Super-resolution thermographic imaging using blind structured illumination

Science.gov (United States)

Burgholzer, Peter; Berer, Thomas; Gruber, Jürgen; Mayr, Günther

2017-07-01

Using an infrared camera for thermographic imaging allows the contactless temperature measurement of many surface pixels simultaneously. From the measured surface data, the structure below the surface, embedded inside a sample or tissue, can be reconstructed and imaged, if heated by an excitation light pulse. The main drawback in active thermographic imaging is the degradation of the spatial resolution with the imaging depth, which results in blurred images for deeper lying structures. We circumvent this degradation by using blind structured illumination combined with a non-linear joint sparsity reconstruction algorithm. We demonstrate imaging of a line pattern and a star-shaped structure through a 3 mm thick steel sheet with a resolution four times better than the width of the thermal point-spread-function. The structured illumination is realized by parallel slits cut in an aluminum foil, where the excitation coming from a flashlight can penetrate. This realization of super-resolution thermographic imaging demonstrates that blind structured illumination allows thermographic imaging without high degradation of the spatial resolution for deeper lying structures. The groundbreaking concept of super-resolution can be transferred from optics to diffusive imaging by defining a thermal point-spread-function, which gives the principle resolution limit for a certain signal-to-noise ratio, similar to the Abbe limit for a certain optical wavelength. In future work, the unknown illumination pattern could be the speckle pattern generated by a short laser pulse inside a light scattering sample or tissue.

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

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Chong Fan

2017-02-01

Full Text Available 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 highresolution (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.

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

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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.

Image super-resolution reconstruction based on regularization technique and guided filter

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Huang, De-tian; Huang, Wei-qin; Gu, Pei-ting; Liu, Pei-zhong; Luo, Yan-min

2017-06-01

In order to improve the accuracy of sparse representation coefficients and the quality of reconstructed images, an improved image super-resolution algorithm based on sparse representation is presented. In the sparse coding stage, the autoregressive (AR) regularization and the non-local (NL) similarity regularization are introduced to improve the sparse coding objective function. A group of AR models which describe the image local structures are pre-learned from the training samples, and one or several suitable AR models can be adaptively selected for each image patch to regularize the solution space. Then, the image non-local redundancy is obtained by the NL similarity regularization to preserve edges. In the process of computing the sparse representation coefficients, the feature-sign search algorithm is utilized instead of the conventional orthogonal matching pursuit algorithm to improve the accuracy of the sparse coefficients. To restore image details further, a global error compensation model based on weighted guided filter is proposed to realize error compensation for the reconstructed images. Experimental results demonstrate that compared with Bicubic, L1SR, SISR, GR, ANR, NE + LS, NE + NNLS, NE + LLE and A + (16 atoms) methods, the proposed approach has remarkable improvement in peak signal-to-noise ratio, structural similarity and subjective visual perception.

Super resolution reconstruction of infrared images based on classified dictionary learning

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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.

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

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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.

Magnetic Resonance Super-resolution Imaging Measurement with Dictionary-optimized Sparse Learning

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Li Jun-Bao

2017-06-01

Full Text Available Magnetic Resonance Super-resolution Imaging Measurement (MRIM is an effective way of measuring materials. MRIM has wide applications in physics, chemistry, biology, geology, medical and material science, especially in medical diagnosis. It is feasible to improve the resolution of MR imaging through increasing radiation intensity, but the high radiation intensity and the longtime of magnetic field harm the human body. Thus, in the practical applications the resolution of hardware imaging reaches the limitation of resolution. Software-based super-resolution technology is effective to improve the resolution of image. This work proposes a framework of dictionary-optimized sparse learning based MR super-resolution method. The framework is to solve the problem of sample selection for dictionary learning of sparse reconstruction. The textural complexity-based image quality representation is proposed to choose the optimal samples for dictionary learning. Comprehensive experiments show that the dictionary-optimized sparse learning improves the performance of sparse representation.

Super-resolution Phase Tomography

KAUST Repository

Depeursinge, Christian; Cotte, Yann; Toy, Fatih; Jourdain, Pascal; Boss, Daiel; Marquet, Pierre; Magistretti, Pierre J.

2013-01-01

Digital Holographic Microscopy (DHM) yields reconstructed complex wavefields. It allows synthesizing the aperture of a virtual microscope up to 2π, offering super-resolution phase images. Live images of micro-organisms and neurons with resolution less than 100 nm are presented.

Super-resolution Phase Tomography

KAUST Repository

Depeursinge, Christian

2013-04-21

Digital Holographic Microscopy (DHM) yields reconstructed complex wavefields. It allows synthesizing the aperture of a virtual microscope up to 2π, offering super-resolution phase images. Live images of micro-organisms and neurons with resolution less than 100 nm are presented.

Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

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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.

A Total Variation Regularization Based Super-Resolution Reconstruction Algorithm for Digital Video

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Zhang Liangpei

2007-01-01

Full Text Available Super-resolution (SR reconstruction technique is capable of producing a high-resolution image from a sequence of low-resolution images. In this paper, we study an efficient SR algorithm for digital video. To effectively deal with the intractable problems in SR video reconstruction, such as inevitable motion estimation errors, noise, blurring, missing regions, and compression artifacts, the total variation (TV regularization is employed in the reconstruction model. We use the fixed-point iteration method and preconditioning techniques to efficiently solve the associated nonlinear Euler-Lagrange equations of the corresponding variational problem in SR. The proposed algorithm has been tested in several cases of motion and degradation. It is also compared with the Laplacian regularization-based SR algorithm and other TV-based SR algorithms. Experimental results are presented to illustrate the effectiveness of the proposed algorithm.

Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image

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YiNan Zhang

2017-01-01

Full Text Available Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template layer and two convolutional layers. The bicubic interpolation template layer is prefixed by mathematics deduction, and two convolutional layers learn from training samples. For saving training medical images, a SIFT feature-based transfer learning method is proposed. Not only can medical images be used to train the proposed method, but also other types of images can be added into training dataset selectively. In empirical experiments, results of eight distinctive medical images show improvement of image quality and time reduction. Further, the proposed method also produces slightly sharper edges than other deep learning approaches in less time and it is projected that the hybrid architecture of prefixed template layer and unfixed hidden layers has potentials in other applications.

Evaluation of deep neural networks for single image super-resolution in a maritime context

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Nieuwenhuizen, R.P.J.; Kruithof, M.; Schutte, K.

2017-01-01

High resolution imagery is of crucial importance for the performance on visual recognition tasks. Super-resolution (SR) reconstruction algorithms aim to enhance the image resolution beyond the capability of the image sensor being used. Traditional SR algorithms approach this inverse problem using

Single image super-resolution based on convolutional neural networks

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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.

Detecting breast microcalcifications using super-resolution and wave-equation ultrasound imaging: a numerical phantom study

Energy Technology Data Exchange (ETDEWEB)

Huang, Lianjie [Los Alamos National Laboratory; Simonetti, Francesco [IMPERIAL COLLEGE LONDON; Huthwaite, Peter [IMPERIAL COLLEGE LONDON; Rosenberg, Robert [UNM; Williamson, Michael [UNM

2010-01-01

Ultrasound image resolution and quality need to be significantly improved for breast microcalcification detection. Super-resolution imaging with the factorization method has recently been developed as a promising tool to break through the resolution limit of conventional imaging. In addition, wave-equation reflection imaging has become an effective method to reduce image speckles by properly handling ultrasound scattering/diffraction from breast heterogeneities during image reconstruction. We explore the capabilities of a novel super-resolution ultrasound imaging method and a wave-equation reflection imaging scheme for detecting breast microcalcifications. Super-resolution imaging uses the singular value decomposition and a factorization scheme to achieve an image resolution that is not possible for conventional ultrasound imaging. Wave-equation reflection imaging employs a solution to the acoustic-wave equation in heterogeneous media to backpropagate ultrasound scattering/diffraction waves to scatters and form images of heterogeneities. We construct numerical breast phantoms using in vivo breast images, and use a finite-difference wave-equation scheme to generate ultrasound data scattered from inclusions that mimic microcalcifications. We demonstrate that microcalcifications can be detected at full spatial resolution using the super-resolution ultrasound imaging and wave-equation reflection imaging methods.

Super-resolution imaging applied to moving object tracking

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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.

Optimized multiple linear mappings for single image super-resolution

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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.

Learning-based compressed sensing for infrared image super resolution

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Zhao, Yao; Sui, Xiubao; Chen, Qian; Wu, Shaochi

2016-05-01

This paper presents an infrared image super-resolution method based on compressed sensing (CS). First, the reconstruction model under the CS framework is established and a Toeplitz matrix is selected as the sensing matrix. Compared with traditional learning-based methods, the proposed method uses a set of sub-dictionaries instead of two coupled dictionaries to recover high resolution (HR) images. And Toeplitz sensing matrix allows the proposed method time-efficient. Second, all training samples are divided into several feature spaces by using the proposed adaptive k-means classification method, which is more accurate than the standard k-means method. On the basis of this approach, a complex nonlinear mapping from the HR space to low resolution (LR) space can be converted into several compact linear mappings. Finally, the relationships between HR and LR image patches can be obtained by multi-sub-dictionaries and HR infrared images are reconstructed by the input LR images and multi-sub-dictionaries. The experimental results show that the proposed method is quantitatively and qualitatively more effective than other state-of-the-art methods.

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

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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.

Effects of whispering gallery mode in microsphere super-resolution imaging

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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.

SINGLE FRAME SUPER RESOLUTION OF NONCOOPERATIVE IRIS IMAGES

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Anand Deshpande

2016-11-01

Full Text Available Image super-resolution, a process to enhance image resolution, has important applications in biometrics, satellite imaging, high definition television, medical imaging, etc. The long range captured iris identification systems often suffer from low resolution and meager focus of the captured iris images. These degrade the iris recognition performance. This paper proposes enhanced iterated back projection (EIBP method to super resolute the long range captured iris polar images. The performance of proposed method is tested and analyzed on CASIA long range iris database by comparing peak signal to noise ratio (PSNR and structural similarity index (SSIM with state-of-the-art super resolution (SR algorithms. It is further analyzed by increasing the up-sampling factor. Performance analysis shows that the proposed method is superior to state-of-the-art algorithms, the peak signal-to-noise ratio improved about 0.1-1.5 dB. The results demonstrate that the proposed method is well suited to super resolve the iris polar images captured at a long distance

A Super-resolution Reconstruction Algorithm for Surveillance Video

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Jian Shao

2017-01-01

Full Text Available Recent technological developments have resulted in surveillance video becoming a primary method of preserving public security. Many city crimes are observed in surveillance video. The most abundant evidence collected by the police is also acquired through surveillance video sources. Surveillance video footage offers very strong support for solving criminal cases, therefore, creating an effective policy, and applying useful methods to the retrieval of additional evidence is becoming increasingly important. However, surveillance video has had its failings, namely, video footage being captured in low resolution (LR and bad visual quality. In this paper, we discuss the characteristics of surveillance video and describe the manual feature registration – maximum a posteriori – projection onto convex sets to develop a super-resolution reconstruction method, which improves the quality of surveillance video. From this method, we can make optimal use of information contained in the LR video image, but we can also control the image edge clearly as well as the convergence of the algorithm. Finally, we make a suggestion on how to adjust the algorithm adaptability by analyzing the prior information of target image.

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

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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.

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

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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.

Overcoming Registration Uncertainty in Image Super-Resolution: Maximize or Marginalize?

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Andrew Zisserman

2007-01-01

Full Text Available In multiple-image super-resolution, a high-resolution image is estimated from a number of lower-resolution images. This usually involves computing the parameters of a generative imaging model (such as geometric and photometric registration, and blur and obtaining a MAP estimate by minimizing a cost function including an appropriate prior. Two alternative approaches are examined. First, both registrations and the super-resolution image are found simultaneously using a joint MAP optimization. Second, we perform Bayesian integration over the unknown image registration parameters, deriving a cost function whose only variables of interest are the pixel values of the super-resolution image. We also introduce a scheme to learn the parameters of the image prior as part of the super-resolution algorithm. We show examples on a number of real sequences including multiple stills, digital video, and DVDs of movies.

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

Science.gov (United States)

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.

Super resolution imaging of genetically labelled synapses in Drosophila brain tissue

Directory of Open Access Journals (Sweden)

Isabelle Ayumi Spühler

2016-05-01

Full Text Available 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 labelled 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

Super-resolution reconstruction of 4D-CT lung data via patch-based low-rank matrix reconstruction

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Fang, Shiting; Wang, Huafeng; Liu, Yueliang; Zhang, Minghui; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

2017-10-01

Lung 4D computed tomography (4D-CT), which is a time-resolved CT data acquisition, performs an important role in explicitly including respiratory motion in treatment planning and delivery. However, the radiation dose is usually reduced at the expense of inter-slice spatial resolution to minimize radiation-related health risk. Therefore, resolution enhancement along the superior-inferior direction is necessary. In this paper, a super-resolution (SR) reconstruction method based on a patch low-rank matrix reconstruction is proposed to improve the resolution of lung 4D-CT images. Specifically, a low-rank matrix related to every patch is constructed by using a patch searching strategy. Thereafter, the singular value shrinkage is employed to recover the high-resolution patch under the constraints of the image degradation model. The output high-resolution patches are finally assembled to output the entire image. This method is extensively evaluated using two public data sets. Quantitative analysis shows that the proposed algorithm decreases the root mean square error by 9.7%-33.4% and the edge width by 11.4%-24.3%, relative to linear interpolation, back projection (BP) and Zhang et al’s algorithm. A new algorithm has been developed to improve the resolution of 4D-CT. In all experiments, the proposed method outperforms various interpolation methods, as well as BP and Zhang et al’s method, thus indicating the effectivity and competitiveness of the proposed algorithm.

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

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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.

Optimization of super-resolution processing using incomplete image sets in PET imaging.

Science.gov (United States)

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

Super-resolution for scanning light stimulation systems

Energy Technology Data Exchange (ETDEWEB)

Bitzer, L. A.; Neumann, K.; Benson, N., E-mail: niels.benson@uni-due.de; Schmechel, R. [Faculty of Engineering, NST and CENIDE, University of Duisburg-Essen, Bismarckstr. 81, 47057 Duisburg (Germany)

2016-09-15

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. 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.

Super resolution reconstruction of μ-CT image of rock sample using neighbour embedding algorithm

Science.gov (United States)

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.

Localization-based super-resolution imaging of cellular structures.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2017-03-01

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.

Example-Based Super-Resolution Fluorescence Microscopy.

Science.gov (United States)

Jia, Shu; Han, Boran; Kutz, J Nathan

2018-04-23

Capturing biological dynamics with high spatiotemporal resolution demands the advancement in imaging technologies. Super-resolution fluorescence microscopy offers spatial resolution surpassing the diffraction limit to resolve near-molecular-level details. While various strategies have been reported to improve the temporal resolution of super-resolution imaging, all super-resolution techniques are still fundamentally limited by the trade-off associated with the longer image acquisition time that is needed to achieve higher spatial information. Here, we demonstrated an example-based, computational method that aims to obtain super-resolution images using conventional imaging without increasing the imaging time. With a low-resolution image input, the method provides an estimate of its super-resolution image based on an example database that contains super- and low-resolution image pairs of biological structures of interest. The computational imaging of cellular microtubules agrees approximately with the experimental super-resolution STORM results. This new approach may offer potential improvements in temporal resolution for experimental super-resolution fluorescence microscopy and provide a new path for large-data aided biomedical imaging.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

Far-field super-resolution imaging of resonant multiples

KAUST Repository

Guo, Bowen

2016-05-20

We demonstrate for the first time that seismic resonant multiples, usually considered as noise, can be used for super-resolution imaging in the far-field region of sources and receivers. Tests with both synthetic data and field data show that resonant multiples can image reflector boundaries with resolutions more than twice the classical resolution limit. Resolution increases with the order of the resonant multiples. This procedure has important applications in earthquake and exploration seismology, radar, sonar, LIDAR (light detection and ranging), and ultrasound imaging, where the multiples can be used to make high-resolution images.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

Li, Guang; Wei, Jie; Kadbi, Mo; Moody, Jason; Sun, August; Zhang, Shirong; Markova, Svetlana; Zakian, Kristen; Hunt, Margie; Deasy, Joseph O.

2017-01-01

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; 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"3) at 2 Hz for 40 seconds and a 3D static BH scan (2 × 2 × 2 mm"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

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

Energy Technology Data Exchange (ETDEWEB)

Li, Guang, E-mail: lig2@mskcc.org [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York (United States); Wei, Jie [Department of Computer Science, City College of New York, New York, New York (United States); Kadbi, Mo [Philips Healthcare, MR Therapy Cleveland, Ohio (United States); Moody, Jason; Sun, August; Zhang, Shirong; Markova, Svetlana; Zakian, Kristen; Hunt, Margie; Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York (United States)

2017-06-01

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; 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-4

Super resolution for astronomical observations

Science.gov (United States)

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.

An Example-Based Super-Resolution Algorithm for Selfie Images

Directory of Open Access Journals (Sweden)

Jino Hans William

2016-01-01

Full Text Available 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.

Isotope specific resolution recovery image reconstruction in high resolution PET imaging

Energy Technology Data Exchange (ETDEWEB)

Kotasidis, Fotis A. [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva, Switzerland and Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, M20 3LJ, Manchester (United Kingdom); Angelis, Georgios I. [Faculty of Health Sciences, Brain and Mind Research Institute, University of Sydney, NSW 2006, Sydney (Australia); Anton-Rodriguez, Jose; Matthews, Julian C. [Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Reader, Andrew J. [Montreal Neurological Institute, McGill University, Montreal QC H3A 2B4, Canada and Department of Biomedical Engineering, Division of Imaging Sciences and Biomedical Engineering, King' s College London, St. Thomas’ Hospital, London SE1 7EH (United Kingdom); Zaidi, Habib [Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospital, CH-1211 Geneva (Switzerland); Geneva Neuroscience Centre, Geneva University, CH-1205 Geneva (Switzerland); Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, PO Box 30 001, Groningen 9700 RB (Netherlands)

2014-05-15

Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution

Isotope specific resolution recovery image reconstruction in high resolution PET imaging

International Nuclear Information System (INIS)

Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib

2014-01-01

Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. Methods: In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. Results: The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Conclusions: Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution

Isotope specific resolution recovery image reconstruction in high resolution PET imaging.

Science.gov (United States)

Kotasidis, Fotis A; Angelis, Georgios I; Anton-Rodriguez, Jose; Matthews, Julian C; Reader, Andrew J; Zaidi, Habib

2014-05-01

Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to perform the PSF measurements. As such, non-optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction, usually underestimating the true PSF owing to the difference in positron range. In high resolution brain and preclinical imaging, this effect is of particular importance since the PSFs become more positron range limited and isotope-specific PSFs can help maximize the performance benefit from using resolution recovery image reconstruction algorithms. In this work, the authors used a printing technique to simultaneously measure multiple point sources on the High Resolution Research Tomograph (HRRT), and the authors demonstrated the feasibility of deriving isotope-dependent system matrices from fluorine-18 and carbon-11 point sources. Furthermore, the authors evaluated the impact of incorporating them within RM image reconstruction, using carbon-11 phantom and clinical datasets on the HRRT. The results obtained using these two isotopes illustrate that even small differences in positron range can result in different PSF maps, leading to further improvements in contrast recovery when used in image reconstruction. The difference is more pronounced in the centre of the field-of-view where the full width at half maximum (FWHM) from the positron range has a larger contribution to the overall FWHM compared to the edge where the parallax error dominates the overall FWHM. Based on the proposed methodology, measured isotope-specific and spatially variant PSFs can be reliably derived and used for improved spatial resolution and variance performance in resolution recovery image reconstruction. The

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

Science.gov (United States)

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 (pmethods 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.

Adaptive patch-based POCS approach for super resolution reconstruction of 4D-CT lung data

International Nuclear Information System (INIS)

Wang, Tingting; Cao, Lei; Yang, Wei; Feng, Qianjin; Chen, Wufan; Zhang, Yu

2015-01-01

Image enhancement of lung four-dimensional computed tomography (4D-CT) data is highly important because image resolution remains a crucial point in lung cancer radiotherapy. In this paper, we proposed a method for lung 4D-CT super resolution (SR) by using an adaptive-patch-based projection onto convex sets (POCS) approach, which is in contrast with the global POCS SR algorithm, to recover fine details with lesser artifacts in images. The main contribution of this patch-based approach is that the interfering local structure from other phases can be rejected by employing a similar patch adaptive selection strategy. The effectiveness of our approach is demonstrated through experiments on simulated images and real lung 4D-CT datasets. A comparison with previously published SR reconstruction methods highlights the favorable characteristics of the proposed method. (paper)

The super-resolution debate

Science.gov (United States)

Won, Rachel

2018-05-01

In the quest for nanoscopy with super-resolution, consensus from the imaging community is that super-resolution is not always needed and that scientists should choose an imaging technique based on their specific application.

Multi-example feature-constrained back-projection method for image super-resolution

Institute of Scientific and Technical Information of China (English)

Junlei Zhang; Dianguang Gai; Xin Zhang; Xuemei Li

2017-01-01

Example-based super-resolution algorithms,which predict unknown high-resolution image information using a relationship model learnt from known high- and low-resolution image pairs, have attracted considerable interest in the field of image processing. In this paper, we propose a multi-example feature-constrained back-projection method for image super-resolution. Firstly, we take advantage of a feature-constrained polynomial interpolation method to enlarge the low-resolution image. Next, we consider low-frequency images of different resolutions to provide an example pair. Then, we use adaptive k NN search to find similar patches in the low-resolution image for every image patch in the high-resolution low-frequency image, leading to a regression model between similar patches to be learnt. The learnt model is applied to the low-resolution high-frequency image to produce high-resolution high-frequency information. An iterative back-projection algorithm is used as the final step to determine the final high-resolution image.Experimental results demonstrate that our method improves the visual quality of the high-resolution image.

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

Science.gov (United States)

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

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

Science.gov (United States)

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

Dual Super-Systolic Core for Real-Time Reconstructive Algorithms of High-Resolution Radar/SAR Imaging Systems

Science.gov (United States)

Atoche, Alejandro Castillo; Castillo, Javier Vázquez

2012-01-01

A high-speed dual super-systolic core for reconstructive signal processing (SP) operations consists of a double parallel systolic array (SA) machine in which each processing element of the array is also conceptualized as another SA in a bit-level fashion. In this study, we addressed the design of a high-speed dual super-systolic array (SSA) core for the enhancement/reconstruction of remote sensing (RS) imaging of radar/synthetic aperture radar (SAR) sensor systems. The selected reconstructive SP algorithms are efficiently transformed in their parallel representation and then, they are mapped into an efficient high performance embedded computing (HPEC) architecture in reconfigurable Xilinx field programmable gate array (FPGA) platforms. As an implementation test case, the proposed approach was aggregated in a HW/SW co-design scheme in order to solve the nonlinear ill-posed inverse problem of nonparametric estimation of the power spatial spectrum pattern (SSP) from a remotely sensed scene. We show how such dual SSA core, drastically reduces the computational load of complex RS regularization techniques achieving the required real-time operational mode. PMID:22736964

Isotope specific resolution recovery image reconstruction in high resolution PET imaging

OpenAIRE

Kotasidis Fotis A.; Kotasidis Fotis A.; Angelis Georgios I.; Anton-Rodriguez Jose; Matthews Julian C.; Reader Andrew J.; Reader Andrew J.; Zaidi Habib; Zaidi Habib; Zaidi Habib

2014-01-01

Purpose: Measuring and incorporating a scanner specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However due to the short half life of clinically used isotopes other long lived isotopes not used in clinical practice are used to perform the PSF measurements. As such non optimal PSF models that do not correspond to those needed for the data to be reconstructed are used within resolution modeling (RM) image reconstruction usuall...

Multiband super-resolution imaging of graded-index photonic crystal flat lens

Science.gov (United States)

Xie, Jianlan; Wang, Junzhong; Ge, Rui; Yan, Bei; Liu, Exian; Tan, Wei; Liu, Jianjun

2018-05-01

Multiband super-resolution imaging of point source is achieved by a graded-index photonic crystal flat lens. With the calculations of six bands in common photonic crystal (CPC) constructed with scatterers of different refractive indices, it can be found that the super-resolution imaging of point source can be realized by different physical mechanisms in three different bands. In the first band, the imaging of point source is based on far-field condition of spherical wave while in the second band, it is based on the negative effective refractive index and exhibiting higher imaging quality than that of the CPC. However, in the fifth band, the imaging of point source is mainly based on negative refraction of anisotropic equi-frequency surfaces. The novel method of employing different physical mechanisms to achieve multiband super-resolution imaging of point source is highly meaningful for the field of imaging.

Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture.

Science.gov (United States)

Yamamoto, Kyosuke; Togami, Takashi; Yamaguchi, Norio

2017-11-06

Unmanned aerial vehicles (UAVs or drones) are a very promising branch of technology, and they have been utilized in agriculture-in cooperation with image processing technologies-for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of plants in the limited time available, but this reduces the spatial resolution of the captured images. In this study, we applied a super-resolution method to the low-resolution images of tomato diseases to recover detailed appearances, such as lesions on plant organs. We also conducted disease classification using high-resolution, low-resolution, and super-resolution images to evaluate the effectiveness of super-resolution methods in disease classification. Our results indicated that the super-resolution method outperformed conventional image scaling methods in spatial resolution enhancement of tomato disease images. The results of disease classification showed that the accuracy attained was also better by a large margin with super-resolution images than with low-resolution images. These results indicated that our approach not only recovered the information lost in low-resolution images, but also exerted a beneficial influence on further image analysis. The proposed approach will accelerate image-based phenotyping and vigor diagnosis in the field, because it not only saves time to capture images of a crop in a cultivation field but also secures the accuracy of these images for further analysis.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Three-dimensional super-resolution imaging for fluorescence emission difference microscopy

Energy Technology Data Exchange (ETDEWEB)

You, Shangting; Kuang, Cuifang, E-mail: cfkuang@zju.edu.cn; Li, Shuai; Liu, Xu; Ding, Zhihua [State key laboratory of modern optical instrumentations, Zhejiang University, Hangzhou 310027 (China)

2015-08-15

We propose a method theoretically to break the diffraction limit and to improve the resolution in all three dimensions for fluorescence emission difference microscopy. We produce two kinds of hollow focal spot by phase modulation. By incoherent superposition, these two kinds of focal spot yield a 3D hollow focal spot. The optimal proportion of these two kinds of spot is given in the paper. By employing 3D hollow focal spot, super-resolution image can be yielded by means of fluorescence emission difference microscopy, with resolution enhanced both laterally and axially. According to computation result, size of point spread function of three-dimensional super-resolution imaging is reduced by about 40% in all three spatial directions with respect to confocal imaging.

