24566632

Sparse representations-based super-resolution of key-frames extracted from frames-sequences generated by a visual sensor network.

PubMed

Sajjad, Muhammad; Mehmood, Irfan; Baik, Sung Wook

2014-02-21

Visual sensor networks (VSNs) usually generate a low-resolution (LR) frame-sequence due to energy and processing constraints. These LR-frames are not very appropriate for use in certain surveillance applications. It is very important to enhance the resolution of the captured LR-frames using resolution enhancement schemes. In this paper, an effective framework for a super-resolution (SR) scheme is proposed that enhances the resolution of LR key-frames extracted from frame-sequences captured by visual-sensors. In a VSN, a visual processing hub (VPH) collects a huge amount of visual data from camera sensors. In the proposed framework, at the VPH, key-frames are extracted using our recent key-frame extraction technique and are streamed to the base station (BS) after compression. A novel effective SR scheme is applied at BS to produce a high-resolution (HR) output from the received key-frames. The proposed SR scheme uses optimized orthogonal matching pursuit (OOMP) for sparse-representation recovery in SR. OOMP does better in terms of detecting true sparsity than orthogonal matching pursuit (OMP). This property of the OOMP helps produce a HR image which is closer to the original image. The K-SVD dictionary learning procedure is incorporated for dictionary learning. Batch-OMP improves the dictionary learning process by removing the limitation in handling a large set of observed signals. Experimental results validate the effectiveness of the proposed scheme and show its superiority over other state-of-the-art schemes.

Hires and beyond

NASA Technical Reports Server (NTRS)

Fowler, John W.; Aumann, H. H.

1994-01-01

The High-Resolution image construction program (HiRes) used at IPAC is based on the Maximum Correlation Method. After HiRes intensity images are constructed from IRAS data, additional images are needed to aid in scientific interpretation. Some of the images that are available for this purpose show the fitting noise, estimates of the achieved resolution, and detector track maps. Two methods have been developed for creating color maps without discarding any more spatial information than absolutely necessary: the 'cross-band simulation' and 'prior-knowledge' methods. These maps are demonstrated using the survey observations of a 2 x 2 degree field centered on M31. Prior knowledge may also be used to achieve super-resolution and to suppress ringing around bright point sources observed against background emission. Tools to suppress noise spikes and for accelerating convergence are also described.

Sensorless adaptive optics for isoSTED nanoscopy

NASA Astrophysics Data System (ADS)

Antonello, Jacopo; Hao, Xiang; Allgeyer, Edward S.; Bewersdorf, Joerg; Rittscher, Jens; Booth, Martin J.

2018-02-01

The presence of aberrations is a major concern when using fluorescence microscopy to image deep inside tissue. Aberrations due to refractive index mismatch and heterogeneity of the specimen under investigation cause severe reduction in the amount of fluorescence emission that is collected by the microscope. Furthermore, aberrations adversely affect the resolution, leading to loss of fine detail in the acquired images. These phenomena are particularly troublesome for super-resolution microscopy techniques such as isotropic stimulated-emission-depletion microscopy (isoSTED), which relies on accurate control of the shape and co-alignment of multiple excitation and depletion foci to operate as expected and to achieve the super-resolution effect. Aberrations can be suppressed by implementing sensorless adaptive optics techniques, whereby aberration correction is achieved by maximising a certain image quality metric. In confocal microscopy for example, one can employ the total image brightness as an image quality metric. Aberration correction is subsequently achieved by iteratively changing the settings of a wavefront corrector device until the metric is maximised. This simplistic approach has limited applicability to isoSTED microscopy where, due to the complex interplay between the excitation and depletion foci, maximising the total image brightness can lead to introducing aberrations in the depletion foci. In this work we first consider the effects that different aberration modes have on isoSTED microscopes. We then propose an iterative, wavelet-based aberration correction algorithm and evaluate its benefits.

Next-generation endomyocardial biopsy: the potential of confocal and super-resolution microscopy.

PubMed

Crossman, David J; Ruygrok, Peter N; Hou, Yu Feng; Soeller, Christian

2015-03-01

Confocal laser scanning microscopy and super-resolution microscopy provide high-contrast and high-resolution fluorescent imaging, which has great potential to increase the diagnostic yield of endomyocardial biopsy (EMB). EMB is currently the gold standard for identification of cardiac allograft rejection, myocarditis, and infiltrative and storage diseases. However, standard analysis is dominated by low-contrast bright-field light and electron microscopy (EM); this lack of contrast makes quantification of pathological features difficult. For example, assessment of cardiac allograft rejection relies on subjective grading of H&E histology, which may lead to diagnostic variability between pathologists. This issue could be solved by utilising the high contrast provided by fluorescence methods such as confocal to quantitatively assess the degree of lymphocytic infiltrate. For infiltrative diseases such as amyloidosis, the nanometre resolution provided by EM can be diagnostic in identifying disease-causing fibrils. The recent advent of super-resolution imaging, particularly direct stochastic optical reconstruction microscopy (dSTORM), provides high-contrast imaging at resolution approaching that of EM. Moreover, dSTORM utilises conventional fluorescence dyes allowing for the same structures to be routinely imaged at the cellular scale and then at the nanoscale. The key benefit of these technologies is that the high contrast facilitates quantitative digital analysis and thereby provides a means to robustly assess critical pathological features. Ultimately, this technology has the ability to provide greater accuracy and precision to EMB assessment, which could result in better outcomes for patients.

The SuperCam Remote Sensing Suite for MARS 2020: Nested and Co-Aligned LIBS, Raman, and VISIR Spectroscopies, and color micro-imaging

NASA Astrophysics Data System (ADS)

Fouchet, Thierry; Wiens, Roger; Maurice, Sylvestre; Johnson, Jeffrey R.; Clegg, Samuel; Sharma, Shiv; Rull, Fernando; Montmessin, Franck; Anderson, Ryan; Beyssac, Olivier; Bonal, Lydie; Deflores, Lauren; Dromart, Gilles; Fischer, William; Forni, Olivier; Gasnault, Olivier; Grotzinger, John P.; Mangold, Nicolas; Martinez-Frias, Jesus; MacLennan, Scott; McCabe, Kevin; cais, Philippe; Nelson, Tony; Angel, Stanley; Beck, Pierre; Benzerara, Karim; Bernard, Sylvain; Bousquet, Bruno; Bridges, Nathan; Cloutis, Edward; Fabre, Cécile; Grasset, Olivier; Lanza, Nina; Lasue, Jeremie; Le Mouélic, Stéphane; Leveille, Rich; Lewin, Eric; McConnochie, Timothy H.; Melikechi, Noureddine; Meslin, Pierre-Yves; Misra, Anupam; Montagnac, Gilles; Newsom, Horton; Ollila, Ann; Pinet, Patrick; Poulet, Francois; Sobron, Pablo

2016-10-01

As chartered by the Science Definition Team, the Mars 2020 mission addresses four primary objectives: A. Characterize the processes that formed and modified the geologic record within an astrobiologically relevant ancient environment, B. Perform astrobiologically relevant investigations to determine habitability, search for materials with biosignature presentation potential, and search for evidence of past life, C. Assemble a returnable cache of samples and D. Contribute to preparation for human exploration of Mars. The SuperCam instrument, selected for the Mars 2020 rover, as a suite of four instruments, provides nested and co-aligned remote investigations: Laser Induced Breakdown Spectroscopy (LIBS), Raman spectroscopy and time-resolved fluorescence (TRF), visible and near-infrared spectroscopy (VISIR), and high resolution color imaging (RMI). SuperCam appeals broadly to the four Mars 2020 objectives.In detail, SuperCam will perform:1. Microscale mineral identification by combining LIBS elemental and VISIR mineralogical spectroscopies, especially targeting secondary minerals2. Determine the sedimental stratigraphy through color imaging and LIBS and VISIR spectroscopy3. Search for organics and bio-signatures with LIBS and Raman spectroscopy4. Quantify the volatile content of the rocks by LIBS spectroscopy to determine the degree of aquaeous alteration5. Characterize the texture of the rocks by color imaging to determine their alteration processes6. Characterize the rocks' coatings by LIBS spectroscopy7. Characterize the soil and its potential for biosignature preservation8. Monitor the odd-oxygen atmospheric chemistry.To meet these goals SuperCam will perform LIBS spectroscopy on 0.5 mm spot up to 7-meter distance, perform Raman and time-resolved fluoresence up to 12-m distance with a 0.8 mrad angular resolution, a 100 ns time gating in the 534-850 nm spectral range, acquire VISIR spectra in the range 0.4-0.85 μm with a resolution of 0.35 nm, and in the IR range over 1.3-2.6 μm, rich in mineral signatures, with a resolution of 20 nm, and provide RGB images with an angular resolution of 40 μrad over a FOV of 20 mrad.We will present the science performances of SuperCam and the forecasted operation plans.

Experimental Study of Super-Resolution Using a Compressive Sensing Architecture

DTIC Science & Technology

2015-03-01

Intelligence 24(9), 1167–1183 (2002). [3] Lin, Z. and Shum, H.-Y., “Fundamental limits of reconstruction-based superresolution algorithms under local...IEEE Transactions on 52, 1289–1306 (April 2006). [9] Marcia, R. and Willett, R., “Compressive coded aperture superresolution image reconstruction,” in

Optical nanoscopy with contact Mie-particles: Resolution analysis

NASA Astrophysics Data System (ADS)

Maslov, Alexey V.; Astratov, Vasily N.

2017-06-01

The theoretical limits of resolution available in microspherical nanoscopy are explored using incoherent point emitters in the air. The images are calculated using a two-dimensional model and solving the Maxwell equations which account for the wave effects on the sub-wavelength scale of the emitter-microsphere interaction. Based on our results, we propose to use small dielectric particles with diameters λ ≲ D ≲ 2 λ made of a high-refractive-index material n ˜2 for imaging sub-wavelength objects. It is shown that such particles form virtual images below and real images above them. At wavelengths of the Mie resonances, these images have slightly better than ˜λ/4 resolution that can be attributed to the image magnification in close proximity to the object and contributions of its near field. The resonant super-resolution imaging of various point-like objects, such as dye molecules, fluorophores, or nanoplasmonic particles, can be realized by using narrow bandpass optical filters spectrally aligned with the Mie resonances.

Snorkelling between the stars: submarine methods for astronomical observations.

NASA Astrophysics Data System (ADS)

Velasco, S.; Quevedo, E.; Font, J.; Oscoz, A.; López, R. L.; Puga, M.; Rebolo, R.; Hernáandez Brito, J.; Llinas, O.; Marrero Callico, G.; Sarmiento, R.

2017-03-01

Trying to reach diffraction-limited astronomical observations from ground-based telescopes is very challenging due to the atmospheric effects contributing to a general blurring of the images. However, astronomy is not the only science facing turbulence problems; obtaining quality images of the undersea world is as ambitious as it is on the sky. One of the solutions contemplated to reach high-resolution images is the use of multiple frames of the same target, known as fusion super-resolution (Quevedo et al. 2015), which is the principle for Lucky Imaging (Velasco et al. 2016). Here we present the successful result of joining efforts between the undersea and the astronomical research done at the Canary Islands.

Super-resolution chemical imaging with dynamic placement of plasmonic hotspots

NASA Astrophysics Data System (ADS)

Olson, Aeli P.; Ertsgaard, Christopher T.; McKoskey, Rachel M.; Rich, Isabel S.; Lindquist, Nathan C.

2015-08-01

We demonstrate dynamic placement of plasmonic "hotspots" for super-resolution chemical imaging via Surface Enhanced Raman Spectroscopy (SERS). A silver nanohole array surface was coated with biological samples and illuminated with a laser. Due to the large plasmonic field enhancements, blinking behavior of the SERS hotspots was observed and processed using a Stochastic Optical Reconstruction Microscopy (STORM) algorithm enabling localization to within 10 nm. However, illumination of the sample with a single static laser beam (i.e., a slightly defocused Gaussian beam) only produced SERS hotspots in fixed locations on the surface, leaving noticeable gaps in any final image. But, by using a spatial light modulator (SLM), the illumination profile of the beam could be altered, shifting any hotspots across the nanohole array surface in sub-wavelength steps. Therefore, by properly structuring an illuminating light field with the SLM, we show the possibility of positioning plasmonic hotspots over a metallic nanohole surface on-the-fly. Using this and our SERS-STORM imaging technique, we show potential for high-resolution chemical imaging without the noticeable gaps that were present with static laser illumination. Interestingly, even illuminating the surface with randomly shifting SLM phase profiles was sufficient to completely fill in a wide field of view for super-resolution SERS imaging of a single strand of 100-nm thick collagen protein fibrils. Images were then compared to those obtained with a scanning electron microscope (SEM). Additionally, we explored alternative methods of phase shifting other than holographic illumination through the SLM to create localization of hotspots necessary for SERS-STORM imaging.

Bimetallic Effect of Single Nanocatalysts Visualized by Super-Resolution Catalysis Imaging

DOE PAGES

Chen, Guanqun; Zou, Ningmu; Chen, Bo; ...

2017-11-01

Compared with their monometallic counterparts, bimetallic nanoparticles often show enhanced catalytic activity associated with the bimetallic interface. Direct quantitation of catalytic activity at the bimetallic interface is important for understanding the enhancement mechanism, but challenging experimentally. Here using single-molecule super-resolution catalysis imaging in correlation with electron microscopy, we report the first quantitative visualization of enhanced bimetallic activity within single bimetallic nanoparticles. We focus on heteronuclear bimetallic PdAu nanoparticles that present a well-defined Pd–Au bimetallic interface in catalyzing a photodriven fluorogenic disproportionation reaction. Our approach also enables a direct comparison between the bimetallic and monometallic regions within the same nanoparticle. Theoreticalmore » calculations further provide insights into the electronic nature of N–O bond activation of the reactant (resazurin) adsorbed on bimetallic sites. Subparticle activity correlation between bimetallic enhancement and monometallic activity suggests that the favorable locations to construct bimetallic sites are those monometallic sites with higher activity, leading to a strategy for making effective bimetallic nanocatalysts. Furthermore, the results highlight the power of super-resolution catalysis imaging in gaining insights that could help improve nanocatalysts.« less

Super-resolution imaging using multi- electrode CMUTs: theoretical design and simulation using point targets.

PubMed

You, Wei; Cretu, Edmond; Rohling, Robert

2013-11-01

This paper investigates a low computational cost, super-resolution ultrasound imaging method that leverages the asymmetric vibration mode of CMUTs. Instead of focusing on the broadband received signal on the entire CMUT membrane, we utilize the differential signal received on the left and right part of the membrane obtained by a multi-electrode CMUT structure. The differential signal reflects the asymmetric vibration mode of the CMUT cell excited by the nonuniform acoustic pressure field impinging on the membrane, and has a resonant component in immersion. To improve the resolution, we propose an imaging method as follows: a set of manifold matrices of CMUT responses for multiple focal directions are constructed off-line with a grid of hypothetical point targets. During the subsequent imaging process, the array sequentially steers to multiple angles, and the amplitudes (weights) of all hypothetical targets at each angle are estimated in a maximum a posteriori (MAP) process with the manifold matrix corresponding to that angle. Then, the weight vector undergoes a directional pruning process to remove the false estimation at other angles caused by the side lobe energy. Ultrasound imaging simulation is performed on ring and linear arrays with a simulation program adapted with a multi-electrode CMUT structure capable of obtaining both average and differential received signals. Because the differential signals from all receiving channels form a more distinctive temporal pattern than the average signals, better MAP estimation results are expected than using the average signals. The imaging simulation shows that using differential signals alone or in combination with the average signals produces better lateral resolution than the traditional phased array or using the average signals alone. This study is an exploration into the potential benefits of asymmetric CMUT responses for super-resolution imaging.

Enhancing SDO/HMI images using deep learning

NASA Astrophysics Data System (ADS)

Baso, C. J. Díaz; Ramos, A. Asensio

2018-06-01

Context. The Helioseismic and Magnetic Imager (HMI) provides continuum images and magnetograms with a cadence better than one per minute. It has been continuously observing the Sun 24 h a day for the past 7 yr. The trade-off between full disk observations and spatial resolution means that HMI is not adequate for analyzing the smallest-scale events in the solar atmosphere. Aims: Our aim is to develop a new method to enhance HMI data, simultaneously deconvolving and super-resolving images and magnetograms. The resulting images will mimic observations with a diffraction-limited telescope twice the diameter of HMI. Methods: Our method, which we call Enhance, is based on two deep, fully convolutional neural networks that input patches of HMI observations and output deconvolved and super-resolved data. The neural networks are trained on synthetic data obtained from simulations of the emergence of solar active regions. Results: We have obtained deconvolved and super-resolved HMI images. To solve this ill-defined problem with infinite solutions we have used a neural network approach to add prior information from the simulations. We test Enhance against Hinode data that has been degraded to a 28 cm diameter telescope showing very good consistency. The code is open source.

Super-resolution imaging of multiple cells by optimized flat-field epi-illumination

NASA Astrophysics Data System (ADS)

Douglass, Kyle M.; Sieben, Christian; Archetti, Anna; Lambert, Ambroise; Manley, Suliana

2016-11-01

Biological processes are inherently multi-scale, and supramolecular complexes at the nanoscale determine changes at the cellular scale and beyond. Single-molecule localization microscopy (SMLM) techniques have been established as important tools for studying cellular features with resolutions of the order of around 10 nm. However, in their current form these modalities are limited by a highly constrained field of view (FOV) and field-dependent image resolution. Here, we develop a low-cost microlens array (MLA)-based epi-illumination system—flat illumination for field-independent imaging (FIFI)—that can efficiently and homogeneously perform simultaneous imaging of multiple cells with nanoscale resolution. The optical principle of FIFI, which is an extension of the Köhler integrator, is further elucidated and modelled with a new, free simulation package. We demonstrate FIFI's capabilities by imaging multiple COS-7 and bacteria cells in 100 × 100 μm2 SMLM images—more than quadrupling the size of a typical FOV and producing near-gigapixel-sized images of uniformly high quality.

STED super-resolution microscopy of clinical paraffin-embedded human rectal cancer tissue.

PubMed

Ilgen, Peter; Stoldt, Stefan; Conradi, Lena-Christin; Wurm, Christian Andreas; Rüschoff, Josef; Ghadimi, B Michael; Liersch, Torsten; Jakobs, Stefan

2014-01-01

Formalin fixed and paraffin-embedded human tissue resected during cancer surgery is indispensable for diagnostic and therapeutic purposes and represents a vast and largely unexploited resource for research. Optical microscopy of such specimen is curtailed by the diffraction-limited resolution of conventional optical microscopy. To overcome this limitation, we used STED super-resolution microscopy enabling optical resolution well below the diffraction barrier. We visualized nanoscale protein distributions in sections of well-annotated paraffin-embedded human rectal cancer tissue stored in a clinical repository. Using antisera against several mitochondrial proteins, STED microscopy revealed distinct sub-mitochondrial protein distributions, suggesting a high level of structural preservation. Analysis of human tissues stored for up to 17 years demonstrated that these samples were still amenable for super-resolution microscopy. STED microscopy of sections of HER2 positive rectal adenocarcinoma revealed details in the surface and intracellular HER2 distribution that were blurred in the corresponding conventional images, demonstrating the potential of super-resolution microscopy to explore the thus far largely untapped nanoscale regime in tissues stored in biorepositories.

STED Super-Resolution Microscopy of Clinical Paraffin-Embedded Human Rectal Cancer Tissue

PubMed Central

Wurm, Christian Andreas; Rüschoff, Josef; Ghadimi, B. Michael; Liersch, Torsten; Jakobs, Stefan

2014-01-01

Formalin fixed and paraffin-embedded human tissue resected during cancer surgery is indispensable for diagnostic and therapeutic purposes and represents a vast and largely unexploited resource for research. Optical microscopy of such specimen is curtailed by the diffraction-limited resolution of conventional optical microscopy. To overcome this limitation, we used STED super-resolution microscopy enabling optical resolution well below the diffraction barrier. We visualized nanoscale protein distributions in sections of well-annotated paraffin-embedded human rectal cancer tissue stored in a clinical repository. Using antisera against several mitochondrial proteins, STED microscopy revealed distinct sub-mitochondrial protein distributions, suggesting a high level of structural preservation. Analysis of human tissues stored for up to 17 years demonstrated that these samples were still amenable for super-resolution microscopy. STED microscopy of sections of HER2 positive rectal adenocarcinoma revealed details in the surface and intracellular HER2 distribution that were blurred in the corresponding conventional images, demonstrating the potential of super-resolution microscopy to explore the thus far largely untapped nanoscale regime in tissues stored in biorepositories. PMID:25025184

Recent advancements in structured-illumination microscopy toward live-cell imaging.

PubMed

Hirano, Yasuhiro; Matsuda, Atsushi; Hiraoka, Yasushi

2015-08-01

Fluorescence microscopy allows us to observe fluorescently labeled molecules in diverse biological processes and organelle structures within living cells. However, the diffraction limit restricts its spatial resolution to about half of its wavelength, limiting the capability of biological observation at the molecular level. Structured-illumination microscopy (SIM), a type of super-resolution microscopy, doubles the spatial resolution in all three dimensions by illuminating the sample with a patterned excitation light, followed by computer reconstruction. SIM uses a relatively low illumination power compared with other methods of super-resolution microscopy and is easily available for multicolor imaging. SIM has great potential for meeting the requirements of live-cell imaging. Recent developments in diverse types of SIM have achieved higher spatial (∼50 nm lateral) and temporal (∼100 Hz) resolutions. Here, we review recent advancements in SIM and discuss its application in noninvasive live-cell imaging. © The Author 2015. Published by Oxford University Press on behalf of The Japanese Society of Microscopy. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Experimental study on microsphere assisted nanoscope in non-contact mode

NASA Astrophysics Data System (ADS)

Ling, Jinzhong; Li, Dancui; Liu, Xin; Wang, Xiaorui

2018-07-01

Microsphere assisted nanoscope was proposed in existing literatures to capture super-resolution images of the nano-structures beneath the microsphere attached on sample surface. In this paper, a microsphere assisted nanoscope working in non-contact mode is designed and demonstrated, in which the microsphere is controlled with a gap separated to sample surface. With a gap, the microsphere is moved in parallel to sample surface non-invasively, so as to observe all the areas of interest. Furthermore, the influence of gap size on image resolution is studied experimentally. Only when the microsphere is close enough to the sample surface, super-resolution image could be obtained. Generally, the resolution decreases when the gap increases as the contribution of evanescent wave disappears. To keep an appropriate gap size, a quantitative method is implemented to estimate the gap variation by observing Newton's rings around the microsphere, serving as a real-time feedback for tuning the gap size. With a constant gap, large-area image with high resolution can be obtained during microsphere scanning. Our study of non-contact mode makes the microsphere assisted nanoscope more practicable and easier to implement.

Comparison between beamforming and super resolution imaging algorithms for non-destructive evaluation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fan, Chengguang; Drinkwater, Bruce W.

In this paper the performance of total focusing method is compared with the widely used time-reversal MUSIC super resolution technique. The algorithms are tested with simulated and experimental ultrasonic array data, each containing different noise levels. The simulated time domain signals allow the effects of array geometry, frequency, scatterer location, scatterer size, scatterer separation and random noise to be carefully controlled. The performance of the imaging algorithms is evaluated in terms of resolution and sensitivity to random noise. It is shown that for the low noise situation, time-reversal MUSIC provides enhanced lateral resolution when compared to the total focusing method.more » However, for higher noise levels, the total focusing method shows robustness, whilst the performance of time-reversal MUSIC is significantly degraded.« less

Super-resolution reconstruction for 4D computed tomography of the lung via the projections onto convex sets approach

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, Yu, E-mail: yuzhang@smu.edu.cn, E-mail: qianjinfeng08@gmail.com; Wu, Xiuxiu; Yang, Wei

2014-11-01

Purpose: The use of 4D computed tomography (4D-CT) of the lung is important in lung cancer radiotherapy for tumor localization and treatment planning. Sometimes, dense sampling is not acquired along the superior–inferior direction. This disadvantage results in an interslice thickness that is much greater than in-plane voxel resolutions. Isotropic resolution is necessary for multiplanar display, but the commonly used interpolation operation blurs images. This paper presents a super-resolution (SR) reconstruction method to enhance 4D-CT resolution. Methods: The authors assume that the low-resolution images of different phases at the same position can be regarded as input “frames” to reconstruct high-resolution images.more » The SR technique is used to recover high-resolution images. Specifically, the Demons deformable registration algorithm is used to estimate the motion field between different “frames.” Then, the projection onto convex sets approach is implemented to reconstruct high-resolution lung images. Results: The performance of the SR algorithm is evaluated using both simulated and real datasets. Their method can generate clearer lung images and enhance image structure compared with cubic spline interpolation and back projection (BP) method. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 40.8% relative to cubic spline interpolation and 10.2% versus BP. Conclusions: A new algorithm has been developed to improve the resolution of 4D-CT. The algorithm outperforms the cubic spline interpolation and BP approaches by producing images with markedly improved structural clarity and greatly reduced artifacts.« less

A Novel Azimuth Super-Resolution Method by Synthesizing Azimuth Bandwidth of Multiple Tracks of Airborne Stripmap SAR Data

PubMed Central

Wang, Yan; Li, Jingwen; Sun, Bing; Yang, Jian

2016-01-01

Azimuth resolution of airborne stripmap synthetic aperture radar (SAR) is restricted by the azimuth antenna size. Conventionally, a higher azimuth resolution should be achieved by employing alternate modes that steer the beam in azimuth to enlarge the synthetic antenna aperture. However, if a data set of a certain region, consisting of multiple tracks of airborne stripmap SAR data, is available, the azimuth resolution of specific small region of interest (ROI) can be conveniently improved by a novel azimuth super-resolution method as introduced by this paper. The proposed azimuth super-resolution method synthesize the azimuth bandwidth of the data selected from multiple discontinuous tracks and contributes to a magnifier-like function with which the ROI can be further zoomed in with a higher azimuth resolution than that of the original stripmap images. Detailed derivation of the azimuth super-resolution method, including the steps of two-dimensional dechirping, residual video phase (RVP) removal, data stitching and data correction, is provided. The restrictions of the proposed method are also discussed. Lastly, the presented approach is evaluated via both the single- and multi-target computer simulations. PMID:27304959

Super-resolution Time-Lapse Seismic Waveform Inversion

NASA Astrophysics Data System (ADS)

Ovcharenko, O.; Kazei, V.; Peter, D. B.; Alkhalifah, T.

2017-12-01

Time-lapse seismic waveform inversion is a technique, which allows tracking changes in the reservoirs over time. Such monitoring is relatively computationally extensive and therefore it is barely feasible to perform it on-the-fly. Most of the expenses are related to numerous FWI iterations at high temporal frequencies, which is inevitable since the low-frequency components can not resolve fine scale features of a velocity model. Inverted velocity changes are also blurred when there is noise in the data, so the problem of low-resolution images is widely known. One of the problems intensively tackled by computer vision research community is the recovering of high-resolution images having their low-resolution versions. Usage of artificial neural networks to reach super-resolution from a single downsampled image is one of the leading solutions for this problem. Each pixel of the upscaled image is affected by all the pixels of its low-resolution version, which enables the workflow to recover features that are likely to occur in the corresponding environment. In the present work, we adopt machine learning image enhancement technique to improve the resolution of time-lapse full-waveform inversion. We first invert the baseline model with conventional FWI. Then we run a few iterations of FWI on a set of the monitoring data to find desired model changes. These changes are blurred and we enhance their resolution by using a deep neural network. The network is trained to map low-resolution model updates predicted by FWI into the real perturbations of the baseline model. For supervised training of the network we generate a set of random perturbations in the baseline model and perform FWI on the noisy data from the perturbed models. We test the approach on a realistic perturbation of Marmousi II model and demonstrate that it outperforms conventional convolution-based deblurring techniques.

Gray-scale transform and evaluation for digital x-ray chest images on CRT monitor

NASA Astrophysics Data System (ADS)

Furukawa, Isao; Suzuki, Junji; Ono, Sadayasu; Kitamura, Masayuki; Ando, Yutaka

1997-04-01

In this paper, an experimental evaluation of a super high definition (SHD) imaging system for digital x-ray chest images is presented. The SHD imaging system is proposed as a platform for integrating conventional image media. We are involved in the use of SHD images in the total digitizing of medical records that include chest x-rays and pathological microscopic images, both which demand the highest level of quality among the various types of medical images. SHD images use progressive scanning and have a spatial resolution of 2000 by 2000 pixels or more and a temporal resolution (frame rate) of 60 frames/sec or more. For displaying medical x-ray images on a CRT, we derived gray scale transform characteristics based on radiologists' comments during the experiment, and elucidated the relationship between that gray scale transform and the linearization transform for maintaining the linear relationship with the luminance of film on a light box (luminance linear transform). We then carried out viewing experiments based on a five-stage evaluation. Nine radiologists participated in our experiment, and the ten cases evaluated included pulmonary fibrosis, lung cancer, and pneumonia. The experimental results indicated that conventional film images and those on super high definition CRT monitors have nearly the same quality. They also show that the gray scale transform for CRT images decided according to radiologists' comments agrees with the luminance linear transform in the high luminance region. And in the low luminance region, it was found that the gray scale transform had the characteristics of level expansion to increase the number of levels that can be expressed.

Low-cost, high-resolution scanning laser ophthalmoscope for the clinical environment

NASA Astrophysics Data System (ADS)

Soliz, P.; Larichev, A.; Zamora, G.; Murillo, S.; Barriga, E. S.

2010-02-01

Researchers have sought to gain greater insight into the mechanisms of the retina and the optic disc at high spatial resolutions that would enable the visualization of small structures such as photoreceptors and nerve fiber bundles. The sources of retinal image quality degradation are aberrations within the human eye, which limit the achievable resolution and the contrast of small image details. To overcome these fundamental limitations, researchers have been applying adaptive optics (AO) techniques to correct for the aberrations. Today, deformable mirror based adaptive optics devices have been developed to overcome the limitations of standard fundus cameras, but at prices that are typically unaffordable for most clinics. In this paper we demonstrate a clinically viable fundus camera with auto-focus and astigmatism correction that is easy to use and has improved resolution. We have shown that removal of low-order aberrations results in significantly better resolution and quality images. Additionally, through the application of image restoration and super-resolution techniques, the images present considerably improved quality. The improvements lead to enhanced visualization of retinal structures associated with pathology.

Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging.

PubMed

Hamaide, Julie; De Groof, Geert; Van Steenkiste, Gwendolyn; Jeurissen, Ben; Van Audekerke, Johan; Naeyaert, Maarten; Van Ruijssevelt, Lisbeth; Cornil, Charlotte; Sijbers, Jan; Verhoye, Marleen; Van der Linden, Annemie

2017-02-01

Zebra finches are an excellent model to study the process of vocal learning, a complex socially-learned tool of communication that forms the basis of spoken human language. So far, structural investigation of the zebra finch brain has been performed ex vivo using invasive methods such as histology. These methods are highly specific, however, they strongly interfere with performing whole-brain analyses and exclude longitudinal studies aimed at establishing causal correlations between neuroplastic events and specific behavioral performances. Therefore, the aim of the current study was to implement an in vivo Diffusion Tensor Imaging (DTI) protocol sensitive enough to detect structural sex differences in the adult zebra finch brain. Voxel-wise comparison of male and female DTI parameter maps shows clear differences in several components of the song control system (i.e. Area X surroundings, the high vocal center (HVC) and the lateral magnocellular nucleus of the anterior nidopallium (LMAN)), which corroborate previous findings and are in line with the clear behavioral difference as only males sing. Furthermore, to obtain additional insights into the 3-dimensional organization of the zebra finch brain and clarify findings obtained by the in vivo study, ex vivo DTI data of the male and female brain were acquired as well, using a recently established super-resolution reconstruction (SRR) imaging strategy. Interestingly, the SRR-DTI approach led to a marked reduction in acquisition time without interfering with the (spatial and angular) resolution and SNR which enabled to acquire a data set characterized by a 78μm isotropic resolution including 90 diffusion gradient directions within 44h of scanning time. Based on the reconstructed SRR-DTI maps, whole brain probabilistic Track Density Imaging (TDI) was performed for the purpose of super resolved track density imaging, further pushing the resolution up to 40μm isotropic. The DTI and TDI maps realized atlas-quality anatomical maps that enable a clear delineation of most components of the song control and auditory systems. In conclusion, this study paves the way for longitudinal in vivo and high-resolution ex vivo experiments aimed at disentangling neuroplastic events that characterize the critical period for vocal learning in zebra finch ontogeny. Copyright © 2016 Elsevier Inc. All rights reserved.

Super-resolution differential interference contrast microscopy by structured illumination.

PubMed

Chen, Jianling; Xu, Yan; Lv, Xiaohua; Lai, Xiaomin; Zeng, Shaoqun

2013-01-14

We propose a structured illumination differential interference contrast (SI-DIC) microscopy, breaking the diffraction resolution limit of differential interference contrast (DIC) microscopy. SI-DIC extends the bandwidth of coherent transfer function of the DIC imaging system, thus the resolution is improved. With 0.8 numerical aperture condenser and objective, the reconstructed SI-DIC image of 53 nm polystyrene beads reveals lateral resolution of approximately 190 nm, doubling that of the conventional DIC image. We also demonstrate biological observations of label-free cells with improved spatial resolution. The SI-DIC microscopy can provide sub-diffraction resolution and high contrast images with marker-free specimens, and has the potential for achieving sub-diffraction resolution quantitative phase imaging.

Single Fluorescent Molecules as Nano-Illuminators for Biological Structure and Function

NASA Astrophysics Data System (ADS)

Moerner, W. E.

2011-03-01

Since the first optical detection and spectroscopy of a single molecule in a solid (Phys. Rev. Lett. {62}, 2535 (1989)), much has been learned about the ability of single molecules to probe local nanoenvironments and individual behavior in biological and nonbiological materials in the absence of ensemble averaging that can obscure heterogeneity. Because each single fluorophore acts a light source roughly 1 nm in size, microscopic imaging of individual fluorophores leads naturally to superlocalization, or determination of the position of the molecule with precision beyond the optical diffraction limit, simply by digitization of the point-spread function from the single emitter. For example, the shape of single filaments in a living cell can be extracted simply by allowing a single molecule to move through the filament (PNAS {103}, 10929 (2006)). The addition of photoinduced control of single-molecule emission allows imaging beyond the diffraction limit (super-resolution) and a new array of acronyms (PALM, STORM, F-PALM etc.) and advances have appeared. We have used the native blinking and switching of a common yellow-emitting variant of green fluorescent protein (EYFP) reported more than a decade ago (Nature {388}, 355 (1997)) to achieve sub-40 nm super-resolution imaging of several protein structures in the bacterium Caulobacter crescentus: the quasi-helix of the actin-like protein MreB (Nat. Meth. {5}, 947 (2008)), the cellular distribution of the DNA binding protein HU (submitted), and the recently discovered division spindle composed of ParA filaments (Nat. Cell Biol. {12}, 791 (2010)). Even with these advances, better emitters would provide more photons and improved resolution, and a new photoactivatable small-molecule emitter has recently been synthesized and targeted to specific structures in living cells to provide super-resolution images (JACS {132}, 15099 (2010)). Finally, a new optical method for extracting three-dimensional position information based on a double-helix point spread function enables quantitative tracking of single mRNA particles in living yeast cells with 15 ms time resolution and 25-50 nm spatial precision (PNAS {107}, 17864 (2010)). These examples illustrate the power of single-molecule optical imaging in extracting new structural and functional information in living cells.

Image super-resolution via adaptive filtering and regularization

NASA Astrophysics Data System (ADS)

Ren, Jingbo; Wu, Hao; Dong, Weisheng; Shi, Guangming

2014-11-01

Image super-resolution (SR) is widely used in the fields of civil and military, especially for the low-resolution remote sensing images limited by the sensor. Single-image SR refers to the task of restoring a high-resolution (HR) image from the low-resolution image coupled with some prior knowledge as a regularization term. One classic method regularizes image by total variation (TV) and/or wavelet or some other transform which introduce some artifacts. To compress these shortages, a new framework for single image SR is proposed by utilizing an adaptive filter before regularization. The key of our model is that the adaptive filter is used to remove the spatial relevance among pixels first and then only the high frequency (HF) part, which is sparser in TV and transform domain, is considered as the regularization term. Concretely, through transforming the original model, the SR question can be solved by two alternate iteration sub-problems. Before each iteration, the adaptive filter should be updated to estimate the initial HF. A high quality HF part and HR image can be obtained by solving the first and second sub-problem, respectively. In experimental part, a set of remote sensing images captured by Landsat satellites are tested to demonstrate the effectiveness of the proposed framework. Experimental results show the outstanding performance of the proposed method in quantitative evaluation and visual fidelity compared with the state-of-the-art methods.

Portable microscopy platform for the clinical and environmental monitoring

NASA Astrophysics Data System (ADS)

Wang, Weiming; Yu, Yan; Huang, Hui; Ou, Jinping

2016-04-01

Light microscopy can not only address various diagnosis needs such as aquatic parasites and bacteria such as E. coli in water, but also provide a method for the screening of red tide. Traditional microscope based on the smartphone created by adding lens couldn't keep the tradeoff between field-of-view(FOV) and the resolution. In this paper, we demonstrate a non-contact, light and cost-effective microscope platform, that can image highly dense samples with a spatial resolution of ~0.8um over a field-of-view(FOV) of >1mm2. After captured the direct images, we performed the pixel super-resolution algorithm to improve the image resolution and overcome the hardware interference. The system would be a good point-of-care diagnostic solution in resource limited settings. We validated the performance of the system by imaging resolution test targets, the squamous cell cancer(SqCC) and green algae that necessary to detect the squamous carcinoma and red tide

Improved axial resolution of FINCH fluorescence microscopy when combined with spinning disk confocal microscopy.

PubMed

Siegel, Nisan; Brooker, Gary

2014-09-22

FINCH holographic fluorescence microscopy creates super-resolved images with enhanced depth of focus. Addition of a Nipkow disk real-time confocal image scanner is shown to reduce the FINCH depth of focus while improving transverse confocal resolution in a combined method called "CINCH".

Three-dimensional refractive index and fluorescence tomography using structured illumination (Conference Presentation)

NASA Astrophysics Data System (ADS)

Park, GwangSik; Shin, SeungWoo; Kim, Kyoohyun; Park, YongKeun

2017-02-01

Optical diffraction tomography (ODT) has been an emerging optical technique for label-free imaging of three-dimensional (3-D) refractive index (RI) distribution of biological samples. ODT employs interferometric microscopy for measuring multiple holograms of samples with various incident angles, from which the Fourier diffraction theorem reconstructs the 3-D RI distribution of samples from retrieved complex optical fields. Since the RI value is linearly proportional to the protein concentration of biological samples where the proportional coefficient is called as refractive index increment (RII), reconstructed 3-D RI tomograms provide precise structural and biochemical information of individual biological samples. Because most proteins have similar RII value, however, ODT has limited molecular specificity, especially for imaging eukaryotic cells having various types of proteins and subcellular organelles. Here, we present an ODT system combined with structured illumination microscopy which can measure the 3-D RI distribution of biological samples as well as 3-D super-resolution fluorescent images in the same optical setup. A digital micromirror device (DMD) controls the incident angle of the illumination beam for tomogram reconstruction, and the same DMD modulates the structured illumination pattern of the excitation beam for super-resolution fluorescent imaging. We first validate the proposed method for simultaneous optical diffraction tomographic imaging and super-resolution fluorescent imaging of fluorescent beads. The proposed method is also exploited for various biological samples.

Super Typhoon Halong off Taiwan

NASA Technical Reports Server (NTRS)

2002-01-01

On July 14, 2002, Super Typhoon Halong was east of Taiwan (left edge) in the western Pacific Ocean. At the time this image was taken the storm was a Category 4 hurricane, with maximum sustained winds of 115 knots (132 miles per hour), but as recently as July 12, winds were at 135 knots (155 miles per hour). Halong has moved northwards and pounded Okinawa, Japan, with heavy rain and high winds, just days after tropical Storm Chataan hit the country, creating flooding and killing several people. The storm is expected to be a continuing threat on Monday and Tuesday. This image was acquired by the Moderate Resolution Imaging Spectroradiometer (MODIS) on the Terra satellite on July 14, 2002. Please note that the high-resolution scene provided here is 500 meters per pixel. For a copy of the scene at the sensor's fullest resolution, visit the MODIS Rapid Response Image Gallery. Image courtesy Jacques Descloitres, MODIS Land Rapid Response Team at NASA GSFC

Enhanced simulator software for image validation and interpretation for multimodal localization super-resolution fluorescence microscopy

NASA Astrophysics Data System (ADS)

Erdélyi, Miklós; Sinkó, József; Gajdos, Tamás.; Novák, Tibor

2017-02-01

Optical super-resolution techniques such as single molecule localization have become one of the most dynamically developed areas in optical microscopy. These techniques routinely provide images of fixed cells or tissues with sub-diffraction spatial resolution, and can even be applied for live cell imaging under appropriate circumstances. Localization techniques are based on the precise fitting of the point spread functions (PSF) to the measured images of stochastically excited, identical fluorescent molecules. These techniques require controlling the rate between the on, off and the bleached states, keeping the number of active fluorescent molecules at an optimum value, so their diffraction limited images can be detected separately both spatially and temporally. Because of the numerous (and sometimes unknown) parameters, the imaging system can only be handled stochastically. For example, the rotation of the dye molecules obscures the polarization dependent PSF shape, and only an averaged distribution - typically estimated by a Gaussian function - is observed. TestSTORM software was developed to generate image stacks for traditional localization microscopes, where localization meant the precise determination of the spatial position of the molecules. However, additional optical properties (polarization, spectra, etc.) of the emitted photons can be used for further monitoring the chemical and physical properties (viscosity, pH, etc.) of the local environment. The image stack generating program was upgraded by several new features, such as: multicolour, polarization dependent PSF, built-in 3D visualization, structured background. These features make the program an ideal tool for optimizing the imaging and sample preparation conditions.

Super-resolution atomic force photoactivated microscopy of biological samples (Conference Presentation)

NASA Astrophysics Data System (ADS)

Lee, Seunghyun; Kim, Hyemin; Shin, Seungjun; Doh, Junsang; Kim, Chulhong

2017-03-01

Optical microscopy (OM) and photoacoustic microscopy (PAM) have previously been used to image the optical absorption of intercellular features of biological cells. However, the optical diffraction limit ( 200 nm) makes it difficult for these modalities to image nanoscale inner cell structures and the distribution of internal cell components. Although super-resolution fluorescence microscopy, such as stimulated emission depletion microscopy (STED) and stochastic optical reconstruction microscopy (STORM), has successfully performed nanoscale biological imaging, these modalities require the use of exogenous fluorescence agents, which are unfavorable for biological samples. Our newly developed atomic force photoactivated microscopy (AFPM) can provide optical absorption images with nanoscale lateral resolution without any exogenous contrast agents. AFPM combines conventional atomic force microscopy (AFM) and an optical excitation system, and simultaneously provides multiple contrasts, such as the topography and magnitude of optical absorption. AFPM can detect the intrinsic optical absorption of samples with 8 nm lateral resolution, easily overcoming the diffraction limit. Using the label-free AFPM system, we have successfully imaged the optical absorption properties of a single melanoma cell (B16F10) and a rosette leaf epidermal cell of Arabidopsis (ecotype Columbia (Col-0)) with nanoscale lateral resolution. The remarkable images show the melanosome distribution of a melanoma cell and the biological structures of a plant cell. AFPM provides superior imaging of optical absorption with a nanoscale lateral resolution, and it promises to become widely used in biological and chemical research.

Distinguishing one from many using super-resolution compressive sensing

DOE Office of Scientific and Technical Information (OSTI.GOV)

Anthony, Stephen Michael; Mulcahy-Stanislawczyk, Johnathan; Shields, Eric A.

We present that distinguishing whether a signal corresponds to a single source or a limited number of highly overlapping point spread functions (PSFs) is a ubiquitous problem across all imaging scales, whether detecting receptor-ligand interactions in cells or detecting binary stars. Super-resolution imaging based upon compressed sensing exploits the relative sparseness of the point sources to successfully resolve sources which may be separated by much less than the Rayleigh criterion. However, as a solution to an underdetermined system of linear equations, compressive sensing requires the imposition of constraints which may not always be valid. One typical constraint is that themore » PSF is known. However, the PSF of the actual optical system may reflect aberrations not present in the theoretical ideal optical system. Even when the optics are well characterized, the actual PSF may reflect factors such as non-uniform emission of the point source (e.g. fluorophore dipole emission). As such, the actual PSF may differ from the PSF used as a constraint. Similarly, multiple different regularization constraints have been suggested including the l 1-norm, l 0-norm, and generalized Gaussian Markov random fields (GGMRFs), each of which imposes a different constraint. Other important factors include the signal-to-noise ratio of the point sources and whether the point sources vary in intensity. In this work, we explore how these factors influence super-resolution image recovery robustness, determining the sensitivity and specificity. In conclusion, we determine an approach that is more robust to the types of PSF errors present in actual optical systems.« less

Distinguishing one from many using super-resolution compressive sensing

DOE PAGES

Anthony, Stephen Michael; Mulcahy-Stanislawczyk, Johnathan; Shields, Eric A.; ...

2018-05-14

We present that distinguishing whether a signal corresponds to a single source or a limited number of highly overlapping point spread functions (PSFs) is a ubiquitous problem across all imaging scales, whether detecting receptor-ligand interactions in cells or detecting binary stars. Super-resolution imaging based upon compressed sensing exploits the relative sparseness of the point sources to successfully resolve sources which may be separated by much less than the Rayleigh criterion. However, as a solution to an underdetermined system of linear equations, compressive sensing requires the imposition of constraints which may not always be valid. One typical constraint is that themore » PSF is known. However, the PSF of the actual optical system may reflect aberrations not present in the theoretical ideal optical system. Even when the optics are well characterized, the actual PSF may reflect factors such as non-uniform emission of the point source (e.g. fluorophore dipole emission). As such, the actual PSF may differ from the PSF used as a constraint. Similarly, multiple different regularization constraints have been suggested including the l 1-norm, l 0-norm, and generalized Gaussian Markov random fields (GGMRFs), each of which imposes a different constraint. Other important factors include the signal-to-noise ratio of the point sources and whether the point sources vary in intensity. In this work, we explore how these factors influence super-resolution image recovery robustness, determining the sensitivity and specificity. In conclusion, we determine an approach that is more robust to the types of PSF errors present in actual optical systems.« less

Super-Resolution Microscopy Techniques and Their Potential for Applications in Radiation Biophysics.

PubMed

Eberle, Jan Philipp; Rapp, Alexander; Krufczik, Matthias; Eryilmaz, Marion; Gunkel, Manuel; Erfle, Holger; Hausmann, Michael

2017-01-01

Fluorescence microscopy is an essential tool for imaging tagged biological structures. Due to the wave nature of light, the resolution of a conventional fluorescence microscope is limited laterally to about 200 nm and axially to about 600 nm, which is often referred to as the Abbe limit. This hampers the observation of important biological structures and dynamics in the nano-scaled range ~10 nm to ~100 nm. Consequentially, various methods have been developed circumventing this limit of resolution. Super-resolution microscopy comprises several of those methods employing physical and/or chemical properties, such as optical/instrumental modifications and specific labeling of samples. In this article, we will give a brief insight into a variety of selected optical microscopy methods reaching super-resolution beyond the Abbe limit. We will survey three different concepts in connection to biological applications in radiation research without making a claim to be complete.