Super-Resolution of Plant Disease Images for the Acceleration of Image-based Phenotyping and Vigor Diagnosis in Agriculture

Directory of Open Access Journals (Sweden)

Kyosuke Yamamoto

2017-11-01

Full Text Available Unmanned aerial vehicles (UAVs or drones are a very promising branch of technology, and they have been utilized in agriculture—in cooperation with image processing technologies—for phenotyping and vigor diagnosis. One of the problems in the utilization of UAVs for agricultural purposes is the limitation in flight time. It is necessary to fly at a high altitude to capture the maximum number of plants in the limited time available, but this reduces the spatial resolution of the captured images. In this study, we applied a super-resolution method to the low-resolution images of tomato diseases to recover detailed appearances, such as lesions on plant organs. We also conducted disease classification using high-resolution, low-resolution, and super-resolution images to evaluate the effectiveness of super-resolution methods in disease classification. Our results indicated that the super-resolution method outperformed conventional image scaling methods in spatial resolution enhancement of tomato disease images. The results of disease classification showed that the accuracy attained was also better by a large margin with super-resolution images than with low-resolution images. These results indicated that our approach not only recovered the information lost in low-resolution images, but also exerted a beneficial influence on further image analysis. The proposed approach will accelerate image-based phenotyping and vigor diagnosis in the field, because it not only saves time to capture images of a crop in a cultivation field but also secures the accuracy of these images for further analysis.

Field-portable pixel super-resolution colour microscope.

Directory of Open Access Journals (Sweden)

Alon Greenbaum

Full Text Available 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.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

The 2015 super-resolution microscopy roadmap

International Nuclear Information System (INIS)

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

2015-01-01

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

Robust microbubble tracking for super resolution imaging in ultrasound

DEFF Research Database (Denmark)

Hansen, Kristoffer B.; Villagómez Hoyos, Carlos Armando; Brasen, Jens Christian

2016-01-01

Currently ultrasound resolution is limited by diffraction to approximately half the wavelength of the sound wave employed. In recent years, super resolution imaging techniques have overcome the diffraction limit through the localization and tracking of a sparse set of microbubbles through...... the vasculature. However, this has only been performed on fixated tissue, limiting its clinical application. This paper proposes a technique for making super resolution images on non-fixated tissue by first compensating for tissue movement and then tracking the individual microbubbles. The experiment is performed...... on the kidney of a anesthetized Sprage-Dawley rat by infusing SonoVue at 0.1× original concentration. The algorithm demonstrated in vivo that the motion compensation was capable of removing the movement caused by the mechanical ventilator. The results shows that microbubbles were localized with a higher...

Color image guided depth image super resolution using fusion filter

Science.gov (United States)

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.

Super-resolution

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2014-01-01

Super-resolution, the process of obtaining one or more high-resolution images from one or more low-resolution observations, has been a very attractive research topic over the last two decades. It has found practical applications in many real world problems in different fields, from satellite...

Super-resolution processing for pulsed neutron imaging system using a high-speed camera

International Nuclear Information System (INIS)

Ishizuka, Ken; Kai, Tetsuya; Shinohara, Takenao; Segawa, Mariko; Mochiki, Koichi

2015-01-01

Super-resolution and center-of-gravity processing improve the resolution of neutron-transmitted images. These processing methods calculate the center-of-gravity pixel or sub-pixel of the neutron point converted into light by a scintillator. The conventional neutron-transmitted image is acquired using a high-speed camera by integrating many frames when a transmitted image with one frame is not provided. It succeeds in acquiring the transmitted image and calculating a spectrum by integrating frames of the same energy. However, because a high frame rate is required for neutron resonance absorption imaging, the number of pixels of the transmitted image decreases, and the resolution decreases to the limit of the camera performance. Therefore, we attempt to improve the resolution by integrating the frames after applying super-resolution or center-of-gravity processing. The processed results indicate that center-of-gravity processing can be effective in pulsed-neutron imaging with a high-speed camera. In addition, the results show that super-resolution processing is effective indirectly. A project to develop a real-time image data processing system has begun, and this system will be used at J-PARC in JAEA. (author)

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Confocal pore size measurement based on super-resolution image restoration.

Science.gov (United States)

Liu, Dali; Wang, Yun; Qiu, Lirong; Mao, Xinyue; Zhao, Weiqian

2014-09-01

A confocal pore size measurement based on super-resolution image restoration is proposed to obtain a fast and accurate measurement for submicrometer pore size of nuclear track-etched membranes (NTEMs). This method facilitates the online inspection of the pore size evolution during etching. Combining confocal microscopy with super-resolution image restoration significantly improves the lateral resolution of the NTEM image, yields a reasonable circle edge-setting criterion of 0.2408, and achieves precise pore edge detection. Theoretical analysis shows that the minimum measuring diameter can reach 0.19 μm, and the root mean square of the residuals is only 1.4 nm. Edge response simulation and experiment reveal that the edge response of the proposed method is better than 80 nm. The NTEM pore size measurement results obtained by the proposed method agree well with that obtained by scanning electron microscopy.

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

International Nuclear Information System (INIS)

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

2017-01-01

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 μ s. 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. (paper)

Microsphere-based super-resolution scanning optical microscope.

Science.gov (United States)

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

2017-06-26

High-refractive index dielectric microspheres positioned within the field of view of a microscope objective in a dielectric medium can focus the light into a so-called photonic nanojet. A sample placed in such nanojet can be imaged by the objective with super-resolution, i.e. with a resolution beyond the classical diffraction limit. However, when imaging nanostructures on a substrate, the propagation distance of a light wave in the dielectric medium in between the substrate and the microsphere must be small enough to reveal the sample's nanometric features. Therefore, only the central part of an image obtained through a microsphere shows super-resolution details, which are typically ∼100 nm using white light (peak at λ = 600 nm). We have performed finite element simulations of the role of this critical distance in the super-resolution effect. Super-resolution imaging of a sample placed beneath the microsphere is only possible within a very restricted central area of ∼10 μm 2 , where the separation distance between the substrate and the microsphere surface is very small (∼1 μm). To generate super-resolution images over larger areas of the sample, we have fixed a microsphere on a frame attached to the microscope objective, which is automatically scanned over the sample in a step-by-step fashion. This generates a set of image tiles, which are subsequently stitched into a single super-resolution image (with resolution of λ/4-λ/5) of a sample area of up to ∼10 4 μm 2 . Scanning a standard optical microscope objective with microsphere therefore enables super-resolution microscopy over the complete field-of-view of the objective.

Super-Resolution for Synthetic Zooming

Directory of Open Access Journals (Sweden)

Li Xin

2006-01-01

Full Text Available Optical zooming is an important feature of imaging systems. In this paper, we investigate a low-cost signal processing alternative to optical zooming—synthetic zooming by super-resolution (SR techniques. Synthetic zooming is achieved by registering a sequence of low-resolution (LR images acquired at varying focal lengths and reconstructing the SR image at a larger focal length or increased spatial resolution. Under the assumptions of constant scene depth and zooming speed, we argue that the motion trajectories of all physical points are related to each other by a unique vanishing point and present a robust technique for estimating its D coordinate. Such a line-geometry-based registration is the foundation of SR for synthetic zooming. We address the issue of data inconsistency arising from the varying focal length of optical lens during the zooming process. To overcome the difficulty of data inconsistency, we propose a two-stage Delaunay-triangulation-based interpolation for fusing the LR image data. We also present a PDE-based nonlinear deblurring to accommodate the blindness and variation of sensor point spread functions. Simulation results with real-world images have verified the effectiveness of the proposed SR techniques for synthetic zooming.

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

Science.gov (United States)

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.

Adaptive optics improves multiphoton super-resolution imaging

Science.gov (United States)

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.

Super resolution PLIF demonstrated in turbulent jet flows seeded with I2

Science.gov (United States)

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.

Sparsity-Based Super Resolution for SEM Images.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Contrast enhancement of microsphere-assisted super-resolution imaging in dark-field microscopy

Science.gov (United States)

Zhou, Yi; Tang, Yan; Deng, Qinyuan; Zhao, Lixin; Hu, Song

2017-08-01

We report a method of boosting the imaging contrast of microsphere-assisted super-resolution visualization by utilizing dark-field illumination (DFI). We conducted experiments on both 10-µm-diameter silica (SiO2) microspheres with refractive index n ∼ 1.46 under no and partial immersion in ethyl alcohol (n ∼ 1.36) and 20-µm-diameter barium titanate glass (BTG, n ∼ 1.9) microspheres with full immersion to show the super-resolution capability. We experimentally demonstrated that the imaging contrast and uniformity were extraordinarily improved in the DFI mode. The intensity profiles in the visualization also numerically confirm the enhanced sharpness for a better imaging quality when applying DFI.

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

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Tomoyuki Obuchi

Full Text Available We develop an approximation formula for the cross-validation error (CVE of a sparse linear regression penalized by ℓ1-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.

Super-resolution fluorescence microscopy by stepwise optical saturation

Science.gov (United States)

Zhang, Yide; Nallathamby, Prakash D.; Vigil, Genevieve D.; Khan, Aamir A.; Mason, Devon E.; Boerckel, Joel D.; Roeder, Ryan K.; Howard, Scott S.

2018-01-01

Super-resolution fluorescence microscopy is an important tool in biomedical research for its ability to discern features smaller than the diffraction limit. However, due to its difficult implementation and high cost, the super-resolution microscopy is not feasible in many applications. In this paper, we propose and demonstrate a saturation-based super-resolution fluorescence microscopy technique that can be easily implemented and requires neither additional hardware nor complex post-processing. The method is based on the principle of stepwise optical saturation (SOS), where M steps of raw fluorescence images are linearly combined to generate an image with a M-fold increase in resolution compared with conventional diffraction-limited images. For example, linearly combining (scaling and subtracting) two images obtained at regular powers extends the resolution by a factor of 1.4 beyond the diffraction limit. The resolution improvement in SOS microscopy is theoretically infinite but practically is limited by the signal-to-noise ratio. We perform simulations and experimentally demonstrate super-resolution microscopy with both one-photon (confocal) and multiphoton excitation fluorescence. We show that with the multiphoton modality, the SOS microscopy can provide super-resolution imaging deep in scattering samples. PMID:29675306

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

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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

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

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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.

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

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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 (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.

Focusing super resolution on the cytoskeleton [version 1; referees: 3 approved

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Eric A. Shelden

2016-05-01

Full Text Available Super resolution imaging is becoming an increasingly important tool in the arsenal of methods available to cell biologists. In recognition of its potential, the Nobel Prize for chemistry was awarded to three investigators involved in the development of super resolution imaging methods in 2014. The availability of commercial instruments for super resolution imaging has further spurred the development of new methods and reagents designed to take advantage of super resolution techniques. Super resolution offers the advantages traditionally associated with light microscopy, including the use of gentle fixation and specimen preparation methods, the ability to visualize multiple elements within a single specimen, and the potential to visualize dynamic changes in living specimens over time. However, imaging of living cells over time is difficult and super resolution imaging is computationally demanding. In this review, we discuss the advantages/disadvantages of different super resolution systems for imaging fixed live specimens, with particular regard to cytoskeleton structures.

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

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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.

Wavelet Filter Banks for Super-Resolution SAR Imaging

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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.

A Fast Algorithm for Image Super-Resolution from Blurred Observations

Directory of Open Access Journals (Sweden)

Ng Michael K

2006-01-01

Full Text Available We study the problem of reconstruction of a high-resolution image from several blurred low-resolution image frames. The image frames consist of blurred, decimated, and noisy versions of a high-resolution image. The high-resolution image is modeled as a Markov random field (MRF, and a maximum a posteriori (MAP estimation technique is used for the restoration. We show that with the periodic boundary condition, a high-resolution image can be restored efficiently by using fast Fourier transforms. We also apply the preconditioned conjugate gradient method to restore high-resolution images in the aperiodic boundary condition. Computer simulations are given to illustrate the effectiveness of the proposed approach.

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

Science.gov (United States)

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.

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

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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.

Adaptive Markov Random Fields for Example-Based Super-resolution of Faces

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Stephenson Todd A

2006-01-01

Full Text Available Image enhancement of low-resolution images can be done through methods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution. Example-based super-resolution, in particular, is suited to images that have a strong prior (for those frameworks that work on only a single image, it is more like image restoration than traditional, multiframe super-resolution. For example, hallucination and Markov random field (MRF methods use examples drawn from the same domain as the image being enhanced to determine what the missing high-frequency information is likely to be. We propose to use even stronger prior information by extending MRF-based super-resolution to use adaptive observation and transition functions, that is, to make these functions region-dependent. We show with face images how we can adapt the modeling for each image patch so as to improve the resolution.

Adaptive Markov Random Fields for Example-Based Super-resolution of Faces

Science.gov (United States)

Stephenson, Todd A.; Chen, Tsuhan

2006-12-01

Image enhancement of low-resolution images can be done through methods such as interpolation, super-resolution using multiple video frames, and example-based super-resolution. Example-based super-resolution, in particular, is suited to images that have a strong prior (for those frameworks that work on only a single image, it is more like image restoration than traditional, multiframe super-resolution). For example, hallucination and Markov random field (MRF) methods use examples drawn from the same domain as the image being enhanced to determine what the missing high-frequency information is likely to be. We propose to use even stronger prior information by extending MRF-based super-resolution to use adaptive observation and transition functions, that is, to make these functions region-dependent. We show with face images how we can adapt the modeling for each image patch so as to improve the resolution.

Spatiotemporal Super-Resolution Reconstruction Based on Robust Optical Flow and Zernike Moment for Video Sequences

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Meiyu Liang

2013-01-01

Full Text Available In order to improve the spatiotemporal resolution of the video sequences, a novel spatiotemporal super-resolution reconstruction model (STSR based on robust optical flow and Zernike moment is proposed in this paper, which integrates the spatial resolution reconstruction and temporal resolution reconstruction into a unified framework. The model does not rely on accurate estimation of subpixel motion and is robust to noise and rotation. Moreover, it can effectively overcome the problems of hole and block artifacts. First we propose an efficient robust optical flow motion estimation model based on motion details preserving, then we introduce the biweighted fusion strategy to implement the spatiotemporal motion compensation. Next, combining the self-adaptive region correlation judgment strategy, we construct a fast fuzzy registration scheme based on Zernike moment for better STSR with higher efficiency, and then the final video sequences with high spatiotemporal resolution can be obtained by fusion of the complementary and redundant information with nonlocal self-similarity between the adjacent video frames. Experimental results demonstrate that the proposed method outperforms the existing methods in terms of both subjective visual and objective quantitative evaluations.

Resolution-recovery-embedded image reconstruction for a high-resolution animal SPECT system.

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Zeraatkar, Navid; Sajedi, Salar; Farahani, Mohammad Hossein; Arabi, Hossein; Sarkar, Saeed; Ghafarian, Pardis; Rahmim, Arman; Ay, Mohammad Reza

2014-11-01

The small-animal High-Resolution SPECT (HiReSPECT) is a dedicated dual-head gamma camera recently designed and developed in our laboratory for imaging of murine models. Each detector is composed of an array of 1.2 × 1.2 mm(2) (pitch) pixelated CsI(Na) crystals. Two position-sensitive photomultiplier tubes (H8500) are coupled to each head's crystal. In this paper, we report on a resolution-recovery-embedded image reconstruction code applicable to the system and present the experimental results achieved using different phantoms and mouse scans. Collimator-detector response functions (CDRFs) were measured via a pixel-driven method using capillary sources at finite distances from the head within the field of view (FOV). CDRFs were then fitted by independent Gaussian functions. Thereafter, linear interpolations were applied to the standard deviation (σ) values of the fitted Gaussians, yielding a continuous map of CDRF at varying distances from the head. A rotation-based maximum-likelihood expectation maximization (MLEM) method was used for reconstruction. A fast rotation algorithm was developed to rotate the image matrix according to the desired angle by means of pre-generated rotation maps. The experiments demonstrated improved resolution utilizing our resolution-recovery-embedded image reconstruction. While the full-width at half-maximum (FWHM) radial and tangential resolution measurements of the system were over 2 mm in nearly all positions within the FOV without resolution recovery, reaching around 2.5 mm in some locations, they fell below 1.8 mm everywhere within the FOV using the resolution-recovery algorithm. The noise performance of the system was also acceptable; the standard deviation of the average counts per voxel in the reconstructed images was 6.6% and 8.3% without and with resolution recovery, respectively. Copyright © 2014 Associazione Italiana di Fisica Medica. Published by Elsevier Ltd. All rights reserved.

Heuristic optimization in penumbral image for high resolution reconstructed image

International Nuclear Information System (INIS)

Azuma, R.; Nozaki, S.; Fujioka, S.; Chen, Y. W.; Namihira, Y.

2010-01-01

Penumbral imaging is a technique which uses the fact that spatial information can be recovered from the shadow or penumbra that an unknown source casts through a simple large circular aperture. The size of the penumbral image on the detector can be mathematically determined as its aperture size, object size, and magnification. Conventional reconstruction methods are very sensitive to noise. On the other hand, the heuristic reconstruction method is very tolerant of noise. However, the aperture size influences the accuracy and resolution of the reconstructed image. In this article, we propose the optimization of the aperture size for the neutron penumbral imaging.

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

Science.gov (United States)

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.

Super-resolution imaging of a 2.5 kb non-repetitive DNA in situ in the nuclear genome using molecular beacon probes

Science.gov (United States)

Ni, Yanxiang; Cao, Bo; Ma, Tszshan; Niu, Gang; Huo, Yingdong; Huang, Jiandong; Chen, Danni; Liu, Yi; Yu, Bin; Zhang, Michael Q; Niu, Hanben

2017-01-01

High-resolution visualization of short non-repetitive DNA in situ in the nuclear genome is essential for studying looping interactions and chromatin organization in single cells. Recent advances in fluorescence in situ hybridization (FISH) using Oligopaint probes have enabled super-resolution imaging of genomic domains with a resolution limit of 4.9 kb. To target shorter elements, we developed a simple FISH method that uses molecular beacon (MB) probes to facilitate the probe-target binding, while minimizing non-specific fluorescence. We used three-dimensional stochastic optical reconstruction microscopy (3D-STORM) with optimized imaging conditions to efficiently distinguish sparsely distributed Alexa-647 from background cellular autofluorescence. Utilizing 3D-STORM and only 29–34 individual MB probes, we observed 3D fine-scale nanostructures of 2.5 kb integrated or endogenous unique DNA in situ in human or mouse genome, respectively. We demonstrated our MB-based FISH method was capable of visualizing the so far shortest non-repetitive genomic sequence in 3D at super-resolution. DOI: http://dx.doi.org/10.7554/eLife.21660.001 PMID:28485713

DESIGN OF DYADIC-INTEGER-COEFFICIENTS BASED BI-ORTHOGONAL WAVELET FILTERS FOR IMAGE SUPER-RESOLUTION USING SUB-PIXEL IMAGE REGISTRATION

Directory of Open Access Journals (Sweden)

P.B. Chopade

2014-05-01

Full Text Available This paper presents image super-resolution scheme based on sub-pixel image registration by the design of a specific class of dyadic-integer-coefficient based wavelet filters derived from the construction of a half-band polynomial. First, the integer-coefficient based half-band polynomial is designed by the splitting approach. Next, this designed half-band polynomial is factorized and assigned specific number of vanishing moments and roots to obtain the dyadic-integer coefficients low-pass analysis and synthesis filters. The possibility of these dyadic-integer coefficients based wavelet filters is explored in the field of image super-resolution using sub-pixel image registration. The two-resolution frames are registered at a specific shift from one another to restore the resolution lost by CCD array of camera. The discrete wavelet transform (DWT obtained from the designed coefficients is applied on these two low-resolution images to obtain the high resolution image. The developed approach is validated by comparing the quality metrics with existing filter banks.

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

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Huang, Lianjie; Labyed, Yassin

2018-05-01

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

Energy Technology Data Exchange (ETDEWEB)

Dong, Bin [Iowa State Univ., Ames, IA (United States)

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 single 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).

High spatial resolution CT image reconstruction using parallel computing

International Nuclear Information System (INIS)

Yin Yin; Liu Li; Sun Gongxing

2003-01-01

Using the PC cluster system with 16 dual CPU nodes, we accelerate the FBP and OR-OSEM reconstruction of high spatial resolution image (2048 x 2048). Based on the number of projections, we rewrite the reconstruction algorithms into parallel format and dispatch the tasks to each CPU. By parallel computing, the speedup factor is roughly equal to the number of CPUs, which can be up to about 25 times when 25 CPUs used. This technique is very suitable for real-time high spatial resolution CT image reconstruction. (authors)

Registration-based approach for reconstruction of high-resolution in utero fetal MR brain images.

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Rousseau, Francois; Glenn, Orit A; Iordanova, Bistra; Rodriguez-Carranza, Claudia; Vigneron, Daniel B; Barkovich, James A; Studholme, Colin

2006-09-01

This paper describes a novel approach to forming high-resolution MR images of the human fetal brain. It addresses the key problem of fetal motion by proposing a registration-refined compounding of multiple sets of orthogonal fast two-dimensional MRI slices, which are currently acquired for clinical studies, into a single high-resolution MRI volume. A robust multiresolution slice alignment is applied iteratively to the data to correct motion of the fetus that occurs between two-dimensional acquisitions. This is combined with an intensity correction step and a super-resolution reconstruction step, to form a single high isotropic resolution volume of the fetal brain. Experimental validation on synthetic image data with known motion types and underlying anatomy, together with retrospective application to sets of clinical acquisitions, are included. Results indicate that this method promises a unique route to acquiring high-resolution MRI of the fetal brain in vivo allowing comparable quality to that of neonatal MRI. Such data provide a highly valuable window into the process of normal and abnormal brain development, which is directly applicable in a clinical setting.

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

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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.

Isotope specific resolution recovery image reconstruction in high resolution PET imaging

NARCIS (Netherlands)

Kotasidis, Fotis A.; Angelis, Georgios I.; Anton-Rodriguez, Jose; Matthews, Julian C.; Reader, Andrew J.; Zaidi, Habib

Purpose: Measuring and incorporating a scanner-specific point spread function (PSF) within image reconstruction has been shown to improve spatial resolution in PET. However, due to the short half-life of clinically used isotopes, other long-lived isotopes not used in clinical practice are used to

Application of regularization technique in image super-resolution algorithm via sparse representation

Science.gov (United States)

Huang, De-tian; Huang, Wei-qin; Huang, Hui; Zheng, Li-xin

2017-11-01

To make use of the prior knowledge of the image more effectively and restore more details of the edges and structures, a novel sparse coding objective function is proposed by applying the principle of the non-local similarity and manifold learning on the basis of super-resolution algorithm via sparse representation. Firstly, the non-local similarity regularization term is constructed by using the similar image patches to preserve the edge information. Then, the manifold learning regularization term is constructed by utilizing the locally linear embedding approach to enhance the structural information. The experimental results validate that the proposed algorithm has a significant improvement compared with several super-resolution algorithms in terms of the subjective visual effect and objective evaluation indices.

Texton-based super-resolution for achieving high spatiotemporal resolution in hybrid camera system

Science.gov (United States)

Kamimura, Kenji; Tsumura, Norimichi; Nakaguchi, Toshiya; Miyake, Yoichi

2010-05-01

Many super-resolution methods have been proposed to enhance the spatial resolution of images by using iteration and multiple input images. In a previous paper, we proposed the example-based super-resolution method to enhance an image through pixel-based texton substitution to reduce the computational cost. In this method, however, we only considered the enhancement of a texture image. In this study, we modified this texton substitution method for a hybrid camera to reduce the required bandwidth of a high-resolution video camera. We applied our algorithm to pairs of high- and low-spatiotemporal-resolution videos, which were synthesized to simulate a hybrid camera. The result showed that the fine detail of the low-resolution video can be reproduced compared with bicubic interpolation and the required bandwidth could be reduced to about 1/5 in a video camera. It was also shown that the peak signal-to-noise ratios (PSNRs) of the images improved by about 6 dB in a trained frame and by 1.0-1.5 dB in a test frame, as determined by comparison with the processed image using bicubic interpolation, and the average PSNRs were higher than those obtained by the well-known Freeman’s patch-based super-resolution method. Compared with that of the Freeman’s patch-based super-resolution method, the computational time of our method was reduced to almost 1/10.

Video-to-Video Dynamic Super-Resolution for Grayscale and Color Sequences

Directory of Open Access Journals (Sweden)

Elad Michael

2006-01-01

Full Text Available We address the dynamic super-resolution (SR problem of reconstructing a high-quality set of monochromatic or color super-resolved images from low-quality monochromatic, color, or mosaiced frames. Our approach includes a joint method for simultaneous SR, deblurring, and demosaicing, this way taking into account practical color measurements encountered in video sequences. For the case of translational motion and common space-invariant blur, the proposed method is based on a very fast and memory efficient approximation of the Kalman filter (KF. Experimental results on both simulated and real data are supplied, demonstrating the presented algorithms, and their strength.

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

Science.gov (United States)

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.

Nonlinear super-resolution nano-optics and applications

CERN Document Server

Wei, Jingsong

2015-01-01

This book covers many advances in the subjects of nano-optics and nano photonics. The author describes the principle and technical schematics of common methods for breaking through the optical diffraction limit and focuses on realizing optical super-resolution with nonlinear effects of thin film materials. The applications of nonlinear optical super-resolution effects in nano-data storage, nanolithography, and nano-imaging are also presented. This book is useful to graduate students majoring in optics and nano science and also serves as a reference book for academic researchers, engineers, technical professionals in the fields of super-resolution optics and laser techniques, nano-optics and nano photonics, nano-data storage, nano imaging, micro/nanofabrication and nanolithography and nonlinear optics.

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Bjoern Traenkle

2017-08-01

Full Text Available 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.

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

Science.gov (United States)

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.

Quantification of resolution in multiplanar reconstructions for digital breast tomosynthesis

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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.

Exploring sex differences in the adult zebra finch brain: In vivo diffusion tensor imaging and ex vivo super-resolution track density imaging.

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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

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

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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.

Performance Evaluations for Super-Resolution Mosaicing on UAS Surveillance Videos

Directory of Open Access Journals (Sweden)

Aldo Camargo

2013-05-01

Full Text Available Abstract Unmanned Aircraft Systems (UAS have been widely applied for reconnaissance and surveillance by exploiting information collected from the digital imaging payload. The super-resolution (SR mosaicing of low-resolution (LR UAS surveillance video frames has become a critical requirement for UAS video processing and is important for further effective image understanding. In this paper we develop a novel super-resolution framework, which does not require the construction of sparse matrices. The proposed method implements image operations in the spatial domain and applies an iterated back-projection to construct super-resolution mosaics from the overlapping UAS surveillance video frames. The Steepest Descent method, the Conjugate Gradient method and the Levenberg-Marquardt algorithm are used to numerically solve the nonlinear optimization problem for estimating a super-resolution mosaic. A quantitative performance comparison in terms of computation time and visual quality of the super-resolution mosaics through the three numerical techniques is presented.

Super-resolution imaging with Pontamine Fast Scarlet 4BS enables direct visualization of cellulose orientation and cell connection architecture in onion epidermis cells

DEFF Research Database (Denmark)

Liesche, Johannes; Ziomkiewicz, Iwona; Schulz, Alexander

2013-01-01

of cellulose fibril orientation and growth. The fluorescent dye Pontamine Fast Scarlet 4BS (PFS) was shown to stain cellulose with high specificity and could be used to visualize cellulose bundles in cell walls of Arabidopsis root epidermal cells with confocal microscopy. The resolution limit of confocal...... present the first super-resolution images of cellulose bundles in the plant cell wall produced by direct stochastic optical reconstruction microscopy (dSTORM) in combination with total internal reflection fluorescence (TIRF) microscopy. Since TIRF limits observation to the cell surface, we tested...... as alternatives 3D-structured illumination microscopy (3D-SIM) and confocal microscopy, combined with image deconvolution. Both methods offer lower resolution than STORM, but enable 3D imaging. While 3D-SIM produced strong artifacts, deconvolution gave good results. The resolution was improved over conventional...

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

Directory of Open Access Journals (Sweden)

Oleh Dzyubachyk

Full Text Available 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.

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

Science.gov (United States)

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.

Comparison of super-resolution benefits for downsampled iages and real low-resolution data

NARCIS (Netherlands)

Peng, Y.; Spreeuwers, Lieuwe Jan; Gökberk, B.; Veldhuis, Raymond N.J.

2013-01-01

Recently, more and more researchers are exploring the benefits of super-resolution methods on low-resolution face recognition. However, often results presented are obtained on downsampled high-resolution face images. Because downsampled images are different from real images taken at low resolution,

From local pixel structure to global image super-resolution: a new face hallucination framework.

Science.gov (United States)

Hu, Yu; Lam, Kin-Man; Qiu, Guoping; Shen, Tingzhi

2011-02-01

We have developed a new face hallucination framework termed from local pixel structure to global image super-resolution (LPS-GIS). Based on the assumption that two similar face images should have similar local pixel structures, the new framework first uses the input low-resolution (LR) face image to search a face database for similar example high-resolution (HR) faces in order to learn the local pixel structures for the target HR face. It then uses the input LR face and the learned pixel structures as priors to estimate the target HR face. We present a three-step implementation procedure for the framework. Step 1 searches the database for K example faces that are the most similar to the input, and then warps the K example images to the input using optical flow. Step 2 uses the warped HR version of the K example faces to learn the local pixel structures for the target HR face. An effective method for learning local pixel structures from an individual face, and an adaptive procedure for fusing the local pixel structures of different example faces to reduce the influence of warping errors, have been developed. Step 3 estimates the target HR face by solving a constrained optimization problem by means of an iterative procedure. Experimental results show that our new method can provide good performances for face hallucination, both in terms of reconstruction error and visual quality; and that it is competitive with existing state-of-the-art methods.

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

Science.gov (United States)

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.

Image Super-Resolution Algorithm Based on an Improved Sparse Autoencoder

Directory of Open Access Journals (Sweden)

Detian Huang

2018-01-01

Full Text Available Due to the limitations of the resolution of the imaging system and the influence of scene changes and other factors, sometimes only low-resolution images can be acquired, which cannot satisfy the practical application’s requirements. To improve the quality of low-resolution images, a novel super-resolution algorithm based on an improved sparse autoencoder is proposed. Firstly, in the training set preprocessing stage, the high- and low-resolution image training sets are constructed, respectively, by using high-frequency information of the training samples as the characterization, and then the zero-phase component analysis whitening technique is utilized to decorrelate the formed joint training set to reduce its redundancy. Secondly, a constructed sparse regularization term is added to the cost function of the traditional sparse autoencoder to further strengthen the sparseness constraint on the hidden layer. Finally, in the dictionary learning stage, the improved sparse autoencoder is adopted to achieve unsupervised dictionary learning to improve the accuracy and stability of the dictionary. Experimental results validate that the proposed algorithm outperforms the existing algorithms both in terms of the subjective visual perception and the objective evaluation indices, including the peak signal-to-noise ratio and the structural similarity measure.

Development of the super high angular resolution principle for X-ray imaging

International Nuclear Information System (INIS)

Zhang Chen; Zhang Shuangnan

2011-01-01

Development of the Super High Angular Resolution Principle (SHARP) for coded-mask X-ray imaging is presented. We prove that SHARP can be considered as a generalized coded mask imaging method with a coding pattern comprised of diffraction-interference fringes in the mask pattern. The angular resolution of SHARP can be improved by detecting the fringes more precisely than the mask's element size, i.e. by using a detector with a pixel size smaller than the mask's element size. The proposed mission SHARP-X for solar X-ray observations is also briefly discussed. (research papers)

Remote classification from an airborne camera using image super-resolution.

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Woods, Matthew; Katsaggelos, Aggelos

2017-02-01

The image processing technique known as super-resolution (SR), which attempts to increase the effective pixel sampling density of a digital imager, has gained rapid popularity over the last decade. The majority of literature focuses on its ability to provide results that are visually pleasing to a human observer. In this paper, we instead examine the ability of SR to improve the resolution-critical capability of an imaging system to perform a classification task from a remote location, specifically from an airborne camera. In order to focus the scope of the study, we address and quantify results for the narrow case of text classification. However, we expect the results generalize to a large set of related, remote classification tasks. We generate theoretical results through simulation, which are corroborated by experiments with a camera mounted on a DJI Phantom 3 quadcopter.

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

Science.gov (United States)

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

Science.gov (United States)

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 Interpolation Kernels for Super-resolution Algorithms

DEFF Research Database (Denmark)

Rasti, Pejman; Orlova, Olga; Tamberg, Gert

2016-01-01

Super resolution (SR) algorithms are widely used in forensics investigations to enhance the resolution of images captured by surveillance cameras. Such algorithms usually use a common interpolation algorithm to generate an initial guess for the desired high resolution (HR) image. This initial guess...... when their original interpolation kernel is replaced by the ones introduced in this work....

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

Science.gov (United States)

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.

New device based on the super spatial resolution (SSR) method

International Nuclear Information System (INIS)

Soluri, A.; Atzeni, G.; Ucci, A.; Bellone, T.; Cusanno, F.; Rodilossi, G.; Massari, R.

2013-01-01

Recently it have been described that innovative methods, namely Super Spatial Resolution (SSR), can be used to improve the scintigraphic imaging. The aim of SSR techniques is the enhancement of the resolution of an imaging system, using information from several images. In this paper we describe a new experimental apparatus that could be used for molecular imaging and small animal imaging. In fact we present a new device, completely automated, that uses the SSR method and provides images with better spatial resolution in comparison to the original resolution. Preliminary small animal imaging studies confirm the feasibility of a very high resolution system in scintigraphic imaging and the possibility to have gamma cameras using the SSR method, to perform the applications on functional imaging. -- Highlights: • Super spatial resolution brings a high resolution image from scintigraphic images. • Resolution improvement depends on the signal to noise ratio of the original images. • The SSR shows significant improvement on spatial resolution in scintigraphic images. • The SSR method is potentially utilizable for all scintigraphic devices

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

Science.gov (United States)

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.

Clinical evaluation of PET image reconstruction using a spatial resolution model

DEFF Research Database (Denmark)

Andersen, Flemming Littrup; Klausen, Thomas Levin; Loft, Annika

2013-01-01

PURPOSE: PET image resolution is variable across the measured field-of-view and described by the point spread function (PSF). When accounting for the PSF during PET image reconstruction image resolution is improved and partial volume effects are reduced. Here, we evaluate the effect of PSF......-based reconstruction on lesion quantification in routine clinical whole-body (WB) PET/CT imaging. MATERIALS AND METHODS: 41 oncology patients were referred for a WB-PET/CT examination (Biograph 40 TruePoint). Emission data were acquired at 2.5min/bed at 1hpi of 400 MBq [18F]-FDG. Attenuation-corrected PET images were...... reconstructed on 336×336-matrices using: (R1) standard AW-OSEM (4 iter, 8 subsets, 4mm Gaussian) and (R2) AW-OSEM with PSF (3 iter, 21 subsets, 2mm). Blinded and randomised reading of R1- and R2-PET images was performed. Individual lesions were located and counted independently on both sets of images...

Shedding light on endocytosis with optimized super-resolution microscopy

NARCIS (Netherlands)

Leyton Puig, D.M.

2017-01-01

Super-resolution microscopy is a relatively new microscopy technique that is still under optimization. In this thesis we focus on the improvement of the quality of super-resolution images, to apply them to the study of the processes of cell signaling and endocytosis. First, we show that the use of a

Single image super resolution algorithm based on edge interpolation in NSCT domain

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Application of super-resolution optical microscopy in biology

International Nuclear Information System (INIS)

Mao Xiuhai; Du Jiancong; Huang Qing; Fan Chunhai; Deng Suhui

2013-01-01

Background: A noninvasive, real-time far-field optical microscopy is needed to study the dynamic function inside cells and proteins. However, the resolution limit of traditional optical microscope is about 200 nm due to the diffraction limit of light. So, it's hard to directly observe the subcellular structures. Over the past several years of microscopy development, the diffraction limit of fluorescence microscopy has been overcome and its resolution limit is about tens of nanometers. Methods: To overcome the diffraction limit of light, many super-resolution fluoresce microscopes, including stimulated emission of depletion microscopy (STED), photoactivation localization microscopy (PALM) and stochastic optical reconstruction microscopy (STORM), have been developed. Conclusions: These methods have been applied in cell biology, microbiology and neurobiology, and the technology of super-resolution provides a new insight into the life science. (authors)

Low-Cost Super-Resolution Algorithms Implementation Over a HW/SW Video Compression Platform

Directory of Open Access Journals (Sweden)

Llopis Rafael Peset

2006-01-01

Full Text Available Two approaches are presented in this paper to improve the quality of digital images over the sensor resolution using super-resolution techniques: iterative super-resolution (ISR and noniterative super-resolution (NISR algorithms. The results show important improvements in the image quality, assuming that sufficient sample data and a reasonable amount of aliasing are available at the input images. These super-resolution algorithms have been implemented over a codesign video compression platform developed by Philips Research, performing minimal changes on the overall hardware architecture. In this way, a novel and feasible low-cost implementation has been obtained by using the resources encountered in a generic hybrid video encoder. Although a specific video codec platform has been used, the methodology presented in this paper is easily extendable to any other video encoder architectures. Finally a comparison in terms of memory, computational load, and image quality for both algorithms, as well as some general statements about the final impact of the sampling process on the quality of the super-resolved (SR image, are also presented.

Finite detector based projection model for super resolution CT

Energy Technology Data Exchange (ETDEWEB)

Yu, Hengyong; Wang, Ge [Wake Forest Univ. Health Sciences, Winston-Salem, NC (United States). Dept. of Radiology; Virgina Tech, Blacksburg, VA (United States). Biomedical Imaging Div.

2011-07-01

For finite detector and focal spot sizes, here we propose a projection model for super resolution CT. First, for a given X-ray source point, a projection datum is modeled as an area integral over a narrow fan-beam connecting the detector elemental borders and the X-ray source point. Then, the final projection value is expressed as the integral obtained in the first step over the whole focal spot support. An ordered-subset simultaneous algebraic reconstruction technique (OS-SART) is developed using the proposed projection model. In the numerical simulation, our method produces super spatial resolution and suppresses high-frequency artifacts. (orig.)

High resolution reconstruction of PET images using the iterative OSEM algorithm

International Nuclear Information System (INIS)

Doll, J.; Bublitz, O.; Werling, A.; Haberkorn, U.; Semmler, W.; Adam, L.E.; Pennsylvania Univ., Philadelphia, PA; Brix, G.

2004-01-01

Aim: Improvement of the spatial resolution in positron emission tomography (PET) by incorporation of the image-forming characteristics of the scanner into the process of iterative image reconstruction. Methods: All measurements were performed at the whole-body PET system ECAT EXACT HR + in 3D mode. The acquired 3D sinograms were sorted into 2D sinograms by means of the Fourier rebinning (FORE) algorithm, which allows the usage of 2D algorithms for image reconstruction. The scanner characteristics were described by a spatially variant line-spread function (LSF), which was determined from activated copper-64 line sources. This information was used to model the physical degradation processes in PET measurements during the course of 2D image reconstruction with the iterative OSEM algorithm. To assess the performance of the high-resolution OSEM algorithm, phantom measurements performed at a cylinder phantom, the hotspot Jaszczack phantom, and the 3D Hoffmann brain phantom as well as different patient examinations were analyzed. Results: Scanner characteristics could be described by a Gaussian-shaped LSF with a full-width at half-maximum increasing from 4.8 mm at the center to 5.5 mm at a radial distance of 10.5 cm. Incorporation of the LSF into the iteration formula resulted in a markedly improved resolution of 3.0 and 3.5 mm, respectively. The evaluation of phantom and patient studies showed that the high-resolution OSEM algorithm not only lead to a better contrast resolution in the reconstructed activity distributions but also to an improved accuracy in the quantification of activity concentrations in small structures without leading to an amplification of image noise or even the occurrence of image artifacts. Conclusion: The spatial and contrast resolution of PET scans can markedly be improved by the presented image restauration algorithm, which is of special interest for the examination of both patients with brain disorders and small animals. (orig.)

Reconstructed Image Spatial Resolution of Multiple Coincidences Compton Imager

Science.gov (United States)

Andreyev, Andriy; Sitek, Arkadiusz; Celler, Anna

2010-02-01

We study the multiple coincidences Compton imager (MCCI) which is based on a simultaneous acquisition of several photons emitted in cascade from a single nuclear decay. Theoretically, this technique should provide a major improvement in localization of a single radioactive source as compared to a standard Compton camera. In this work, we investigated the performance and limitations of MCCI using Monte Carlo computer simulations. Spatial resolutions of the reconstructed point source have been studied as a function of the MCCI parameters, including geometrical dimensions and detector characteristics such as materials, energy and spatial resolutions.

A super-high angular resolution principle for coded-mask X-ray imaging beyond the diffraction limit of a single pinhole

International Nuclear Information System (INIS)

Zhang Chen; Zhang Shuangnan

2009-01-01

High angular resolution X-ray imaging is always useful in astrophysics and solar physics. In principle, it can be performed by using coded-mask imaging with a very long mask-detector distance. Previously, the diffraction-interference effect was thought to degrade coded-mask imaging performance dramatically at the low energy end with its very long mask-detector distance. The diffraction-interference effect is described with numerical calculations, and the diffraction-interference cross correlation reconstruction method (DICC) is developed in order to overcome the imaging performance degradation. Based on the DICC, a super-high angular resolution principle (SHARP) for coded-mask X-ray imaging is proposed. The feasibility of coded mask imaging beyond the diffraction limit of a single pinhole is demonstrated with simulations. With the specification that the mask element size is 50 x 50 μm 2 and the mask-detector distance is 50 m, the achieved angular resolution is 0.32 arcsec above about 10 keV and 0.36 arcsec at 1.24 keV (λ = 1 nm), where diffraction cannot be neglected. The on-axis source location accuracy is better than 0.02 arcsec. Potential applications for solar observations and wide-field X-ray monitors are also briefly discussed. (invited reviews)

A resolution-enhancing image reconstruction method for few-view differential phase-contrast tomography

Science.gov (United States)

Guan, Huifeng; Anastasio, Mark A.

2017-03-01

It is well-known that properly designed image reconstruction methods can facilitate reductions in imaging doses and data-acquisition times in tomographic imaging. The ability to do so is particularly important for emerging modalities such as differential X-ray phase-contrast tomography (D-XPCT), which are currently limited by these factors. An important application of D-XPCT is high-resolution imaging of biomedical samples. However, reconstructing high-resolution images from few-view tomographic measurements remains a challenging task. In this work, a two-step sub-space reconstruction strategy is proposed and investigated for use in few-view D-XPCT image reconstruction. It is demonstrated that the resulting iterative algorithm can mitigate the high-frequency information loss caused by data incompleteness and produce images that have better preserved high spatial frequency content than those produced by use of a conventional penalized least squares (PLS) estimator.

Underwater video enhancement using multi-camera super-resolution

Science.gov (United States)

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.

Simultaneous super-resolution and blind deconvolution

International Nuclear Information System (INIS)

Sroubek, F; Flusser, J; Cristobal, G

2008-01-01

In many real applications, blur in input low-resolution images is a nuisance, which prevents traditional super-resolution methods from working correctly. This paper presents a unifying approach to the blind deconvolution and superresolution problem of multiple degraded low-resolution frames of the original scene. We introduce a method which assumes no prior information about the shape of degradation blurs and which is properly defined for any rational (fractional) resolution factor. The method minimizes a regularized energy function with respect to the high-resolution image and blurs, where regularization is carried out in both the image and blur domains. The blur regularization is based on a generalized multichannel blind deconvolution constraint. Experiments on real data illustrate robustness and utilization of the method

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

Science.gov (United States)

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

Hyperspectral Super-Resolution of Locally Low Rank Images From Complementary Multisource Data.

Science.gov (United States)

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.

Robust Single Image Super-Resolution via Deep Networks With Sparse Prior.

Science.gov (United States)

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.

Generation of super-resolution stills from video

CSIR Research Space (South Africa)

Duvenhage, B

2014-11-01

Full Text Available plane. If one accurately registers the image of the target on the focal plane to some reference then one can increase the effective sensor pixel density by stacking or appropriately combining the registered images. The super-resolution technique operates...

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

Science.gov (United States)

Huang, Lianjie; Labyed, Yassin

2018-05-01

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.

Extreme super-resolution using the spherical geodesic waveguide

Science.gov (United States)

Miñano, Juan Carlos; González, Juan Carlos; Benítez, Pablo; Grabovičkić, Dejan

2012-06-01

Leonhardt demonstrated (2009) that the 2D Maxwell Fish Eye lens (MFE) can focus perfectly 2D Helmholtz waves of arbitrary frequency, i.e., it can transport perfectly an outward (monopole) 2D Helmholtz wave field, generated by a point source, towards a "perfect point drain" located at the corresponding image point. Moreover, a prototype with λ/5 super-resolution (SR) property for one microwave frequency has been manufactured and tested (Ma et al, 2010). Although this prototype has been loaded with an impedance different from the "perfect point drain", it has shown super-resolution property. However, neither software simulations nor experimental measurements for a broad band of frequencies have yet been reported. Here we present steady state simulations for two cases, using perfect drain as suggested by Leonhardt and without perfect drain as in the prototype. All the simulations have been done using a device equivalent to the MFE, called the Spherical Geodesic Waveguide (SGW). The results show the super-resolution up to λ/3000, for the system loaded with the perfect drain, and up to λ /500 for a not perfect load. In both cases super-resolution only happens for discrete number of frequencies. Out of these frequencies, the SGW does not show super-resolution in the analysis carried out.

Super-resolution fluorescence imaging of nanoimprinted polymer patterns by selective fluorophore adsorption combined with redox switching

KAUST Repository

Yabiku, Y.; Kubo, S.; Nakagawa, M.; Vacha, M.; Habuchi, Satoshi

2013-01-01

We applied a super-resolution fluorescence imaging based on selective adsorption and redox switching of the fluorescent dye molecules for studying polymer nanostructures. We demonstrate that nano-scale structures of polymer thin films can

Solid-immersion fluorescence microscopy with increased emission and super resolution

Energy Technology Data Exchange (ETDEWEB)

Liau, Z. L.; Porter, J. M. [Lincoln Laboratory, Massachusetts Institute of Technology, Lexington, Massachusetts 02420 (United States); Liau, A. A.; Chen, J. J. [Institute for Medical Engineering and Science, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Salmon, W. C. [Whitehead Institute, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139 (United States); Sheu, S. S. [Department of Medicine, Jefferson Medical College, Philadelphia, Pennsylvania 19107 (United States)

2015-01-07

We investigate solid-immersion fluorescence microscopy suitable for super-resolution nanotechnology and biological imaging, and have observed limit of resolution as small as 15 nm with microspheres, mitochondria, and chromatin fibers. We have further observed that fluorescence efficiency increases with excitation power density, implicating appreciable stimulated emission and increased resolution. We discuss potential advantages of the solid-immersion microscopy, including combined use with previously established super-resolution techniques for reaching deeper beyond the conventional diffraction limit.

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

OpenAIRE

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)...

Development of a super-resolution optical microscope for directional dark matter search experiment

International Nuclear Information System (INIS)

Alexandrov, A.; Asada, T.; Consiglio, L.; D'Ambrosio, N.; De Lellis, G.; Di Crescenzo, A.; Di Marco, N.; Furuya, S.; Hakamata, K.; Ishikawa, M.; Katsuragawa, T.; Kuwabara, K.; Machii, S.; Naka, T.; Pupilli, F.; Sirignano, C.; Tawara, Y.; Tioukov, V.; Umemoto, A.; Yoshimoto, M.

2016-01-01

Nuclear emulsion is a perfect choice for a detector for directional DM search because of its high density and excellent position accuracy. The minimal detectable track length of a recoil nucleus in emulsion is required to be at least 100 nm, making the resolution of conventional optical microscopes insufficient to resolve them. Here we report about the R&D on a super-resolution optical microscope to be used in future directional DM search experiments with nuclear emulsion as a detector media. The microscope will be fully automatic, will use novel image acquisition and analysis techniques, will achieve the spatial resolution of the order of few tens of nm and will be capable of reconstructing recoil tracks with the length of at least 100 nm with high angular resolution.

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

Science.gov (United States)

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.

Super-resolved terahertz microscopy by knife-edge scan

Science.gov (United States)

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.

Triple-color super-resolution imaging of live cells: resolving submicroscopic receptor organization in the plasma membrane.

Science.gov (United States)

Wilmes, Stephan; Staufenbiel, Markus; Lisse, Domenik; Richter, Christian P; Beutel, Oliver; Busch, Karin B; Hess, Samuel T; Piehler, Jacob

2012-05-14

In living color: efficient intracellular covalent labeling of proteins with a photoswitchable dye using the HaloTag for dSTORM super-resolution imaging in live cells is described. The dynamics of cellular nanostructures at the plasma membrane were monitored with a time resolution of a few seconds. In combination with dual-color FPALM imaging, submicroscopic receptor organization within the context of the membrane skeleton was resolved. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Statistical dynamic image reconstruction in state-of-the-art high-resolution PET

International Nuclear Information System (INIS)

Rahmim, Arman; Cheng, J-C; Blinder, Stephan; Camborde, Maurie-Laure; Sossi, Vesna

2005-01-01

Modern high-resolution PET is now more than ever in need of scrutiny into the nature and limitations of the imaging modality itself as well as image reconstruction techniques. In this work, we have reviewed, analysed and addressed the following three considerations within the particular context of state-of-the-art dynamic PET imaging: (i) the typical average numbers of events per line-of-response (LOR) are now (much) less than unity (ii) due to the physical and biological decay of the activity distribution, one requires robust and efficient reconstruction algorithms applicable to a wide range of statistics and (iii) the computational considerations in dynamic imaging are much enhanced (i.e., more frames to be stored and reconstructed). Within the framework of statistical image reconstruction, we have argued theoretically and shown experimentally that the sinogram non-negativity constraint (when using the delayed-coincidence and/or scatter-subtraction techniques) is especially expected to result in an overestimation bias. Subsequently, two schemes are considered: (a) subtraction techniques in which an image non-negativity constraint has been imposed and (b) implementation of random and scatter estimates inside the reconstruction algorithms, thus enabling direct processing of Poisson-distributed prompts. Both techniques are able to remove the aforementioned bias, while the latter, being better conditioned theoretically, is able to exhibit superior noise characteristics. We have also elaborated upon and verified the applicability of the accelerated list-mode image reconstruction method as a powerful solution for accurate, robust and efficient dynamic reconstructions of high-resolution data (as well as a number of additional benefits in the context of state-of-the-art PET)

Image quality assessment for selfies with and without super resolution

Science.gov (United States)

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.