Optical super-resolution effect induced by nonlinear characteristics of graphene oxide films

NASA Astrophysics Data System (ADS)

Zhao, Yong-chuang; Nie, Zhong-quan; Zhai, Ai-ping; Tian, Yan-ting; Liu, Chao; Shi, Chang-kun; Jia, Bao-hua

2018-01-01

In this work, we focus on the optical super-resolution effect induced by strong nonlinear saturation absorption (NSA) of graphene oxide (GO) membranes. The third-order optical nonlinearities are characterized by the canonical Z-scan technique under femtosecond laser (wavelength: 800 nm, pulse width: 100 fs) excitation. Through controlling the applied femtosecond laser energy, NSA of the GO films can be tuned continuously. The GO film is placed at the focal plane as a unique amplitude filter to improve the resolution of the focused field. A multi-layer system model is proposed to present the generation of a deep sub-wavelength spot associated with the nonlinearity of GO films. Moreover, the parameter conditions to achieve the best resolution (˜λ/6) are determined entirely. The demonstrated results here are useful for high density optical recoding and storage, nanolithography, and super-resolution optical imaging.

Common fluorescent proteins for single-molecule localization microscopy

NASA Astrophysics Data System (ADS)

Klementieva, Natalia V.; Bozhanova, Nina G.; Mishina, Natalie M.; Zagaynova, Elena V.; Lukyanov, Konstantin A.; Mishin, Alexander S.

2015-07-01

Super-resolution techniques for breaking the diffraction barrier are spread out over multiple studies nowadays. Single-molecule localization microscopy such as PALM, STORM, GSDIM, etc allow to get super-resolved images of cell ultrastructure by precise localization of individual fluorescent molecules via their temporal isolation. However, these methods are supposed the use of fluorescent dyes and proteins with special characteristics (photoactivation/photoconversion). At the same time, there is a need for retaining high photostability of fluorophores during long-term acquisition. Here, we first showed the potential of common red fluorescent protein for single-molecule localization microscopy based on spontaneous intrinsic blinking. Also, we assessed the effect of different imaging media on photobleaching of these fluorescent proteins. Monomeric orange and red fluorescent proteins were examined for stochastic switching from a dark state to a bright fluorescent state. We studied fusions with cytoskeletal proteins in NIH/3T3 and HeLa cells. Imaging was performed on the Nikon N-STORM system equipped with EMCCD camera. To define the optimal imaging conditions we tested several types of cell culture media and buffers. As a result, high-resolution images of cytoskeleton structure were obtained. Essentially, low-intensity light was sufficient to initiate the switching of tested red fluorescent protein reducing phototoxicity and provide long-term live-cell imaging.

Image quality assessment for selfies with and without super resolution

NASA Astrophysics Data System (ADS)

Kubota, Aya; Gohshi, Seiichi

2018-04-01

With the advent of cellphone cameras, in particular, on smartphones, many people now take photos of themselves alone and with others in the frame; such photos are popularly known as "selfies". Most smartphones are equipped with two cameras: the front-facing and rear cameras. The camera located on the back of the smartphone is referred to as the "out-camera," whereas the one located on the front of the smartphone is called the "in-camera." In-cameras are mainly used for selfies. Some smartphones feature high-resolution cameras. However, the original image quality cannot be obtained because smartphone cameras often have low-performance lenses. Super resolution (SR) is one of the recent technological advancements that has increased image resolution. We developed a new SR technology that can be processed on smartphones. Smartphones with new SR technology are currently available in the market have already registered sales. However, the effective use of new SR technology has not yet been verified. Comparing the image quality with and without SR on smartphone display is necessary to confirm the usefulness of this new technology. Methods that are based on objective and subjective assessments are required to quantitatively measure image quality. It is known that the typical object assessment value, such as Peak Signal to Noise Ratio (PSNR), does not go together with how we feel when we assess image/video. When digital broadcast started, the standard was determined using subjective assessment. Although subjective assessment usually comes at high cost because of personnel expenses for observers, the results are highly reproducible when they are conducted under right conditions and statistical analysis. In this study, the subjective assessment results for selfie images are reported.

Details of Layers in Victoria Crater's Cape St. Vincent

NASA Technical Reports Server (NTRS)

2007-01-01

NASA's Mars Exploration Rover Opportunity rover spent about 300 sols (Martian days) during 2006 and 2007 traversing the rim of Victoria Crater. Besides looking for a good place to enter the crater, the rover obtained images of rock outcrops exposed at several cliffs along the way.

The cliff in this image from Opportunity's panoramic camera (Pancam) is informally named Cape St. Vincent. It is a promontory approximately 12 meters (39 feet) tall on the northern rim of Victoria crater, near the farthest point along the rover's traverse around the rim. Layers seen in Cape St. Vincent have proven to be among the best examples of meter scale cross-bedding observed on Mars to date. Cross-bedding is a geologic term for rock layers which are inclined relative to the horizontal and which are indicative of ancient sand dune deposits. In order to get a better look at these outcrops, Pancam 'super-resolution' imaging techniques were utilized. Super-resolution is a type of imaging mode which acquires many pictures of the same target to reconstruct a digital image at a higher resolution than is native to the camera. These super-resolution images have allowed scientists to discern that the rocks at Victoria Crater once represented a large dune field, not unlike the Sahara desert on Earth, and that this dune field migrated with an ancient wind flowing from the north to the south across the region. Other rover chemical and mineral measurements have shown that many of the ancient sand dunes studied in Meridiani Planum were modified by surface and subsurface liquid water long ago.

This is a Mars Exploration Rover Opportunity Panoramic Camera image acquired on sol 1167 (May 7, 2007), and was constructed from a mathematical combination of 16 different blue filter (480 nm) images.

A smartphone-based chip-scale microscope using ambient illumination.

PubMed

Lee, Seung Ah; Yang, Changhuei

2014-08-21

Portable chip-scale microscopy devices can potentially address various imaging needs in mobile healthcare and environmental monitoring. Here, we demonstrate the adaptation of a smartphone's camera to function as a compact lensless microscope. Unlike other chip-scale microscopy schemes, this method uses ambient illumination as its light source and does not require the incorporation of a dedicated light source. The method is based on the shadow imaging technique where the sample is placed on the surface of the image sensor, which captures direct shadow images under illumination. To improve the image resolution beyond the pixel size, we perform pixel super-resolution reconstruction with multiple images at different angles of illumination, which are captured while the user is manually tilting the device around any ambient light source, such as the sun or a lamp. The lensless imaging scheme allows for sub-micron resolution imaging over an ultra-wide field-of-view (FOV). Image acquisition and reconstruction are performed on the device using a custom-built Android application, constructing a stand-alone imaging device for field applications. We discuss the construction of the device using a commercial smartphone and demonstrate the imaging capabilities of our system.

A smartphone-based chip-scale microscope using ambient illumination

PubMed Central

Lee, Seung Ah; Yang, Changhuei

2014-01-01

Portable chip-scale microscopy devices can potentially address various imaging needs in mobile healthcare and environmental monitoring. Here, we demonstrate the adaptation of a smartphone’s camera to function as a compact lensless microscope. Unlike other chip-scale microscopy schemes, this method uses ambient illumination as its light source and does not require the incorporation of a dedicated light source. The method is based on the shadow imaging technique where the sample is placed on the surface of the image sensor, which captures direct shadow images under illumination. To improve the imaging resolution beyond the pixel size, we perform pixel super-resolution reconstruction with multiple images at different angles of illumination, which are captured while the user is manually tilting the device around any ambient light source, such as the sun or a lamp. The lensless imaging scheme allows for sub-micron resolution imaging over an ultra-wide field-of-view (FOV). Image acquisition and reconstruction is performed on the device using a custom-built android application, constructing a stand-alone imaging device for field applications. We discuss the construction of the device using a commercial smartphone and demonstrate the imaging capabilities of our system. PMID:24964209

Comparison of two structured illumination techniques based on different 3D illumination patterns

NASA Astrophysics Data System (ADS)

Shabani, H.; Patwary, N.; Doblas, A.; Saavedra, G.; Preza, C.

2017-02-01

Manipulating the excitation pattern in optical microscopy has led to several super-resolution techniques. Among different patterns, the lateral sinusoidal excitation was used for the first demonstration of structured illumination microscopy (SIM), which provides the fastest SIM acquisition system (based on the number of raw images required) compared to the multi-spot illumination approach. Moreover, 3D patterns that include lateral and axial variations in the illumination have attracted more attention recently as they address resolution enhancement in three dimensions. A threewave (3W) interference technique based on coherent illumination has already been shown to provide super-resolution and optical sectioning in 3D-SIM. In this paper, we investigate a novel tunable technique that creates a 3D pattern from a set of multiple incoherently illuminated parallel slits that act as light sources for a Fresnel biprism. This setup is able to modulate the illumination pattern in the object space both axially and laterally with adjustable modulation frequencies. The 3D forward model for the new system is developed here to consider the effect of the axial modulation due to the 3D patterned illumination. The performance of 3D-SIM based on 3W interference and the tunable system are investigated in simulation and compared based on two different criteria. First, restored images obtained for both 3D-SIM systems using a generalized Wiener filter are compared to determine the effect of the illumination pattern on the reconstruction. Second, the effective frequency response of both systems is studied to determine the axial and lateral resolution enhancement that is obtained in each case.

Development of targeted STORM for super resolution imaging of biological samples using digital micro-mirror device

NASA Astrophysics Data System (ADS)

Valiya Peedikakkal, Liyana; Steventon, Victoria; Furley, Andrew; Cadby, Ashley J.

2017-12-01

We demonstrate a simple illumination system based on a digital mirror device which allows for fine control over the power and pattern of illumination. We apply this to localization microscopy (LM), specifically stochastic optical reconstruction microscopy (STORM). Using this targeted STORM, we were able to image a selected area of a labelled cell without causing photo-damage to the surrounding areas of the cell.

Single image super resolution algorithm based on edge interpolation in NSCT domain

NASA Astrophysics Data System (ADS)

Zhang, Mengqun; Zhang, Wei; He, Xinyu

2017-11-01

In order to preserve the texture and edge information and to improve the space resolution of single frame, a superresolution algorithm based on Contourlet (NSCT) is proposed. The original low resolution image is transformed by NSCT, and the directional sub-band coefficients of the transform domain are obtained. According to the scale factor, the high frequency sub-band coefficients are amplified by the interpolation method based on the edge direction to the desired resolution. For high frequency sub-band coefficients with noise and weak targets, Bayesian shrinkage is used to calculate the threshold value. The coefficients below the threshold are determined by the correlation among the sub-bands of the same scale to determine whether it is noise and de-noising. The anisotropic diffusion filter is used to effectively enhance the weak target in the low contrast region of the target and background. Finally, the high-frequency sub-band is amplified by the bilinear interpolation method to the desired resolution, and then combined with the high-frequency subband coefficients after de-noising and small target enhancement, the NSCT inverse transform is used to obtain the desired resolution image. In order to verify the effectiveness of the proposed algorithm, the proposed algorithm and several common image reconstruction methods are used to test the synthetic image, motion blurred image and hyperspectral image, the experimental results show that compared with the traditional single resolution algorithm, the proposed algorithm can obtain smooth edges and good texture features, and the reconstructed image structure is well preserved and the noise is suppressed to some extent.

Structure-aware depth super-resolution using Gaussian mixture model

NASA Astrophysics Data System (ADS)

Kim, Sunok; Oh, Changjae; Kim, Youngjung; Sohn, Kwanghoon

2015-03-01

This paper presents a probabilistic optimization approach to enhance the resolution of a depth map. Conventionally, a high-resolution color image is considered as a cue for depth super-resolution under the assumption that the pixels with similar color likely belong to similar depth. This assumption might induce a texture transferring from the color image into the depth map and an edge blurring artifact to the depth boundaries. In order to alleviate these problems, we propose an efficient depth prior exploiting a Gaussian mixture model in which an estimated depth map is considered to a feature for computing affinity between two pixels. Furthermore, a fixed-point iteration scheme is adopted to address the non-linearity of a constraint derived from the proposed prior. The experimental results show that the proposed method outperforms state-of-the-art methods both quantitatively and qualitatively.

Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution.

PubMed

Hsieh, Sheng-Hsun; Li, Yung-Hui; Tien, Chung-Hao; Chang, Chin-Chen

2016-12-01

Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system's high recognition rate.

Building block extraction and classification by means of aerial images fused with super-resolution reconstructed elevation data

NASA Astrophysics Data System (ADS)

Panagiotopoulou, Antigoni; Bratsolis, Emmanuel; Charou, Eleni; Perantonis, Stavros

2017-10-01

The detailed three-dimensional modeling of buildings utilizing elevation data, such as those provided by light detection and ranging (LiDAR) airborne scanners, is increasingly demanded today. There are certain application requirements and available datasets to which any research effort has to be adapted. Our dataset includes aerial orthophotos, with a spatial resolution 20 cm, and a digital surface model generated from LiDAR, with a spatial resolution 1 m and an elevation resolution 20 cm, from an area of Athens, Greece. The aerial images are fused with LiDAR, and we classify these data with a multilayer feedforward neural network for building block extraction. The innovation of our approach lies in the preprocessing step in which the original LiDAR data are super-resolution (SR) reconstructed by means of a stochastic regularized technique before their fusion with the aerial images takes place. The Lorentzian estimator combined with the bilateral total variation regularization performs the SR reconstruction. We evaluate the performance of our approach against that of fusing unprocessed LiDAR data with aerial images. We present the classified images and the statistical measures confusion matrix, kappa coefficient, and overall accuracy. The results demonstrate that our approach predominates over that of fusing unprocessed LiDAR data with aerial images.

Comparing the imaging performance of computed super resolution and magnification tomosynthesis

NASA Astrophysics Data System (ADS)

Maidment, Tristan D.; Vent, Trevor L.; Ferris, William S.; Wurtele, David E.; Acciavatti, Raymond J.; Maidment, Andrew D. A.

2017-03-01

Computed super-resolution (SR) is a method of reconstructing images with pixels that are smaller than the detector element size; superior spatial resolution is achieved through the elimination of aliasing and alteration of the sampling function imposed by the reconstructed pixel aperture. By comparison, magnification mammography is a method of projection imaging that uses geometric magnification to increase spatial resolution. This study explores the development and application of magnification digital breast tomosynthesis (MDBT). Four different acquisition geometries are compared in terms of various image metrics. High-contrast spatial resolution was measured in various axes using a lead star pattern. A modified Defrise phantom was used to determine the low-frequency spatial resolution. An anthropomorphic phantom was used to simulate clinical imaging. Each experiment was conducted at three different magnifications: contact (1.04x), MAG1 (1.3x), and MAG2 (1.6x). All images were taken on our next generation tomosynthesis system, an in-house solution designed to optimize SR. It is demonstrated that both computed SR and MDBT (MAG1 and MAG2) provide improved spatial resolution over non-SR contact imaging. To achieve the highest resolution, SR and MDBT should be combined. However, MDBT is adversely affected by patient motion at higher magnifications. In addition, MDBT requires more radiation dose and delays diagnosis, since MDBT would be conducted upon recall. By comparison, SR can be conducted with the original screening data. In conclusion, this study demonstrates that computed SR and MDBT are both viable methods of imaging the breast.

Discovery of Super-Thin Disks in Nearby Edge-on Spiral Galaxies

NASA Astrophysics Data System (ADS)

Schechtman-Rook, A.; Bershady, M. A.

2014-03-01

We report the identification of a super-thin disk (hz˜ 60 pc) in the edge-on spiral galaxy NGC 891. This component is only apparent after we perform a physically motivated attenuation correction, based on detailed radiation transfer models, to our sub-arcsecond resolution near-infrared imaging. In addition to the super-thin disk, we also find several structural features near the center of NGC 891, including an inner disk truncation at ˜3 kpc. Inner disk truncations may be commonplace among massive spiral galaxies, possibly due to the effects of instabilities, such as bars. Having successfully demonstrated our methods, we are poised to apply them to a small sample of nearby edge-on galaxies, consisting both of massive and low-mass spirals.

Statistical Limits to Super Resolution

NASA Astrophysics Data System (ADS)

Lucy, L. B.

1992-08-01

The limits imposed by photon statistics on the degree to which Rayleigh's resolution limit for diffraction-limited images can be surpassed by applying image restoration techniques are investigated. An approximate statistical theory is given for the number of detected photons required in the image of an unresolved pair of equal point sources in order that its information content allows in principle resolution by restoration. This theory is confirmed by numerical restoration experiments on synthetic images, and quantitative limits are presented for restoration of diffraction-limited images formed by slit and circular apertures.

Multi-color localization microscopy of fixed cells as a promising tool to study organization of bacterial cytoskeleton

NASA Astrophysics Data System (ADS)

Vedyaykin, A. D.; Gorbunov, V. V.; Sabantsev, A. V.; Polinovskaya, V. S.; Vishnyakov, I. E.; Melnikov, A. S.; Serdobintsev, P. Yu; Khodorkovskii, M. A.

2015-11-01

Localization microscopy allows visualization of biological structures with resolution well below the diffraction limit. Localization microscopy was used to study FtsZ organization in Escherichia coli previously in combination with fluorescent protein labeling, but the fact that fluorescent chimeric protein was unable to rescue temperature-sensitive ftsZ mutants suggests that obtained images may not represent native FtsZ structures faithfully. Indirect immunolabeling of FtsZ not only overcomes this problem, but also allows the use of the powerful visualization methods arsenal available for different structures in fixed cells. In this work we simultaneously obtained super-resolution images of FtsZ structures and diffraction-limited or super-resolution images of DNA and cell surface in E. coli, which allows for the study of the spatial arrangement of FtsZ structures with respect to the nucleoid positions and septum formation.

The formation of quantum images and their transformation and super-resolution reading

NASA Astrophysics Data System (ADS)

Balakin, D. A.; Belinsky, A. V.

2016-05-01

Images formed by light with suppressed photon fluctuations are interesting objects for studies with the aim of increasing their limiting information capacity and quality. This light in the sub-Poisson state can be prepared in a resonator filled with a medium with Kerr nonlinearity, in which self-phase modulation takes place. Spatially and temporally multimode light beams are studied and the production of spatial frequency spectra of suppressed photon fluctuations is described. The efficient operation regimes of the system are found. A particular schematic solution is described, which allows one to realize the potential possibilities laid in the formation of the squeezed states of light to a maximum degree during self-phase modulation in a resonator for the maximal suppression of amplitude quantum noises upon two-dimensional imaging. The efficiency of using light with suppressed quantum fluctuations for computer image processing is studied. An algorithm is described for interpreting measurements for increasing the resolution with respect to the geometrical resolution. A mathematical model that characterizes the measurement scheme is constructed and the problem of the image reconstruction is solved. The algorithm for the interpretation of images is verified. Conditions are found for the efficient application of sub-Poisson light for super-resolution imaging. It is found that the image should have a low contrast and be maximally transparent.

Improved axial resolution of FINCH fluorescence microscopy when combined with spinning disk confocal microscopy

PubMed Central

Siegel, Nisan; Brooker, Gary

2014-01-01

FINCH holographic fluorescence microscopy creates super-resolved images with enhanced depth of focus. Addition of a Nipkow disk real-time confocal image scanner is shown to reduce the FINCH depth of focus while improving transverse confocal resolution in a combined method called “CINCH”. PMID:25321701

Prospects of third-generation femtosecond laser technology in biological spectromicroscopy

NASA Astrophysics Data System (ADS)

Fattahi, Hanieh; Fattahi, Zohreh; Ghorbani, Asghar

2018-05-01

The next generation of biological imaging modalities will be a movement towards super-resolution, label-free approaches to realize subcellular images in a nonperturbative, non-invasive manner and towards new detection metrologies to reach a higher sensitivity and dynamic range. In this paper, we discuss how the third generation femtosecond laser technology in combination with the already existing concepts in time-resolved spectroscopy could fulfill the requirements of these exciting prospects. The expected enhanced specificity and sensitivity of the envisioned super-resolution microscope could lead us to a better understanding of the inter- and intra-cellular molecular transport and DNA-protein interaction.

Computational microscopy: illumination coding and nonlinear optimization enables gigapixel 3D phase imaging

NASA Astrophysics Data System (ADS)

Tian, Lei; Waller, Laura

2017-05-01

Microscope lenses can have either large field of view (FOV) or high resolution, not both. Computational microscopy based on illumination coding circumvents this limit by fusing images from different illumination angles using nonlinear optimization algorithms. The result is a Gigapixel-scale image having both wide FOV and high resolution. We demonstrate an experimentally robust reconstruction algorithm based on a 2nd order quasi-Newton's method, combined with a novel phase initialization scheme. To further extend the Gigapixel imaging capability to 3D, we develop a reconstruction method to process the 4D light field measurements from sequential illumination scanning. The algorithm is based on a 'multislice' forward model that incorporates both 3D phase and diffraction effects, as well as multiple forward scatterings. To solve the inverse problem, an iterative update procedure that combines both phase retrieval and 'error back-propagation' is developed. To avoid local minimum solutions, we further develop a novel physical model-based initialization technique that accounts for both the geometric-optic and 1st order phase effects. The result is robust reconstructions of Gigapixel 3D phase images having both wide FOV and super resolution in all three dimensions. Experimental results from an LED array microscope were demonstrated.

Near-field examination of perovskite-based superlenses and superlens-enhanced probe-object coupling.

PubMed

Kehr, S C; Liu, Y M; Martin, L W; Yu, P; Gajek, M; Yang, S-Y; Yang, C-H; Wenzel, M T; Jacob, R; von Ribbeck, H-G; Helm, M; Zhang, X; Eng, L M; Ramesh, R

2011-01-01

A planar slab of negative-index material works as a superlens with sub-diffraction-limited resolution, as propagating waves are focused and, moreover, evanescent waves are reconstructed in the image plane. Here we demonstrate a superlens for electric evanescent fields with low losses using perovskites in the mid-infrared regime. The combination of near-field microscopy with a tunable free-electron laser allows us to address precisely the polariton modes, which are critical for super-resolution imaging. We spectrally study the lateral and vertical distributions of evanescent waves around the image plane of such a lens, and achieve imaging resolution of λ/14 at the superlensing wavelength. Interestingly, at certain distances between the probe and sample surface, we observe a maximum of these evanescent fields. Comparisons with numerical simulations indicate that this maximum originates from an enhanced coupling between probe and object, which might be applicable for multifunctional circuits, infrared spectroscopy and thermal sensors.

Single Anisotropic 3-D MR Image Upsampling via Overcomplete Dictionary Trained From In-Plane High Resolution Slices.

PubMed

Jia, Yuanyuan; He, Zhongshi; Gholipour, Ali; Warfield, Simon K

2016-11-01

In magnetic resonance (MR), hardware limitation, scanning time, and patient comfort often result in the acquisition of anisotropic 3-D MR images. Enhancing image resolution is desired but has been very challenging in medical image processing. Super resolution reconstruction based on sparse representation and overcomplete dictionary has been lately employed to address this problem; however, these methods require extra training sets, which may not be always available. This paper proposes a novel single anisotropic 3-D MR image upsampling method via sparse representation and overcomplete dictionary that is trained from in-plane high resolution slices to upsample in the out-of-plane dimensions. The proposed method, therefore, does not require extra training sets. Abundant experiments, conducted on simulated and clinical brain MR images, show that the proposed method is more accurate than classical interpolation. When compared to a recent upsampling method based on the nonlocal means approach, the proposed method did not show improved results at low upsampling factors with simulated images, but generated comparable results with much better computational efficiency in clinical cases. Therefore, the proposed approach can be efficiently implemented and routinely used to upsample MR images in the out-of-planes views for radiologic assessment and postacquisition processing.