Super Resolution and Interference Suppression Technique applied to SHARAD Radar Data

Science.gov (United States)

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).

Comparison between beamforming and super resolution imaging algorithms for non-destructive evaluation

Energy Technology Data Exchange (ETDEWEB)

Fan, Chengguang [College of Mechatronic Engineering and Automation, National University of Defense Technology, Changsha 410073, PR China and Department of Mechanical Engineering, University of Bristol, Queen' s Building, University Walk, Bristol BS8 1TR (United Kingdom); Drinkwater, Bruce W. [Department of Mechanical Engineering, University of Bristol, Queen' s Building, University Walk, Bristol BS8 1TR (United Kingdom)

2014-02-18

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. However, for higher noise levels, the total focusing method shows robustness, whilst the performance of time-reversal MUSIC is significantly degraded.

Comparison between beamforming and super resolution imaging algorithms for non-destructive evaluation

International Nuclear Information System (INIS)

Fan, Chengguang; Drinkwater, Bruce W.

2014-01-01

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. However, for higher noise levels, the total focusing method shows robustness, whilst the performance of time-reversal MUSIC is significantly degraded

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Single image super-resolution using locally adaptive multiple linear regression.

Science.gov (United States)

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

2015-12-01

This paper presents a regularized superresolution (SR) reconstruction method using locally adaptive multiple linear regression to overcome the limitation of spatial resolution of digital images. In order to make the SR problem better-posed, the proposed method incorporates the locally adaptive multiple linear regression into the regularization process as a local prior. The local regularization prior assumes that the target high-resolution (HR) pixel is generated by a linear combination of similar pixels in differently scaled patches and optimum weight parameters. In addition, we adapt a modified version of the nonlocal means filter as a smoothness prior to utilize the patch redundancy. Experimental results show that the proposed algorithm better restores HR images than existing state-of-the-art methods in the sense of the most objective measures in the literature.

Super-resolution fluorescence imaging of nanoimprinted polymer patterns by selective fluorophore adsorption combined with redox switching

KAUST Repository

Yabiku, Y.

2013-10-22

We applied a super-resolution fluorescence imaging based on selective adsorption and redox switching of the fluorescent dye molecules for studying polymer nanostructures. We demonstrate that nano-scale structures of polymer thin films can be visualized with the image resolution better than 80 nm. The method was applied to image 100 nm-wide polymer nanopatterns fabricated by thermal nanoimprinting. The results point to the applicability of the method for evaluating residual polymer thin films and dewetting defect of the polymer resist patterns which are important for the quality control of the fine nanoimprinted patterns. 2013 Author(s).

Super-resolution fluorescence imaging of nanoimprinted polymer patterns by selective fluorophore adsorption combined with redox switching

Directory of Open Access Journals (Sweden)

Yu Yabiku

2013-10-01

Full Text Available We applied a super-resolution fluorescence imaging based on selective adsorption and redox switching of the fluorescent dye molecules for studying polymer nanostructures. We demonstrate that nano-scale structures of polymer thin films can be visualized with the image resolution better than 80 nm. The method was applied to image 100 nm-wide polymer nanopatterns fabricated by thermal nanoimprinting. The results point to the applicability of the method for evaluating residual polymer thin films and dewetting defect of the polymer resist patterns which are important for the quality control of the fine nanoimprinted patterns.

A new method for measuring temporal resolution in electrocardiogram-gated reconstruction image with area-detector computed tomography

International Nuclear Information System (INIS)

Kaneko, Takeshi; Takagi, Masachika; Kato, Ryohei; Anno, Hirofumi; Kobayashi, Masanao; Yoshimi, Satoshi; Sanda, Yoshihiro; Katada, Kazuhiro

2012-01-01

The purpose of this study was to design and construct a phantom for using motion artifact in the electrocardiogram (ECG)-gated reconstruction image. In addition, the temporal resolution under various conditions was estimated. A stepping motor was used to move the phantom over an arc in a reciprocating manner. The program for controlling the stepping motor permitted the stationary period and the heart rate to be adjusted as desired. Images of the phantom were obtained using a 320-row area-detector computed tomography (ADCT) system under various conditions using the ECG-gated reconstruction method. For estimation, the reconstruction phase was continuously changed and the motion artifacts were quantitatively assessed. The temporal resolution was calculated from the number of motion-free images. Changes in the temporal resolution according to heart rate, rotation time, the number of reconstruction segments and acquisition position in z-axis were also investigated. The measured temporal resolution of ECG-gated half reconstruction is 180 ms, which is in good agreement with the nominal temporal resolution of 175 ms. The measured temporal resolution of ECG-gated segmental reconstruction is in good agreement with the nominal temporal resolution in most cases. The estimated temporal resolution improved to approach the nominal temporal resolution as the number of reconstruction segments was increased. Temporal resolution in changing acquisition position is equal. This study shows that we could design a new phantom for estimating temporal resolution. (author)

Interior tomography in microscopic CT with image reconstruction constrained by full field of view scan at low spatial resolution

Science.gov (United States)

Luo, Shouhua; Shen, Tao; Sun, Yi; Li, Jing; Li, Guang; Tang, Xiangyang

2018-04-01

In high resolution (microscopic) CT applications, the scan field of view should cover the entire specimen or sample to allow complete data acquisition and image reconstruction. However, truncation may occur in projection data and results in artifacts in reconstructed images. In this study, we propose a low resolution image constrained reconstruction algorithm (LRICR) for interior tomography in microscopic CT at high resolution. In general, the multi-resolution acquisition based methods can be employed to solve the data truncation problem if the project data acquired at low resolution are utilized to fill up the truncated projection data acquired at high resolution. However, most existing methods place quite strict restrictions on the data acquisition geometry, which greatly limits their utility in practice. In the proposed LRICR algorithm, full and partial data acquisition (scan) at low and high resolutions, respectively, are carried out. Using the image reconstructed from sparse projection data acquired at low resolution as the prior, a microscopic image at high resolution is reconstructed from the truncated projection data acquired at high resolution. Two synthesized digital phantoms, a raw bamboo culm and a specimen of mouse femur, were utilized to evaluate and verify performance of the proposed LRICR algorithm. Compared with the conventional TV minimization based algorithm and the multi-resolution scout-reconstruction algorithm, the proposed LRICR algorithm shows significant improvement in reduction of the artifacts caused by data truncation, providing a practical solution for high quality and reliable interior tomography in microscopic CT applications. The proposed LRICR algorithm outperforms the multi-resolution scout-reconstruction method and the TV minimization based reconstruction for interior tomography in microscopic CT.

Extracting a Good Quality Frontal Face Image from a Low-Resolution Video Sequence

DEFF Research Database (Denmark)

Nasrollahi, Kamal; Moeslund, Thomas B.

2011-01-01

Feeding low-resolution and low-quality images, from inexpensive surveillance cameras, to systems like, e.g., face recognition, produces erroneous and unstable results. Therefore, there is a need for a mechanism to bridge the gap between on one hand low-resolution and low-quality images......, we use a learning-based super-resolution algorithm applied to the result of the reconstruction-based part to improve the quality by another factor of two. This results in an improvement factor of four for the entire system. The proposed system has been tested on 122 low-resolution sequences from two...... different databases. The experimental results show that the proposed system can indeed produce a high-resolution and good quality frontal face image from low-resolution video sequences....

Unraveling the Thousand Word Picture: An Introduction to Super-Resolution Data Analysis.

Science.gov (United States)

Lee, Antony; Tsekouras, Konstantinos; Calderon, Christopher; Bustamante, Carlos; Pressé, Steve

2017-06-14

Super-resolution microscopy provides direct insight into fundamental biological processes occurring at length scales smaller than light's diffraction limit. The analysis of data at such scales has brought statistical and machine learning methods into the mainstream. Here we provide a survey of data analysis methods starting from an overview of basic statistical techniques underlying the analysis of super-resolution and, more broadly, imaging data. We subsequently break down the analysis of super-resolution data into four problems: the localization problem, the counting problem, the linking problem, and what we've termed the interpretation problem.

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

Science.gov (United States)

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.

3D Super-Resolution Motion-Corrected MRI: Validation of Fetal Posterior Fossa Measurements.

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Pier, Danielle B; Gholipour, Ali; Afacan, Onur; Velasco-Annis, Clemente; Clancy, Sean; Kapur, Kush; Estroff, Judy A; Warfield, Simon K

2016-09-01

Current diagnosis of fetal posterior fossa anomalies by sonography and conventional MRI is limited by fetal position, motion, and by two-dimensional (2D), rather than three-dimensional (3D), representation. In this study, we aimed to validate the use of a novel magnetic resonance imaging (MRI) technique, 3D super-resolution motion-corrected MRI, to image the fetal posterior fossa. From a database of pregnant women who received fetal MRIs at our institution, images of 49 normal fetal brains were reconstructed. Six measurements of the cerebellum, vermis, and pons were obtained for all cases on 2D conventional and 3D reconstructed MRI, and the agreement between the two methods was determined using concordance correlation coefficients. Concordance of axial and coronal measurements of the transcerebellar diameter was also assessed within each method. Between the two methods, the concordance of measurements was high for all six structures (P fetal motion and orthogonal slice acquisition. This technique will facilitate further study of fetal abnormalities of the posterior fossa. Copyright © 2016 by the American Society of Neuroimaging.

Learning from errors in super-resolution.

Science.gov (United States)

Tang, Yi; Yuan, Yuan

2014-11-01

A novel framework of learning-based super-resolution is proposed by employing the process of learning from the estimation errors. The estimation errors generated by different learning-based super-resolution algorithms are statistically shown to be sparse and uncertain. The sparsity of the estimation errors means most of estimation errors are small enough. The uncertainty of the estimation errors means the location of the pixel with larger estimation error is random. Noticing the prior information about the estimation errors, a nonlinear boosting process of learning from these estimation errors is introduced into the general framework of the learning-based super-resolution. Within the novel framework of super-resolution, a low-rank decomposition technique is used to share the information of different super-resolution estimations and to remove the sparse estimation errors from different learning algorithms or training samples. The experimental results show the effectiveness and the efficiency of the proposed framework in enhancing the performance of different learning-based algorithms.

B-Spline potential function for maximum a-posteriori image reconstruction in fluorescence microscopy

Directory of Open Access Journals (Sweden)

Shilpa Dilipkumar

2015-03-01

Full Text Available An iterative image reconstruction technique employing B-Spline potential function in a Bayesian framework is proposed for fluorescence microscopy images. B-splines are piecewise polynomials with smooth transition, compact support and are the shortest polynomial splines. Incorporation of the B-spline potential function in the maximum-a-posteriori reconstruction technique resulted in improved contrast, enhanced resolution and substantial background reduction. The proposed technique is validated on simulated data as well as on the images acquired from fluorescence microscopes (widefield, confocal laser scanning fluorescence and super-resolution 4Pi microscopy. A comparative study of the proposed technique with the state-of-art maximum likelihood (ML and maximum-a-posteriori (MAP with quadratic potential function shows its superiority over the others. B-Spline MAP technique can find applications in several imaging modalities of fluorescence microscopy like selective plane illumination microscopy, localization microscopy and STED.

Alpha image reconstruction (AIR): A new iterative CT image reconstruction approach using voxel-wise alpha blending

International Nuclear Information System (INIS)

Hofmann, Christian; Sawall, Stefan; Knaup, Michael; Kachelrieß, Marc

2014-01-01

Purpose: Iterative image reconstruction gains more and more interest in clinical routine, as it promises to reduce image noise (and thereby patient dose), to reduce artifacts, or to improve spatial resolution. Among vendors and researchers, however, there is no consensus of how to best achieve these aims. The general approach is to incorporatea priori knowledge into iterative image reconstruction, for example, by adding additional constraints to the cost function, which penalize variations between neighboring voxels. However, this approach to regularization in general poses a resolution noise trade-off because the stronger the regularization, and thus the noise reduction, the stronger the loss of spatial resolution and thus loss of anatomical detail. The authors propose a method which tries to improve this trade-off. The proposed reconstruction algorithm is called alpha image reconstruction (AIR). One starts with generating basis images, which emphasize certain desired image properties, like high resolution or low noise. The AIR algorithm reconstructs voxel-specific weighting coefficients that are applied to combine the basis images. By combining the desired properties of each basis image, one can generate an image with lower noise and maintained high contrast resolution thus improving the resolution noise trade-off. Methods: All simulations and reconstructions are performed in native fan-beam geometry. A water phantom with resolution bar patterns and low contrast disks is simulated. A filtered backprojection (FBP) reconstruction with a Ram-Lak kernel is used as a reference reconstruction. The results of AIR are compared against the FBP results and against a penalized weighted least squares reconstruction which uses total variation as regularization. The simulations are based on the geometry of the Siemens Somatom Definition Flash scanner. To quantitatively assess image quality, the authors analyze line profiles through resolution patterns to define a contrast

Special issue on high-resolution optical imaging

Science.gov (United States)

Smith, Peter J. S.; Davis, Ilan; Galbraith, Catherine G.; Stemmer, Andreas

2013-09-01

The pace of development in the field of advanced microscopy is truly breath-taking, and is leading to major breakthroughs in our understanding of molecular machines and cell function. This special issue of Journal of Optics draws attention to a number of interesting approaches, ranging from fluorescence and imaging of unlabelled cells, to computational methods, all of which are describing the ever increasing detail of the dynamic behaviour of molecules in the living cell. This is a field which traditionally, and currently, demonstrates a marvellous interplay between the disciplines of physics, chemistry and biology, where apparent boundaries to resolution dissolve and living cells are viewed in ever more clarity. It is fertile ground for those interested in optics and non-conventional imaging to contribute high-impact outputs in the fields of cell biology and biomedicine. The series of articles presented here has been selected to demonstrate this interdisciplinarity and to encourage all those with a background in the physical sciences to 'dip their toes' into the exciting and dynamic discoveries surrounding cell function. Although single molecule super-resolution microscopy is commercially available, specimen preparation and interpretation of single molecule data remain a major challenge for scientists wanting to adopt the techniques. The paper by Allen and Davidson [1] provides a much needed detailed introduction to the practical aspects of stochastic optical reconstruction microscopy, including sample preparation, image acquisition and image analysis, as well as a brief description of the different variants of single molecule localization microscopy. Since super-resolution microscopy is no longer restricted to three-dimensional imaging of fixed samples, the review by Fiolka [2] is a timely introduction to techniques that have been successfully applied to four-dimensional live cell super-resolution microscopy. The combination of multiple high-resolution techniques

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

International Nuclear Information System (INIS)

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

2017-01-01

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. (paper)

A super-resolution approach for uncertainty estimation of PIV measurements

NARCIS (Netherlands)

Sciacchitano, A.; Wieneke, B.; Scarano, F.

2012-01-01

A super-resolution approach is proposed for the a posteriori uncertainty estimation of PIV measurements. The measured velocity field is employed to determine the displacement of individual particle images. A disparity set is built from the residual distance between paired particle images of

Online detector response calculations for high-resolution PET image reconstruction

Energy Technology Data Exchange (ETDEWEB)

Pratx, Guillem [Department of Radiation Oncology, Stanford University, Stanford, CA 94305 (United States); Levin, Craig, E-mail: cslevin@stanford.edu [Departments of Radiology, Physics and Electrical Engineering, and Molecular Imaging Program at Stanford, Stanford University, Stanford, CA 94305 (United States)

2011-07-07

Positron emission tomography systems are best described by a linear shift-varying model. However, image reconstruction often assumes simplified shift-invariant models to the detriment of image quality and quantitative accuracy. We investigated a shift-varying model of the geometrical system response based on an analytical formulation. The model was incorporated within a list-mode, fully 3D iterative reconstruction process in which the system response coefficients are calculated online on a graphics processing unit (GPU). The implementation requires less than 512 Mb of GPU memory and can process two million events per minute (forward and backprojection). For small detector volume elements, the analytical model compared well to reference calculations. Images reconstructed with the shift-varying model achieved higher quality and quantitative accuracy than those that used a simpler shift-invariant model. For an 8 mm sphere in a warm background, the contrast recovery was 95.8% for the shift-varying model versus 85.9% for the shift-invariant model. In addition, the spatial resolution was more uniform across the field-of-view: for an array of 1.75 mm hot spheres in air, the variation in reconstructed sphere size was 0.5 mm RMS for the shift-invariant model, compared to 0.07 mm RMS for the shift-varying model.

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

Science.gov (United States)

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.

Correlative Stochastic Optical Reconstruction Microscopy and Electron Microscopy

Science.gov (United States)

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

Efficient methodologies for system matrix modelling in iterative image reconstruction for rotating high-resolution PET

Energy Technology Data Exchange (ETDEWEB)

Ortuno, J E; Kontaxakis, G; Rubio, J L; Santos, A [Departamento de Ingenieria Electronica (DIE), Universidad Politecnica de Madrid, Ciudad Universitaria s/n, 28040 Madrid (Spain); Guerra, P [Networking Research Center on Bioengineering, Biomaterials and Nanomedicine (CIBER-BBN), Madrid (Spain)], E-mail: juanen@die.upm.es

2010-04-07

A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries.

Statistical list-mode image reconstruction for the high resolution research tomograph

International Nuclear Information System (INIS)

Rahmim, A; Lenox, M; Reader, A J; Michel, C; Burbar, Z; Ruth, T J; Sossi, V

2004-01-01

We have investigated statistical list-mode reconstruction applicable to a depth-encoding high resolution research tomograph. An image non-negativity constraint has been employed in the reconstructions and is shown to effectively remove the overestimation bias introduced by the sinogram non-negativity constraint. We have furthermore implemented a convergent subsetized (CS) list-mode reconstruction algorithm, based on previous work (Hsiao et al 2002 Conf. Rec. SPIE Med. Imaging 4684 10-19; Hsiao et al 2002 Conf. Rec. IEEE Int. Symp. Biomed. Imaging 409-12) on convergent histogram OSEM reconstruction. We have demonstrated that the first step of the convergent algorithm is exactly equivalent (unlike the histogram-mode case) to the regular subsetized list-mode EM algorithm, while the second and final step takes the form of additive updates in image space. We have shown that in terms of contrast, noise as well as FWHM width behaviour, the CS algorithm is robust and does not result in limit cycles. A hybrid algorithm based on the ordinary and the convergent algorithms is also proposed, and is shown to combine the advantages of the two algorithms (i.e. it is able to reach a higher image quality in fewer iterations while maintaining the convergent behaviour), making the hybrid approach a good alternative to the ordinary subsetized list-mode EM algorithm

Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy

International Nuclear Information System (INIS)

Tang, Jing; Rahmim, Arman

2015-01-01

A promising approach in PET image reconstruction is to incorporate high resolution anatomical information (measured from MR or CT) taking the anato-functional similarity measures such as mutual information or joint entropy (JE) as the prior. These similarity measures only classify voxels based on intensity values, while neglecting structural spatial information. In this work, we developed an anatomy-assisted maximum a posteriori (MAP) reconstruction algorithm wherein the JE measure is supplied by spatial information generated using wavelet multi-resolution analysis. The proposed wavelet-based JE (WJE) MAP algorithm involves calculation of derivatives of the subband JE measures with respect to individual PET image voxel intensities, which we have shown can be computed very similarly to how the inverse wavelet transform is implemented. We performed a simulation study with the BrainWeb phantom creating PET data corresponding to different noise levels. Realistically simulated T1-weighted MR images provided by BrainWeb modeling were applied in the anatomy-assisted reconstruction with the WJE-MAP algorithm and the intensity-only JE-MAP algorithm. Quantitative analysis showed that the WJE-MAP algorithm performed similarly to the JE-MAP algorithm at low noise level in the gray matter (GM) and white matter (WM) regions in terms of noise versus bias tradeoff. When noise increased to medium level in the simulated data, the WJE-MAP algorithm started to surpass the JE-MAP algorithm in the GM region, which is less uniform with smaller isolated structures compared to the WM region. In the high noise level simulation, the WJE-MAP algorithm presented clear improvement over the JE-MAP algorithm in both the GM and WM regions. In addition to the simulation study, we applied the reconstruction algorithms to real patient studies involving DPA-173 PET data and Florbetapir PET data with corresponding T1-MPRAGE MRI images. Compared to the intensity-only JE-MAP algorithm, the WJE

Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy

Science.gov (United States)

Tang, Jing; Rahmim, Arman

2015-01-01

A promising approach in PET image reconstruction is to incorporate high resolution anatomical information (measured from MR or CT) taking the anato-functional similarity measures such as mutual information or joint entropy (JE) as the prior. These similarity measures only classify voxels based on intensity values, while neglecting structural spatial information. In this work, we developed an anatomy-assisted maximum a posteriori (MAP) reconstruction algorithm wherein the JE measure is supplied by spatial information generated using wavelet multi-resolution analysis. The proposed wavelet-based JE (WJE) MAP algorithm involves calculation of derivatives of the subband JE measures with respect to individual PET image voxel intensities, which we have shown can be computed very similarly to how the inverse wavelet transform is implemented. We performed a simulation study with the BrainWeb phantom creating PET data corresponding to different noise levels. Realistically simulated T1-weighted MR images provided by BrainWeb modeling were applied in the anatomy-assisted reconstruction with the WJE-MAP algorithm and the intensity-only JE-MAP algorithm. Quantitative analysis showed that the WJE-MAP algorithm performed similarly to the JE-MAP algorithm at low noise level in the gray matter (GM) and white matter (WM) regions in terms of noise versus bias tradeoff. When noise increased to medium level in the simulated data, the WJE-MAP algorithm started to surpass the JE-MAP algorithm in the GM region, which is less uniform with smaller isolated structures compared to the WM region. In the high noise level simulation, the WJE-MAP algorithm presented clear improvement over the JE-MAP algorithm in both the GM and WM regions. In addition to the simulation study, we applied the reconstruction algorithms to real patient studies involving DPA-173 PET data and Florbetapir PET data with corresponding T1-MPRAGE MRI images. Compared to the intensity-only JE-MAP algorithm, the WJE

Optimized labeling of membrane proteins for applications to super-resolution imaging in confined cellular environments using monomeric streptavidin.

Science.gov (United States)

Chamma, Ingrid; Rossier, Olivier; Giannone, Grégory; Thoumine, Olivier; Sainlos, Matthieu

2017-04-01

Recent progress in super-resolution imaging (SRI) has created a strong need to improve protein labeling with probes of small size that minimize the target-to-label distance, increase labeling density, and efficiently penetrate thick biological tissues. This protocol describes a method for labeling genetically modified proteins incorporating a small biotin acceptor peptide with a 3-nm fluorescent probe, monomeric streptavidin. We show how to express, purify, and conjugate the probe to organic dyes with different fluorescent properties, and how to label selectively biotinylated membrane proteins for SRI techniques (point accumulation in nanoscale topography (PAINT), stimulated emission depletion (STED), stochastic optical reconstruction microscopy (STORM)). This method is complementary to the previously described anti-GFP-nanobody/SNAP-tag strategies, with the main advantage being that it requires only a short 15-amino-acid tag, and can thus be used with proteins resistant to fusion with large tags and for multicolor imaging. The protocol requires standard molecular biology/biochemistry equipment, making it easily accessible for laboratories with only basic skills in cell biology and biochemistry. The production/purification/conjugation steps take ∼5 d, and labeling takes a few minutes to an hour.

LOR-interleaving image reconstruction for PET imaging with fractional-crystal collimation

International Nuclear Information System (INIS)

Li, Yusheng; Matej, Samuel; Karp, Joel S; Metzler, Scott D

2015-01-01

Positron emission tomography (PET) has become an important modality in medical and molecular imaging. However, in most PET applications, the resolution is still mainly limited by the physical crystal sizes or the detector’s intrinsic spatial resolution. To achieve images with better spatial resolution in a central region of interest (ROI), we have previously proposed using collimation in PET scanners. The collimator is designed to partially mask detector crystals to detect lines of response (LORs) within fractional crystals. A sequence of collimator-encoded LORs is measured with different collimation configurations. This novel collimated scanner geometry makes the reconstruction problem challenging, as both detector and collimator effects need to be modeled to reconstruct high-resolution images from collimated LORs. In this paper, we present a LOR-interleaving (LORI) algorithm, which incorporates these effects and has the advantage of reusing existing reconstruction software, to reconstruct high-resolution images for PET with fractional-crystal collimation. We also develop a 3D ray-tracing model incorporating both the collimator and crystal penetration for simulations and reconstructions of the collimated PET. By registering the collimator-encoded LORs with the collimator configurations, high-resolution LORs are restored based on the modeled transfer matrices using the non-negative least-squares method and EM algorithm. The resolution-enhanced images are then reconstructed from the high-resolution LORs using the MLEM or OSEM algorithm. For validation, we applied the LORI method to a small-animal PET scanner, A-PET, with a specially designed collimator. We demonstrate through simulated reconstructions with a hot-rod phantom and MOBY phantom that the LORI reconstructions can substantially improve spatial resolution and quantification compared to the uncollimated reconstructions. The LORI algorithm is crucial to improve overall image quality of collimated PET, which

Super-resolution in plenoptic cameras using FPGAs.

Science.gov (United States)

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.

Super-Resolution in Plenoptic Cameras Using FPGAs

Directory of Open Access Journals (Sweden)

Joel Pérez

2014-05-01

Full Text Available 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.

Deterministic phase measurements exhibiting super-sensitivity and super-resolution

DEFF Research Database (Denmark)

Schäfermeier, Clemens; Ježek, Miroslav; Madsen, Lars S.

2018-01-01

Phase super-sensitivity is obtained when the sensitivity in a phase measurement goes beyond the quantum shot noise limit, whereas super-resolution is obtained when the interference fringes in an interferometer are narrower than half the input wavelength. Here we show experimentally that these two...

Use of scanner characteristics in iterative image reconstruction for high-resolution positron emission tomography studies of small animals

Energy Technology Data Exchange (ETDEWEB)

Brix, G. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Doll, J. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Bellemann, M.E. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Trojan, H. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Haberkorn, U. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Schmidlin, P. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany); Ostertag, H. [Research Program ``Radiological Diagnostics and Therapy``, German Cancer Research Center (DKFZ), Heidelberg (Germany)

1997-07-01

The purpose of this work was to improve of the spatial resolution of a whole-body PET system for experimental studies of small animals by incorporation of scanner characteristics into the process of iterative image reconstruction. The image-forming characteristics of the PET camera were characterized by a spatially variant line-spread function (LSF), which was determined from 49 activated copper-64 line sources positioned over a field of view (FOV) of 21.0 cm. During the course of iterative image reconstruction, the forward projection of the estimated image was blurred with the LSF at each iteration step before the estimated projections were compared with the measured projections. Moreover, imaging studies of a rat and two nude mice were performed to evaluate the imaging properties of our approach in vivo. The spatial resolution of the scanner perpendicular to the direction of projection could be approximated by a one-dimensional Gaussian-shaped LSF with a full-width at half-maximum increasing from 6.5 mm at the centre to 6.7 mm at a radial distance of 10.5 cm. The incorporation of this blurring kernel into the iteration formula resulted in a significantly improved spatial resolution of about 3.9 mm over the examined FOV. As demonstrated by the phantom and the animal experiments, the high-resolution algorithm not only led to a better contrast resolution in the reconstructed emission scans but also improved the accuracy for quantitating activity concentrations in small tissue structures without leading to an amplification of image noise or image mottle. The presented data-handling strategy incorporates the image restoration step directly into the process of algebraic image reconstruction and obviates the need for ill-conditioned ``deconvolution`` procedures to be performed on the projections or on the reconstructed image. In our experience, the proposed algorithm is of special interest in experimental studies of small animals. (orig./AJ). With 9 figs.

Use of scanner characteristics in iterative image reconstruction for high-resolution positron emission tomography studies of small animals

International Nuclear Information System (INIS)

Brix, G.; Doll, J.; Bellemann, M.E.; Trojan, H.; Haberkorn, U.; Schmidlin, P.; Ostertag, H.

1997-01-01

The purpose of this work was to improve of the spatial resolution of a whole-body PET system for experimental studies of small animals by incorporation of scanner characteristics into the process of iterative image reconstruction. The image-forming characteristics of the PET camera were characterized by a spatially variant line-spread function (LSF), which was determined from 49 activated copper-64 line sources positioned over a field of view (FOV) of 21.0 cm. During the course of iterative image reconstruction, the forward projection of the estimated image was blurred with the LSF at each iteration step before the estimated projections were compared with the measured projections. Moreover, imaging studies of a rat and two nude mice were performed to evaluate the imaging properties of our approach in vivo. The spatial resolution of the scanner perpendicular to the direction of projection could be approximated by a one-dimensional Gaussian-shaped LSF with a full-width at half-maximum increasing from 6.5 mm at the centre to 6.7 mm at a radial distance of 10.5 cm. The incorporation of this blurring kernel into the iteration formula resulted in a significantly improved spatial resolution of about 3.9 mm over the examined FOV. As demonstrated by the phantom and the animal experiments, the high-resolution algorithm not only led to a better contrast resolution in the reconstructed emission scans but also improved the accuracy for quantitating activity concentrations in small tissue structures without leading to an amplification of image noise or image mottle. The presented data-handling strategy incorporates the image restoration step directly into the process of algebraic image reconstruction and obviates the need for ill-conditioned ''deconvolution'' procedures to be performed on the projections or on the reconstructed image. In our experience, the proposed algorithm is of special interest in experimental studies of small animals. (orig./AJ). With 9 figs

Super-Resolution Molecular and Functional Imaging of Nanoscale Architectures in Life and Materials Science

KAUST Repository

Habuchi, Satoshi

2014-06-12

Super-resolution (SR) fluorescence microscopy has been revolutionizing the way in which we investigate the structures, dynamics, and functions of a wide range of nanoscale systems. In this review, I describe the current state of various SR fluorescence microscopy techniques along with the latest developments of fluorophores and labeling for the SR microscopy. I discuss the applications of SR microscopy in the fields of life science and materials science with a special emphasis on quantitative molecular imaging and nanoscale functional imaging. These studies open new opportunities for unraveling the physical, chemical, and optical properties of a wide range of nanoscale architectures together with their nanostructures and will enable the development of new (bio-)nanotechnology.

Three-dimensional inversion recovery manganese-enhanced MRI of mouse brain using super-resolution reconstruction to visualize nuclei involved in higher brain function.

Science.gov (United States)

Poole, Dana S; Plenge, Esben; Poot, Dirk H J; Lakke, Egbert A J F; Niessen, Wiro J; Meijering, Erik; van der Weerd, Louise

2014-07-01

The visualization of activity in mouse brain using inversion recovery spin echo (IR-SE) manganese-enhanced MRI (MEMRI) provides unique contrast, but suffers from poor resolution in the slice-encoding direction. Super-resolution reconstruction (SRR) is a resolution-enhancing post-processing technique in which multiple low-resolution slice stacks are combined into a single volume of high isotropic resolution using computational methods. In this study, we investigated, first, whether SRR can improve the three-dimensional resolution of IR-SE MEMRI in the slice selection direction, whilst maintaining or improving the contrast-to-noise ratio of the two-dimensional slice stacks. Second, the contrast-to-noise ratio of SRR IR-SE MEMRI was compared with a conventional three-dimensional gradient echo (GE) acquisition. Quantitative experiments were performed on a phantom containing compartments of various manganese concentrations. The results showed that, with comparable scan times, the signal-to-noise ratio of three-dimensional GE acquisition is higher than that of SRR IR-SE MEMRI. However, the contrast-to-noise ratio between different compartments can be superior with SRR IR-SE MEMRI, depending on the chosen inversion time. In vivo experiments were performed in mice receiving manganese using an implanted osmotic pump. The results showed that SRR works well as a resolution-enhancing technique in IR-SE MEMRI experiments. In addition, the SRR image also shows a number of brain structures that are more clearly discernible from the surrounding tissues than in three-dimensional GE acquisition, including a number of nuclei with specific higher brain functions, such as memory, stress, anxiety and reward behavior. Copyright © 2014 John Wiley & Sons, Ltd.

Stochastic Optical Reconstruction Microscopy (STORM).

Science.gov (United States)

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.

1024 matrix image reconstruction: usefulness in high resolution chest CT

International Nuclear Information System (INIS)

Jeong, Sun Young; Chung, Myung Jin; Chong, Se Min; Sung, Yon Mi; Lee, Kyung Soo

2006-01-01

We tried to evaluate whether high resolution chest CT with a 1,024 matrix has a significant advantage in image quality compared to a 512 matrix. Each set of 512 and 1024 matrix high resolution chest CT scans with both 0.625 mm and 1.25 mm slice thickness were obtained from 26 patients. Seventy locations that contained twenty-four low density lesions without sharp boundary such as emphysema, and forty-six sharp linear densities such as linear fibrosis were selected; these were randomly displayed on a five mega pixel LCD monitor. All the images were masked for information concerning the matrix size and slice thickness. Two chest radiologists scored the image quality of each ar rowed lesion as follows: (1) undistinguishable, (2) poorly distinguishable, (3) fairly distinguishable, (4) well visible and (5) excellently visible. The scores were compared from the aspects of matrix size, slice thickness and the different observers by using ANOVA tests. The average and standard deviation of image quality were 3.09 (± .92) for the 0.625 mm x 512 matrix, 3.16 (± .84) for the 0.625 mm x 1024 matrix, 2.49 (± 1.02) for the 1.25 mm x 512 matrix, and 2.35 (± 1.02) for the 1.25 mm x 1024 matrix, respectively. The image quality on both matrices of the high resolution chest CT scans with a 0.625 mm slice thickness was significantly better than that on the 1.25 mm slice thickness (ρ < 0.001). However, the image quality on the 1024 matrix high resolution chest CT scans was not significantly different from that on the 512 matrix high resolution chest CT scans (ρ = 0.678). The interobserver variation between the two observers was not significant (ρ = 0.691). We think that 1024 matrix image reconstruction for high resolution chest CT may not be clinical useful

EIT image reconstruction with four dimensional regularization.

Science.gov (United States)

Dai, Tao; Soleimani, Manuchehr; Adler, Andy

2008-09-01

Electrical impedance tomography (EIT) reconstructs internal impedance images of the body from electrical measurements on body surface. The temporal resolution of EIT data can be very high, although the spatial resolution of the images is relatively low. Most EIT reconstruction algorithms calculate images from data frames independently, although data are actually highly correlated especially in high speed EIT systems. This paper proposes a 4-D EIT image reconstruction for functional EIT. The new approach is developed to directly use prior models of the temporal correlations among images and 3-D spatial correlations among image elements. A fast algorithm is also developed to reconstruct the regularized images. Image reconstruction is posed in terms of an augmented image and measurement vector which are concatenated from a specific number of previous and future frames. The reconstruction is then based on an augmented regularization matrix which reflects the a priori constraints on temporal and 3-D spatial correlations of image elements. A temporal factor reflecting the relative strength of the image correlation is objectively calculated from measurement data. Results show that image reconstruction models which account for inter-element correlations, in both space and time, show improved resolution and noise performance, in comparison to simpler image models.

Brain Slice Staining and Preparation for Three-Dimensional Super-Resolution Microscopy

Science.gov (United States)

German, Christopher L.; Gudheti, Manasa V.; Fleckenstein, Annette E.; Jorgensen, Erik M.

2018-01-01

Localization microscopy techniques – such as photoactivation localization microscopy (PALM), fluorescent PALM (FPALM), ground state depletion (GSD), and stochastic optical reconstruction microscopy (STORM) – provide the highest precision for single molecule localization currently available. However, localization microscopy has been largely limited to cell cultures due to the difficulties that arise in imaging thicker tissue sections. Sample fixation and antibody staining, background fluorescence, fluorophore photoinstability, light scattering in thick sections, and sample movement create significant challenges for imaging intact tissue. We have developed a sample preparation and image acquisition protocol to address these challenges in rat brain slices. The sample preparation combined multiple fixation steps, saponin permeabilization, and tissue clarification. Together, these preserve intracellular structures, promote antibody penetration, reduce background fluorescence and light scattering, and allow acquisition of images deep in a 30 μm thick slice. Image acquisition challenges were resolved by overlaying samples with a permeable agarose pad and custom-built stainless steel imaging adapter, and sealing the imaging chamber. This approach kept slices flat, immobile, bathed in imaging buffer, and prevented buffer oxidation during imaging. Using this protocol, we consistently obtained single molecule localizations of synaptic vesicle and active zone proteins in three-dimensions within individual synaptic terminals of the striatum in rat brain slices. These techniques may be easily adapted to the preparation and imaging of other tissues, substantially broadening the application of super-resolution imaging. PMID:28924666

Single-shot full resolution region-of-interest (ROI) reconstruction in image plane digital holographic microscopy

Science.gov (United States)

Singh, Mandeep; Khare, Kedar

2018-05-01

We describe a numerical processing technique that allows single-shot region-of-interest (ROI) reconstruction in image plane digital holographic microscopy with full pixel resolution. The ROI reconstruction is modelled as an optimization problem where the cost function to be minimized consists of an L2-norm squared data fitting term and a modified Huber penalty term that are minimized alternately in an adaptive fashion. The technique can provide full pixel resolution complex-valued images of the selected ROI which is not possible to achieve with the commonly used Fourier transform method. The technique can facilitate holographic reconstruction of individual cells of interest from a large field-of-view digital holographic microscopy data. The complementary phase information in addition to the usual absorption information already available in the form of bright field microscopy can make the methodology attractive to the biomedical user community.

Video super-resolution using simultaneous motion and intensity calculations

DEFF Research Database (Denmark)

Keller, Sune Høgild; Lauze, Francois Bernard; Nielsen, Mads

2011-01-01

for the joint estimation of a super-resolution sequence and its flow field. Via the calculus of variations, this leads to a coupled system of partial differential equations for image sequence and motion estimation. We solve a simplified form of this system and as a by-product we indeed provide a motion field...

Video Super-Resolution via Bidirectional Recurrent Convolutional Networks.

Science.gov (United States)

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.

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

Science.gov (United States)

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.

A super-oscillatory lens optical microscope for subwavelength imaging.

Science.gov (United States)

Rogers, Edward T F; Lindberg, Jari; Roy, Tapashree; Savo, Salvatore; Chad, John E; Dennis, Mark R; Zheludev, Nikolay I

2012-03-25

The past decade has seen an intensive effort to achieve optical imaging resolution beyond the diffraction limit. Apart from the Pendry-Veselago negative index superlens, implementation of which in optics faces challenges of losses and as yet unattainable fabrication finesse, other super-resolution approaches necessitate the lens either to be in the near proximity of the object or manufactured on it, or work only for a narrow class of samples, such as intensely luminescent or sparse objects. Here we report a new super-resolution microscope for optical imaging that beats the diffraction limit of conventional instruments and the recently demonstrated near-field optical superlens and hyperlens. This non-invasive subwavelength imaging paradigm uses a binary amplitude mask for direct focusing of laser light into a subwavelength spot in the post-evanescent field by precisely tailoring the interference of a large number of beams diffracted from a nanostructured mask. The new technology, which--in principle--has no physical limits on resolution, could be universally used for imaging at any wavelength and does not depend on the luminescence of the object, which can be tens of micrometres away from the mask. It has been implemented as a straightforward modification of a conventional microscope showing resolution better than λ/6.

Digital holography super-resolution for accurate three-dimensional reconstruction of particle holograms.

Science.gov (United States)

Verrier, Nicolas; Fournier, Corinne

2015-01-15

In-line digital holography (DH) is used in many fields to locate and size micro or nano-objects spread in a volume. To reconstruct simple shaped objects, the optimal approach is to fit an imaging model to accurately estimate their position and their characteristic parameters. Increasing the accuracy of the reconstruction is a big issue in DH, particularly when the pixel is large or the signal-to-noise ratio is low. We suggest exploiting the information redundancy of videos to improve the reconstruction of the holograms by jointly estimating the position of the objects and the characteristic parameters. Using synthetic and experimental data, we checked experimentally that this approach can improve the accuracy of the reconstruction by a factor more than the square root of the image number.

High-speed reconstruction of compressed images

Science.gov (United States)

Cox, Jerome R., Jr.; Moore, Stephen M.

1990-07-01

A compression scheme is described that allows high-definition radiological images with greater than 8-bit intensity resolution to be represented by 8-bit pixels. Reconstruction of the images with their original intensity resolution can be carried out by means of a pipeline architecture suitable for compact, high-speed implementation. A reconstruction system is described that can be fabricated according to this approach and placed between an 8-bit display buffer and the display's video system thereby allowing contrast control of images at video rates. Results for 50 CR chest images are described showing that error-free reconstruction of the original 10-bit CR images can be achieved.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Detector response restoration in image reconstruction of high resolution positron emission tomography

International Nuclear Information System (INIS)

Liang, Z.

1994-01-01

A mathematical method was studied to model the detector response of high spatial-resolution positron emission tomography systems consisting of close-packed small crystals, and to restore the resolution deteriorated due to crystal penetration and/or nonuniform sampling across the field-of-view (FOV). The simulated detector system had 600 bismuth germanate crystals of 3.14 mm width and 30 mm length packed on a single ring of 60 cm diameter. The space between crystal was filled up with lead. Each crystal was in coincidence with 200 opposite crystals so that the FOV had a radius of 30 cm. The detector response was modeled based on the attenuating properties of the crystals and the septa, as well as the geometry of the detector system. The modeled detector-response function was used to restore the projections from the sinogram of the ring-detector system. The restored projections had a uniform sampling of 1.57 mm across the FOV. The crystal penetration and/or the nonuniform sampling were compensated in the projections. A penalized maximum-likelihood algorithm was employed to accomplish the restoration. The restored projections were then filtered and backprojected to reconstruct the image. A chest phantom with a few small circular ''cold'' objects located at the center and near the periphery of FOV was computer generated and used to test the restoration. The reconstructed images from the restored projections demonstrated resolution improvement off the FOV center, while preserving the resolution near the center

Restoration and Super-Resolution of Diffraction-Limited Imagery Data by Bayesian and Set-Theoretic Approaches

National Research Council Canada - National Science Library

Sundareshan, Malur

2001-01-01

This project was primarily aimed at the design of novel algorithms for the restoration and super-resolution processing of imagery data to improve the resolution in images acquired from practical sensing operations...

High-resolution and super stacking of time-reversal mirrors in locating seismic sources

KAUST Repository

Cao, Weiping

2011-07-08

Time reversal mirrors can be used to backpropagate and refocus incident wavefields to their actual source location, with the subsequent benefits of imaging with high-resolution and super-stacking properties. These benefits of time reversal mirrors have been previously verified with computer simulations and laboratory experiments but not with exploration-scale seismic data. We now demonstrate the high-resolution and the super-stacking properties in locating seismic sources with field seismic data that include multiple scattering. Tests on both synthetic data and field data show that a time reversal mirror has the potential to exceed the Rayleigh resolution limit by factors of 4 or more. Results also show that a time reversal mirror has a significant resilience to strong Gaussian noise and that accurate imaging of source locations from passive seismic data can be accomplished with traces having signal-to-noise ratios as low as 0.001. Synthetic tests also demonstrate that time reversal mirrors can sometimes enhance the signal by a factor proportional to the square root of the product of the number of traces, denoted as N and the number of events in the traces. This enhancement property is denoted as super-stacking and greatly exceeds the classical signal-to-noise enhancement factor of. High-resolution and super-stacking are properties also enjoyed by seismic interferometry and reverse-time migration with the exact velocity model. © 2011 European Association of Geoscientists & Engineers.

Resolution doubling in 3D-STORM imaging through improved buffers.

Science.gov (United States)

Olivier, Nicolas; Keller, Debora; Gönczy, Pierre; Manley, Suliana

2013-01-01

Super-resolution imaging methods have revolutionized fluorescence microscopy by revealing the nanoscale organization of labeled proteins. In particular, single-molecule methods such as Stochastic Optical Reconstruction Microscopy (STORM) provide resolutions down to a few tens of nanometers by exploiting the cycling of dyes between fluorescent and non-fluorescent states to obtain a sparse population of emitters and precisely localizing them individually. This cycling of dyes is commonly induced by adding different chemicals, which are combined to create a STORM buffer. Despite their importance, the composition of these buffers has scarcely evolved since they were first introduced, fundamentally limiting what can be resolved with STORM. By identifying a new chemical suitable for STORM and optimizing the buffer composition for Alexa-647, we significantly increased the number of photons emitted per cycle by each dye, providing a simple means to enhance the resolution of STORM independently of the optical setup used. Using this buffer to perform 3D-STORM on biological samples, we obtained images with better than 10 nanometer lateral and 30 nanometer axial resolution.

Resolution doubling in 3D-STORM imaging through improved buffers.

Directory of Open Access Journals (Sweden)

Nicolas Olivier

Full Text Available Super-resolution imaging methods have revolutionized fluorescence microscopy by revealing the nanoscale organization of labeled proteins. In particular, single-molecule methods such as Stochastic Optical Reconstruction Microscopy (STORM provide resolutions down to a few tens of nanometers by exploiting the cycling of dyes between fluorescent and non-fluorescent states to obtain a sparse population of emitters and precisely localizing them individually. This cycling of dyes is commonly induced by adding different chemicals, which are combined to create a STORM buffer. Despite their importance, the composition of these buffers has scarcely evolved since they were first introduced, fundamentally limiting what can be resolved with STORM. By identifying a new chemical suitable for STORM and optimizing the buffer composition for Alexa-647, we significantly increased the number of photons emitted per cycle by each dye, providing a simple means to enhance the resolution of STORM independently of the optical setup used. Using this buffer to perform 3D-STORM on biological samples, we obtained images with better than 10 nanometer lateral and 30 nanometer axial resolution.

Automatic cortical surface reconstruction of high-resolution T1 echo planar imaging data.

Science.gov (United States)

Renvall, Ville; Witzel, Thomas; Wald, Lawrence L; Polimeni, Jonathan R

2016-07-01

Echo planar imaging (EPI) is the method of choice for the majority of functional magnetic resonance imaging (fMRI), yet EPI is prone to geometric distortions and thus misaligns with conventional anatomical reference data. The poor geometric correspondence between functional and anatomical data can lead to severe misplacements and corruption of detected activation patterns. However, recent advances in imaging technology have provided EPI data with increasing quality and resolution. Here we present a framework for deriving cortical surface reconstructions directly from high-resolution EPI-based reference images that provide anatomical models exactly geometric distortion-matched to the functional data. Anatomical EPI data with 1mm isotropic voxel size were acquired using a fast multiple inversion recovery time EPI sequence (MI-EPI) at 7T, from which quantitative T1 maps were calculated. Using these T1 maps, volumetric data mimicking the tissue contrast of standard anatomical data were synthesized using the Bloch equations, and these T1-weighted data were automatically processed using FreeSurfer. The spatial alignment between T2(⁎)-weighted EPI data and the synthetic T1-weighted anatomical MI-EPI-based images was improved compared to the conventional anatomical reference. In particular, the alignment near the regions vulnerable to distortion due to magnetic susceptibility differences was improved, and sampling of the adjacent tissue classes outside of the cortex was reduced when using cortical surface reconstructions derived directly from the MI-EPI reference. The MI-EPI method therefore produces high-quality anatomical data that can be automatically segmented with standard software, providing cortical surface reconstructions that are geometrically matched to the BOLD fMRI data. Copyright © 2016 Elsevier Inc. All rights reserved.

Efficient fully 3D list-mode TOF PET image reconstruction using a factorized system matrix with an image domain resolution model

International Nuclear Information System (INIS)

Zhou, Jian; Qi, Jinyi

2014-01-01

A factorized system matrix utilizing an image domain resolution model is attractive in fully 3D time-of-flight PET image reconstruction using list-mode data. In this paper, we study a factored model based on sparse matrix factorization that is comprised primarily of a simplified geometrical projection matrix and an image blurring matrix. Beside the commonly-used Siddon’s ray-tracer, we propose another more simplified geometrical projector based on the Bresenham’s ray-tracer which further reduces the computational cost. We discuss in general how to obtain an image blurring matrix associated with a geometrical projector, and provide theoretical analysis that can be used to inspect the efficiency in model factorization. In simulation studies, we investigate the performance of the proposed sparse factorization model in terms of spatial resolution, noise properties and computational cost. The quantitative results reveal that the factorization model can be as efficient as a non-factored model, while its computational cost can be much lower. In addition we conduct Monte Carlo simulations to identify the conditions under which the image resolution model can become more efficient in terms of image contrast recovery. We verify our observations using the provided theoretical analysis. The result offers a general guide to achieve the optimal reconstruction performance based on a sparse factorization model with an image domain resolution model. (paper)

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

Directory of Open Access Journals (Sweden)

Fabiana A Caetano

2015-12-01

Full Text Available 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.

A generalized framework unifying image registration and respiratory motion models and incorporating image reconstruction, for partial image data or full images

Science.gov (United States)

McClelland, Jamie R.; Modat, Marc; Arridge, Simon; Grimes, Helen; D'Souza, Derek; Thomas, David; O' Connell, Dylan; Low, Daniel A.; Kaza, Evangelia; Collins, David J.; Leach, Martin O.; Hawkes, David J.

2017-06-01

Surrogate-driven respiratory motion models relate the motion of the internal anatomy to easily acquired respiratory surrogate signals, such as the motion of the skin surface. They are usually built by first using image registration to determine the motion from a number of dynamic images, and then fitting a correspondence model relating the motion to the surrogate signals. In this paper we present a generalized framework that unifies the image registration and correspondence model fitting into a single optimization. This allows the use of ‘partial’ imaging data, such as individual slices, projections, or k-space data, where it would not be possible to determine the motion from an individual frame of data. Motion compensated image reconstruction can also be incorporated using an iterative approach, so that both the motion and a motion-free image can be estimated from the partial image data. The framework has been applied to real 4DCT, Cine CT, multi-slice CT, and multi-slice MR data, as well as simulated datasets from a computer phantom. This includes the use of a super-resolution reconstruction method for the multi-slice MR data. Good results were obtained for all datasets, including quantitative results for the 4DCT and phantom datasets where the ground truth motion was known or could be estimated.

Reducible Dictionaries for Single Image Super-Resolution based on Patch Matching and Mean Shifting

DEFF Research Database (Denmark)

Rasti, Pejman; Nasrollahi, Kamal; Orlova, Olga

2017-01-01

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...