Super-resolved Mirau digital holography by structured illumination

NASA Astrophysics Data System (ADS)

Ganjkhani, Yasaman; Charsooghi, Mohammad A.; Akhlaghi, Ehsan A.; Moradi, Ali-Reza

2017-12-01

In this paper, we apply structured illumination toward super-resolved 3D imaging in a common-path digital holography arrangement. Digital holographic microscopy (DHM) provides non-invasive 3D images of transparent samples as well as 3D profiles of reflective surfaces. A compact and vibration-immune arrangement for DHM may be obtained through the use of a Mirau microscope objective. However, high-magnification Mirau objectives have a low working distance and are expensive. Low-magnification ones, on the other hand, suffer from low lateral resolution. Structured illumination has been widely used for resolution improvement of intensity images, but the technique can also be readily applied to DHM. We apply structured illumination to Mirau DHM by implementing successive sinusoidal gratings with different orientations onto a spatial light modulator (SLM) and forming its image on the specimen. Moreover, we show that, instead of different orientations of 1D gratings, alternative single 2D gratings, e.g. checkerboard or hexagonal patterns, can provide resolution enhancement in multiple directions. Our results show a 35% improvement in the resolution power of the DHM. The presented arrangement has the potential to serve as a table-top device for high resolution holographic microscopy.

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data.

PubMed

Veganzones, Miguel A; Simoes, Miguel; Licciardi, Giorgio; Yokoya, Naoto; Bioucas-Dias, Jose M; Chanussot, Jocelyn

2016-01-01

Remote sensing hyperspectral images (HSIs) are quite often low rank, in the sense that the data belong to a low dimensional subspace/manifold. This has been recently exploited for the fusion of low spatial resolution HSI with high spatial resolution multispectral images in order to obtain super-resolution HSI. Most approaches adopt an unmixing or a matrix factorization perspective. The derived methods have led to state-of-the-art results when the spectral information lies in a low-dimensional subspace/manifold. However, if the subspace/manifold dimensionality spanned by the complete data set is large, i.e., larger than the number of multispectral bands, the performance of these methods mainly decreases because the underlying sparse regression problem is severely ill-posed. In this paper, we propose a local approach to cope with this difficulty. Fundamentally, we exploit the fact that real world HSIs are locally low rank, that is, pixels acquired from a given spatial neighborhood span a very low-dimensional subspace/manifold, i.e., lower or equal than the number of multispectral bands. Thus, we propose to partition the image into patches and solve the data fusion problem independently for each patch. This way, in each patch the subspace/manifold dimensionality is low enough, such that the problem is not ill-posed anymore. We propose two alternative approaches to define the hyperspectral super-resolution through local dictionary learning using endmember induction algorithms. We also explore two alternatives to define the local regions, using sliding windows and binary partition trees. The effectiveness of the proposed approaches is illustrated with synthetic and semi real data.

Adaptive optics improves multiphoton super-resolution imaging

NASA Astrophysics Data System (ADS)

Zheng, Wei; Wu, Yicong; Winter, Peter; Shroff, Hari

2018-02-01

Three dimensional (3D) fluorescence microscopy has been essential for biological studies. It allows interrogation of structure and function at spatial scales spanning the macromolecular, cellular, and tissue levels. Critical factors to consider in 3D microscopy include spatial resolution, signal-to-noise (SNR), signal-to-background (SBR), and temporal resolution. Maintaining high quality imaging becomes progressively more difficult at increasing depth (where optical aberrations, induced by inhomogeneities of refractive index in the sample, degrade resolution and SNR), and in thick or densely labeled samples (where out-of-focus background can swamp the valuable, in-focus-signal from each plane). In this report, we introduce our new instrumentation to address these problems. A multiphoton structured illumination microscope was simply modified to integrate an adpative optics system for optical aberrations correction. Firstly, the optical aberrations are determined using direct wavefront sensing with a nonlinear guide star and subsequently corrected using a deformable mirror, restoring super-resolution information. We demonstrate the flexibility of our adaptive optics approach on a variety of semi-transparent samples, including bead phantoms, cultured cells in collagen gels and biological tissues. The performance of our super-resolution microscope is improved in all of these samples, as peak intensity is increased (up to 40-fold) and resolution recovered (up to 176+/-10 nm laterally and 729+/-39 nm axially) at depths up to 250 μm from the coverslip surface.

Localization microscopy of DNA in situ using Vybrant{sup ®} DyeCycle™ Violet fluorescent probe: A new approach to study nuclear nanostructure at single molecule resolution

DOE Office of Scientific and Technical Information (OSTI.GOV)

Żurek-Biesiada, Dominika; Szczurek, Aleksander T.; Prakash, Kirti

Higher order chromatin structure is not only required to compact and spatially arrange long chromatids within a nucleus, but have also important functional roles, including control of gene expression and DNA processing. However, studies of chromatin nanostructures cannot be performed using conventional widefield and confocal microscopy because of the limited optical resolution. Various methods of superresolution microscopy have been described to overcome this difficulty, like structured illumination and single molecule localization microscopy. We report here that the standard DNA dye Vybrant{sup ®} DyeCycle™ Violet can be used to provide single molecule localization microscopy (SMLM) images of DNA in nuclei ofmore » fixed mammalian cells. This SMLM method enabled optical isolation and localization of large numbers of DNA-bound molecules, usually in excess of 10{sup 6} signals in one cell nucleus. The technique yielded high-quality images of nuclear DNA density, revealing subdiffraction chromatin structures of the size in the order of 100 nm; the interchromatin compartment was visualized at unprecedented optical resolution. The approach offers several advantages over previously described high resolution DNA imaging methods, including high specificity, an ability to record images using a single wavelength excitation, and a higher density of single molecule signals than reported in previous SMLM studies. The method is compatible with DNA/multicolor SMLM imaging which employs simple staining methods suited also for conventional optical microscopy. - Highlights: • Super-resolution imaging of nuclear DNA with Vybrant Violet and blue excitation. • 90nm resolution images of DNA structures in optically thick eukaryotic nuclei. • Enhanced resolution confirms the existence of DNA-free regions inside the nucleus. • Optimized imaging conditions enable multicolor super-resolution imaging.« less

Correction of a Depth-Dependent Lateral Distortion in 3D Super-Resolution Imaging

PubMed Central

Manley, Suliana

2015-01-01

Three-dimensional (3D) localization-based super-resolution microscopy (SR) requires correction of aberrations to accurately represent 3D structure. Here we show how a depth-dependent lateral shift in the apparent position of a fluorescent point source, which we term `wobble`, results in warped 3D SR images and provide a software tool to correct this distortion. This system-specific, lateral shift is typically > 80 nm across an axial range of ~ 1 μm. A theoretical analysis based on phase retrieval data from our microscope suggests that the wobble is caused by non-rotationally symmetric phase and amplitude aberrations in the microscope’s pupil function. We then apply our correction to the bacterial cytoskeletal protein FtsZ in live bacteria and demonstrate that the corrected data more accurately represent the true shape of this vertically-oriented ring-like structure. We also include this correction method in a registration procedure for dual-color, 3D SR data and show that it improves target registration error (TRE) at the axial limits over an imaging depth of 1 μm, yielding TRE values of < 20 nm. This work highlights the importance of correcting aberrations in 3D SR to achieve high fidelity between the measurements and the sample. PMID:26600467

Quantitative super-resolution imaging of Bruchpilot distinguishes active zone states

NASA Astrophysics Data System (ADS)

Ehmann, Nadine; van de Linde, Sebastian; Alon, Amit; Ljaschenko, Dmitrij; Keung, Xi Zhen; Holm, Thorge; Rings, Annika; Diantonio, Aaron; Hallermann, Stefan; Ashery, Uri; Heckmann, Manfred; Sauer, Markus; Kittel, Robert J.

2014-08-01

The precise molecular architecture of synaptic active zones (AZs) gives rise to different structural and functional AZ states that fundamentally shape chemical neurotransmission. However, elucidating the nanoscopic protein arrangement at AZs is impeded by the diffraction-limited resolution of conventional light microscopy. Here we introduce new approaches to quantify endogenous protein organization at single-molecule resolution in situ with super-resolution imaging by direct stochastic optical reconstruction microscopy (dSTORM). Focusing on the Drosophila neuromuscular junction (NMJ), we find that the AZ cytomatrix (CAZ) is composed of units containing ~137 Bruchpilot (Brp) proteins, three quarters of which are organized into about 15 heptameric clusters. We test for a quantitative relationship between CAZ ultrastructure and neurotransmitter release properties by engaging Drosophila mutants and electrophysiology. Our results indicate that the precise nanoscopic organization of Brp distinguishes different physiological AZ states and link functional diversification to a heretofore unrecognized neuronal gradient of the CAZ ultrastructure.

Two-photon speckle illumination for super-resolution microscopy.

PubMed

Negash, Awoke; Labouesse, Simon; Chaumet, Patrick C; Belkebir, Kamal; Giovannini, Hugues; Allain, Marc; Idier, Jérôme; Sentenac, Anne

2018-06-01

We present a numerical study of a microscopy setup in which the sample is illuminated with uncontrolled speckle patterns and the two-photon excitation fluorescence is collected on a camera. We show that, using a simple deconvolution algorithm for processing the speckle low-resolution images, this wide-field imaging technique exhibits resolution significantly better than that of two-photon excitation scanning microscopy or one-photon excitation bright-field microscopy.

Perspectives in Super-resolved Fluorescence Microscopy: What comes next?

NASA Astrophysics Data System (ADS)

Cremer, Christoph; Birk, Udo

2016-04-01

The Nobel Prize in Chemistry 2014 has been awarded to three scientists involved in the development of STED and PALM super-resolution fluorescence microscopy (SRM) methods. They have proven that it is possible to overcome the hundred year old theoretical limit for the resolution potential of light microscopy (of about 200 nm for visible light), which for decades has precluded a direct glimpse of the molecular machinery of life. None of the present-day super-resolution techniques have invalidated the Abbe limit for light optical detection; however, they have found clever ways around it. In this report, we discuss some of the challenges still to be resolved before arising SRM approaches will be fit to bring about the revolution in Biology and Medicine envisaged. Some of the challenges discussed are the applicability to image live and/or large samples, the further enhancement of resolution, future developments of labels, and multi-spectral approaches.

Breaking the acoustic diffraction barrier with localization optoacoustic tomography

NASA Astrophysics Data System (ADS)

Deán-Ben, X. Luís.; Razansky, Daniel

2018-02-01

Diffraction causes blurring of high-resolution features in images and has been traditionally associated to the resolution limit in light microscopy and other imaging modalities. The resolution of an imaging system can be generally assessed via its point spread function, corresponding to the image acquired from a point source. However, the precision in determining the position of an isolated source can greatly exceed the diffraction limit. By combining the estimated positions of multiple sources, localization-based imaging has resulted in groundbreaking methods such as super-resolution fluorescence optical microscopy and has also enabled ultrasound imaging of microvascular structures with unprecedented spatial resolution in deep tissues. Herein, we introduce localization optoacoustic tomography (LOT) and discuss on the prospects of using localization imaging principles in optoacoustic imaging. LOT was experimentally implemented by real-time imaging of flowing particles in 3D with a recently-developed volumetric optoacoustic tomography system. Provided the particles were separated by a distance larger than the diffraction-limited resolution, their individual locations could be accurately determined in each frame of the acquired image sequence and the localization image was formed by superimposing a set of points corresponding to the localized positions of the absorbers. The presented results demonstrate that LOT can significantly enhance the well-established advantages of optoacoustic imaging by breaking the acoustic diffraction barrier in deep tissues and mitigating artifacts due to limited-view tomographic acquisitions.

Fusion and Visualization of HiRISE Super-Resolution, Shape-from-Shading DTM with MER Stereo 3D Reconstructions

NASA Astrophysics Data System (ADS)

Gupta, S.; Paar, G.; Muller, J. P.; Tao, Y.; Tyler, L.; Traxler, C.; Hesina, G.; Huber, B.; Nauschnegg, B.

2014-12-01

The FP7-SPACE project PRoViDE has assembled a major portion of the imaging data gathered so far from rover vehicles, landers and probes on extra-terrestrial planetary surfaces into a unique database, bringing them into a common planetary geospatial context and providing access to a complete set of 3D vision products. One major aim of PRoViDE is the fusion between orbiter and rover image products. To close the gap between HiRISE imaging resolution (down to 25cm for the OrthoRectified image (ORI), down to 1m for the DTM) and surface vision products, images from multiple HiRISE acquisitions are combined into a super resolution data set (Tao & Muller, 2014), increasing to 5cm resolution the Ortho images. Furthermore, shape-from-shading is applied to one of the ORIs at its original resolution for refinement of the HiRISE DTM, leading to DTM ground resolutions of up to 25 cm. After texture-based co-registration with these refined orbiter 3D products, MER PanCam and NavCam 3D image products can be smoothly pasted into a multi-resolution 3D data representation. Typical results from the MER mission are presented by a dedicated real-time rendering tool which is fed by a hierarchical 3D data structure that is able to cope with all involved scales from global planetary scale down to close-up reconstructions in the mm range. This allows us to explore and analyze the geological characteristics of rock outcrops, for example the detailed geometry and internal features of sedimentary rock layers, to aid paleoenvironmental interpretation. This integrated approach enables more efficient development of geological models of martian rock outcrops. The rendering tool also provides measurement tools to obtain geospatial data of surface points and distances between them. We report on novel scientific use cases and the added value potential of the resultant high-quality data set and presentation means to support further geologic investigations. The research leading to these results has received funding from the EC's 7th Framework Programme (FP7/2007-2013) under grant agreement n° 312377.

Cassette Series Designed for Live-Cell Imaging of Proteins and High Resolution Techniques in Yeast

PubMed Central

Young, Carissa L.; Raden, David L.; Caplan, Jeffrey; Czymmek, Kirk; Robinson, Anne S.

2012-01-01

During the past decade, it has become clear that protein function and regulation are highly dependent upon intracellular localization. Although fluorescent protein variants are ubiquitously used to monitor protein dynamics, localization, and abundance; fluorescent light microscopy techniques often lack the resolution to explore protein heterogeneity and cellular ultrastructure. Several approaches have been developed to identify, characterize, and monitor the spatial localization of proteins and complexes at the sub-organelle level; yet, many of these techniques have not been applied to yeast. Thus, we have constructed a series of cassettes containing codon-optimized epitope tags, fluorescent protein variants that cover the full spectrum of visible light, a TetCys motif used for FlAsH-based localization, and the first evaluation in yeast of a photoswitchable variant – mEos2 – to monitor discrete subpopulations of proteins via confocal microscopy. This series of modules, complete with six different selection markers, provides the optimal flexibility during live-cell imaging and multicolor labeling in vivo. Furthermore, high-resolution imaging techniques include the yeast-enhanced TetCys motif that is compatible with diaminobenzidine photooxidation used for protein localization by electron microscopy and mEos2 that is ideal for super-resolution microscopy. We have examined the utility of our cassettes by analyzing all probes fused to the C-terminus of Sec61, a polytopic membrane protein of the endoplasmic reticulum of moderate protein concentration, in order to directly compare fluorescent probes, their utility and technical applications. Our series of cassettes expand the repertoire of molecular tools available to advance targeted spatiotemporal investigations using multiple live-cell, super-resolution or electron microscopy imaging techniques. PMID:22473760

Differential localization of SAP102 and PSD-95 is revealed in hippocampal spines using super-resolution light microscopy.

PubMed

Zheng, Chan-Ying; Wang, Ya-Xia; Kachar, Bechara; Petralia, Ronald S

2011-01-01

Synapse-associated protein 102 (SAP102) and postsynaptic density 95 (PSD-95) are two major cytoskeleton proteins in the postsynaptic density (PSD). Both of them belong to the membrane-associated guanylate kinase (MAGUK) family, which clusters and anchors glutamate receptors and other proteins at synapses. In our previous study, we found that SAP102 and PSD-95 have different distributions, using combined light/electron microscopy (LM/EM) methods.1 Here, we double labeled endogenous SAP102 and PSD-95 in mature hippocampal neurons, and then took images by two different kinds of super resolution microscopy-Stimulated Emission Depletion microscopy (STED) and DeltaVision OMX 3D super resolution microscopy. We found that our 2D and 3D super resolution data were consistent with our previous LM/EM data, showing significant differences in the localization of SAP102 and PSD-95 in spines: SAP102 is distributed in both the PSD and cytoplasm of spines, while PSD-95 is concentrated only in the PSD area. These results indicate functional differences between SAP102 and PSD-95 in synaptic organization and plasticity.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Meddens, Marjolein B. M.; Liu, Sheng; Finnegan, Patrick S.

Here, we have developed a method for performing light-sheet microscopy with a single high numerical aperture lens by integrating reflective side walls into a microfluidic chip. These 45° side walls generate light-sheet illumination by reflecting a vertical light-sheet into the focal plane of the objective. Light-sheet illumination of cells loaded in the channels increases image quality in diffraction limited imaging via reduction of out-of-focus background light. Single molecule super-resolution is also improved by the decreased background resulting in better localization precision and decreased photo-bleaching, leading to more accepted localizations overall and higher quality images. Moreover, 2D and 3D single moleculemore » super-resolution data can be acquired faster by taking advantage of the increased illumination intensities as compared to wide field, in the focused light-sheet.« less

Super-resolved Parallel MRI by Spatiotemporal Encoding

PubMed Central

Schmidt, Rita; Baishya, Bikash; Ben-Eliezer, Noam; Seginer, Amir; Frydman, Lucio

2016-01-01

Recent studies described an alternative “ultrafast” scanning method based on spatiotemporal (SPEN) principles. SPEN demonstrates numerous potential advantages over EPI-based alternatives, at no additional expense in experimental complexity. An important aspect that SPEN still needs to achieve for providing a competitive acquisition alternative entails exploiting parallel imaging algorithms, without compromising its proven capabilities. The present work introduces a combination of multi-band frequency-swept pulses simultaneously encoding multiple, partial fields-of-view; together with a new algorithm merging a Super-Resolved SPEN image reconstruction and SENSE multiple-receiving methods. The ensuing approach enables one to reduce both the excitation and acquisition times of ultrafast SPEN acquisitions by the customary acceleration factor R, without compromises in either the ensuing spatial resolution, SAR deposition, or the capability to operate in multi-slice mode. The performance of these new single-shot imaging sequences and their ancillary algorithms were explored on phantoms and human volunteers at 3T. The gains of the parallelized approach were particularly evident when dealing with heterogeneous systems subject to major T2/T2* effects, as is the case upon single-scan imaging near tissue/air interfaces. PMID:24120293

Joint Prior Learning for Visual Sensor Network Noisy Image Super-Resolution

PubMed Central

Yue, Bo; Wang, Shuang; Liang, Xuefeng; Jiao, Licheng; Xu, Caijin

2016-01-01

The visual sensor network (VSN), a new type of wireless sensor network composed of low-cost wireless camera nodes, is being applied for numerous complex visual analyses in wild environments, such as visual surveillance, object recognition, etc. However, the captured images/videos are often low resolution with noise. Such visual data cannot be directly delivered to the advanced visual analysis. In this paper, we propose a joint-prior image super-resolution (JPISR) method using expectation maximization (EM) algorithm to improve VSN image quality. Unlike conventional methods that only focus on upscaling images, JPISR alternatively solves upscaling mapping and denoising in the E-step and M-step. To meet the requirement of the M-step, we introduce a novel non-local group-sparsity image filtering method to learn the explicit prior and induce the geometric duality between images to learn the implicit prior. The EM algorithm inherently combines the explicit prior and implicit prior by joint learning. Moreover, JPISR does not rely on large external datasets for training, which is much more practical in a VSN. Extensive experiments show that JPISR outperforms five state-of-the-art methods in terms of both PSNR, SSIM and visual perception. PMID:26927114

High-resolution single-molecule fluorescence imaging of zeolite aggregates within real-life fluid catalytic cracking particles.

PubMed

Ristanović, Zoran; Kerssens, Marleen M; Kubarev, Alexey V; Hendriks, Frank C; Dedecker, Peter; Hofkens, Johan; Roeffaers, Maarten B J; Weckhuysen, Bert M

2015-02-02

Fluid catalytic cracking (FCC) is a major process in oil refineries to produce gasoline and base chemicals from crude oil fractions. The spatial distribution and acidity of zeolite aggregates embedded within the 50-150 μm-sized FCC spheres heavily influence their catalytic performance. Single-molecule fluorescence-based imaging methods, namely nanometer accuracy by stochastic chemical reactions (NASCA) and super-resolution optical fluctuation imaging (SOFI) were used to study the catalytic activity of sub-micrometer zeolite ZSM-5 domains within real-life FCC catalyst particles. The formation of fluorescent product molecules taking place at Brønsted acid sites was monitored with single turnover sensitivity and high spatiotemporal resolution, providing detailed insight in dispersion and catalytic activity of zeolite ZSM-5 aggregates. The results point towards substantial differences in turnover frequencies between the zeolite aggregates, revealing significant intraparticle heterogeneities in Brønsted reactivity. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Robust Single Image Super-Resolution via Deep Networks With Sparse Prior.

PubMed

Liu, Ding; Wang, Zhaowen; Wen, Bihan; Yang, Jianchao; Han, Wei; Huang, Thomas S

2016-07-01

Single image super-resolution (SR) is an ill-posed problem, which tries to recover a high-resolution image from its low-resolution observation. To regularize the solution of the problem, previous methods have focused on designing good priors for natural images, such as sparse representation, or directly learning the priors from a large data set with models, such as deep neural networks. In this paper, we argue that domain expertise from the conventional sparse coding model can be combined with the key ingredients of deep learning to achieve further improved results. We demonstrate that a sparse coding model particularly designed for SR can be incarnated as a neural network with the merit of end-to-end optimization over training data. The network has a cascaded structure, which boosts the SR performance for both fixed and incremental scaling factors. The proposed training and testing schemes can be extended for robust handling of images with additional degradation, such as noise and blurring. A subjective assessment is conducted and analyzed in order to thoroughly evaluate various SR techniques. Our proposed model is tested on a wide range of images, and it significantly outperforms the existing state-of-the-art methods for various scaling factors both quantitatively and perceptually.

Optimized computational imaging methods for small-target sensing in lens-free holographic microscopy

NASA Astrophysics Data System (ADS)

Xiong, Zhen; Engle, Isaiah; Garan, Jacob; Melzer, Jeffrey E.; McLeod, Euan

2018-02-01

Lens-free holographic microscopy is a promising diagnostic approach because it is cost-effective, compact, and suitable for point-of-care applications, while providing high resolution together with an ultra-large field-of-view. It has been applied to biomedical sensing, where larger targets like eukaryotic cells, bacteria, or viruses can be directly imaged without labels, and smaller targets like proteins or DNA strands can be detected via scattering labels like micro- or nano-spheres. Automated image processing routines can count objects and infer target concentrations. In these sensing applications, sensitivity and specificity are critically affected by image resolution and signal-to-noise ratio (SNR). Pixel super-resolution approaches have been shown to boost resolution and SNR by synthesizing a high-resolution image from multiple, partially redundant, low-resolution images. However, there are several computational methods that can be used to synthesize the high-resolution image, and previously, it has been unclear which methods work best for the particular case of small-particle sensing. Here, we quantify the SNR achieved in small-particle sensing using regularized gradient-descent optimization method, where the regularization is based on cardinal-neighbor differences, Bayer-pattern noise reduction, or sparsity in the image. In particular, we find that gradient-descent with sparsity-based regularization works best for small-particle sensing. These computational approaches were evaluated on images acquired using a lens-free microscope that we assembled from an off-the-shelf LED array and color image sensor. Compared to other lens-free imaging systems, our hardware integration, calibration, and sample preparation are particularly simple. We believe our results will help to enable the best performance in lens-free holographic sensing.