Robust super-resolution by fusion of interpolated frames for color and grayscale images

Directory of Open Access Journals (Sweden)

Barry eKarch

2015-04-01

Full Text Available Multi-frame super-resolution (SR processing seeks to overcome undersampling issues that can lead to undesirable aliasing artifacts. The key to effective multi-frame SR is accurate subpixel inter-frame registration. This accurate registration is challenging when the motion does not obey a simple global translational model and may include local motion. SR processing is further complicated when the camera uses a division-of-focal-plane (DoFP sensor, such as the Bayer color filter array. Various aspects of these SR challenges have been previously investigated. Fast SR algorithms tend to have difficulty accommodating complex motion and DoFP sensors. Furthermore, methods that can tolerate these complexities tend to be iterative in nature and may not be amenable to real-time processing. In this paper, we present a new fast approach for performing SR in the presence of these challenging imaging conditions. We refer to the new approach as Fusion of Interpolated Frames (FIF SR. The FIF SR method decouples the demosaicing, interpolation, and restoration steps to simplify the algorithm. Frames are first individually demosaiced and interpolated to the desired resolution. Next, FIF uses a novel weighted sum of the interpolated frames to fuse them into an improved resolution estimate. Finally, restoration is applied to deconvolve the modeled system PSF. The proposed FIF approach has a lower computational complexity than most iterative methods, making it a candidate for real-time implementation. We provide a detailed description of the FIF SR method and show experimental results using synthetic and real datasets in both constrained and complex imaging scenarios. The experiments include airborne grayscale imagery and Bayer color array images with affine background motion plus local motion.

Optical super-resolution effect induced by nonlinear characteristics of graphene oxide films

Science.gov (United States)

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.

FIRST SCIENCE RESULTS FROM SOFIA/FORCAST: SUPER-RESOLUTION IMAGING OF THE S140 CLUSTER AT 37 {mu}m

Energy Technology Data Exchange (ETDEWEB)

Harvey, Paul M. [Astronomy Department, University of Texas at Austin, 1 University Station C1400, Austin, TX 78712-0259 (United States); Adams, Joseph D.; Herter, Terry L.; Gull, George; Schoenwald, Justin, E-mail: pmh@astro.as.utexas.edu, E-mail: jdadams@astro.cornell.edu, E-mail: tlh10@cornell.edu, E-mail: geg3@cornell.edu, E-mail: jps10@cornell.edu [Center for Radiophysics and Space Research, Space Science Building, Cornell University, Ithaca, NY 14853 (United States); and others

2012-04-20

We present 37 {mu}m imaging of the S140 complex of infrared sources centered on IRS1 made with the FORCAST camera on SOFIA. These observations are the longest wavelength imaging to resolve clearly the three main sources seen at shorter wavelengths, IRS 1, 2, and 3, and are nearly at the diffraction limit of the 2.5 m telescope. We also obtained a small number of images at 11 and 31 {mu}m that are useful for flux measurement. Our images cover the area of several strong submillimeter sources seen in the area-SMM 1, 2, and 3-that are not coincident with any mid-infrared sources and are not visible in our longer wavelength imaging either. Our new observations confirm previous estimates of the relative dust optical depth and source luminosity for the components in this likely cluster of early B stars. We also investigate the use of super-resolution to go beyond the basic diffraction limit in imaging on SOFIA and find that the van Cittert algorithm, together with the 'multi-resolution' technique, provides excellent results.

Image reconstruction with shift-variant filtration and its implication for noise and resolution properties in fan-beam computed tomography

International Nuclear Information System (INIS)

Pan Xiaochuan; Yu Lifeng

2003-01-01

In computed tomography (CT), the fan-beam filtered backprojection (FFBP) algorithm is used widely for image reconstruction. It is known that the FFBP algorithm can significantly amplify data noise and aliasing artifacts in situations where the focal lengths are comparable to or smaller than the size of the field of measurement (FOM). In this work, we propose an algorithm that is less susceptible to data noise, aliasing, and other data inconsistencies than is the FFBP algorithm while retaining the favorable resolution properties of the FFBP algorithm. In an attempt to evaluate the noise properties in reconstructed images, we derive analytic expressions for image variances obtained by use of the FFBP algorithm and the proposed algorithm. Computer simulation studies are conducted for quantitative evaluation of the spatial resolution and noise properties of images reconstructed by use of the algorithms. Numerical results of these studies confirm the favorable spatial resolution and noise properties of the proposed algorithm and verify the validity of the theoretically predicted image variances. The proposed algorithm and the derived analytic expressions for image variances can have practical implications for both estimation and detection/classification tasks making use of CT images, and they can readily be generalized to other fan-beam geometries

Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

Energy Technology Data Exchange (ETDEWEB)

Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc [German Cancer Research Center, Heidelberg (Germany).

2017-10-01

Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

Optimization of the alpha image reconstruction. An iterative CT-image reconstruction with well-defined image quality metrics

International Nuclear Information System (INIS)

Lebedev, Sergej; Sawall, Stefan; Knaup, Michael; Kachelriess, Marc

2017-01-01

Optimization of the AIR-algorithm for improved convergence and performance. TThe AIR method is an iterative algorithm for CT image reconstruction. As a result of its linearity with respect to the basis images, the AIR algorithm possesses well defined, regular image quality metrics, e.g. point spread function (PSF) or modulation transfer function (MTF), unlike other iterative reconstruction algorithms. The AIR algorithm computes weighting images α to blend between a set of basis images that preferably have mutually exclusive properties, e.g. high spatial resolution or low noise. The optimized algorithm uses an approach that alternates between the optimization of rawdata fidelity using an OSSART like update and regularization using gradient descent, as opposed to the initially proposed AIR using a straightforward gradient descent implementation. A regularization strength for a given task is chosen by formulating a requirement for the noise reduction and checking whether it is fulfilled for different regularization strengths, while monitoring the spatial resolution using the voxel-wise defined modulation transfer function for the AIR image. The optimized algorithm computes similar images in a shorter time compared to the initial gradient descent implementation of AIR. The result can be influenced by multiple parameters that can be narrowed down to a relatively simple framework to compute high quality images. The AIR images, for instance, can have at least a 50% lower noise level compared to the sharpest basis image, while the spatial resolution is mostly maintained. The optimization improves performance by a factor of 6, while maintaining image quality. Furthermore, it was demonstrated that the spatial resolution for AIR can be determined using regular image quality metrics, given smooth weighting images. This is not possible for other iterative reconstructions as a result of their non linearity. A simple set of parameters for the algorithm is discussed that provides

Fluorescent Nanodiamond: A Versatile Tool for Long-Term Cell Tracking, Super-Resolution Imaging, and Nanoscale Temperature Sensing.

Science.gov (United States)

Hsiao, Wesley Wei-Wen; Hui, Yuen Yung; Tsai, Pei-Chang; Chang, Huan-Cheng

2016-03-15

Fluorescent nanodiamond (FND) has recently played a central role in fueling new discoveries in interdisciplinary fields spanning biology, chemistry, physics, and materials sciences. The nanoparticle is unique in that it contains a high density ensemble of negatively charged nitrogen-vacancy (NV(-)) centers as built-in fluorophores. The center possesses a number of outstanding optical and magnetic properties. First, NV(-) has an absorption maximum at ∼550 nm, and when exposed to green-orange light, it emits bright fluorescence at ∼700 nm with a lifetime of longer than 10 ns. These spectroscopic properties are little affected by surface modification but are distinctly different from those of cell autofluorescence and thus enable background-free imaging of FNDs in tissue sections. Such characteristics together with its excellent biocompatibility render FND ideal for long-term cell tracking applications, particularly in stem cell research. Next, as an artificial atom in the solid state, the NV(-) center is perfectly photostable, without photobleaching and blinking. Therefore, the NV-containing FND is suitable as a contrast agent for super-resolution imaging by stimulated emission depletion (STED). An improvement of the spatial resolution by 20-fold is readily achievable by using a high-power STED laser to deplete the NV(-) fluorescence. Such improvement is crucial in revealing the detailed structures of biological complexes and assemblies, including cellular organelles and subcellular compartments. Further enhancement of the resolution for live cell imaging is possible by manipulating the charge states of the NV centers. As the "brightest" member of the nanocarbon family, FND holds great promise and potential for bioimaging with unprecedented resolution and precision. Lastly, the NV(-) center in diamond is an atom-like quantum system with a total electron spin of 1. The ground states of the spins show a crystal field splitting of 2.87 GHz, separating the ms = 0 and

Super-resolution for a point source better than λ/500 using positive refraction

Science.gov (United States)

Miñano, Juan C.; Marqués, Ricardo; González, Juan C.; Benítez, Pablo; Delgado, Vicente; Grabovickic, Dejan; Freire, Manuel

2011-12-01

Leonhardt (2009 New J. Phys. 11 093040) demonstrated that the two-dimensional (2D) Maxwell fish eye (MFE) lens can focus perfectly 2D Helmholtz waves of arbitrary frequency; that is, it can transport perfectly an outward (monopole) 2D Helmholtz wave field, generated by a point source, towards a ‘perfect point drain’ located at the corresponding image point. Moreover, a prototype with λ/5 super-resolution property for one microwave frequency has been manufactured and tested (Ma et al 2010 arXiv:1007.2530v1; Ma et al 2010 New J. Phys. 13 033016). However, neither software simulations nor experimental measurements for a broad band of frequencies have yet been reported. Here, we present steady-state simulations with a non-perfect drain for a device equivalent to the MFE, called the spherical geodesic waveguide (SGW), which predicts up to λ/500 super-resolution close to discrete frequencies. Out of these frequencies, the SGW does not show super-resolution in the analysis carried out.

Super-resolution for a point source better than λ/500 using positive refraction

International Nuclear Information System (INIS)

Miñano, Juan C; González, Juan C; Benítez, Pablo; Grabovickic, Dejan; Marqués, Ricardo; Delgado, Vicente; Freire, Manuel

2011-01-01

Leonhardt (2009 New J. Phys. 11 093040) demonstrated that the two-dimensional (2D) Maxwell fish eye (MFE) lens can focus perfectly 2D Helmholtz waves of arbitrary frequency; that is, it can transport perfectly an outward (monopole) 2D Helmholtz wave field, generated by a point source, towards a ‘perfect point drain’ located at the corresponding image point. Moreover, a prototype with λ/5 super-resolution property for one microwave frequency has been manufactured and tested (Ma et al 2010 arXiv:1007.2530v1; Ma et al 2010 New J. Phys. 13 033016). However, neither software simulations nor experimental measurements for a broad band of frequencies have yet been reported. Here, we present steady-state simulations with a non-perfect drain for a device equivalent to the MFE, called the spherical geodesic waveguide (SGW), which predicts up to λ/500 super-resolution close to discrete frequencies. Out of these frequencies, the SGW does not show super-resolution in the analysis carried out. (paper)

Stokes image reconstruction for two-color microgrid polarization imaging systems.

Science.gov (United States)

Lemaster, Daniel A

2011-07-18

The Air Force Research Laboratory has developed a new microgrid polarization imaging system capable of simultaneously reconstructing linear Stokes parameter images in two colors on a single focal plane array. In this paper, an effective method for extracting Stokes images is presented for this type of camera system. It is also shown that correlations between the color bands can be exploited to significantly increase overall spatial resolution. Test data is used to show the advantages of this approach over bilinear interpolation. The bounds (in terms of available reconstruction bandwidth) on image resolution are also provided.

Actin restructuring during Salmonella typhimurium infection investigated by confocal and super-resolution microscopy

Science.gov (United States)

Han, Jason J.; Kunde, Yuliya A.; Hong-Geller, Elizabeth; Werner, James H.

2014-01-01

We have used super-resolution optical microscopy and confocal microscopy to visualize the cytoskeletal restructuring of HeLa cells that accompanies and enables Salmonella typhimurium internalization. Herein, we report the use of confocal microscopy to verify and explore infection conditions that would be compatible with super-resolution optical microscopy, using Alexa-488 labeled phalloidin to stain the actin cytoskeletal network. While it is well known that actin restructuring and cytoskeletal rearrangements often accompany and assist in bacterial infection, most studies have employed conventional diffraction-limited fluorescence microscopy to explore these changes. Here we show that the superior spatial resolution provided by single-molecule localization methods (such as direct stochastic optical reconstruction microscopy) enables more precise visualization of the nanoscale changes in the actin cytoskeleton that accompany bacterial infection. In particular, we found that a thin (100-nm) ring of actin often surrounds an invading bacteria 10 to 20 min postinfection, with this ring being transitory in nature. We estimate that a few hundred monofilaments of actin surround the S. typhimurium in this heretofore unreported bacterial internalization intermediate.

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

Science.gov (United States)

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.

High-resolution and super stacking of time-reversal mirrors in locating seismic sources

KAUST Repository

Cao, Weiping; Hanafy, Sherif M.; Schuster, Gerard T.; Zhan, Ge; Boonyasiriwat, Chaiwoot

2011-01-01

Time reversal mirrors can be used to backpropagate and refocus incident wavefields to their actual source location, with the subsequent benefits of imaging with high-resolution and super-stacking properties. These benefits of time reversal mirrors

Enhanced simulator software for image validation and interpretation for multimodal localization super-resolution fluorescence microscopy

Science.gov (United States)

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

International Nuclear Information System (INIS)

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

2013-01-01

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

4D super-resolution microscopy with conventional fluorophores and single wavelength excitation in optically thick cells and tissues.

Directory of Open Access Journals (Sweden)

David Baddeley

Full Text Available BACKGROUND: Optical super-resolution imaging of fluorescently stained biological samples is rapidly becoming an important tool to investigate protein distribution at the molecular scale. It is therefore important to develop practical super-resolution methods that allow capturing the full three-dimensional nature of biological systems and also can visualize multiple protein species in the same sample. METHODOLOGY/PRINCIPAL FINDINGS: We show that the use of a combination of conventional near-infrared dyes, such as Alexa 647, Alexa 680 and Alexa 750, all excited with a 671 nm diode laser, enables 3D multi-colour super-resolution imaging of complex biological samples. Optically thick samples, including human tissue sections, cardiac rat myocytes and densely grown neuronal cultures were imaged with lateral resolutions of ∼15 nm (std. dev. while reducing marker cross-talk to <1%. Using astigmatism an axial resolution of ∼65 nm (std. dev. was routinely achieved. The number of marker species that can be distinguished depends on the mean photon number of single molecule events. With the typical photon yields from Alexa 680 of ∼2000 up to 5 markers may in principle be resolved with <2% crosstalk. CONCLUSIONS/SIGNIFICANCE: Our approach is based entirely on the use of conventional, commercially available markers and requires only a single laser. It provides a very straightforward way to investigate biological samples at the nanometre scale and should help establish practical 4D super-resolution microscopy as a routine research tool in many laboratories.

All-optical control and super-resolution imaging of quantum emitters in layered materials.

Science.gov (United States)

Kianinia, Mehran; Bradac, Carlo; Sontheimer, Bernd; Wang, Fan; Tran, Toan Trong; Nguyen, Minh; Kim, Sejeong; Xu, Zai-Quan; Jin, Dayong; Schell, Andreas W; Lobo, Charlene J; Aharonovich, Igor; Toth, Milos

2018-02-28

Layered van der Waals materials are emerging as compelling two-dimensional platforms for nanophotonics, polaritonics, valleytronics and spintronics, and have the potential to transform applications in sensing, imaging and quantum information processing. Among these, hexagonal boron nitride (hBN) is known to host ultra-bright, room-temperature quantum emitters, whose nature is yet to be fully understood. Here we present a set of measurements that give unique insight into the photophysical properties and level structure of hBN quantum emitters. Specifically, we report the existence of a class of hBN quantum emitters with a fast-decaying intermediate and a long-lived metastable state accessible from the first excited electronic state. Furthermore, by means of a two-laser repumping scheme, we show an enhanced photoluminescence and emission intensity, which can be utilized to realize a new modality of far-field super-resolution imaging. Our findings expand current understanding of quantum emitters in hBN and show new potential ways of harnessing their nonlinear optical properties in sub-diffraction nanoscopy.

Super-resolution for everybody: An image processing workflow to obtain high-resolution images with a standard confocal microscope.

Science.gov (United States)

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.

Design and analysis of a cross-type structured-illumination confocal microscope for high speed and high resolution

International Nuclear Information System (INIS)

Kim, Young-Duk; Ahn, MyoungKi; Kim, Taejoong; Gweon, DaeGab; Yoo, Hongki

2012-01-01

There have been many studies about a super resolution microscope for many years. A super resolution microscope can detect the physical phenomena or morphology of a biological sample more precisely than conventional microscopes. The structured-illumination microscope (SIM) is one of the technologies that demonstrate super resolution. However, the conventional SIM requires more time to obtain one resolution-enhanced image than other super resolution microscopes. More specifically, the conventional SIM uses three images with a 120° phase difference for each direction and three different directions are image-processed to make one resolution enhancement by increasing the optical transfer function in three directions. In this paper, we present a novel cross structured-illumination confocal microscope (CSICM) that takes the advantage of the technology of both SIM and the confocal microscope. The CSICM uses only two directions with three phase difference images, for a total of six images. By reducing the number of images that must be obtained, the total image acquisition time and image reconstruction time in obtaining the final output images can be decreased, and the confocal microscope provides axial information of the sample automatically. We demonstrate our method of cross illumination and evaluate the performance of the CSICM and compare it to the conventional SIM and the confocal microscope. (paper)

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

Energy Technology Data Exchange (ETDEWEB)

Li, G; Zakian, K; Deasy, J [Memorial Sloan Kettering Cancer Center, New York, NY (United States); Wei, J [City College of New York, New York, NY (United States); Hunt, M [Mem Sloan-Kettering Cancer Ctr, New York, NY (United States)

2016-06-15

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. 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

Super-resolution for imagery from integrated microgrid polarimeters.

Science.gov (United States)

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.

Photoacoustic image reconstruction: a quantitative analysis

Science.gov (United States)

Sperl, Jonathan I.; Zell, Karin; Menzenbach, Peter; Haisch, Christoph; Ketzer, Stephan; Marquart, Markus; Koenig, Hartmut; Vogel, Mika W.

2007-07-01

Photoacoustic imaging is a promising new way to generate unprecedented contrast in ultrasound diagnostic imaging. It differs from other medical imaging approaches, in that it provides spatially resolved information about optical absorption of targeted tissue structures. Because the data acquisition process deviates from standard clinical ultrasound, choice of the proper image reconstruction method is crucial for successful application of the technique. In the literature, multiple approaches have been advocated, and the purpose of this paper is to compare four reconstruction techniques. Thereby, we focused on resolution limits, stability, reconstruction speed, and SNR. We generated experimental and simulated data and reconstructed images of the pressure distribution using four different methods: delay-and-sum (DnS), circular backprojection (CBP), generalized 2D Hough transform (HTA), and Fourier transform (FTA). All methods were able to depict the point sources properly. DnS and CBP produce blurred images containing typical superposition artifacts. The HTA provides excellent SNR and allows a good point source separation. The FTA is the fastest and shows the best FWHM. In our study, we found the FTA to show the best overall performance. It allows a very fast and theoretically exact reconstruction. Only a hardware-implemented DnS might be faster and enable real-time imaging. A commercial system may also perform several methods to fully utilize the new contrast mechanism and guarantee optimal resolution and fidelity.

Enhanced temporal resolution at cardiac CT with a novel CT image reconstruction algorithm: Initial patient experience

Energy Technology Data Exchange (ETDEWEB)

Apfaltrer, Paul, E-mail: paul.apfaltrer@medma.uni-heidelberg.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Institute of Clinical Radiology and Nuclear Medicine, Medical Faculty Mannheim, Heidelberg University, Theodor-Kutzer-Ufer 1-3, D-68167 Mannheim (Germany); Schoendube, Harald, E-mail: harald.schoendube@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Schoepf, U. Joseph, E-mail: schoepf@musc.edu [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Allmendinger, Thomas, E-mail: thomas.allmendinger@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Tricarico, Francesco, E-mail: francescotricarico82@gmail.com [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Department of Bioimaging and Radiological Sciences, Catholic University of the Sacred Heart, “A. Gemelli” Hospital, Largo A. Gemelli 8, Rome (Italy); Schindler, Andreas, E-mail: andreas.schindler@campus.lmu.de [Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, PO Box 250322, 169 Ashley Avenue, Charleston, SC 29425 (United States); Vogt, Sebastian, E-mail: sebastian.vogt@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); Sunnegårdh, Johan, E-mail: johan.sunnegardh@siemens.com [Siemens Healthcare, CT Division, Forchheim Siemens, Siemensstr. 1, 91301 Forchheim (Germany); and others

2013-02-15

Objective: To evaluate the effect of a temporal resolution improvement method (TRIM) for cardiac CT on diagnostic image quality for coronary artery assessment. Materials and methods: The TRIM-algorithm employs an iterative approach to reconstruct images from less than 180° of projections and uses a histogram constraint to prevent the occurrence of limited-angle artifacts. This algorithm was applied in 11 obese patients (7 men, 67.2 ± 9.8 years) who had undergone second generation dual-source cardiac CT with 120 kV, 175–426 mAs, and 500 ms gantry rotation. All data were reconstructed with a temporal resolution of 250 ms using traditional filtered-back projection (FBP) and of 200 ms using the TRIM-algorithm. Contrast attenuation and contrast-to-noise-ratio (CNR) were measured in the ascending aorta. The presence and severity of coronary motion artifacts was rated on a 4-point Likert scale. Results: All scans were considered of diagnostic quality. Mean BMI was 36 ± 3.6 kg/m{sup 2}. Average heart rate was 60 ± 9 bpm. Mean effective dose was 13.5 ± 4.6 mSv. When comparing FBP- and TRIM reconstructed series, the attenuation within the ascending aorta (392 ± 70.7 vs. 396.8 ± 70.1 HU, p > 0.05) and CNR (13.2 ± 3.2 vs. 11.7 ± 3.1, p > 0.05) were not significantly different. A total of 110 coronary segments were evaluated. All studies were deemed diagnostic; however, there was a significant (p < 0.05) difference in the severity score distribution of coronary motion artifacts between FBP (median = 2.5) and TRIM (median = 2.0) reconstructions. Conclusion: The algorithm evaluated here delivers diagnostic imaging quality of the coronary arteries despite 500 ms gantry rotation. Possible applications include improvement of cardiac imaging on slower gantry rotation systems or mitigation of the trade-off between temporal resolution and CNR in obese patients.

Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography

Science.gov (United States)

Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.

2014-11-01

Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as "Muon Central Slice Theorem". Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction.

Preliminary frequency-domain analysis for the reconstructed spatial resolution of muon tomography

International Nuclear Information System (INIS)

Yu, B.; Zhao, Z.; Wang, X.; Wang, Y.; Wu, D.; Zeng, Z.; Zeng, M.; Yi, H.; Luo, Z.; Yue, X.; Cheng, J.

2014-01-01

Muon tomography is an advanced technology to non-destructively detect high atomic number materials. It exploits the multiple Coulomb scattering information of muon to reconstruct the scattering density image of the traversed object. Because of the statistics of muon scattering, the measurement error of system and the data incompleteness, the reconstruction is always accompanied with a certain level of interference, which will influence the reconstructed spatial resolution. While statistical noises can be reduced by extending the measuring time, system parameters determine the ultimate spatial resolution that one system can reach. In this paper, an effective frequency-domain model is proposed to analyze the reconstructed spatial resolution of muon tomography. The proposed method modifies the resolution analysis in conventional computed tomography (CT) to fit the different imaging mechanism in muon scattering tomography. The measured scattering information is described in frequency domain, then a relationship between the measurements and the original image is proposed in Fourier domain, which is named as M uon Central Slice Theorem . Furthermore, a preliminary analytical expression of the ultimate reconstructed spatial is derived, and the simulations are performed for validation. While the method is able to predict the ultimate spatial resolution of a given system, it can also be utilized for the optimization of system design and construction

Target-oriented retrieval of subsurface wave fields - Pushing the resolution limits in seismic imaging

Science.gov (United States)

Vasconcelos, Ivan; Ozmen, Neslihan; van der Neut, Joost; Cui, Tianci

2017-04-01

Travelling wide-bandwidth seismic waves have long been used as a primary tool in exploration seismology because they can probe the subsurface over large distances, while retaining relatively high spatial resolution. The well-known Born resolution limit often seems to be the lower bound on spatial imaging resolution in real life examples. In practice, data acquisition cost, time constraints and other factors can worsen the resolution achieved by wavefield imaging. Could we obtain images whose resolution beats the Born limits? Would it be practical to achieve it, and what are we missing today to achieve this? In this talk, we will cover aspects of linear and nonlinear seismic imaging to understand elements that play a role in obtaining "super-resolved" seismic images. New redatuming techniques, such as the Marchenko method, enable the retrieval of subsurface fields that include multiple scattering interactions, while requiring relatively little knowledge of model parameters. Together with new concepts in imaging, such as Target-Enclosing Extended Images, these new redatuming methods enable new targeted imaging frameworks. We will make a case as to why target-oriented approaches to reconstructing subsurface-domain wavefields from surface data may help in increasing the resolving power of seismic imaging, and in pushing the limits on parameter estimation. We will illustrate this using a field data example. Finally, we will draw connections between seismic and other imaging modalities, and discuss how this framework could be put to use in other applications

Super-resolution from single photon emission: toward biological application

Science.gov (United States)

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.

Cryo-EM Structure Determination Using Segmented Helical Image Reconstruction.

Science.gov (United States)

Fromm, S A; Sachse, C

2016-01-01

Treating helices as single-particle-like segments followed by helical image reconstruction has become the method of choice for high-resolution structure determination of well-ordered helical viruses as well as flexible filaments. In this review, we will illustrate how the combination of latest hardware developments with optimized image processing routines have led to a series of near-atomic resolution structures of helical assemblies. Originally, the treatment of helices as a sequence of segments followed by Fourier-Bessel reconstruction revealed the potential to determine near-atomic resolution structures from helical specimens. In the meantime, real-space image processing of helices in a stack of single particles was developed and enabled the structure determination of specimens that resisted classical Fourier helical reconstruction and also facilitated high-resolution structure determination. Despite the progress in real-space analysis, the combination of Fourier and real-space processing is still commonly used to better estimate the symmetry parameters as the imposition of the correct helical symmetry is essential for high-resolution structure determination. Recent hardware advancement by the introduction of direct electron detectors has significantly enhanced the image quality and together with improved image processing procedures has made segmented helical reconstruction a very productive cryo-EM structure determination method. © 2016 Elsevier Inc. All rights reserved.

Super-Resolution Microscopy: Shedding Light on the Cellular Plasma Membrane.

Science.gov (United States)

Stone, Matthew B; Shelby, Sarah A; Veatch, Sarah L

2017-06-14

Lipids and the membranes they form are fundamental building blocks of cellular life, and their geometry and chemical properties distinguish membranes from other cellular environments. Collective processes occurring within membranes strongly impact cellular behavior and biochemistry, and understanding these processes presents unique challenges due to the often complex and myriad interactions between membrane components. Super-resolution microscopy offers a significant gain in resolution over traditional optical microscopy, enabling the localization of individual molecules even in densely labeled samples and in cellular and tissue environments. These microscopy techniques have been used to examine the organization and dynamics of plasma membrane components, providing insight into the fundamental interactions that determine membrane functions. Here, we broadly introduce the structure and organization of the mammalian plasma membrane and review recent applications of super-resolution microscopy to the study of membranes. We then highlight some inherent challenges faced when using super-resolution microscopy to study membranes, and we discuss recent technical advancements that promise further improvements to super-resolution microscopy and its application to the plasma membrane.

High-resolution coded-aperture design for compressive X-ray tomography using low resolution detectors

Science.gov (United States)

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.

Super-resolution of facial images in forensics scenarios

DEFF Research Database (Denmark)

Satiro, Joao; Nasrollahi, Kamal; Correia, Paulo

2015-01-01

-resolution (SR) algorithms might be used. But, the problem with these algorithms is that they mostly require motion estimation between LR and low-quality images which is not always practical. To deal with this, we first simply interpolate the LR input images and then perform motion estimation. The estimated...... motion parameters are then used in a non-local mean-based SR algorithm to produce a higher quality image. This image is further fused with the interpolated version of the reference image via an alpha-blending approach. The experimental results on benchmark datasets and locally collected videos from...

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

Science.gov (United States)

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.

Cell-specific STORM super-resolution imaging reveals nanoscale organization of cannabinoid signaling.

Science.gov (United States)

Dudok, Barna; Barna, László; Ledri, Marco; Szabó, Szilárd I; Szabadits, Eszter; Pintér, Balázs; Woodhams, Stephen G; Henstridge, Christopher M; Balla, Gyula Y; Nyilas, Rita; Varga, Csaba; Lee, Sang-Hun; Matolcsi, Máté; Cervenak, Judit; Kacskovics, Imre; Watanabe, Masahiko; Sagheddu, Claudia; Melis, Miriam; Pistis, Marco; Soltesz, Ivan; Katona, István

2015-01-01

A major challenge in neuroscience is to determine the nanoscale position and quantity of signaling molecules in a cell type- and subcellular compartment-specific manner. We developed a new approach to this problem by combining cell-specific physiological and anatomical characterization with super-resolution imaging and studied the molecular and structural parameters shaping the physiological properties of synaptic endocannabinoid signaling in the mouse hippocampus. We found that axon terminals of perisomatically projecting GABAergic interneurons possessed increased CB1 receptor number, active-zone complexity and receptor/effector ratio compared with dendritically projecting interneurons, consistent with higher efficiency of cannabinoid signaling at somatic versus dendritic synapses. Furthermore, chronic Δ(9)-tetrahydrocannabinol administration, which reduces cannabinoid efficacy on GABA release, evoked marked CB1 downregulation in a dose-dependent manner. Full receptor recovery required several weeks after the cessation of Δ(9)-tetrahydrocannabinol treatment. These findings indicate that cell type-specific nanoscale analysis of endogenous protein distribution is possible in brain circuits and identify previously unknown molecular properties controlling endocannabinoid signaling and cannabis-induced cognitive dysfunction.

Sparsity-Based Pixel Super Resolution for Lens-Free Digital In-line Holography.

Science.gov (United States)

Song, Jun; Leon Swisher, Christine; Im, Hyungsoon; Jeong, Sangmoo; Pathania, Divya; Iwamoto, Yoshiko; Pivovarov, Misha; Weissleder, Ralph; Lee, Hakho

2016-04-21

Lens-free digital in-line holography (LDIH) is a promising technology for portable, wide field-of-view imaging. Its resolution, however, is limited by the inherent pixel size of an imaging device. Here we present a new computational approach to achieve sub-pixel resolution for LDIH. The developed method is a sparsity-based reconstruction with the capability to handle the non-linear nature of LDIH. We systematically characterized the algorithm through simulation and LDIH imaging studies. The method achieved the spatial resolution down to one-third of the pixel size, while requiring only single-frame imaging without any hardware modifications. This new approach can be used as a general framework to enhance the resolution in nonlinear holographic systems.

HIV taken by STORM: Super-resolution fluorescence microscopy of a viral infection

Directory of Open Access Journals (Sweden)

Pereira Cândida F

2012-05-01

Full Text Available Abstract Background The visualization of viral proteins has been hindered by the resolution limit of conventional fluorescent microscopes, as the dimension of any single fluorescent signal is often greater than most virion particles. Super-resolution microscopy has the potential to unveil the distribution of proteins at the resolution approaching electron microscopy without relying on morphological features of existing characteristics of the biological specimen that are needed in EM. Results Using direct stochastic optical reconstruction microscopy (dSTORM to achieve a lateral resolution of 15–20 nm, we quantified the 2-D molecular distribution of the major structural proteins of the infectious human immunodeficiency virus type 1 (HIV-1 before and after infection of lymphoid cells. We determined that the HIV-1 matrix and capsid proteins undergo restructuring soon after HIV-1 infection. Conclusions This study provides the proof-of-concept for the use of dSTORM to visualize the changes in the molecular distribution of viral proteins during an infection.

Image superresolution of cytology images using wavelet based patch search

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Xiwei Huang

2016-11-01

Full Text Available 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.

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

Science.gov (United States)

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.

MRI isotropic resolution reconstruction from two orthogonal scans

Science.gov (United States)

Tamez-Pena, Jose G.; Totterman, Saara; Parker, Kevin J.

2001-07-01

An algorithm for the reconstructions of ISO-resolution volumetric MR data sets from two standard orthogonal MR scans having anisotropic resolution has been developed. The reconstruction algorithm starts by registering a pair of orthogonal volumetric MR data sets. The registration is done by maximizing the correlation between the gradient magnitude using a simple translation-rotation model in a multi-resolution approach. Then algorithm assumes that the individual voxels on the MR data are an average of the magnetic resonance properties of an elongated imaging volume. Then, the process is modeled as the projection of MR properties into a single sensor. This model allows the derivation of a set of linear equations that can be used to recover the MR properties of every single voxel in the SO-resolution volume given only two orthogonal MR scans. Projections on convex sets (POCS) was used to solve the set of linear equations. Experimental results show the advantage of having a ISO-resolution reconstructions for the visualization and analysis of small and thin muscular structures.

Transceiver Design for CMUT-Based Super-Resolution Ultrasound Imaging.

Science.gov (United States)

Behnamfar, Parisa; Molavi, Reza; Mirabbasi, Shahriar

2016-04-01

A recently introduced structure for the capacitive micromachined ultrasonic transducers (CMUTs) has focused on the applications of the asymmetric mode of vibration and has shown promising results in construction of super-resolution ultrasound images. This paper presents the first implementation and experimental results of a transceiver circuit to interface such CMUT structures. The multiple input/multiple output receiver in this work supports both fundamental and asymmetric modes of operation and includes transimpedance amplifiers and low-power variable-gain stages. These circuit blocks are designed considering the trade-offs between gain, input impedance, noise, linearity and power consumption. The high-voltage transmitter can generate pulse voltages up to 60 V while occupying a considerably small area. The overall circuit is designed and laid out in a 0.35 μm CMOS process and a four-channel transceiver occupies 0.86 × 0.38 mm(2). The prototype chip is characterized in both electrical and mechanical domains. Measurement results show that each receiver channel has a nominal gain of 110 dBΩ with a 3 dB bandwidth of 9 MHz while consuming 1.02 mW from a 3.3 V supply. The receiver is also highly linear, with 1 dB compression point of minimum 1.05 V which is considerably higher than the previously reported designs. The transmitter consumes 98.1 mW from a 30 V supply while generating 1.38 MHz, 30 V pulses. The CMOS-CMUT system is tested in the transmit mode and shows full functionality in air medium.

Spatial resolution recovery utilizing multi-ray tracing and graphic processing unit in PET image reconstruction

International Nuclear Information System (INIS)

Liang, Yicheng; Peng, Hao

2015-01-01

Depth-of-interaction (DOI) poses a major challenge for a PET system to achieve uniform spatial resolution across the field-of-view, particularly for small animal and organ-dedicated PET systems. In this work, we implemented an analytical method to model system matrix for resolution recovery, which was then incorporated in PET image reconstruction on a graphical processing unit platform, due to its parallel processing capacity. The method utilizes the concepts of virtual DOI layers and multi-ray tracing to calculate the coincidence detection response function for a given line-of-response. The accuracy of the proposed method was validated for a small-bore PET insert to be used for simultaneous PET/MR breast imaging. In addition, the performance comparisons were studied among the following three cases: 1) no physical DOI and no resolution modeling; 2) two physical DOI layers and no resolution modeling; and 3) no physical DOI design but with a different number of virtual DOI layers. The image quality was quantitatively evaluated in terms of spatial resolution (full-width-half-maximum and position offset), contrast recovery coefficient and noise. The results indicate that the proposed method has the potential to be used as an alternative to other physical DOI designs and achieve comparable imaging performances, while reducing detector/system design cost and complexity. (paper)

Computed tomography imaging with the Adaptive Statistical Iterative Reconstruction (ASIR) algorithm: dependence of image quality on the blending level of reconstruction.

Science.gov (United States)

Barca, Patrizio; Giannelli, Marco; Fantacci, Maria Evelina; Caramella, Davide

2018-06-01

Computed tomography (CT) is a useful and widely employed imaging technique, which represents the largest source of population exposure to ionizing radiation in industrialized countries. Adaptive Statistical Iterative Reconstruction (ASIR) is an iterative reconstruction algorithm with the potential to allow reduction of radiation exposure while preserving diagnostic information. The aim of this phantom study was to assess the performance of ASIR, in terms of a number of image quality indices, when different reconstruction blending levels are employed. CT images of the Catphan-504 phantom were reconstructed using conventional filtered back-projection (FBP) and ASIR with reconstruction blending levels of 20, 40, 60, 80, and 100%. Noise, noise power spectrum (NPS), contrast-to-noise ratio (CNR) and modulation transfer function (MTF) were estimated for different scanning parameters and contrast objects. Noise decreased and CNR increased non-linearly up to 50 and 100%, respectively, with increasing blending level of reconstruction. Also, ASIR has proven to modify the NPS curve shape. The MTF of ASIR reconstructed images depended on tube load/contrast and decreased with increasing blending level of reconstruction. In particular, for low radiation exposure and low contrast acquisitions, ASIR showed lower performance than FBP, in terms of spatial resolution for all blending levels of reconstruction. CT image quality varies substantially with the blending level of reconstruction. ASIR has the potential to reduce noise whilst maintaining diagnostic information in low radiation exposure CT imaging. Given the opposite variation of CNR and spatial resolution with the blending level of reconstruction, it is recommended to use an optimal value of this parameter for each specific clinical application.

Fan-beam and cone-beam image reconstruction via filtering the backprojection image of differentiated projection data

International Nuclear Information System (INIS)

Zhuang Tingliang; Leng Shuai; Nett, Brian E; Chen Guanghong

2004-01-01

In this paper, a new image reconstruction scheme is presented based on Tuy's cone-beam inversion scheme and its fan-beam counterpart. It is demonstrated that Tuy's inversion scheme may be used to derive a new framework for fan-beam and cone-beam image reconstruction. In this new framework, images are reconstructed via filtering the backprojection image of differentiated projection data. The new framework is mathematically exact and is applicable to a general source trajectory provided the Tuy data sufficiency condition is satisfied. By choosing a piece-wise constant function for one of the components in the factorized weighting function, the filtering kernel is one dimensional, viz. the filtering process is along a straight line. Thus, the derived image reconstruction algorithm is mathematically exact and efficient. In the cone-beam case, the derived reconstruction algorithm is applicable to a large class of source trajectories where the pi-lines or the generalized pi-lines exist. In addition, the new reconstruction scheme survives the super-short scan mode in both the fan-beam and cone-beam cases provided the data are not transversely truncated. Numerical simulations were conducted to validate the new reconstruction scheme for the fan-beam case

Filter and slice thickness selection in SPECT image reconstruction

International Nuclear Information System (INIS)

Ivanovic, M.; Weber, D.A.; Wilson, G.A.; O'Mara, R.E.

1985-01-01

The choice of filter and slice thickness in SPECT image reconstruction as function of activity and linear and angular sampling were investigated in phantom and patient imaging studies. Reconstructed transverse and longitudinal spatial resolution of the system were measured using a line source in a water filled phantom. Phantom studies included measurements of the Data Spectrum phantom; clinical studies included tomographic procedures in 40 patients undergoing imaging of the temporomandibular joint. Slices of the phantom and patient images were evaluated for spatial of the phantom and patient images were evaluated for spatial resolution, noise, and image quality. Major findings include; spatial resolution and image quality improve with increasing linear sampling frequencies over the range of 4-8 mm/p in the phantom images, best spatial resolution and image quality in clinical images were observed at a linear sampling frequency of 6mm/p, Shepp and Logan filter gives the best spatial resolution for phantom studies at the lowest linear sampling frequency; smoothed Shepp and Logan filter provides best quality images without loss of resolution at higher frequencies and, spatial resolution and image quality improve with increased angular sampling frequency in the phantom at 40 c/p but appear to be independent of angular sampling frequency at 400 c/p

Correction of a Depth-Dependent Lateral Distortion in 3D Super-Resolution Imaging.

Directory of Open Access Journals (Sweden)

Lina Carlini

Full Text Available 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.

3D super-resolution imaging with blinking quantum dots

Science.gov (United States)

Wang, Yong; Fruhwirth, Gilbert; Cai, En; Ng, Tony; Selvin, Paul R.

2013-01-01

Quantum dots are promising candidates for single molecule imaging due to their exceptional photophysical properties, including their intense brightness and resistance to photobleaching. They are also notorious for their blinking. Here we report a novel way to take advantage of quantum dot blinking to develop an imaging technique in three-dimensions with nanometric resolution. We first applied this method to simulated images of quantum dots, and then to quantum dots immobilized on microspheres. We achieved imaging resolutions (FWHM) of 8–17 nm in the x-y plane and 58 nm (on coverslip) or 81 nm (deep in solution) in the z-direction, approximately 3–7 times better than what has been achieved previously with quantum dots. This approach was applied to resolve the 3D distribution of epidermal growth factor receptor (EGFR) molecules at, and inside of, the plasma membrane of resting basal breast cancer cells. PMID:24093439

Painting Supramolecular Polymers in Organic Solvents by Super-resolution Microscopy

Science.gov (United States)

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

Facile method to stain the bacterial cell surface for super-resolution fluorescence microscopy

Energy Technology Data Exchange (ETDEWEB)

Gunsolus, Ian L.; Hu, Dehong; Mihai, Cosmin; Lohse, Samuel E.; Lee, Chang-Soo; Torelli, Marco; Hamers, Robert J.; Murphy, Catherine; Orr, Galya; Haynes, Christy L.

2014-01-01

A method to fluorescently stain the surfaces of both Gram-negative and Gram-positive bacterial cells compatible with super-resolution fluorescence microscopy is presented. This method utilizes a commercially-available fluorescent probe to label primary amines at the surface of the cell. We demonstrate efficient staining of two bacterial strains, the Gram-negative Shewanella oneidensis MR-1 and the Gram-positive Bacillus subtilis 168. Using structured illumination microscopy and stochastic optical reconstruction microscopy, which require high quantum yield or specialized dyes, we show that this staining method may be used to resolve the bacterial cell surface with sub-diffraction-limited resolution. We further use this method to identify localization patterns of nanomaterials, specifically cadmium selenide quantum dots, following interaction with bacterial cells.

Macromolecular 3D SEM reconstruction strategies: Signal to noise ratio and resolution

International Nuclear Information System (INIS)

Woodward, J.D.; Wepf, R.A.

2014-01-01

Three-dimensional scanning electron microscopy generates quantitative volumetric structural data from SEM images of macromolecules. This technique provides a quick and easy way to define the quaternary structure and handedness of protein complexes. Here, we apply a variety of preparation and imaging methods to filamentous actin in order to explore the relationship between resolution, signal-to-noise ratio, structural preservation and dataset size. This information can be used to define successful imaging strategies for different applications. - Highlights: • F-actin SEM datasets were collected using 8 different preparation/ imaging techniques. • Datasets were reconstructed by back projection and compared/analyzed • 3DSEM actin reconstructions can be produced with <100 views of the asymmetric unit. • Negatively stained macromolecules can be reconstructed by 3DSEM to ∼3 nm resolution

Low contrast detectability and spatial resolution with model-based iterative reconstructions of MDCT images: a phantom and cadaveric study

Energy Technology Data Exchange (ETDEWEB)

Millon, Domitille; Coche, Emmanuel E. [Universite Catholique de Louvain, Department of Radiology and Medical Imaging, Cliniques Universitaires Saint Luc, Brussels (Belgium); Vlassenbroek, Alain [Philips Healthcare, Brussels (Belgium); Maanen, Aline G. van; Cambier, Samantha E. [Universite Catholique de Louvain, Statistics Unit, King Albert II Cancer Institute, Brussels (Belgium)

2017-03-15

To compare image quality [low contrast (LC) detectability, noise, contrast-to-noise (CNR) and spatial resolution (SR)] of MDCT images reconstructed with an iterative reconstruction (IR) algorithm and a filtered back projection (FBP) algorithm. The experimental study was performed on a 256-slice MDCT. LC detectability, noise, CNR and SR were measured on a Catphan phantom scanned with decreasing doses (48.8 down to 0.7 mGy) and parameters typical of a chest CT examination. Images were reconstructed with FBP and a model-based IR algorithm. Additionally, human chest cadavers were scanned and reconstructed using the same technical parameters. Images were analyzed to illustrate the phantom results. LC detectability and noise were statistically significantly different between the techniques, supporting model-based IR algorithm (p < 0.0001). At low doses, the noise in FBP images only enabled SR measurements of high contrast objects. The superior CNR of model-based IR algorithm enabled lower dose measurements, which showed that SR was dose and contrast dependent. Cadaver images reconstructed with model-based IR illustrated that visibility and delineation of anatomical structure edges could be deteriorated at low doses. Model-based IR improved LC detectability and enabled dose reduction. At low dose, SR became dose and contrast dependent. (orig.)

Super-nonlinear fluorescence microscopy for high-contrast deep tissue imaging

Science.gov (United States)

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.

High resolution depth reconstruction from monocular images and sparse point clouds using deep convolutional neural network

Science.gov (United States)

Dimitrievski, Martin; Goossens, Bart; Veelaert, Peter; Philips, Wilfried

2017-09-01

Understanding the 3D structure of the environment is advantageous for many tasks in the field of robotics and autonomous vehicles. From the robot's point of view, 3D perception is often formulated as a depth image reconstruction problem. In the literature, dense depth images are often recovered deterministically from stereo image disparities. Other systems use an expensive LiDAR sensor to produce accurate, but semi-sparse depth images. With the advent of deep learning there have also been attempts to estimate depth by only using monocular images. In this paper we combine the best of the two worlds, focusing on a combination of monocular images and low cost LiDAR point clouds. We explore the idea that very sparse depth information accurately captures the global scene structure while variations in image patches can be used to reconstruct local depth to a high resolution. The main contribution of this paper is a supervised learning depth reconstruction system based on a deep convolutional neural network. The network is trained on RGB image patches reinforced with sparse depth information and the output is a depth estimate for each pixel. Using image and point cloud data from the KITTI vision dataset we are able to learn a correspondence between local RGB information and local depth, while at the same time preserving the global scene structure. Our results are evaluated on sequences from the KITTI dataset and our own recordings using a low cost camera and LiDAR setup.

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

Science.gov (United States)

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.

Spatio-temporal image correlation spectroscopy and super-resolution microscopy to quantify molecular dynamics in T cells.

Science.gov (United States)

Ashdown, George W; Owen, Dylan M

2018-02-02

Many cellular processes are regulated by the spatio-temporal organisation of signalling complexes, cytoskeletal components and membranes. One such example is at the T cell immunological synapse where the retrograde flow of cortical filamentous (F)-actin from the synapse periphery drives signalling protein microclusters towards the synapse centre. The density of this mesh however, makes visualisation and analysis of individual actin fibres difficult due to the resolution limit of conventional microscopy. Recently, super-resolution methods such as structured illumination microscopy (SIM) have surpassed this resolution limit. Here, we apply SIM to better visualise the dense cortical actin meshwork in T cell synapses formed against activating, antibody-coated surfaces and image under total-internal reflection fluorescence (TIRF) illumination. To analyse the observed molecular flows, and the relationship between them, we apply spatio-temporal image correlation spectroscopy (STICS) and its cross-correlation variant (STICCS). We show that the dynamic cortical actin mesh can be visualised with unprecedented detail and that STICS/STICCS can output accurate, quantitative maps of molecular flow velocity and directionality from such data. We find that the actin flow can be disrupted using small molecule inhibitors of actin polymerisation. This combination of imaging and quantitative analysis may provide an important new tool for researchers to investigate the molecular dynamics at cellular length scales. Here we demonstrate the retrograde flow of F-actin which may be important for the clustering and dynamics of key signalling proteins within the plasma membrane, a phenomenon which is vital to correct T cell activation and therefore the mounting of an effective immune response. Copyright © 2018. Published by Elsevier Inc.

Novel ultrahigh resolution data acquisition and image reconstruction for multi-detector row CT

International Nuclear Information System (INIS)

Flohr, T. G.; Stierstorfer, K.; Suess, C.; Schmidt, B.; Primak, A. N.; McCollough, C. H.

2007-01-01

We present and evaluate a special ultrahigh resolution mode providing considerably enhanced spatial resolution both in the scan plane and in the z-axis direction for a routine medical multi-detector row computed tomography (CT) system. Data acquisition is performed by using a flying focal spot both in the scan plane and in the z-axis direction in combination with tantalum grids that are inserted in front of the multi-row detector to reduce the aperture of the detector elements both in-plane and in the z-axis direction. The dose utilization of the system for standard applications is not affected, since the grids are moved into place only when needed and are removed for standard scanning. By means of this technique, image slices with a nominal section width of 0.4 mm (measured full width at half maximum=0.45 mm) can be reconstructed in spiral mode on a CT system with a detector configuration of 32x0.6 mm. The measured 2% value of the in-plane modulation transfer function (MTF) is 20.4 lp/cm, the measured 2% value of the longitudinal (z axis) MTF is 21.5 lp/cm. In a resolution phantom with metal line pair test patterns, spatial resolution of 20 lp/cm can be demonstrated both in the scan plane and along the z axis. This corresponds to an object size of 0.25 mm that can be resolved. The new mode is intended for ultrahigh resolution bone imaging, in particular for wrists, joints, and inner ear studies, where a higher level of image noise due to the reduced aperture is an acceptable trade-off for the clinical benefit brought about by the improved spatial resolution

Proton computed tomography images with algebraic reconstruction

Energy Technology Data Exchange (ETDEWEB)

Bruzzi, M. [Physics and Astronomy Department, University of Florence, Florence (Italy); Civinini, C.; Scaringella, M. [INFN - Florence Division, Florence (Italy); Bonanno, D. [INFN - Catania Division, Catania (Italy); Brianzi, M. [INFN - Florence Division, Florence (Italy); Carpinelli, M. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Cirrone, G.A.P.; Cuttone, G. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Presti, D. Lo [INFN - Catania Division, Catania (Italy); Physics and Astronomy Department, University of Catania, Catania (Italy); Maccioni, G. [INFN – Cagliari Division, Cagliari (Italy); Pallotta, S. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Randazzo, N. [INFN - Catania Division, Catania (Italy); Romano, F. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Sipala, V. [INFN - Laboratori Nazionali del Sud, Catania (Italy); Chemistry and Pharmacy Department, University of Sassari, Sassari (Italy); Talamonti, C. [INFN - Florence Division, Florence (Italy); Department of Biomedical, Experimental and Clinical Sciences, University of Florence, Florence (Italy); SOD Fisica Medica, Azienda Ospedaliero-Universitaria Careggi, Firenze (Italy); Vanzi, E. [Fisica Sanitaria, Azienda Ospedaliero-Universitaria Senese, Siena (Italy)

2017-02-11

A prototype of proton Computed Tomography (pCT) system for hadron-therapy has been manufactured and tested in a 175 MeV proton beam with a non-homogeneous phantom designed to simulate high-contrast material. BI-SART reconstruction algorithms have been implemented with GPU parallelism, taking into account of most likely paths of protons in matter. Reconstructed tomography images with density resolutions r.m.s. down to ~1% and spatial resolutions <1 mm, achieved within processing times of ~15′ for a 512×512 pixels image prove that this technique will be beneficial if used instead of X-CT in hadron-therapy.