Sensing Super-position: Visual Instrument Sensor Replacement

NASA Technical Reports Server (NTRS)

Maluf, David A.; Schipper, John F.

2006-01-01

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This project addresses the technical feasibility of augmenting human vision through Sensing Super-position using a Visual Instrument Sensory Organ Replacement (VISOR). The current implementation of the VISOR device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of the human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system.

Technical Review: Microscopy and Image Processing Tools to Analyze Plant Chromatin: Practical Considerations.

PubMed

Baroux, Célia; Schubert, Veit

2018-01-01

In situ nucleus and chromatin analyses rely on microscopy imaging that benefits from versatile, efficient fluorescent probes and proteins for static or live imaging. Yet the broad choice in imaging instruments offered to the user poses orientation problems. Which imaging instrument should be used for which purpose? What are the main caveats and what are the considerations to best exploit each instrument's ability to obtain informative and high-quality images? How to infer quantitative information on chromatin or nuclear organization from microscopy images? In this review, we present an overview of common, fluorescence-based microscopy systems and discuss recently developed super-resolution microscopy systems, which are able to bridge the resolution gap between common fluorescence microscopy and electron microscopy. We briefly present their basic principles and discuss their possible applications in the field, while providing experience-based recommendations to guide the user toward best-possible imaging. In addition to raw data acquisition methods, we discuss commercial and noncommercial processing tools required for optimal image presentation and signal evaluation in two and three dimensions.

Super Resolution Image of Yogi

NASA Technical Reports Server (NTRS)

1997-01-01

Yogi is a meter-size rock about 5 meters northwest of the Mars Pathfinder lander and was the second rock visited by the Sojourner Rover's alpha proton X-ray spectrometer (APXS) instrument. This mosaic shows super resolution techniques applied to the second APXS target rock, which was poorly illuminated in the rover's forward camera view taken before the instrument was deployed. Super resolution was applied to help to address questions about the texture of this rock and what it might tell us about its mode of origin.

This mosaic of Yogi was produced by combining four 'Super Pan' frames taken with the IMP camera. This composite color mosaic consists of 7 frames from the right eye, taken with different color filters that were enlarged by 500% and then co-added using Adobe Photoshop to produce, in effect, a super-resolution panchromatic frame that is sharper than an individual frame would be. This panchromatic frame was then colorized with the red, green, and blue filtered images from the same sequence. The color balance was adjusted to approximate the true color of Mars. Shadows were processed separately from the rest of the rock and combined with the rest of the scene to bring out details in the shadow of Yogi that would be too dark to view at the same time as the sunlit surfaces.

Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. The Jet Propulsion Laboratory, Pasadena, CA, developed and manages the Mars Pathfinder mission for NASA's Office of Space Science, Washington, D.C. JPL is a division of the California Institute of Technology (Caltech).

Alpha particle spectroscopy using FNTD and SIM super-resolution microscopy.

PubMed

Kouwenberg, J J M; Kremers, G J; Slotman, J A; Wolterbeek, H T; Houtsmuller, A B; Denkova, A G; Bos, A J J

2018-06-01

Structured illumination microscopy (SIM) for the imaging of alpha particle tracks in fluorescent nuclear track detectors (FNTD) was evaluated and compared to confocal laser scanning microscopy (CLSM). FNTDs were irradiated with an external alpha source and imaged using both methodologies. SIM imaging resulted in improved resolution, without increase in scan time. Alpha particle energy estimation based on the track length, direction and intensity produced results in good agreement with the expected alpha particle energy distribution. A pronounced difference was seen in the spatial scattering of alpha particles in the detectors, where SIM showed an almost 50% reduction compared to CLSM. The improved resolution of SIM allows for more detailed studies of the tracks induced by ionising particles. The combination of SIM and FNTDs for alpha radiation paves the way for affordable and fast alpha spectroscopy and dosimetry. © 2018 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.

Fast high resolution reconstruction in multi-slice and multi-view cMRI

NASA Astrophysics Data System (ADS)

Velasco Toledo, Nelson; Romero Castro, Eduardo

2015-01-01

Cardiac magnetic resonance imaging (cMRI) is an useful tool in diagnosis, prognosis and research since it functionally tracks the heart structure. Although useful, this imaging technique is limited in spatial resolution because heart is a constant moving organ, also there are other non controled conditions such as patient movements and volumetric changes during apnea periods when data is acquired, those conditions limit the time to capture high quality information. This paper presents a very fast and simple strategy to reconstruct high resolution 3D images from a set of low resolution series of 2D images. The strategy is based on an information reallocation algorithm which uses the DICOM header to relocate voxel intensities in a regular grid. An interpolation method is applied to fill empty places with estimated data, the interpolation resamples the low resolution information to estimate the missing information. As a final step a gaussian filter that denoises the final result. A reconstructed image evaluation is performed using as a reference a super-resolution reconstructed image. The evaluation reveals that the method maintains the general heart structure with a small loss in detailed information (edge sharpening and blurring), some artifacts related with input information quality are detected. The proposed method requires low time and computational resources.

Demonstration of Single-Barium-Ion Sensitivity for Neutrinoless Double-Beta Decay Using Single-Molecule Fluorescence Imaging

DOE PAGES

McDonald, A. D.; Jones, B. J. P.; Nygren, D. R.; ...

2018-03-26

A new method to tag the barium daughter in the double beta decay ofmore » $$^{136}$$Xe is reported. Using the technique of single molecule fluorescent imaging (SMFI), individual barium dication (Ba$$^{++}$$) resolution at a transparent scanning surface has been demonstrated. A single-step photo-bleach confirms the single ion interpretation. Individual ions are localized with super-resolution ($$\\sim$$2~nm), and detected with a statistical significance of 12.9~$$\\sigma$$ over backgrounds. This lays the foundation for a new and potentially background-free neutrinoless double beta decay technology, based on SMFI coupled to high pressure xenon gas time projection chambers.« less

Pulsed-neutron imaging by a high-speed camera and center-of-gravity processing

NASA Astrophysics Data System (ADS)

Mochiki, K.; Uragaki, T.; Koide, J.; Kushima, Y.; Kawarabayashi, J.; Taketani, A.; Otake, Y.; Matsumoto, Y.; Su, Y.; Hiroi, K.; Shinohara, T.; Kai, T.

2018-01-01

Pulsed-neutron imaging is attractive technique in the research fields of energy-resolved neutron radiography and RANS (RIKEN) and RADEN (J-PARC/JAEA) are small and large accelerator-driven pulsed-neutron facilities for its imaging, respectively. To overcome the insuficient spatial resolution of the conunting type imaging detectors like μ NID, nGEM and pixelated detectors, camera detectors combined with a neutron color image intensifier were investigated. At RANS center-of-gravity technique was applied to spots image obtained by a CCD camera and the technique was confirmed to be effective for improving spatial resolution. At RADEN a high-frame-rate CMOS camera was used and super resolution technique was applied and it was recognized that the spatial resolution was futhermore improved.

Study on super-resolution three-dimensional range-gated imaging technology

NASA Astrophysics Data System (ADS)

Guo, Huichao; Sun, Huayan; Wang, Shuai; Fan, Youchen; Li, Yuanmiao

2018-04-01

Range-gated three dimensional imaging technology is a hotspot in recent years, because of the advantages of high spatial resolution, high range accuracy, long range, and simultaneous reflection of target reflectivity information. Based on the study of the principle of intensity-related method, this paper has carried out theoretical analysis and experimental research. The experimental system adopts the high power pulsed semiconductor laser as light source, gated ICCD as the imaging device, can realize the imaging depth and distance flexible adjustment to achieve different work mode. The imaging experiment of small imaging depth is carried out aiming at building 500m away, and 26 group images were obtained with distance step 1.5m. In this paper, the calculation method of 3D point cloud based on triangle method is analyzed, and 15m depth slice of the target 3D point cloud are obtained by using two frame images, the distance precision is better than 0.5m. The influence of signal to noise ratio, illumination uniformity and image brightness on distance accuracy are analyzed. Based on the comparison with the time-slicing method, a method for improving the linearity of point cloud is proposed.

Periventricular Nodular Heterotopia: Detection of Abnormal Microanatomic Fiber Structures with Whole-Brain Diffusion MR Imaging Tractography.

PubMed

Farquharson, Shawna; Tournier, J-Donald; Calamante, Fernando; Mandelstam, Simone; Burgess, Rosemary; Schneider, Michal E; Berkovic, Samuel F; Scheffer, Ingrid E; Jackson, Graeme D; Connelly, Alan

2016-12-01

Purpose To investigate whether it is possible in patients with periventricular nodular heterotopia (PVNH) to detect abnormal fiber projections that have only previously been reported in the histopathology literature. Materials and Methods Whole-brain diffusion-weighted (DW) imaging data from 14 patients with bilateral PVNH and 14 age- and sex-matched healthy control subjects were prospectively acquired by using 3.0-T magnetic resonance (MR) imaging between August 1, 2008, and December 5, 2012. All participants provided written informed consent. The DW imaging data were processed to generate whole-brain constrained spherical deconvolution (CSD)-based tractography data and super-resolution track-density imaging (TDI) maps. The tractography data were overlaid on coregistered three-dimensional T1-weighted images to visually assess regions of heterotopia. A panel of MR imaging researchers independently assessed each case and indicated numerically (no = 1, yes = 2) as to the presence of abnormal fiber tracks in nodular tissue. The Fleiss κ statistical measure was applied to assess the reader agreement. Results Abnormal fiber tracks emanating from one or more regions of heterotopia were reported by all four readers in all 14 patients with PVNH (Fleiss κ = 1). These abnormal structures were not visible on the tractography data from any of the control subjects and were not discernable on the conventional T1-weighted images of the patients with PVNH. Conclusion Whole-brain CSD-based fiber tractography and super-resolution TDI mapping reveals abnormal fiber projections in nodular tissue suggestive of abnormal organization of white matter (with abnormal fibers both within nodules and projecting to the surrounding white matter) in patients with bilateral PVNH. © RSNA, 2016.

A state space based approach to localizing single molecules from multi-emitter images.

PubMed

Vahid, Milad R; Chao, Jerry; Ward, E Sally; Ober, Raimund J

2017-01-28

Single molecule super-resolution microscopy is a powerful tool that enables imaging at sub-diffraction-limit resolution. In this technique, subsets of stochastically photoactivated fluorophores are imaged over a sequence of frames and accurately localized, and the estimated locations are used to construct a high-resolution image of the cellular structures labeled by the fluorophores. Available localization methods typically first determine the regions of the image that contain emitting fluorophores through a process referred to as detection. Then, the locations of the fluorophores are estimated accurately in an estimation step. We propose a novel localization method which combines the detection and estimation steps. The method models the given image as the frequency response of a multi-order system obtained with a balanced state space realization algorithm based on the singular value decomposition of a Hankel matrix, and determines the locations of intensity peaks in the image as the pole locations of the resulting system. The locations of the most significant peaks correspond to the locations of single molecules in the original image. Although the accuracy of the location estimates is reasonably good, we demonstrate that, by using the estimates as the initial conditions for a maximum likelihood estimator, refined estimates can be obtained that have a standard deviation close to the Cramér-Rao lower bound-based limit of accuracy. We validate our method using both simulated and experimental multi-emitter images.

Autofocusing Airy beam STED microscopy with long focal distance

NASA Astrophysics Data System (ADS)

Hu, Di; Liang, Yao; Chen, Yin; Chen, Zan Hui; Huang, Xu Guang

2017-12-01

Stimulated emission depletion (STED) is a very important technique in super-resolution microscopy. Until now, while autofocusing Airy beam (AAB) has been an attractive theme for both theoretical and applied researches, there are almost no report on AABs being used in STED microscopy. In this paper, we propose a novel STED microscopy based on AABs. A radially symmetric 3/2 phase plate is involved to simultaneously generate autofocusing excitation- and depletion-Airy beams. Remarkably, the AAB can auto-focus to a wavelength-scale spot with a long focal depth (several millimeters): on the contrary, the working distance of a conventional high numerical aperture (NA) objective is usually very short (about 200 μm). Our calculations indicate that the AAB based STED microscopy can achieve a super-resolution spot with FWHM of 58 nm while the focal length is 4.638 mm. Moreover, with properties of non-diffracting and self-healing, the Airy beam could enable a reduction of the scattering distortion induced by the specimens and has a great potential in imaging thick specimens.

Super-Resolution Person Re-Identification With Semi-Coupled Low-Rank Discriminant Dictionary Learning.

PubMed

Jing, Xiao-Yuan; Zhu, Xiaoke; Wu, Fei; Hu, Ruimin; You, Xinge; Wang, Yunhong; Feng, Hui; Yang, Jing-Yu

2017-03-01

Person re-identification has been widely studied due to its importance in surveillance and forensics applications. In practice, gallery images are high resolution (HR), while probe images are usually low resolution (LR) in the identification scenarios with large variation of illumination, weather, or quality of cameras. Person re-identification in this kind of scenarios, which we call super-resolution (SR) person re-identification, has not been well studied. In this paper, we propose a semi-coupled low-rank discriminant dictionary learning (SLD 2 L) approach for SR person re-identification task. With the HR and LR dictionary pair and mapping matrices learned from the features of HR and LR training images, SLD 2 L can convert the features of the LR probe images into HR features. To ensure that the converted features have favorable discriminative capability and the learned dictionaries can well characterize intrinsic feature spaces of the HR and LR images, we design a discriminant term and a low-rank regularization term for SLD 2 L. Moreover, considering that low resolution results in different degrees of loss for different types of visual appearance features, we propose a multi-view SLD 2 L (MVSLD 2 L) approach, which can learn the type-specific dictionary pair and mappings for each type of feature. Experimental results on multiple publicly available data sets demonstrate the effectiveness of our proposed approaches for the SR person re-identification task.

Scanning superlens microscopy for non-invasive large field-of-view visible light nanoscale imaging

NASA Astrophysics Data System (ADS)

Wang, Feifei; Liu, Lianqing; Yu, Haibo; Wen, Yangdong; Yu, Peng; Liu, Zhu; Wang, Yuechao; Li, Wen Jung

2016-12-01

Nanoscale correlation of structural information acquisition with specific-molecule identification provides new insight for studying rare subcellular events. To achieve this correlation, scanning electron microscopy has been combined with super-resolution fluorescent microscopy, despite its destructivity when acquiring biological structure information. Here we propose time-efficient non-invasive microsphere-based scanning superlens microscopy that enables the large-area observation of live-cell morphology or sub-membrane structures with sub-diffraction-limited resolution and is demonstrated by observing biological and non-biological objects. This microscopy operates in both non-invasive and contact modes with ~200 times the acquisition efficiency of atomic force microscopy, which is achieved by replacing the point of an atomic force microscope tip with an imaging area of microspheres and stitching the areas recorded during scanning, enabling sub-diffraction-limited resolution. Our method marks a possible path to non-invasive cell imaging and simultaneous tracking of specific molecules with nanoscale resolution, facilitating the study of subcellular events over a total cell period.

Interferometric temporal focusing microscopy using three-photon excitation fluorescence.

PubMed

Toda, Keisuke; Isobe, Keisuke; Namiki, Kana; Kawano, Hiroyuki; Miyawaki, Atsushi; Midorikawa, Katsumi

2018-04-01

Super-resolution microscopy has become a powerful tool for biological research. However, its spatial resolution and imaging depth are limited, largely due to background light. Interferometric temporal focusing (ITF) microscopy, which combines structured illumination microscopy and three-photon excitation fluorescence microscopy, can overcome these limitations. Here, we demonstrate ITF microscopy using three-photon excitation fluorescence, which has a spatial resolution of 106 nm at an imaging depth of 100 µm with an excitation wavelength of 1060 nm.

Three-dimensional wide-field pump-probe structured illumination microscopy

PubMed Central

Kim, Yang-Hyo; So, Peter T.C.

2017-01-01

We propose a new structured illumination scheme for achieving depth resolved wide-field pump-probe microscopy with sub-diffraction limit resolution. By acquiring coherent pump-probe images using a set of 3D structured light illumination patterns, a 3D super-resolution pump-probe image can be reconstructed. We derive the theoretical framework to describe the coherent image formation and reconstruction scheme for this structured illumination pump-probe imaging system and carry out numerical simulations to investigate its imaging performance. The results demonstrate a lateral resolution improvement by a factor of three and providing 0.5 µm level axial optical sectioning. PMID:28380860

Optical sectioning using a digital Fresnel incoherent-holography-based confocal imaging system

PubMed Central

Kelner, Roy; Katz, Barak; Rosen, Joseph

2015-01-01

We propose a new type of confocal microscope using Fresnel incoherent correlation holography (FINCH). Presented here is a confocal configuration of FINCH using a phase pinhole and point illumination that is able to suppress out-of-focus information from the recorded hologram and hence combine the super-resolution capabilities of FINCH with the sectioning capabilities of confocal microscopy. PMID:26413560

Tip-enhanced near-field optical microscope with side-on and ATR-mode sample excitation for super-resolution Raman imaging of surfaces

NASA Astrophysics Data System (ADS)

Heilman, A. L.; Gordon, M. J.

2016-06-01

A tip-enhanced near-field optical microscope with side-on and attenuated total reflectance (ATR) excitation and collection is described and used to demonstrate sub-diffraction-limited (super-resolution) optical and chemical characterization of surfaces. ATR illumination is combined with an Au optical antenna tip to show that (i) the tip can quantitatively transduce the optical near-field (evanescent waves) above the surface by scattering photons into the far-field, (ii) the ATR geometry enables excitation and characterization of surface plasmon polaritons (SPPs), whose associated optical fields are shown to enhance Raman scattering from a thin layer of copper phthalocyanine (CuPc), and (iii) SPPs can be used to plasmonically excite the tip for super-resolution chemical imaging of patterned CuPc via tip-enhanced Raman spectroscopy (TERS). ATR-illumination TERS is also quantitatively compared with the more conventional side-on illumination scheme. In both cases, spatial resolution was better than 40 nm and tip on/tip off Raman enhancement factors were >6500. Furthermore, ATR illumination was shown to provide similar Raman signal levels at lower "effective" pump powers due to additional optical energy delivered by SPPs to the active region in the tip-surface gap.

Tip-enhanced near-field optical microscope with side-on and ATR-mode sample excitation for super-resolution Raman imaging of surfaces

DOE Office of Scientific and Technical Information (OSTI.GOV)

Heilman, A. L.; Gordon, M. J.

A tip-enhanced near-field optical microscope with side-on and attenuated total reflectance (ATR) excitation and collection is described and used to demonstrate sub-diffraction-limited (super-resolution) optical and chemical characterization of surfaces. ATR illumination is combined with an Au optical antenna tip to show that (i) the tip can quantitatively transduce the optical near-field (evanescent waves) above the surface by scattering photons into the far-field, (ii) the ATR geometry enables excitation and characterization of surface plasmon polaritons (SPPs), whose associated optical fields are shown to enhance Raman scattering from a thin layer of copper phthalocyanine (CuPc), and (iii) SPPs can be used tomore » plasmonically excite the tip for super-resolution chemical imaging of patterned CuPc via tip-enhanced Raman spectroscopy (TERS). ATR-illumination TERS is also quantitatively compared with the more conventional side-on illumination scheme. In both cases, spatial resolution was better than 40 nm and tip on/tip off Raman enhancement factors were >6500. Furthermore, ATR illumination was shown to provide similar Raman signal levels at lower “effective” pump powers due to additional optical energy delivered by SPPs to the active region in the tip-surface gap.« less

Automated dynamic feature tracking of RSLs on the Martian surface through HiRISE super-resolution restoration and 3D reconstruction techniques

NASA Astrophysics Data System (ADS)

Tao, Y.; Muller, J.-P.

2017-09-01

In this paper, we demonstrate novel Super-resolution restoration and 3D reconstruction tools developed within the EU FP7 projects and their applications to advanced dynamic feature tracking through HiRISE repeat stereo. We show an example with one of the RSL sites in the Palikir Crater took 8 repeat-pass 25cm HiRISE images from which a 5cm RSL-free SRR image is generated using GPT-SRR. Together with repeat 3D modelling of the same area, it allows us to overlay tracked dynamic features onto the reconstructed "original" surface, providing a much more comprehensive interpretation of the surface formation processes in 3D.

Near-field examination of perovskite-based superlenses and superlens-enhanced probe-object coupling

PubMed Central

Kehr, S.C.; Liu, Y.M.; Martin, L.W.; Yu, P.; Gajek, M.; Yang, S.-Y.; Yang, C.-H.; Wenzel, M.T.; Jacob, R.; von Ribbeck, H.-G.; Helm, M.; Zhang, X.; Eng, L.M.; Ramesh, R.

2011-01-01

A planar slab of negative-index material works as a superlens with sub-diffraction-limited resolution, as propagating waves are focused and, moreover, evanescent waves are reconstructed in the image plane. Here we demonstrate a superlens for electric evanescent fields with low losses using perovskites in the mid-infrared regime. The combination of near-field microscopy with a tunable free-electron laser allows us to address precisely the polariton modes, which are critical for super-resolution imaging. We spectrally study the lateral and vertical distributions of evanescent waves around the image plane of such a lens, and achieve imaging resolution of λ/14 at the superlensing wavelength. Interestingly, at certain distances between the probe and sample surface, we observe a maximum of these evanescent fields. Comparisons with numerical simulations indicate that this maximum originates from an enhanced coupling between probe and object, which might be applicable for multifunctional circuits, infrared spectroscopy and thermal sensors. PMID:21427720

High-resolution reconstruction for terahertz imaging.

PubMed

Xu, Li-Min; Fan, Wen-Hui; Liu, Jia

2014-11-20

We present a high-resolution (HR) reconstruction model and algorithms for terahertz imaging, taking advantage of super-resolution methodology and algorithms. The algorithms used include projection onto a convex sets approach, iterative backprojection approach, Lucy-Richardson iteration, and 2D wavelet decomposition reconstruction. Using the first two HR reconstruction methods, we successfully obtain HR terahertz images with improved definition and lower noise from four low-resolution (LR) 22×24 terahertz images taken from our homemade THz-TDS system at the same experimental conditions with 1.0 mm pixel. Using the last two HR reconstruction methods, we transform one relatively LR terahertz image to a HR terahertz image with decreased noise. This indicates potential application of HR reconstruction methods in terahertz imaging with pulsed and continuous wave terahertz sources.

A kind of color image segmentation algorithm based on super-pixel and PCNN

NASA Astrophysics Data System (ADS)

Xu, GuangZhu; Wang, YaWen; Zhang, Liu; Zhao, JingJing; Fu, YunXia; Lei, BangJun

2018-04-01

Image segmentation is a very important step in the low-level visual computing. Although image segmentation has been studied for many years, there are still many problems. PCNN (Pulse Coupled Neural network) has biological background, when it is applied to image segmentation it can be viewed as a region-based method, but due to the dynamics properties of PCNN, many connectionless neurons will pulse at the same time, so it is necessary to identify different regions for further processing. The existing PCNN image segmentation algorithm based on region growing is used for grayscale image segmentation, cannot be directly used for color image segmentation. In addition, the super-pixel can better reserve the edges of images, and reduce the influences resulted from the individual difference between the pixels on image segmentation at the same time. Therefore, on the basis of the super-pixel, the original PCNN algorithm based on region growing is improved by this paper. First, the color super-pixel image was transformed into grayscale super-pixel image which was used to seek seeds among the neurons that hadn't been fired. And then it determined whether to stop growing by comparing the average of each color channel of all the pixels in the corresponding regions of the color super-pixel image. Experiment results show that the proposed algorithm for the color image segmentation is fast and effective, and has a certain effect and accuracy.

Operating organic light-emitting diodes imaged by super-resolution spectroscopy

DOE Office of Scientific and Technical Information (OSTI.GOV)

King, John T.; Granick, Steve

Super-resolution stimulated emission depletion (STED) microscopy is adapted here for materials characterization that would not otherwise be possible. With the example of organic light-emitting diodes (OLEDs), spectral imaging with pixel-by-pixel wavelength discrimination allows us to resolve local-chain environment encoded in the spectral response of the semi-conducting polymer, and correlate chain packing with local electroluminescence by using externally applied current as the excitation source. We observe nanoscopic defects that would be unresolvable by traditional microscopy. They are revealed in electroluminescence maps in operating OLEDs with 50 nm spatial resolution. We find that brightest emission comes from regions with more densely packedmore » chains. Conventional microscopy of an operating OLED would lack the resolution needed to discriminate these features, while traditional methods to resolve nanoscale features generally cannot be performed when the device is operating. As a result, this points the way towards real-time analysis of materials design principles in devices as they actually operate.« less

Operating organic light-emitting diodes imaged by super-resolution spectroscopy

DOE PAGES

King, John T.; Granick, Steve

2016-06-21

Super-resolution stimulated emission depletion (STED) microscopy is adapted here for materials characterization that would not otherwise be possible. With the example of organic light-emitting diodes (OLEDs), spectral imaging with pixel-by-pixel wavelength discrimination allows us to resolve local-chain environment encoded in the spectral response of the semi-conducting polymer, and correlate chain packing with local electroluminescence by using externally applied current as the excitation source. We observe nanoscopic defects that would be unresolvable by traditional microscopy. They are revealed in electroluminescence maps in operating OLEDs with 50 nm spatial resolution. We find that brightest emission comes from regions with more densely packedmore » chains. Conventional microscopy of an operating OLED would lack the resolution needed to discriminate these features, while traditional methods to resolve nanoscale features generally cannot be performed when the device is operating. As a result, this points the way towards real-time analysis of materials design principles in devices as they actually operate.« less

Spatial super-resolution of colored images by micro mirrors

NASA Astrophysics Data System (ADS)

Dahan, Daniel; Yaacobi, Ami; Pinsky, Ephraim; Zalevsky, Zeev

2018-06-01

In this paper, we present two methods of dealing with the geometric resolution limit of color imaging sensors. It is possible to overcome the pixel size limit by adding a digital micro-mirror device component on the intermediate image plane of an optical system, and adapting its pattern in a computerized manner before sampling each frame. The full RGB image can be reconstructed from the Bayer camera by building a dedicated optical design, or by adjusting the demosaicing process to the special format of the enhanced image.

Comparison of Confocal and Super-Resolution Reflectance Imaging of Metal Oxide Nanoparticles

PubMed Central

Guggenheim, Emily J.; Khan, Abdullah; Pike, Jeremy; Chang, Lynne; Lynch, Iseult; Rappoport, Joshua Z.

2016-01-01

The potential for human exposure to manufactured nanoparticles (NPs) has increased in recent years, in part through the incorporation of engineered particles into a wide range of commercial goods and medical applications. NP are ideal candidates for use as therapeutic and diagnostic tools within biomedicine, however concern exists regarding their efficacy and safety. Thus, developing techniques for the investigation of NP uptake into cells is critically important. Current intracellular NP investigations rely on the use of either Transmission Electron Microscopy (TEM), which provides ultrahigh resolution, but involves cumbersome sample preparation rendering the technique incompatible with live cell imaging, or fluorescent labelling, which suffers from photobleaching, poor bioconjugation and, often, alteration of NP surface properties. Reflected light imaging provides an alternative non-destructive label free technique well suited, but not limited to, the visualisation of NP uptake within model systems, such as cells. Confocal reflectance microscopy provides optical sectioning and live imaging capabilities, with little sample preparation. However confocal microscopy is diffraction limited, thus the X-Y resolution is restricted to ~250 nm, substantially larger than the <100 nm size of NPs. Techniques such as super-resolution light microscopy overcome this fundamental limitation, providing increased X-Y resolution. The use of Reflectance SIM (R-SIM) for NP imaging has previously only been demonstrated on custom built microscopes, restricting the widespread use and limiting NP investigations. This paper demonstrates the use of a commercial SIM microscope for the acquisition of super-resolution reflectance data with X-Y resolution of 115 nm, a greater than two-fold increase compared to that attainable with RCM. This increase in resolution is advantageous for visualising small closely spaced structures, such as NP clusters, previously unresolvable by RCM. This is advantageous when investigating the subcellular trafficking of NP within fluorescently labelled cellular compartments. NP signal can be observed using RCM, R-SIM and TEM and a direct comparison is presented. Each of these techniques has its own benefits and limitations; RCM and R-SIM provide novel complementary information while the combination of modalities provides a unique opportunity to gain additional information regarding NP uptake. The use of multiple imaging methods therefore greatly enhances the range of NPs that can be studied under label-free conditions. PMID:27695038

Framework for Detection and Localization of Extreme Climate Event with Pixel Recursive Super Resolution

NASA Astrophysics Data System (ADS)

Kim, S. K.; Lee, J.; Zhang, C.; Ames, S.; Williams, D. N.

2017-12-01

Deep learning techniques have been successfully applied to solve many problems in climate and geoscience using massive-scaled observed and modeled data. For extreme climate event detections, several models based on deep neural networks have been recently proposed and attend superior performance that overshadows all previous handcrafted expert based method. The issue arising, though, is that accurate localization of events requires high quality of climate data. In this work, we propose framework capable of detecting and localizing extreme climate events in very coarse climate data. Our framework is based on two models using deep neural networks, (1) Convolutional Neural Networks (CNNs) to detect and localize extreme climate events, and (2) Pixel recursive recursive super resolution model to reconstruct high resolution climate data from low resolution climate data. Based on our preliminary work, we have presented two CNNs in our framework for different purposes, detection and localization. Our results using CNNs for extreme climate events detection shows that simple neural nets can capture the pattern of extreme climate events with high accuracy from very coarse reanalysis data. However, localization accuracy is relatively low due to the coarse resolution. To resolve this issue, the pixel recursive super resolution model reconstructs the resolution of input of localization CNNs. We present a best networks using pixel recursive super resolution model that synthesizes details of tropical cyclone in ground truth data while enhancing their resolution. Therefore, this approach not only dramat- ically reduces the human effort, but also suggests possibility to reduce computing cost required for downscaling process to increase resolution of data.

Temporally flickering nanoparticles for compound cellular imaging and super resolution

NASA Astrophysics Data System (ADS)

Ilovitsh, Tali; Danan, Yossef; Meir, Rinat; Meiri, Amihai; Zalevsky, Zeev

2016-03-01

This work presents the use of flickering nanoparticles for imaging biological samples. The method has high noise immunity, and it enables the detection of overlapping types of GNPs, at significantly sub-diffraction distances, making it attractive for super resolving localization microscopy techniques. The method utilizes a lock-in technique at which the imaging of the sample is done using a time-modulated laser beam that match the number of the types of gold nanoparticles (GNPs) that label a given sample, and resulting in the excitation of the temporal flickering of the scattered light at known temporal frequencies. The final image where the GNPs are spatially separated is obtained using post processing where the proper spectral components corresponding to the different modulation frequencies are extracted. This allows the simultaneous super resolved imaging of multiple types of GNPs that label targets of interest within biological samples. Additionally applying the post-processing algorithm of the K-factor image decomposition algorithm can further improve the performance of the proposed approach.

Acoustic superlens using Helmholtz-resonator-based metamaterials

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yang, Xishan; Yin, Jing; Yu, Gaokun, E-mail: gkyu@ouc.edu.cn

2015-11-09

Acoustic superlens provides a way to overcome the diffraction limit with respect to the wavelength of the bulk wave in air. However, the operating frequency range of subwavelength imaging is quite narrow. Here, an acoustic superlens is designed using Helmholtz-resonator-based metamaterials to broaden the bandwidth of super-resolution. An experiment is carried out to verify subwavelength imaging of double slits, the imaging of which can be well resolved in the frequency range from 570 to 650 Hz. Different from previous works based on the Fabry-Pérot resonance, the corresponding mechanism of subwavelength imaging is the Fano resonance, and the strong coupling between themore » neighbouring Helmholtz resonators separated at the subwavelength interval leads to the enhanced sound transmission over a relatively wide frequency range.« less

Optimization of super-resolution processing using incomplete image sets in PET imaging.

PubMed

Chang, Guoping; Pan, Tinsu; Clark, John W; Mawlawi, Osama R

2008-12-01

Super-resolution (SR) techniques are used in PET imaging to generate a high-resolution image by combining multiple low-resolution images that have been acquired from different points of view (POVs). The number of low-resolution images used defines the processing time and memory storage necessary to generate the SR image. In this paper, the authors propose two optimized SR implementations (ISR-1 and ISR-2) that require only a subset of the low-resolution images (two sides and diagonal of the image matrix, respectively), thereby reducing the overall processing time and memory storage. In an N x N matrix of low-resolution images, ISR-1 would be generated using images from the two sides of the N x N matrix, while ISR-2 would be generated from images across the diagonal of the image matrix. The objective of this paper is to investigate whether the two proposed SR methods can achieve similar performance in contrast and signal-to-noise ratio (SNR) as the SR image generated from a complete set of low-resolution images (CSR) using simulation and experimental studies. A simulation, a point source, and a NEMA/IEC phantom study were conducted for this investigation. In each study, 4 (2 x 2) or 16 (4 x 4) low-resolution images were reconstructed from the same acquired data set while shifting the reconstruction grid to generate images from different POVs. SR processing was then applied in each study to combine all as well as two different subsets of the low-resolution images to generate the CSR, ISR-1, and ISR-2 images, respectively. For reference purpose, a native reconstruction (NR) image using the same matrix size as the three SR images was also generated. The resultant images (CSR, ISR-1, ISR-2, and NR) were then analyzed using visual inspection, line profiles, SNR plots, and background noise spectra. The simulation study showed that the contrast and the SNR difference between the two ISR images and the CSR image were on average 0.4% and 0.3%, respectively. Line profiles of the point source study showed that the three SR images exhibited similar signal amplitudes and FWHM. The NEMA/IEC study showed that the average difference in SNR among the three SR images was 2.1% with respect to one another and they contained similar noise structure. ISR-1 and ISR-2 can be used to replace CSR, thereby reducing the total SR processing time and memory storage while maintaining similar contrast, resolution, SNR, and noise structure.

Super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging

NASA Astrophysics Data System (ADS)

Wei, Lu; Zhu, Xinxin; Chen, Zhixing; Min, Wei

2014-02-01

Two-photon excited fluorescence microscopy (TPFM) offers the highest penetration depth with subcellular resolution in light microscopy, due to its unique advantage of nonlinear excitation. However, a fundamental imaging-depth limit, accompanied by a vanishing signal-to-background contrast, still exists for TPFM when imaging deep into scattering samples. Formally, the focusing depth, at which the in-focus signal and the out-of-focus background are equal to each other, is defined as the fundamental imaging-depth limit. To go beyond this imaging-depth limit of TPFM, we report a new class of super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging, including multiphoton activation and imaging (MPAI) harnessing novel photo-activatable fluorophores, stimulated emission reduced fluorescence (SERF) microscopy by adding a weak laser beam for stimulated emission, and two-photon induced focal saturation imaging with preferential depletion of ground-state fluorophores at focus. The resulting image contrasts all exhibit a higher-order (third- or fourth- order) nonlinear signal dependence on laser intensity than that in the standard TPFM. Both the physical principles and the imaging demonstrations will be provided for each super-nonlinear microscopy. In all these techniques, the created super-nonlinearity significantly enhances the imaging contrast and concurrently extends the imaging depth-limit of TPFM. Conceptually different from conventional multiphoton processes mediated by virtual states, our strategy constitutes a new class of fluorescence microscopy where high-order nonlinearity is mediated by real population transfer.

A New Sparse Representation Framework for Reconstruction of an Isotropic High Spatial Resolution MR Volume From Orthogonal Anisotropic Resolution Scans.

PubMed

Jia, Yuanyuan; Gholipour, Ali; He, Zhongshi; Warfield, Simon K

2017-05-01

In magnetic resonance (MR), hardware limitations, scan time constraints, and patient movement often result in the acquisition of anisotropic 3-D MR images with limited spatial resolution in the out-of-plane views. Our goal is to construct an isotropic high-resolution (HR) 3-D MR image through upsampling and fusion of orthogonal anisotropic input scans. We propose a multiframe super-resolution (SR) reconstruction technique based on sparse representation of MR images. Our proposed algorithm exploits the correspondence between the HR slices and the low-resolution (LR) sections of the orthogonal input scans as well as the self-similarity of each input scan to train pairs of overcomplete dictionaries that are used in a sparse-land local model to upsample the input scans. The upsampled images are then combined using wavelet fusion and error backprojection to reconstruct an image. Features are learned from the data and no extra training set is needed. Qualitative and quantitative analyses were conducted to evaluate the proposed algorithm using simulated and clinical MR scans. Experimental results show that the proposed algorithm achieves promising results in terms of peak signal-to-noise ratio, structural similarity image index, intensity profiles, and visualization of small structures obscured in the LR imaging process due to partial volume effects. Our novel SR algorithm outperforms the nonlocal means (NLM) method using self-similarity, NLM method using self-similarity and image prior, self-training dictionary learning-based SR method, averaging of upsampled scans, and the wavelet fusion method. Our SR algorithm can reduce through-plane partial volume artifact by combining multiple orthogonal MR scans, and thus can potentially improve medical image analysis, research, and clinical diagnosis.

High-Resolution Millimeter-VLBI Imaging of the super-massive black hole candidate at the Galactic center - Sgr A*

NASA Astrophysics Data System (ADS)

Shen, Zqs

Sagittarius A* (Sgr A*), the extremely compact radio source at the Galactic center (GC), is the best candidate for the single super-massive black hole (SMBH). The accurate measurements of its mass (as a gravitational source) and size (as a radiative source) are of great importance in testing its SMBH hypothesis. Great progress has been made on determining its central dark mass of 3.7 million solar masses. Here, we will present the highest resolution VLBI imaging observations of Sgr A* made at both 7.0 and 3.5 millimeters with the Very Long Baseline Array (VLBA) plus the Green Bank Telescope (GBT) and the VLBA, respectively. Both the imaging and the model-fitting with the closure amplitudes show a consistent East-West elongated elliptical Gaussian emission. The inferred possible intrinsic emitting region is less than 1 AU at the distance of 8 kpc to GC.

Sequential Super-Resolution Imaging of Bacterial Regulatory Proteins: The Nucleoid and the Cell Membrane in Single, Fixed E. coli Cells.

PubMed

Spahn, Christoph; Glaesmann, Mathilda; Gao, Yunfeng; Foo, Yong Hwee; Lampe, Marko; Kenney, Linda J; Heilemann, Mike

2017-01-01

Despite their small size and the lack of compartmentalization, bacteria exhibit a striking degree of cellular organization, both in time and space. During the last decade, a group of new microscopy techniques emerged, termed super-resolution microscopy or nanoscopy, which facilitate visualizing the organization of proteins in bacteria at the nanoscale. Single-molecule localization microscopy (SMLM) is especially well suited to reveal a wide range of new information regarding protein organization, interaction, and dynamics in single bacterial cells. Recent developments in click chemistry facilitate the visualization of bacterial chromatin with a resolution of ~20 nm, providing valuable information about the ultrastructure of bacterial nucleoids, especially at short generation times. In this chapter, we describe a simple-to-realize protocol that allows determining precise structural information of bacterial nucleoids in fixed cells, using direct stochastic optical reconstruction microscopy (dSTORM). In combination with quantitative photoactivated localization microscopy (PALM), the spatial relationship of proteins with the bacterial chromosome can be studied. The position of a protein of interest with respect to the nucleoids and the cell cylinder can be visualized by super-resolving the membrane using point accumulation for imaging in nanoscale topography (PAINT). The combination of the different SMLM techniques in a sequential workflow maximizes the information that can be extracted from single cells, while maintaining optimal imaging conditions for each technique.

Bright monomeric photoactivatable red fluorescent protein for two-color super-resolution sptPALM of live cells.

PubMed

Subach, Fedor V; Patterson, George H; Renz, Malte; Lippincott-Schwartz, Jennifer; Verkhusha, Vladislav V

2010-05-12

Rapidly emerging techniques of super-resolution single-molecule microscopy of living cells rely on the continued development of genetically encoded photoactivatable fluorescent proteins. On the basis of monomeric TagRFP, we have developed a photoactivatable TagRFP protein that is initially dark but becomes red fluorescent after violet light irradiation. Compared to other monomeric dark-to-red photoactivatable proteins including PAmCherry, PATagRFP has substantially higher molecular brightness, better pH stability, substantially less sensitivity to blue light, and better photostability in both ensemble and single-molecule modes. Spectroscopic analysis suggests that PATagRFP photoactivation is a two-step photochemical process involving sequential one-photon absorbance by two distinct chromophore forms. True monomeric behavior, absence of green fluorescence, and single-molecule performance in live cells make PATagRFP an excellent protein tag for two-color imaging techniques, including conventional diffraction-limited photoactivation microscopy, super-resolution photoactivated localization microscopy (PALM), and single particle tracking PALM (sptPALM) of living cells. Two-color sptPALM imaging was demonstrated using several PATagRFP tagged transmembrane proteins together with PAGFP-tagged clathrin light chain. Analysis of the resulting sptPALM images revealed that single-molecule transmembrane proteins, which are internalized into a cell via endocytosis, colocalize in space and time with plasma membrane domains enriched in clathrin light-chain molecules.

Super-resolution microscopy as a potential approach to diagnosis of platelet granule disorders.

PubMed

Westmoreland, D; Shaw, M; Grimes, W; Metcalf, D J; Burden, J J; Gomez, K; Knight, A E; Cutler, D F

2016-04-01

Many platelet functions are dependent on bioactive molecules released from their granules. Deficiencies of these granules in number, shape or content are associated with bleeding. The small size of these granules is such that imaging them for diagnosis has traditionally required electron microscopy. However, recently developed super-resolution microscopes provide sufficient spatial resolution to effectively image platelet granules. When combined with automated image analysis, these methods provide a quantitative, unbiased, rapidly acquired dataset that can readily and reliably reveal differences in platelet granules between individuals. To demonstrate the ability of structured illumination microscopy (SIM) to efficiently differentiate between healthy volunteers and three patients with Hermansky-Pudlak syndrome. Blood samples were taken from three patients with Hermansky-Pudlak syndrome and seven controls. Patients 1-3 have gene defects in HPS1, HPS6 and HPS5, respectively; all controls were healthy volunteers. Platelet-rich plasma was isolated from blood and the platelets fixed, stained for CD63 and processed for analysis by immunofluorescence microscopy, using a custom-built SIM microscope. SIM can successfully resolve CD63-positive structures in fixed platelets. A determination of the number of CD63-positive structures per platelet allowed us to conclude that each patient was significantly different from all of the controls with 99% confidence. A super-resolution imaging approach is effective and rapid in objectively differentiating between patients with a platelet bleeding disorder and healthy volunteers. CD63 is a useful marker for predicting Hermansky-Pudlak syndrome and could be used in the diagnosis of patients suspected of other platelet granule disorders. © 2016 The Authors. Journal of Thrombosis and Haemostasis published by Wiley Periodicals, Inc. on behalf of International Society on Thrombosis and Haemostasis.

Optimizing Imaging Conditions for Demanding Multi-Color Super Resolution Localization Microscopy

PubMed Central

Nahidiazar, Leila; Agronskaia, Alexandra V.; Broertjes, Jorrit; van den Broek, Bram; Jalink, Kees

2016-01-01

Single Molecule Localization super-resolution Microscopy (SMLM) has become a powerful tool to study cellular architecture at the nanometer scale. In SMLM, single fluorophore labels are made to repeatedly switch on and off (“blink”), and their exact locations are determined by mathematically finding the centers of individual blinks. The image quality obtainable by SMLM critically depends on efficacy of blinking (brightness, fraction of molecules in the on-state) and on preparation longevity and labeling density. Recent work has identified several combinations of bright dyes and imaging buffers that work well together. Unfortunately, different dyes blink optimally in different imaging buffers, and acquisition of good quality 2- and 3-color images has therefore remained challenging. In this study we describe a new imaging buffer, OxEA, that supports 3-color imaging of the popular Alexa dyes. We also describe incremental improvements in preparation technique that significantly decrease lateral- and axial drift, as well as increase preparation longevity. We show that these improvements allow us to collect very large series of images from the same cell, enabling image stitching, extended 3D imaging as well as multi-color recording. PMID:27391487

Superlensing effect for surface acoustic waves in a pillar-based phononic crystal with negative refractive index

DOE Office of Scientific and Technical Information (OSTI.GOV)

Addouche, Mahmoud, E-mail: mamoud.addouche@femto-st.fr; Al-Lethawe, Mohammed A., E-mail: mohammed.abdulridha@femto-st.fr; Choujaa, Abdelkrim, E-mail: achoujaa@femto-st.fr

2014-07-14

We demonstrate super resolution imaging for surface acoustic waves using a phononic structure displaying negative refractive index. This phononic structure is made of a monolithic square lattice of cylindrical pillars standing on a semi-infinite medium. The pillars act as acoustic resonator and induce a surface propagating wave with unusual dispersion. We found, under specific geometrical parameters, one propagating mode that exhibits negative refraction effect with negative effective index close to −1. Furthermore, a flat lens with finite number of pillars is designed to allow the focusing of an acoustic point source into an image with a resolution of (λ)/3 ,more » overcoming the Rayleigh diffraction limit.« less

Painting Supramolecular Polymers in Organic Solvents by Super-resolution Microscopy

PubMed Central

2018-01-01

Despite the rapid development of complex functional supramolecular systems, visualization of these architectures under native conditions at high resolution has remained a challenging endeavor. Super-resolution microscopy was recently proposed as an effective tool to unveil one-dimensional nanoscale structures in aqueous media upon chemical functionalization with suitable fluorescent probes. Building upon our previous work, which enabled photoactivation localization microscopy in organic solvents, herein, we present the imaging of one-dimensional supramolecular polymers in their native environment by interface point accumulation for imaging in nanoscale topography (iPAINT). The noncovalent staining, typical of iPAINT, allows the investigation of supramolecular polymers’ structure in situ without any chemical modification. The quasi-permanent adsorption of the dye to the polymer is exploited to identify block-like arrangements within supramolecular fibers, which were obtained upon mixing homopolymers that were prestained with different colors. The staining of the blocks, maintained by the lack of exchange of the dyes, permits the imaging of complex structures for multiple days. This study showcases the potential of PAINT-like strategies such as iPAINT to visualize multicomponent dynamic systems in their native environment with an easy, synthesis-free approach and high spatial resolution. PMID:29697958

Providing Internet Access to High-Resolution Lunar Images

NASA Technical Reports Server (NTRS)

Plesea, Lucian

2008-01-01

The OnMoon server is a computer program that provides Internet access to high-resolution Lunar images, maps, and elevation data, all suitable for use in geographical information system (GIS) software for generating images, maps, and computational models of the Moon. The OnMoon server implements the Open Geospatial Consortium (OGC) Web Map Service (WMS) server protocol and supports Moon-specific extensions. Unlike other Internet map servers that provide Lunar data using an Earth coordinate system, the OnMoon server supports encoding of data in Moon-specific coordinate systems. The OnMoon server offers access to most of the available high-resolution Lunar image and elevation data. This server can generate image and map files in the tagged image file format (TIFF) or the Joint Photographic Experts Group (JPEG), 8- or 16-bit Portable Network Graphics (PNG), or Keyhole Markup Language (KML) format. Image control is provided by use of the OGC Style Layer Descriptor (SLD) protocol. Full-precision spectral arithmetic processing is also available, by use of a custom SLD extension. This server can dynamically add shaded relief based on the Lunar elevation to any image layer. This server also implements tiled WMS protocol and super-overlay KML for high-performance client application programs.

Downscaling remotely sensed imagery using area-to-point cokriging and multiple-point geostatistical simulation

NASA Astrophysics Data System (ADS)

Tang, Yunwei; Atkinson, Peter M.; Zhang, Jingxiong

2015-03-01

A cross-scale data integration method was developed and tested based on the theory of geostatistics and multiple-point geostatistics (MPG). The goal was to downscale remotely sensed images while retaining spatial structure by integrating images at different spatial resolutions. During the process of downscaling, a rich spatial correlation model in the form of a training image was incorporated to facilitate reproduction of similar local patterns in the simulated images. Area-to-point cokriging (ATPCK) was used as locally varying mean (LVM) (i.e., soft data) to deal with the change of support problem (COSP) for cross-scale integration, which MPG cannot achieve alone. Several pairs of spectral bands of remotely sensed images were tested for integration within different cross-scale case studies. The experiment shows that MPG can restore the spatial structure of the image at a fine spatial resolution given the training image and conditioning data. The super-resolution image can be predicted using the proposed method, which cannot be realised using most data integration methods. The results show that ATPCK-MPG approach can achieve greater accuracy than methods which do not account for the change of support issue.

Optimized protocol for combined PALM-dSTORM imaging.

PubMed

Glushonkov, O; Réal, E; Boutant, E; Mély, Y; Didier, P

2018-06-08

Multi-colour super-resolution localization microscopy is an efficient technique to study a variety of intracellular processes, including protein-protein interactions. This technique requires specific labels that display transition between fluorescent and non-fluorescent states under given conditions. For the most commonly used label types, photoactivatable fluorescent proteins and organic fluorophores, these conditions are different, making experiments that combine both labels difficult. Here, we demonstrate that changing the standard imaging buffer of thiols/oxygen scavenging system, used for organic fluorophores, to the commercial mounting medium Vectashield increased the number of photons emitted by the fluorescent protein mEos2 and enhanced the photoconversion rate between its green and red forms. In addition, the photophysical properties of organic fluorophores remained unaltered with respect to the standard imaging buffer. The use of Vectashield together with our optimized protocol for correction of sample drift and chromatic aberrations enabled us to perform two-colour 3D super-resolution imaging of the nucleolus and resolve its three compartments.

Planar super-oscillatory lens for sub-diffraction optical needles at violet wavelengths

PubMed Central

Yuan, Guanghui; Rogers, Edward T. F.; Roy, Tapashree; Adamo, Giorgio; Shen, Zexiang; Zheludev, Nikolay I.

2014-01-01

Planar optical lenses are fundamental elements of miniaturized photonic devices. However, conventional planar optical lenses are constrained by the diffraction limit in the optical far-field due to the band-limited wavevectors supported by free-space and loss of high-spatial-frequency evanescent components. As inspired by Einstein's radiation ‘needle stick', electromagnetic energy can be delivered into an arbitrarily small solid angle. Such sub-diffraction optical needles have been numerically investigated using diffractive optical elements (DOEs) together with specially polarized optical beams, but experimental demonstration is extremely difficult due to the bulky size of DOEs and the required alignment precision. Planar super-oscillatory lenses (SOLs) were proposed to overcome these constraints and demonstrated that sub-diffraction focal spots can actually be formed without any evanescent waves, making far-field, label-free super-resolution imaging possible. Here we extend the super-oscillation concept into the vectorial-field regime to work with circularly polarized light, and experimentally demonstrate, for the first time, a circularly polarized optical needle with sub-diffraction transverse spot size (0.45λ) and axial long depth of focus (DOF) of 15λ using a planar SOL at a violet wavelength of 405 nm. This sub-diffraction circularly polarized optical needle has potential applications in circular dichroism spectroscopy, super-resolution imaging, high-density optical storage, heat-assisted magnetic recording, nano-manufacturing and nano-metrology. PMID:25208611

A Guide to Structured Illumination TIRF Microscopy at High Speed with Multiple Colors

PubMed Central

Young, Laurence J.; Ströhl, Florian; Kaminski, Clemens F.

2016-01-01

Optical super-resolution imaging with structured illumination microscopy (SIM) is a key technology for the visualization of processes at the molecular level in the chemical and biomedical sciences. Although commercial SIM systems are available, systems that are custom designed in the laboratory can outperform commercial systems, the latter typically designed for ease of use and general purpose applications, both in terms of imaging fidelity and speed. This article presents an in-depth guide to building a SIM system that uses total internal reflection (TIR) illumination and is capable of imaging at up to 10 Hz in three colors at a resolution reaching 100 nm. Due to the combination of SIM and TIRF, the system provides better image contrast than rival technologies. To achieve these specifications, several optical elements are used to enable automated control over the polarization state and spatial structure of the illumination light for all available excitation wavelengths. Full details on hardware implementation and control are given to achieve synchronization between excitation light pattern generation, wavelength, polarization state, and camera control with an emphasis on achieving maximum acquisition frame rate. A step-by-step protocol for system alignment and calibration is presented and the achievable resolution improvement is validated on ideal test samples. The capability for video-rate super-resolution imaging is demonstrated with living cells. PMID:27285848

A multi-emitter fitting algorithm for potential live cell super-resolution imaging over a wide range of molecular densities.

PubMed

Takeshima, T; Takahashi, T; Yamashita, J; Okada, Y; Watanabe, S

2018-05-25

Multi-emitter fitting algorithms have been developed to improve the temporal resolution of single-molecule switching nanoscopy, but the molecular density range they can analyse is narrow and the computation required is intensive, significantly limiting their practical application. Here, we propose a computationally fast method, wedged template matching (WTM), an algorithm that uses a template matching technique to localise molecules at any overlapping molecular density from sparse to ultrahigh density with subdiffraction resolution. WTM achieves the localization of overlapping molecules at densities up to 600 molecules μm -2 with a high detection sensitivity and fast computational speed. WTM also shows localization precision comparable with that of DAOSTORM (an algorithm for high-density super-resolution microscopy), at densities up to 20 molecules μm -2 , and better than DAOSTORM at higher molecular densities. The application of WTM to a high-density biological sample image demonstrated that it resolved protein dynamics from live cell images with subdiffraction resolution and a temporal resolution of several hundred milliseconds or less through a significant reduction in the number of camera images required for a high-density reconstruction. WTM algorithm is a computationally fast, multi-emitter fitting algorithm that can analyse over a wide range of molecular densities. The algorithm is available through the website. https://doi.org/10.17632/bf3z6xpn5j.1. © 2018 The Authors. Journal of Microscopy published by JohnWiley & Sons Ltd on behalf of Royal Microscopical Society.

Super-pixel extraction based on multi-channel pulse coupled neural network

NASA Astrophysics Data System (ADS)

Xu, GuangZhu; Hu, Song; Zhang, Liu; Zhao, JingJing; Fu, YunXia; Lei, BangJun

2018-04-01

Super-pixel extraction techniques group pixels to form over-segmented image blocks according to the similarity among pixels. Compared with the traditional pixel-based methods, the image descripting method based on super-pixel has advantages of less calculation, being easy to perceive, and has been widely used in image processing and computer vision applications. Pulse coupled neural network (PCNN) is a biologically inspired model, which stems from the phenomenon of synchronous pulse release in the visual cortex of cats. Each PCNN neuron can correspond to a pixel of an input image, and the dynamic firing pattern of each neuron contains both the pixel feature information and its context spatial structural information. In this paper, a new color super-pixel extraction algorithm based on multi-channel pulse coupled neural network (MPCNN) was proposed. The algorithm adopted the block dividing idea of SLIC algorithm, and the image was divided into blocks with same size first. Then, for each image block, the adjacent pixels of each seed with similar color were classified as a group, named a super-pixel. At last, post-processing was adopted for those pixels or pixel blocks which had not been grouped. Experiments show that the proposed method can adjust the number of superpixel and segmentation precision by setting parameters, and has good potential for super-pixel extraction.

A practical approach to superresolution

NASA Astrophysics Data System (ADS)

Farsiu, Sina; Elad, Michael; Milanfar, Peyman

2006-01-01

Theoretical and practical limitations usually constrain the achievable resolution of any imaging device. Super-Resolution (SR) methods are developed through the years to go beyond this limit by acquiring and fusing several low-resolution (LR) images of the same scene, producing a high-resolution (HR) image. The early works on SR, although occasionally mathematically optimal for particular models of data and noise, produced poor results when applied to real images. In this paper, we discuss two of the main issues related to designing a practical SR system, namely reconstruction accuracy and computational efficiency. Reconstruction accuracy refers to the problem of designing a robust SR method applicable to images from different imaging systems. We study a general framework for optimal reconstruction of images from grayscale, color, or color filtered (CFA) cameras. The performance of our proposed method is boosted by using powerful priors and is robust to both measurement (e.g. CCD read out noise) and system noise (e.g. motion estimation error). Noting that the motion estimation is often considered a bottleneck in terms of SR performance, we introduce the concept of "constrained motions" for enhancing the quality of super-resolved images. We show that using such constraints will enhance the quality of the motion estimation and therefore results in more accurate reconstruction of the HR images. We also justify some practical assumptions that greatly reduce the computational complexity and memory requirements of the proposed methods. We use efficient approximation of the Kalman Filter (KF) and adopt a dynamic point of view to the SR problem. Novel methods for addressing these issues are accompanied by experimental results on real data.

High-resolution coded-aperture design for compressive X-ray tomography using low resolution detectors

NASA Astrophysics Data System (ADS)

Mojica, Edson; Pertuz, Said; Arguello, Henry

2017-12-01

One of the main challenges in Computed Tomography (CT) is obtaining accurate reconstructions of the imaged object while keeping a low radiation dose in the acquisition process. In order to solve this problem, several researchers have proposed the use of compressed sensing for reducing the amount of measurements required to perform CT. This paper tackles the problem of designing high-resolution coded apertures for compressed sensing computed tomography. In contrast to previous approaches, we aim at designing apertures to be used with low-resolution detectors in order to achieve super-resolution. The proposed method iteratively improves random coded apertures using a gradient descent algorithm subject to constraints in the coherence and homogeneity of the compressive sensing matrix induced by the coded aperture. Experiments with different test sets show consistent results for different transmittances, number of shots and super-resolution factors.

Effects of immersion depth on super-resolution properties of index-different microsphere-assisted nanoimaging

NASA Astrophysics Data System (ADS)

Zhou, Yi; Tang, Yan; He, Yu; Liu, Xi; Hu, Song

2018-03-01

In related applications of microsphere-assisted super-resolution imaging in biomedical visualization and microfluidic detection, liquids are widely used as background media. For the first time, we quantitatively demonstrate that the maximum irradiances, focal lengths, and waists of photonic nanojets (PNJs) will logically vary with different immersion depths (IMDs). The experimental observations also numerically illustrate the trends of the lateral magnification and field of view (FOV) with the gradual evaporation of ethyl alcohol. This work can provide exact quantitative information for the proper selection of microspheres and IMD for the high-quality discernment of nanostructures.

Analytical SuperSTEM for extraterrestrial materials research

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bradley, J P; Dai, Z R

2009-09-08

Electron-beam studies of extraterrestrial materials with significantly improved spatial resolution, energy resolution and sensitivity are enabled using a 300 keV SuperSTEM scanning transmission electron microscope with a monochromator and two spherical aberration correctors. The improved technical capabilities enable analyses previously not possible. Mineral structures can be directly imaged and analyzed with single-atomic-column resolution, liquids and implanted gases can be detected, and UV-VIS optical properties can be measured. Detection limits for minor/trace elements in thin (<100 nm thick) specimens are improved such that quantitative measurements of some extend to the sub-500 ppm level. Electron energy-loss spectroscopy (EELS) can be carried outmore » with 0.10-0.20 eV energy resolution and atomic-scale spatial resolution such that variations in oxidation state from one atomic column to another can be detected. Petrographic mapping is extended down to the atomic scale using energy-dispersive x-ray spectroscopy (EDS) and energy-filtered transmission electron microscopy (EFTEM) imaging. Technical capabilities and examples of the applications of SuperSTEM to extraterrestrial materials are presented, including the UV spectral properties and organic carbon K-edge fine structure of carbonaceous matter in interplanetary dust particles (IDPs), x-ray elemental maps showing the nanometer-scale distribution of carbon within GEMS (glass with embedded metal and sulfides), the first detection and quantification of trace Ti in GEMS using EDS, and detection of molecular H{sub 2}O in vesicles and implanted H{sub 2} and He in irradiated mineral and glass grains.« less

MEMS-Based Handheld Fourier Domain Doppler Optical Coherence Tomography for Intraoperative Microvascular Anastomosis Imaging

PubMed Central

Huang, Yong; Furtmüller, Georg J.; Tong, Dedi; Zhu, Shan; Lee, W. P. Andrew; Brandacher, Gerald; Kang, Jin U.

2014-01-01

Purpose To demonstrate the feasibility of a miniature handheld optical coherence tomography (OCT) imager for real time intraoperative vascular patency evaluation in the setting of super-microsurgical vessel anastomosis. Methods A novel handheld imager Fourier domain Doppler optical coherence tomography based on a 1.3-µm central wavelength swept source for extravascular imaging was developed. The imager was minimized through the adoption of a 2.4-mm diameter microelectromechanical systems (MEMS) scanning mirror, additionally a 12.7-mm diameter lens system was designed and combined with the MEMS mirror to achieve a small form factor that optimize functionality as a handheld extravascular OCT imager. To evaluate in-vivo applicability, super-microsurgical vessel anastomosis was performed in a mouse femoral vessel cut and repair model employing conventional interrupted suture technique as well as a novel non-suture cuff technique. Vascular anastomosis patency after clinically successful repair was evaluated using the novel handheld OCT imager. Results With an adjustable lateral image field of view up to 1.5 mm by 1.5 mm, high-resolution simultaneous structural and flow imaging of the blood vessels were successfully acquired for BALB/C mouse after orthotopic hind limb transplantation using a non-suture cuff technique and BALB/C mouse after femoral artery anastomosis using a suture technique. We experimentally quantify the axial and lateral resolution of the OCT to be 12.6 µm in air and 17.5 µm respectively. The OCT has a sensitivity of 84 dB and sensitivity roll-off of 5.7 dB/mm over an imaging range of 5 mm. Imaging with a frame rate of 36 Hz for an image size of 1000(lateral)×512(axial) pixels using a 50,000 A-lines per second swept source was achieved. Quantitative vessel lumen patency, lumen narrowing and thrombosis analysis were performed based on acquired structure and Doppler images. Conclusions A miniature handheld OCT imager that can be used for intraoperative evaluation of microvascular anastomosis was successfully demonstrated. PMID:25474742

DOE Office of Scientific and Technical Information (OSTI.GOV)

McDonald, A. D.; Jones, B. J. P.; Nygren, D. R.

A new method to tag the barium daughter in the double beta decay ofmore » $$^{136}$$Xe is reported. Using the technique of single molecule fluorescent imaging (SMFI), individual barium dication (Ba$$^{++}$$) resolution at a transparent scanning surface has been demonstrated. A single-step photo-bleach confirms the single ion interpretation. Individual ions are localized with super-resolution ($$\\sim$$2~nm), and detected with a statistical significance of 12.9~$$\\sigma$$ over backgrounds. This lays the foundation for a new and potentially background-free neutrinoless double beta decay technology, based on SMFI coupled to high pressure xenon gas time projection chambers.« less

Quantification of resolution in multiplanar reconstructions for digital breast tomosynthesis

NASA Astrophysics Data System (ADS)

Vent, Trevor L.; Acciavatti, Raymond J.; Kwon, Young Joon; Maidment, Andrew D. A.

2016-03-01

Multiplanar reconstruction (MPR) in digital breast tomosynthesis (DBT) allows tomographic images to be portrayed in various orientations. We have conducted research to determine the resolution of tomosynthesis MPR. We built a phantom that houses a star test pattern to measure resolution. This phantom provides three rotational degrees of freedom. The design consists of two hemispheres with longitudinal and latitudinal grooves that reference angular increments. When joined together, the hemispheres form a dome that sits inside a cylindrical encasement. The cylindrical encasement contains reference notches to match the longitudinal and latitudinal grooves that guide the phantom's rotations. With this design, any orientation of the star-pattern can be analyzed. Images of the star-pattern were acquired using a DBT mammography system at the Hospital of the University of Pennsylvania. Images taken were reconstructed and analyzed by two different methods. First, the maximum visible frequency (in line pairs per millimeter) of the star test pattern was measured. Then, the contrast was calculated at a fixed spatial frequency. These analyses confirm that resolution decreases with tilt relative to the breast support. They also confirm that resolution in tomosynthesis MPR is dependent on object orientation. Current results verify that the existence of super-resolution depends on the orientation of the frequency; the direction parallel to x-ray tube motion shows super-resolution. In conclusion, this study demonstrates that the direction of the spatial frequency relative to the motion of the x-ray tube is a determinant of resolution in MPR for DBT.

GPU-Accelerated Hybrid Algorithm for 3D Localization of Fluorescent Emitters in Dense Clusters

NASA Astrophysics Data System (ADS)

Jung, Yoon; Barsic, Anthony; Piestun, Rafael; Fakhri, Nikta

In stochastic switching-based super-resolution imaging, a random subset of fluorescent emitters are imaged and localized for each frame to construct a single high resolution image. However, the condition of non-overlapping point spread functions (PSFs) imposes constraints on experimental parameters. Recent development in post processing methods such as dictionary-based sparse support recovery using compressive sensing has shown up to an order of magnitude higher recall rate than single emitter fitting methods. However, the computational complexity of this approach scales poorly with the grid size and requires long runtime. Here, we introduce a fast and accurate compressive sensing algorithm for localizing fluorescent emitters in high density in 3D, namely sparse support recovery using Orthogonal Matching Pursuit (OMP) and L1-Homotopy algorithm for reconstructing STORM images (SOLAR STORM). SOLAR STORM combines OMP with L1-Homotopy to reduce computational complexity, which is further accelerated by parallel implementation using GPUs. This method can be used in a variety of experimental conditions for both in vitro and live cell fluorescence imaging.

Super-Resolution Imaging Reveals TCTN2 Depletion-Induced IFT88 Lumen Leakage and Ciliary Weakening.

PubMed

Weng, Rueyhung Roc; Yang, T Tony; Huang, Chia-En; Chang, Chih-Wei; Wang, Won-Jing; Liao, Jung-Chi

2018-06-01

The primary cilium is an essential organelle mediating key signaling activities, such as sonic hedgehog signaling. The molecular composition of the ciliary compartment is distinct from that of the cytosol, with the transition zone (TZ) gated the ciliary base. The TZ is a packed and organized protein complex containing multiple ciliopathy-associated protein species. Tectonic 2 (TCTN2) is one of the TZ proteins in the vicinity of the ciliary membrane, and its mutation is associated with Meckel syndrome. Despite its importance in ciliopathies, the role of TCTN2 in ciliary structure and molecules remains unclear. Here, we created a CRISPR/Cas9 TCTN2 knockout human retinal pigment epithelial cell line and conducted quantitative analysis of geometric localization using both wide-field and super-resolution microscopy techniques. We found that TCTN2 depletion resulted in partial TZ damage, loss of ciliary membrane proteins, leakage of intraflagellar transport protein IFT88 toward the basal body lumen, and cilium shortening and curving. The basal body lumen occupancy of IFT88 was also observed in si-RPGRIP1L cells and cytochalasin-D-treated wild-type cells, suggesting varying lumen accessibility for intraflagellar transport proteins under different perturbed conditions. Our findings support two possible models for the lumen leakage of IFT88, i.e., a tip leakage model and a misregulation model. Together, our quantitative image analysis augmented by super-resolution microscopy facilitates the observation of structural destruction and molecular redistribution in TCTN2 -/- cilia, shedding light on mechanistic understanding of TZ-protein-associated ciliopathies. Copyright © 2018 Biophysical Society. Published by Elsevier Inc. All rights reserved.

Hyperlens-array-implemented optical microscopy

NASA Astrophysics Data System (ADS)

Iwanaga, Masanobu

2014-08-01

Limit of resolution of conventional optical microscopes has never reached below 100 nm under visible light illumination. We show that numerically designed high-transmittance hyperlens array (HLA) is implemented in an optical microscope and works in practice for achieving one-shot-recording optical images of in-situ placed objects with sub 50 nm resolution in lateral direction. Direct resolution test employing well-defined nanopatterns proves that the HLA-implemented imaging is super-resolution optical microscopy, which works even under nW/mm2 visible illumination for objects. The HLA implementation makes the resolution of conventional microscopes one-scale higher, leading to the 1/10 illumination wavelength range, that is, mesoscopic range.

Barnacle Bill in Super Resolution from Insurance Panorama

NASA Technical Reports Server (NTRS)

1998-01-01

Barnacle Bill is a small rock immediately west-northwest of the Mars Pathfinder lander and was the first rock visited by the Sojourner Rover's alpha proton X-ray spectrometer (APXS) instrument. This image shows super resolution techniques applied to the first APXS target rock, which was never imaged with the rover's forward cameras. Super resolution was applied to help to address questions about the texture of this rock and what it might tell us about its mode of origin.

This view of Barnacle Bill was produced by combining the 'Insurance Pan' frames taken while the IMP camera was still in its stowed position on sol2. The composite color frames that make up this anaglyph were produced for both the right and left eye of the IMP. The right eye composite consists of 5 frames, taken with different color filters, the left eye consists of only 1 frame. The resultant image from each eye was enlarged by 500% and then co-added using Adobe Photoshop to produce, in effect, a super-resolution panchromatic frame that is sharper than an individual frame would be. These panchromatic frames were then colorized with the red, green, and blue filtered images from the same sequence. The color balance was adjusted to approximate the true color of Mars.

The anaglyph view was produced by combining the left with the right eye color composite frames by assigning the left eye composite view to the red color plane and the right eye composite view to the green and blue color planes (cyan), to produce a stereo anaglyph mosaic. This mosaic can be viewed in 3-D on your computer monitor or in color print form by wearing red-blue 3-D glasses.

Mars Pathfinder is the second in NASA's Discovery program of low-cost spacecraft with highly focused science goals. Barnacle Bill is a small rock immediately west-northwest of the Mars Pathfinder lander and was the first rock visited by the Sojourner Rover's alpha proton X-ray spectrometer (APXS) instrument.

Efficient Spatiotemporal Clutter Rejection and Nonlinear Filtering-based Dim Resolved and Unresolved Object Tracking Algorithms

NASA Astrophysics Data System (ADS)

Tartakovsky, A.; Tong, M.; Brown, A. P.; Agh, C.

2013-09-01

We develop efficient spatiotemporal image processing algorithms for rejection of non-stationary clutter and tracking of multiple dim objects using non-linear track-before-detect methods. For clutter suppression, we include an innovative image alignment (registration) algorithm. The images are assumed to contain elements of the same scene, but taken at different angles, from different locations, and at different times, with substantial clutter non-stationarity. These challenges are typical for space-based and surface-based IR/EO moving sensors, e.g., highly elliptical orbit or low earth orbit scenarios. The algorithm assumes that the images are related via a planar homography, also known as the projective transformation. The parameters are estimated in an iterative manner, at each step adjusting the parameter vector so as to achieve improved alignment of the images. Operating in the parameter space rather than in the coordinate space is a new idea, which makes the algorithm more robust with respect to noise as well as to large inter-frame disturbances, while operating at real-time rates. For dim object tracking, we include new advancements to a particle non-linear filtering-based track-before-detect (TrbD) algorithm. The new TrbD algorithm includes both real-time full image search for resolved objects not yet in track and joint super-resolution and tracking of individual objects in closely spaced object (CSO) clusters. The real-time full image search provides near-optimal detection and tracking of multiple extremely dim, maneuvering objects/clusters. The super-resolution and tracking CSO TrbD algorithm provides efficient near-optimal estimation of the number of unresolved objects in a CSO cluster, as well as the locations, velocities, accelerations, and intensities of the individual objects. We demonstrate that the algorithm is able to accurately estimate the number of CSO objects and their locations when the initial uncertainty on the number of objects is large. We demonstrate performance of the TrbD algorithm both for satellite-based and surface-based EO/IR surveillance scenarios.

Hierarchical super-structure identified by polarized light microscopy, electron microscopy and nanoindentation: Implications for the limits of biological control over the growth mode of abalone sea shells

PubMed Central

2012-01-01

Background Mollusc shells are commonly investigated using high-resolution imaging techniques based on cryo-fixation. Less detailed information is available regarding the light-optical properties. Sea shells of Haliotis pulcherina were embedded for polishing in defined orientations in order to investigate the interface between prismatic calcite and nacreous aragonite by standard materialographic methods. A polished thin section of the interface was prepared with a defined thickness of 60 μm for quantitative birefringence analysis using polarized light and LC-PolScope microscopy. Scanning electron microscopy images were obtained for comparison. In order to study structural-mechanical relationships, nanoindentation experiments were performed. Results Incident light microscopy revealed a super-structure in semi-transparent regions of the polished cross-section under a defined angle. This super-structure is not visible in transmitted birefringence analysis due to the blurred polarization of small nacre platelets and numerous organic interfaces. The relative orientation and homogeneity of calcite prisms was directly identified, some of them with their optical axes exactly normal to the imaging plane. Co-oriented "prism colonies" were identified by polarized light analyses. The nacreous super-structure was also visualized by secondary electron imaging under defined angles. The domains of the super-structure were interpreted to consist of crystallographically aligned platelet stacks. Nanoindentation experiments showed that mechanical properties changed with the same periodicity as the domain size. Conclusions In this study, we have demonstrated that insights into the growth mechanisms of nacre can be obtained by conventional light-optical methods. For example, we observed super-structures formed by co-oriented nacre platelets as previously identified using X-ray Photo-electron Emission Microscopy (X-PEEM) [Gilbert et al., Journal of the American Chemical Society 2008, 130:17519–17527]. Polarized optical microscopy revealed unprecedented super-structures in the calcitic shell part. This bears, in principle, the potential for in vivo studies, which might be useful for investigating the growth modes of nacre and other shell types. PMID:22967319

Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm

NASA Astrophysics Data System (ADS)

Wang, Yuzhu; Rahman, Sheik S.; Arns, Christoph H.

2018-03-01

X-ray computed tomography (μ-CT) is considered to be the most effective way to obtain the inner structure of rock sample without destructions. However, its limited resolution hampers its ability to probe sub-micro structures which is critical for flow transportation of rock sample. In this study, we propose an innovative methodology to improve the resolution of μ-CT image using neighbour embedding algorithm where low frequency information is provided by μ-CT image itself while high frequency information is supplemented by high resolution scanning electron microscopy (SEM) image. In order to obtain prior for reconstruction, a large number of image patch pairs contain high- and low- image patches are extracted from the Gaussian image pyramid generated by SEM image. These image patch pairs contain abundant information about tomographic evolution of local porous structures under different resolution spaces. Relying on the assumption of self-similarity of porous structure, this prior information can be used to supervise the reconstruction of high resolution μ-CT image effectively. The experimental results show that the proposed method is able to achieve the state-of-the-art performance.

Automatic Near-Real-Time Image Processing Chain for Very High Resolution Optical Satellite Data

NASA Astrophysics Data System (ADS)

Ostir, K.; Cotar, K.; Marsetic, A.; Pehani, P.; Perse, M.; Zaksek, K.; Zaletelj, J.; Rodic, T.

2015-04-01

In response to the increasing need for automatic and fast satellite image processing SPACE-SI has developed and implemented a fully automatic image processing chain STORM that performs all processing steps from sensor-corrected optical images (level 1) to web-delivered map-ready images and products without operator's intervention. Initial development was tailored to high resolution RapidEye images, and all crucial and most challenging parts of the planned full processing chain were developed: module for automatic image orthorectification based on a physical sensor model and supported by the algorithm for automatic detection of ground control points (GCPs); atmospheric correction module, topographic corrections module that combines physical approach with Minnaert method and utilizing anisotropic illumination model; and modules for high level products generation. Various parts of the chain were implemented also for WorldView-2, THEOS, Pleiades, SPOT 6, Landsat 5-8, and PROBA-V. Support of full-frame sensor currently in development by SPACE-SI is in plan. The proposed paper focuses on the adaptation of the STORM processing chain to very high resolution multispectral images. The development concentrated on the sub-module for automatic detection of GCPs. The initially implemented two-step algorithm that worked only with rasterized vector roads and delivered GCPs with sub-pixel accuracy for the RapidEye images, was improved with the introduction of a third step: super-fine positioning of each GCP based on a reference raster chip. The added step exploits the high spatial resolution of the reference raster to improve the final matching results and to achieve pixel accuracy also on very high resolution optical satellite data.

Experimental observation of sub-Rayleigh quantum imaging with a two-photon entangled source

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, De-Qin; School of Science, Tianjin University of Technology and Education, Tianjin 300222; Song, Xin-Bing

It has been theoretically predicted that N-photon quantum imaging can realize either an N-fold resolution improvement (Heisenberg-like scaling) or a √(N)-fold resolution improvement (standard quantum limit) beyond the Rayleigh diffraction bound, over classical imaging. Here, we report the experimental study on spatial sub-Rayleigh quantum imaging using a two-photon entangled source. Two experimental schemes are proposed and performed. In a Fraunhofer diffraction scheme with a lens, two-photon Airy disk pattern is observed with subwavelength diffraction property. In a lens imaging apparatus, however, two-photon sub-Rayleigh imaging for an object is realized with super-resolution property. The experimental results agree with the theoretical predictionmore » in the two-photon quantum imaging regime.« less

Super-resolution for everybody: An image processing workflow to obtain high-resolution images with a standard confocal microscope.

PubMed

Lam, France; Cladière, Damien; Guillaume, Cyndélia; Wassmann, Katja; Bolte, Susanne

2017-02-15

In the presented work we aimed at improving confocal imaging to obtain highest possible resolution in thick biological samples, such as the mouse oocyte. We therefore developed an image processing workflow that allows improving the lateral and axial resolution of a standard confocal microscope. Our workflow comprises refractive index matching, the optimization of microscope hardware parameters and image restoration by deconvolution. We compare two different deconvolution algorithms, evaluate the necessity of denoising and establish the optimal image restoration procedure. We validate our workflow by imaging sub resolution fluorescent beads and measuring the maximum lateral and axial resolution of the confocal system. Subsequently, we apply the parameters to the imaging and data restoration of fluorescently labelled meiotic spindles of mouse oocytes. We measure a resolution increase of approximately 2-fold in the lateral and 3-fold in the axial direction throughout a depth of 60μm. This demonstrates that with our optimized workflow we reach a resolution that is comparable to 3D-SIM-imaging, but with better depth penetration for confocal images of beads and the biological sample. Copyright © 2016 Elsevier Inc. All rights reserved.

Super-Resolution in Plenoptic Cameras Using FPGAs

PubMed Central

Pérez, Joel; Magdaleno, Eduardo; Pérez, Fernando; Rodríguez, Manuel; Hernández, David; Corrales, Jaime

2014-01-01

Plenoptic cameras are a new type of sensor that extend the possibilities of current commercial cameras allowing 3D refocusing or the capture of 3D depths. One of the limitations of plenoptic cameras is their limited spatial resolution. In this paper we describe a fast, specialized hardware implementation of a super-resolution algorithm for plenoptic cameras. The algorithm has been designed for field programmable graphic array (FPGA) devices using VHDL (very high speed integrated circuit (VHSIC) hardware description language). With this technology, we obtain an acceleration of several orders of magnitude using its extremely high-performance signal processing capability through parallelism and pipeline architecture. The system has been developed using generics of the VHDL language. This allows a very versatile and parameterizable system. The system user can easily modify parameters such as data width, number of microlenses of the plenoptic camera, their size and shape, and the super-resolution factor. The speed of the algorithm in FPGA has been successfully compared with the execution using a conventional computer for several image sizes and different 3D refocusing planes. PMID:24841246

Super-resolution in plenoptic cameras using FPGAs.

PubMed

Pérez, Joel; Magdaleno, Eduardo; Pérez, Fernando; Rodríguez, Manuel; Hernández, David; Corrales, Jaime

2014-05-16

Plenoptic cameras are a new type of sensor that extend the possibilities of current commercial cameras allowing 3D refocusing or the capture of 3D depths. One of the limitations of plenoptic cameras is their limited spatial resolution. In this paper we describe a fast, specialized hardware implementation of a super-resolution algorithm for plenoptic cameras. The algorithm has been designed for field programmable graphic array (FPGA) devices using VHDL (very high speed integrated circuit (VHSIC) hardware description language). With this technology, we obtain an acceleration of several orders of magnitude using its extremely high-performance signal processing capability through parallelism and pipeline architecture. The system has been developed using generics of the VHDL language. This allows a very versatile and parameterizable system. The system user can easily modify parameters such as data width, number of microlenses of the plenoptic camera, their size and shape, and the super-resolution factor. The speed of the algorithm in FPGA has been successfully compared with the execution using a conventional computer for several image sizes and different 3D refocusing planes.

Flexible non-diffractive vortex microscope for three-dimensional depth-enhanced super-localization of dielectric, metal and fluorescent nanoparticles

NASA Astrophysics Data System (ADS)

Bouchal, Petr; Bouchal, Zdeněk

2017-10-01

In the past decade, probe-based super-resolution using temporally resolved localization of emitters became a groundbreaking imaging strategy in fluorescence microscopy. Here we demonstrate a non-diffractive vortex microscope (NVM), enabling three-dimensional super-resolution fluorescence imaging and localization and tracking of metal and dielectric nanoparticles. The NVM benefits from vortex non-diffractive beams (NBs) creating a double-helix point spread function that rotates under defocusing while maintaining its size and shape unchanged. Using intrinsic properties of the NBs, the dark-field localization of weakly scattering objects is achieved in a large axial range exceeding the depth of field of the microscope objective up to 23 times. The NVM was developed using an upright microscope Nikon Eclipse E600 operating with a spiral lithographic mask optimized using Fisher information and built into an add-on imaging module or microscope objective. In evaluation of the axial localization accuracy the root mean square error below 18 nm and 280 nm was verified over depth ranges of 3.5 μm and 13.6 μm, respectively. Subwavelength gold and polystyrene beads were localized with isotropic precision below 10 nm in the axial range of 3.5 μm and the axial precision reduced to 30 nm in the extended range of 13.6 μm. In the fluorescence imaging, the localization with isotropic precision below 15 nm was demonstrated in the range of 2.5 μm, whereas in the range of 8.3 μm, the precision of 15 nm laterally and 30-50 nm axially was achieved. The tracking of nanoparticles undergoing Brownian motion was demonstrated in the volume of 14 × 10 × 16 μm3. Applicability of the NVM was tested by fluorescence imaging of LW13K2 cells and localization of cellular proteins.

Characterization of Urban Landscape Using Super-Resolution UAS Data, Multiple Textural Scales and Data-Mining Techniques

NASA Astrophysics Data System (ADS)

Voss, M.; Blundell, B.

2015-12-01

Characterization of urban environments is a high priority for the U.S. Army as battlespaces have transitioned from the predominantly open spaces of the 20th century to urban areas where soldiers have reduced situational awareness due to the diversity and density of their surroundings. Creating high-resolution urban terrain geospatial information will improve mission planning and soldier effectiveness. In this effort, super-resolution true-color imagery was collected with an Altivan NOVA unmanned aerial system over the Muscatatuck Urban Training Center near Butlerville, Indiana on September 16, 2014. Multispectral texture analysis using different algorithms was conducted for urban surface characterization at a variety of scales. Training samples extracted from the true-color and texture images. These data were processed using a variety of meta-algorithms with a decision tree classifier to create a high-resolution urban features map. In addition to improving accuracy over traditional image classification methods, this technique allowed the determination of the most significant textural scales in creating urban terrain maps for tactical exploitation.

Super-Resolution Imaging by Arrays of High-Index Spheres Embedded in Transparent Matrices

DTIC Science & Technology

2014-06-25

microsphere-assisted imaging. Roles of surface excitations, plasmons, polaritons and Tamm-states, as well as the role of nanoscale gap separating the object...nanometric gap between the object and spheres and the role of surface polariton -plasmons in the metallic nanostructures. Our results, however, show that

Super-Resolving Toraldo Pupils for Radio Astronomical Applications: Current Status and Future Prospects

NASA Astrophysics Data System (ADS)

Olmi, Luca

2017-11-01

More than half a century ago, in 1952, Giuliano Toraldo di Francia suggested that the resolving power of an optical instrument could be improved using a filter consisting of finite-width concentric coronae of different amplitude and phase transmittance, now known as Toraldo Pupils (TPs). The concept of 'super- resolution' was born, and in the cur- rent literature it is generally associated with various meth- ods for improving the angular resolution of an optical imag- ing system beyond the classical diffraction limit. In the mi- crowave range, the first successful laboratory test of TPs was performed in 2003. These first results suggested that TPs could represent a viable approach to achieve super- resolution in Radio Astronomy. We have therefore started a project devoted to an exhaustive study of TPs and how they could be implemented on a radio telescope. In this work we present a summary of the status of this project, and then we will describe our future plans.

Improving multiphoton STED nanoscopy with separation of photons by LIfetime Tuning (SPLIT)

NASA Astrophysics Data System (ADS)

Coto Hernández, Iván.; Lanzano, Luca; Castello, Marco; Jowett, Nate; Tortarolo, Giorgio; Diaspro, Alberto; Vicidomini, Giuseppe

2018-02-01

Stimulated emission depletion (STED) microscopy is a powerful bio-imaging technique since it provides molecular spatial resolution whilst preserving the most important assets of fluorescence microscopy. When combined with twophoton excitation (2PE) microscopy (2PE-STED), the sub-diffraction imaging ability of STED microscopy can be achieved also on thick biological samples. The most straightforward implementation of 2PE-STED microscopy is obtained by introducing a STED beam operating in continuous wave (CW) into a conventional Ti:Sapphire based 2PE microscope (2PE-CW-STED). In this implementation, an effective resolution enhancement is mainly obtained implementing a time-gated detection scheme, which however can drastically reduce the signal-to-noise/background ratio of the final image. Herein, we combine the lifetime tuning (SPLIT) approach with 2PE-CW-STED to overcome this limitation. The SPLIT approach is employed to discard fluorescence photons lacking super-resolution information, by means of a pixel-by-pixel phasor approach. Combining the SPLIT approach with image deconvolution further optimizes the signal-to-noise/background ratio.

The PMC-Turbo Balloon Mission to Study Gravity Waves and Turbulence through High-Resolution Imaging of Polar Mesospheric Clouds

NASA Astrophysics Data System (ADS)

Williams, B. P.; Kjellstrand, B.; Jones, G.; Reimuller, J. D.; Fritts, D. C.; Miller, A.; Geach, C.; Limon, M.; Hanany, S.; Kaifler, B.; Wang, L.; Taylor, M. J.

2017-12-01

PMC-Turbo is a NASA long-duration, high-altitude balloon mission that will deploy 7 high-resolution cameras to image polar mesospheric clouds (PMC) and measure gravity wave breakdown and turbulence. The mission has been enhanced by the addition of the DLR Balloon Lidar Experiment (BOLIDE) and an OH imager from Utah State University. This instrument suite will provide high horizontal and vertical resolution of the wave-modified PMC structure along a several thousand kilometer flight track. We have requested a flight from Kiruna, Sweden to Canada in June 2017 or McMurdo Base, Antarctica in Dec 2017. Three of the PMC camera systems were deployed on an aircraft and two tomographic ground sites for the High Level campaign in Canada in June/July 2017. On several nights the cameras observed PMC's with strong gravity wave breaking signatures. One PMC camera will piggyback on the Super Tiger mission scheduled to be launched in Dec 2017 from McMurdo, so we will obtain PMC images and wave/turbulence data from both the northern and southern hemispheres.

Sparse synthetic aperture with Fresnel elements (S-SAFE) using digital incoherent holograms

PubMed Central

Kashter, Yuval; Rivenson, Yair; Stern, Adrian; Rosen, Joseph

2015-01-01

Creating a large-scale synthetic aperture makes it possible to break the resolution boundaries dictated by the wave nature of light of common optical systems. However, their implementation is challenging, since the generation of a large size continuous mosaic synthetic aperture composed of many patterns is complicated in terms of both phase matching and time-multiplexing duration. In this study we present an advanced configuration for an incoherent holographic imaging system with super resolution qualities that creates a partial synthetic aperture. The new system, termed sparse synthetic aperture with Fresnel elements (S-SAFE), enables significantly decreasing the number of the recorded elements, and it is free from positional constrains on their location. Additionally, in order to obtain the best image quality we propose an optimal mosaicking structure derived on the basis of physical and numerical considerations, and introduce three reconstruction approaches which are compared and discussed. The super-resolution capabilities of the proposed scheme and its limitations are analyzed, numerically simulated and experimentally demonstrated. PMID:26367947

Quantitative evaluation of software packages for single-molecule localization microscopy.

PubMed

Sage, Daniel; Kirshner, Hagai; Pengo, Thomas; Stuurman, Nico; Min, Junhong; Manley, Suliana; Unser, Michael

2015-08-01

The quality of super-resolution images obtained by single-molecule localization microscopy (SMLM) depends largely on the software used to detect and accurately localize point sources. In this work, we focus on the computational aspects of super-resolution microscopy and present a comprehensive evaluation of localization software packages. Our philosophy is to evaluate each package as a whole, thus maintaining the integrity of the software. We prepared synthetic data that represent three-dimensional structures modeled after biological components, taking excitation parameters, noise sources, point-spread functions and pixelation into account. We then asked developers to run their software on our data; most responded favorably, allowing us to present a broad picture of the methods available. We evaluated their results using quantitative and user-interpretable criteria: detection rate, accuracy, quality of image reconstruction, resolution, software usability and computational resources. These metrics reflect the various tradeoffs of SMLM software packages and help users to choose the software that fits their needs.

On the dynamic readout characteristic of nonlinear super-resolution optical storage

NASA Astrophysics Data System (ADS)

Wei, Jingsong

2013-03-01

Researchers have developed nonlinear super-resolution optical storage for the past twenty years. However, several concerns remain, including (1) the presence of readout threshold power; (2) the increase of threshold power with the reduction of the mark size, and (3) the increase of the carrier-to-noise ratio (CNR) at the initial stage and then decrease with the increase of readout laser power or laser irradiation time. The present work calculates and analyzes the super-resolution spot formed by the thin film masks and the readout threshold power characteristic according to the derived formula and based on the nonlinear saturable absorption characteristic and threshold of structural change. The obtained theoretical calculation and experimental data answer the concerns regarding the dynamic readout threshold characteristic and CNR dependence on laser power and irradiation time. The near-field optical spot scanning experiment further verifies the super-resolution spot formation produced through the nonlinear thin film masks.

Single cell genomic quantification by non-fluorescence nonlinear microscopy

NASA Astrophysics Data System (ADS)

Kota, Divya; Liu, Jing

2017-02-01

Human epidermal growth receptor 2 (Her2) is a gene which plays a major role in breast cancer development. The quantification of Her2 expression in single cells is limited by several drawbacks in existing fluorescence-based single molecule techniques, such as low signal-to-noise ratio (SNR), strong autofluorescence and background signals from biological components. For rigorous genomic quantification, a robust method of orthogonal detection is highly desirable and we demonstrated it by two non-fluorescent imaging techniques -transient absorption microscopy (TAM) and second harmonic generation (SHG). In TAM, gold nanoparticles (AuNPs) are chosen as an orthogonal probes for detection of single molecules which gives background-free quantifications of single mRNA transcript. In SHG, emission from barium titanium oxide (BTO) nanoprobes was demonstrated which allows stable signal beyond the autofluorescence window. Her2 mRNA was specifically labeled with nanoprobes which are conjugated with antibodies or oligonucleotides and quantified at single copy sensitivity in the cancer cells and tissues. Furthermore, a non-fluorescent super-resolution concept, named as second harmonic super-resolution microscopy (SHaSM), was proposed to quantify individual Her2 transcripts in cancer cells beyond the diffraction limit. These non-fluorescent imaging modalities will provide new dimensions in biomarker quantification at single molecule sensitivity in turbid biological samples, offering a strong cross-platform strategy for clinical monitoring at single cell resolution.

Single Broadband Phase-Shaped Pulse Stimulated Raman Spectroscopy for Standoff Trace Explosive Detection.

PubMed

Glenn, Rachel; Dantus, Marcos

2016-01-07

Recent success with trace explosives detection based on the single ultrafast pulse excitation for remote stimulated Raman scattering (SUPER-SRS) prompts us to provide new results and a Perspective that describes the theoretical foundation of the strategy used for achieving the desired sensitivity and selectivity. SUPER-SRS provides fast and selective imaging while being blind to optical properties of the substrate such as color, texture, or laser speckle. We describe the strategy of combining coherent vibrational excitation with a reference pulse in order to detect stimulated Raman gain or loss. A theoretical model is used to reproduce experimental spectra and to determine the ideal pulse parameters for best sensitivity, selectivity, and resolution when detecting one or more compounds simultaneously.

Sensor and computing resource management for a small satellite

NASA Astrophysics Data System (ADS)

Bhatia, Abhilasha; Goehner, Kyle; Sand, John; Straub, Jeremy; Mohammad, Atif; Korvald, Christoffer; Nervold, Anders Kose

A small satellite in a low-Earth orbit (e.g., approximately a 300 to 400 km altitude) has an orbital velocity in the range of 8.5 km/s and completes an orbit approximately every 90 minutes. For a satellite with minimal attitude control, this presents a significant challenge in obtaining multiple images of a target region. Presuming an inclination in the range of 50 to 65 degrees, a limited number of opportunities to image a given target or communicate with a given ground station are available, over the course of a 24-hour period. For imaging needs (where solar illumination is required), the number of opportunities is further reduced. Given these short windows of opportunity for imaging, data transfer, and sending commands, scheduling must be optimized. In addition to the high-level scheduling performed for spacecraft operations, payload-level scheduling is also required. The mission requires that images be post-processed to maximize spatial resolution and minimize data transfer (through removing overlapping regions). The payload unit includes GPS and inertial measurement unit (IMU) hardware to aid in image alignment for the aforementioned. The payload scheduler must, thus, split its energy and computing-cycle budgets between determining an imaging sequence (required to capture the highly-overlapping data required for super-resolution and adjacent areas required for mosaicking), processing the imagery (to perform the super-resolution and mosaicking) and preparing the data for transmission (compressing it, etc.). This paper presents an approach for satellite control, scheduling and operations that allows the cameras, GPS and IMU to be used in conjunction to acquire higher-resolution imagery of a target region.