Prospects of linear reconstruction in atomic resolution electron holographic tomography

International Nuclear Information System (INIS)

Krehl, Jonas; Lubk, Axel

2015-01-01

Tomography commonly requires a linear relation between the measured signal and the underlying specimen property; for Electron Holographic Tomography this is given by the Phase Grating Approximation (PGA). While largely valid at medium resolution, discrepancies arise at high resolution imaging conditions. We set out to investigate the artefacts that are produced if the reconstruction still assumes the PGA even with an atomic resolution tilt series. To forego experimental difficulties the holographic tilt series was simulated. The reconstructed electric potential clearly shows peaks at the positions of the atoms. These peaks have characterisitic deformations, which can be traced back to the defocus a particular atom has in the holograms of the tilt series. Exchanging an atom for one of a different atomic number results in a significant change in the reconstructed potential that is well contained within the atom's peak. - Highlights: • We simulate a holographic tilt series of a nanocrystal with atomic resolution. • Using PGA-based Holographic Tomography we reconstruct the atomic structure. • The reconstruction shows characteristic artefacts, chiefly caused by defocus. • Changing one atom's Z produces a well localised in the reconstruction

Prospects of linear reconstruction in atomic resolution electron holographic tomography

Energy Technology Data Exchange (ETDEWEB)

Krehl, Jonas, E-mail: Jonas.Krehl@triebenberg.de; Lubk, Axel

2015-03-15

Tomography commonly requires a linear relation between the measured signal and the underlying specimen property; for Electron Holographic Tomography this is given by the Phase Grating Approximation (PGA). While largely valid at medium resolution, discrepancies arise at high resolution imaging conditions. We set out to investigate the artefacts that are produced if the reconstruction still assumes the PGA even with an atomic resolution tilt series. To forego experimental difficulties the holographic tilt series was simulated. The reconstructed electric potential clearly shows peaks at the positions of the atoms. These peaks have characterisitic deformations, which can be traced back to the defocus a particular atom has in the holograms of the tilt series. Exchanging an atom for one of a different atomic number results in a significant change in the reconstructed potential that is well contained within the atom's peak. - Highlights: • We simulate a holographic tilt series of a nanocrystal with atomic resolution. • Using PGA-based Holographic Tomography we reconstruct the atomic structure. • The reconstruction shows characteristic artefacts, chiefly caused by defocus. • Changing one atom's Z produces a well localised in the reconstruction.

Super-resolution fluorescence imaging of membrane nanoscale architectures of hematopoietic stem cell homing and migration molecules

KAUST Repository

AbuZineh, Karmen

2017-12-01

Recent development of super-resolution (SR) fluorescence microscopy techniques has provided a new tool for direct visualization of subcellular structures and their dynamics in cells. The homing of Hematopoietic stem/progenitor cells (HSPCs) to bone marrow is a multistep process that is initiated by tethering of HSPCs to endothelium and mediated by spatiotemporally organised ligand-receptor interactions of selectins expressed on endothelial cells to their ligands expressed on HSPCs which occurs against the shear stress exerted by blood flow. Although molecules and biological processes involved in this multi-step cellular interaction have been studied extensively, molecular mechanisms of the homing, in particular the nanoscale spatiotemporal behaviour of ligand-receptor interactions and their role in the cellular interaction, remain elusive. Using our new method of microfluidics-based super-resolution fluorescence imaging platform we can now characterize the correlation between both nanoscale ligand-receptor interactions and tethering/rolling of cells under external shear stress. We found that cell rolling on E-selectin caused significant reorganization of the nanoscale clustering behavior of CD44 and CD43, from a patchy clusters of ~ 200 nm in size to an elongated network-like structures where for PSGL-1 the clustering size did not change significantly as it was 85 nm and after cell rolling the PSGL-1 aggregated to one side or even exhibited an increase in the footprint. Furthermore, I have established the use of 3D SR images that indicated that the patchy clusters of CD44 localize to protruding structures of the cell surface. On the other hand, a significant amount of the network-like elongated CD44 clusters observed after the rolling were located in the close proximity to the E-selectin surface. The effect of the nanoscale reorganization of the clusters on the HSPC rolling over selectins is still an open question at this stage. Nevertheless, my results further

Temporal super resolution using variational methods

DEFF Research Database (Denmark)

Keller, Sune Høgild; Lauze, Francois Bernard; Nielsen, Mads

2010-01-01

Temporal super resolution (TSR) is the ability to convert video from one frame rate to another and is as such a key functionality in modern video processing systems. A higher frame rate than what is recorded is desired for high frame rate displays, for super slow-motion, and for video/film format...... observed when watching video on large and bright displays where the motion of high contrast edges often seem jerky and unnatural. A novel motion compensated (MC) TSR algorithm using variational methods for both optical flow calculation and the actual new frame interpolation is presented. The flow...

Aberrations and adaptive optics in super-resolution microscopy

Science.gov (United States)

Booth, Martin; Andrade, Débora; Burke, Daniel; Patton, Brian; Zurauskas, Mantas

2015-01-01

As one of the most powerful tools in the biological investigation of cellular structures and dynamic processes, fluorescence microscopy has undergone extraordinary developments in the past decades. The advent of super-resolution techniques has enabled fluorescence microscopy – or rather nanoscopy – to achieve nanoscale resolution in living specimens and unravelled the interior of cells with unprecedented detail. The methods employed in this expanding field of microscopy, however, are especially prone to the detrimental effects of optical aberrations. In this review, we discuss how super-resolution microscopy techniques based upon single-molecule switching, stimulated emission depletion and structured illumination each suffer from aberrations in different ways that are dependent upon intrinsic technical aspects. We discuss the use of adaptive optics as an effective means to overcome this problem. PMID:26124194

Principle and Reconstruction Algorithm for Atomic-Resolution Holography

Science.gov (United States)

Matsushita, Tomohiro; Muro, Takayuki; Matsui, Fumihiko; Happo, Naohisa; Hosokawa, Shinya; Ohoyama, Kenji; Sato-Tomita, Ayana; Sasaki, Yuji C.; Hayashi, Kouichi

2018-06-01

Atomic-resolution holography makes it possible to obtain the three-dimensional (3D) structure around a target atomic site. Translational symmetry of the atomic arrangement of the sample is not necessary, and the 3D atomic image can be measured when the local structure of the target atomic site is oriented. Therefore, 3D local atomic structures such as dopants and adsorbates are observable. Here, the atomic-resolution holography comprising photoelectron holography, X-ray fluorescence holography, neutron holography, and their inverse modes are treated. Although the measurement methods are different, they can be handled with a unified theory. The algorithm for reconstructing 3D atomic images from holograms plays an important role. Although Fourier transform-based methods have been proposed, they require the multiple-energy holograms. In addition, they cannot be directly applied to photoelectron holography because of the phase shift problem. We have developed methods based on the fitting method for reconstructing from single-energy and photoelectron holograms. The developed methods are applicable to all types of atomic-resolution holography.

Super-resolution fluorescence imaging of membrane nanoscale architectures of hematopoietic stem cell homing and migration molecules

KAUST Repository

AbuZineh, Karmen

2017-01-01

Recent development of super-resolution (SR) fluorescence microscopy techniques has provided a new tool for direct visualization of subcellular structures and their dynamics in cells. The homing of Hematopoietic stem/progenitor cells (HSPCs) to bone

Radionuclide imaging with coded apertures and three-dimensional image reconstruction from focal-plane tomography

International Nuclear Information System (INIS)

Chang, L.T.

1976-05-01

Two techniques for radionuclide imaging and reconstruction have been studied;; both are used for improvement of depth resolution. The first technique is called coded aperture imaging, which is a technique of tomographic imaging. The second technique is a special 3-D image reconstruction method which is introduced as an improvement to the so called focal-plane tomography

Research on compressive sensing reconstruction algorithm based on total variation model

Science.gov (United States)

Gao, Yu-xuan; Sun, Huayan; Zhang, Tinghua; Du, Lin

2017-12-01

Compressed sensing for breakthrough Nyquist sampling theorem provides a strong theoretical , making compressive sampling for image signals be carried out simultaneously. In traditional imaging procedures using compressed sensing theory, not only can it reduces the storage space, but also can reduce the demand for detector resolution greatly. Using the sparsity of image signal, by solving the mathematical model of inverse reconfiguration, realize the super-resolution imaging. Reconstruction algorithm is the most critical part of compression perception, to a large extent determine the accuracy of the reconstruction of the image.The reconstruction algorithm based on the total variation (TV) model is more suitable for the compression reconstruction of the two-dimensional image, and the better edge information can be obtained. In order to verify the performance of the algorithm, Simulation Analysis the reconstruction result in different coding mode of the reconstruction algorithm based on the TV reconstruction algorithm. The reconstruction effect of the reconfigurable algorithm based on TV based on the different coding methods is analyzed to verify the stability of the algorithm. This paper compares and analyzes the typical reconstruction algorithm in the same coding mode. On the basis of the minimum total variation algorithm, the Augmented Lagrangian function term is added and the optimal value is solved by the alternating direction method.Experimental results show that the reconstruction algorithm is compared with the traditional classical algorithm based on TV has great advantages, under the low measurement rate can be quickly and accurately recovers target image.

Reconstruction of Undersampled Atomic Force Microscopy Images

DEFF Research Database (Denmark)

Jensen, Tobias Lindstrøm; Arildsen, Thomas; Østergaard, Jan

2013-01-01

Atomic force microscopy (AFM) is one of the most advanced tools for high-resolution imaging and manipulation of nanoscale matter. Unfortunately, standard AFM imaging requires a timescale on the order of seconds to minutes to acquire an image which makes it complicated to observe dynamic processes....... Moreover, it is often required to take several images before a relevant observation region is identified. In this paper we show how to significantly reduce the image acquisition time by undersampling. The reconstruction of an undersampled AFM image can be viewed as an inpainting, interpolating problem...... should be reconstructed using interpolation....

Evaluation of Composite Wire Ropes Using Unsaturated Magnetic Excitation and Reconstruction Image with Super-Resolution

Directory of Open Access Journals (Sweden)

Xiaojiang Tan

2018-05-01

Full Text Available Estimating the exact residual lifetime of wire rope involves the security of industry manufacturing, mining, tourism, and so on. In this paper, a novel testing technology was developed based on unsaturated magnetic excitation, and a fabricating prototype overcame the shortcomings of traditional detection equipment in terms of volume, sensibility, reliability, and weight. Massive artificial discontinuities were applied to examine the effectiveness of this new technology with a giant magneto resistance(GMR sensor array, which included types of small gaps, curling wires, wide fractures, and abrasion. A resolution enhancement method, which was adopted for multiframe images, was proposed for promoting magnetic flux leakage images of a few sensors. Characteristic vectors of statistics and geometry were extracted, then we applied a radial basis function neural network to achieve a quantitative recognition rate of 91.43% with one wire-limiting error. Experimental results showed that the new device can detect defects in various types of wire rope and prolong the service life with high lift-off distance and high reliability, and the system could provide useful options to evaluate the lifetime of wire rope.

Initial phantom study comparing image quality in computed tomography using adaptive statistical iterative reconstruction and new adaptive statistical iterative reconstruction v.

Science.gov (United States)

Lim, Kyungjae; Kwon, Heejin; Cho, Jinhan; Oh, Jongyoung; Yoon, Seongkuk; Kang, Myungjin; Ha, Dongho; Lee, Jinhwa; Kang, Eunju

2015-01-01

The purpose of this study was to assess the image quality of a novel advanced iterative reconstruction (IR) method called as "adaptive statistical IR V" (ASIR-V) by comparing the image noise, contrast-to-noise ratio (CNR), and spatial resolution from those of filtered back projection (FBP) and adaptive statistical IR (ASIR) on computed tomography (CT) phantom image. We performed CT scans at 5 different tube currents (50, 70, 100, 150, and 200 mA) using 3 types of CT phantoms. Scanned images were subsequently reconstructed in 7 different scan settings, such as FBP, and 3 levels of ASIR and ASIR-V (30%, 50%, and 70%). The image noise was measured in the first study using body phantom. The CNR was measured in the second study using contrast phantom and the spatial resolutions were measured in the third study using a high-resolution phantom. We compared the image noise, CNR, and spatial resolution among the 7 reconstructed image scan settings to determine whether noise reduction, high CNR, and high spatial resolution could be achieved at ASIR-V. At quantitative analysis of the first and second studies, it showed that the images reconstructed using ASIR-V had reduced image noise and improved CNR compared with those of FBP and ASIR (P ASIR-V had significantly improved spatial resolution than those of FBP and ASIR (P ASIR-V provides a significant reduction in image noise and a significant improvement in CNR as well as spatial resolution. Therefore, this technique has the potential to reduce the radiation dose further without compromising image quality.

Refinement procedure for the image alignment in high-resolution electron tomography.

Science.gov (United States)

Houben, L; Bar Sadan, M

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. Copyright © 2011 Elsevier B.V. All rights reserved.

Image Positioning Accuracy Analysis for Super Low Altitude Remote Sensing Satellites

Directory of Open Access Journals (Sweden)

Ming Xu

2012-10-01

Full Text Available Super low altitude remote sensing satellites maintain lower flight altitudes by means of ion propulsion in order to improve image resolution and positioning accuracy. The use of engineering data in design for achieving image positioning accuracy is discussed in this paper based on the principles of the photogrammetry theory. The exact line-of-sight rebuilding of each detection element and this direction precisely intersecting with the Earth's elliptical when the camera on the satellite is imaging are both ensured by the combined design of key parameters. These parameters include: orbit determination accuracy, attitude determination accuracy, camera exposure time, accurately synchronizing the reception of ephemeris with attitude data, geometric calibration and precise orbit verification. Precise simulation calculations show that image positioning accuracy of super low altitude remote sensing satellites is not obviously improved. The attitude determination error of a satellite still restricts its positioning accuracy.

Image reconstruction with an adaptive threshold technique in electrical resistance tomography

International Nuclear Information System (INIS)

Kim, Bong Seok; Khambampati, Anil Kumar; Kim, Sin; Kim, Kyung Youn

2011-01-01

In electrical resistance tomography, electrical currents are injected through the electrodes placed on the surface of a domain and the corresponding voltages are measured. Based on these currents and voltage data, the cross-sectional resistivity distribution is reconstructed. Electrical resistance tomography shows high temporal resolution for monitoring fast transient processes, but it still remains a challenging problem to improve the spatial resolution of the reconstructed images. In this paper, a novel image reconstruction technique is proposed to improve the spatial resolution by employing an adaptive threshold method to the iterative Gauss–Newton method. Numerical simulations and phantom experiments have been performed to illustrate the superior performance of the proposed scheme in the sense of spatial resolution

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

Science.gov (United States)

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 vision optical correction of the human eye.

Tomographic Image Reconstruction Using Training Images with Matrix and Tensor Formulations

DEFF Research Database (Denmark)

Soltani, Sara

the image resolution compared to a classical reconstruction method such as Filtered Back Projection (FBP). Some priors for the tomographic reconstruction take the form of cross-section images of similar objects, providing a set of the so-called training images, that hold the key to the structural......Reducing X-ray exposure while maintaining the image quality is a major challenge in computed tomography (CT); since the imperfect data produced from the few view and/or low intensity projections results in low-quality images that are suffering from severe artifacts when using conventional...... information about the solution. The training images must be reliable and application-specific. This PhD project aims at providing a mathematical and computational framework for the use of training sets as non-parametric priors for the solution in tomographic image reconstruction. Through an unsupervised...

Reprocessing the Historical Satellite Passive Microwave Record at Enhanced Spatial Resolutions using Image Reconstruction

Science.gov (United States)

Hardman, M.; Brodzik, M. J.; Long, D. G.; Paget, A. C.; Armstrong, R. L.

2015-12-01

Beginning in 1978, the satellite passive microwave data record has been a mainstay of remote sensing of the cryosphere, providing twice-daily, near-global spatial coverage for monitoring changes in hydrologic and cryospheric parameters that include precipitation, soil moisture, surface water, vegetation, snow water equivalent, sea ice concentration and sea ice motion. Currently available global gridded passive microwave data sets serve a diverse community of hundreds of data users, but do not meet many requirements of modern Earth System Data Records (ESDRs) or Climate Data Records (CDRs), most notably in the areas of intersensor calibration, quality-control, provenance and consistent processing methods. The original gridding techniques were relatively primitive and were produced on 25 km grids using the original EASE-Grid definition that is not easily accommodated in modern software packages. Further, since the first Level 3 data sets were produced, the Level 2 passive microwave data on which they were based have been reprocessed as Fundamental CDRs (FCDRs) with improved calibration and documentation. We are funded by NASA MEaSUREs to reprocess the historical gridded data sets as EASE-Grid 2.0 ESDRs, using the most mature available Level 2 satellite passive microwave (SMMR, SSM/I-SSMIS, AMSR-E) records from 1978 to the present. We have produced prototype data from SSM/I and AMSR-E for the year 2003, for review and feedback from our Early Adopter user community. The prototype data set includes conventional, low-resolution ("drop-in-the-bucket" 25 km) grids and enhanced-resolution grids derived from the two candidate image reconstruction techniques we are evaluating: 1) Backus-Gilbert (BG) interpolation and 2) a radiometer version of Scatterometer Image Reconstruction (SIR). We summarize our temporal subsetting technique, algorithm tuning parameters and computational costs, and include sample SSM/I images at enhanced resolutions of up to 3 km. We are actively

Parallel detecting super-resolution microscopy using correlation based image restoration

Science.gov (United States)

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.

Signal Characteristics of Super-Resolution Near-Field Structure Disks with 100 GB Capacity

Science.gov (United States)

Kim, Jooho; Hwang, Inoh; Kim, Hyunki; Park, Insik; Tominaga, Junji

2005-05-01

We report the basic characteristics of super resolution near-field structure (Super-RENS) media at a blue laser optical system (laser wavelength 405 nm, numerical aperture 0.85). Using a novel write once read many (WORM) structure for a blue laser system, we obtained a carrier-to-noise ratio (CNR) above 33 dB from the signal of the 37.5 nm mark length, which is equivalent to a 100 GB capacity with a 0.32 micrometer track pitch, and an eye pattern for 50 GB (2T: 75 nm) capacity using a patterned signal. Using a novel super-resolution material (tellurium, Te) with low super-resolution readout power, we also improved the read stability.

Passive Standoff Super Resolution Imaging using Spatial-Spectral Multiplexing

Science.gov (United States)

2017-08-14

OPD is mainly influenced by the indices of refraction and thicknesses for the two glass plates/fluids (n1/t1 and n2/t2) and the angle of incidence...the algorithm’s robustness. To be specific, this reconstruction algorithm is shown to be effective on both smoothly varying and point cloud objects...applications in the field of hydrology, oceanography, glaciology, forest, climate , urban, military and meteorology [62]. With remotely sensed images

Fetal brain volumetry through MRI volumetric reconstruction and segmentation

Science.gov (United States)

Estroff, Judy A.; Barnewolt, Carol E.; Connolly, Susan A.; Warfield, Simon K.

2013-01-01

Purpose Fetal MRI volumetry is a useful technique but it is limited by a dependency upon motion-free scans, tedious manual segmentation, and spatial inaccuracy due to thick-slice scans. An image processing pipeline that addresses these limitations was developed and tested. Materials and methods The principal sequences acquired in fetal MRI clinical practice are multiple orthogonal single-shot fast spin echo scans. State-of-the-art image processing techniques were used for inter-slice motion correction and super-resolution reconstruction of high-resolution volumetric images from these scans. The reconstructed volume images were processed with intensity non-uniformity correction and the fetal brain extracted by using supervised automated segmentation. Results Reconstruction, segmentation and volumetry of the fetal brains for a cohort of twenty-five clinically acquired fetal MRI scans was done. Performance metrics for volume reconstruction, segmentation and volumetry were determined by comparing to manual tracings in five randomly chosen cases. Finally, analysis of the fetal brain and parenchymal volumes was performed based on the gestational age of the fetuses. Conclusion The image processing pipeline developed in this study enables volume rendering and accurate fetal brain volumetry by addressing the limitations of current volumetry techniques, which include dependency on motion-free scans, manual segmentation, and inaccurate thick-slice interpolation. PMID:20625848

Speeding up image reconstruction in computed tomography

CERN Multimedia

CERN. Geneva

2018-01-01

Computed tomography (CT) is a technique for imaging cross-sections of an object using X-ray measurements taken from different angles. In last decades a significant progress has happened there: today advanced algorithms allow fast image reconstruction and obtaining high-quality images even with missing or dirty data, modern detectors provide high resolution without increasing radiation dose, and high-performance multi-core computing devices are there to help us solving such tasks even faster. I will start with CT basics, then briefly present existing classes of reconstruction algorithms and their differences. After that I will proceed to employing distinctive architectural features of modern multi-core devices (CPUs and GPUs) and popular program interfaces (OpenMP, MPI, CUDA, OpenCL) for developing effective parallel realizations of image reconstruction algorithms. Decreasing full reconstruction time from long hours up to minutes or even seconds has a revolutionary impact in diagnostic medicine and industria...

Compressive Transient Imaging

KAUST Repository

Sun, Qilin

2017-04-01

High resolution transient/3D imaging technology is of high interest in both scientific research and commercial application. Nowadays, all of the transient imaging methods suffer from low resolution or time consuming mechanical scanning. We proposed a new method based on TCSPC and Compressive Sensing to achieve a high resolution transient imaging with a several seconds capturing process. Picosecond laser sends a serious of equal interval pulse while synchronized SPAD camera\\'s detecting gate window has a precise phase delay at each cycle. After capturing enough points, we are able to make up a whole signal. By inserting a DMD device into the system, we are able to modulate all the frames of data using binary random patterns to reconstruct a super resolution transient/3D image later. Because the low fill factor of SPAD sensor will make a compressive sensing scenario ill-conditioned, We designed and fabricated a diffractive microlens array. We proposed a new CS reconstruction algorithm which is able to denoise at the same time for the measurements suffering from Poisson noise. Instead of a single SPAD senor, we chose a SPAD array because it can drastically reduce the requirement for the number of measurements and its reconstruction time. Further more, it not easy to reconstruct a high resolution image with only one single sensor while for an array, it just needs to reconstruct small patches and a few measurements. In this thesis, we evaluated the reconstruction methods using both clean measurements and the version corrupted by Poisson noise. The results show how the integration over the layers influence the image quality and our algorithm works well while the measurements suffer from non-trival Poisson noise. It\\'s a breakthrough in the areas of both transient imaging and compressive sensing.

Ordinal Regression Based Subpixel Shift Estimation for Video Super-Resolution

Directory of Open Access Journals (Sweden)

Petrovic Nemanja

2007-01-01

Full Text Available We present a supervised learning-based approach for subpixel motion estimation which is then used to perform video super-resolution. The novelty of this work is the formulation of the problem of subpixel motion estimation in a ranking framework. The ranking formulation is a variant of classification and regression formulation, in which the ordering present in class labels namely, the shift between patches is explicitly taken into account. Finally, we demonstrate the applicability of our approach on superresolving synthetically generated images with global subpixel shifts and enhancing real video frames by accounting for both local integer and subpixel shifts.

Reconstruction of magnetic resonance imaging by three-dimensional dual-dictionary learning.

Science.gov (United States)

Song, Ying; Zhu, Zhen; Lu, Yang; Liu, Qiegen; Zhao, Jun

2014-03-01

To improve the magnetic resonance imaging (MRI) data acquisition speed while maintaining the reconstruction quality, a novel method is proposed for multislice MRI reconstruction from undersampled k-space data based on compressed-sensing theory using dictionary learning. There are two aspects to improve the reconstruction quality. One is that spatial correlation among slices is used by extending the atoms in dictionary learning from patches to blocks. The other is that the dictionary-learning scheme is used at two resolution levels; i.e., a low-resolution dictionary is used for sparse coding and a high-resolution dictionary is used for image updating. Numerical experiments are carried out on in vivo 3D MR images of brains and abdomens with a variety of undersampling schemes and ratios. The proposed method (dual-DLMRI) achieves better reconstruction quality than conventional reconstruction methods, with the peak signal-to-noise ratio being 7 dB higher. The advantages of the dual dictionaries are obvious compared with the single dictionary. Parameter variations ranging from 50% to 200% only bias the image quality within 15% in terms of the peak signal-to-noise ratio. Dual-DLMRI effectively uses the a priori information in the dual-dictionary scheme and provides dramatically improved reconstruction quality. Copyright © 2013 Wiley Periodicals, Inc.

Partial fourier and parallel MR image reconstruction with integrated gradient nonlinearity correction.

Science.gov (United States)

Tao, Shengzhen; Trzasko, Joshua D; Shu, Yunhong; Weavers, Paul T; Huston, John; Gray, Erin M; Bernstein, Matt A

2016-06-01

To describe how integrated gradient nonlinearity (GNL) correction can be used within noniterative partial Fourier (homodyne) and parallel (SENSE and GRAPPA) MR image reconstruction strategies, and demonstrate that performing GNL correction during, rather than after, these routines mitigates the image blurring and resolution loss caused by postreconstruction image domain based GNL correction. Starting from partial Fourier and parallel magnetic resonance imaging signal models that explicitly account for GNL, noniterative image reconstruction strategies for each accelerated acquisition technique are derived under the same core mathematical assumptions as their standard counterparts. A series of phantom and in vivo experiments on retrospectively undersampled data were performed to investigate the spatial resolution benefit of integrated GNL correction over conventional postreconstruction correction. Phantom and in vivo results demonstrate that the integrated GNL correction reduces the image blurring introduced by the conventional GNL correction, while still correcting GNL-induced coarse-scale geometrical distortion. Images generated from undersampled data using the proposed integrated GNL strategies offer superior depiction of fine image detail, for example, phantom resolution inserts and anatomical tissue boundaries. Noniterative partial Fourier and parallel imaging reconstruction methods with integrated GNL correction reduce the resolution loss that occurs during conventional postreconstruction GNL correction while preserving the computational efficiency of standard reconstruction techniques. Magn Reson Med 75:2534-2544, 2016. © 2015 Wiley Periodicals, Inc. © 2015 Wiley Periodicals, Inc.

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

Science.gov (United States)

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.

Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging

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Errico, Claudia; Pierre, Juliette; Pezet, Sophie; Desailly, Yann; Lenkei, Zsolt; Couture, Olivier; Tanter, Mickael

2015-11-01

Non-invasive imaging deep into organs at microscopic scales remains an open quest in biomedical imaging. Although optical microscopy is still limited to surface imaging owing to optical wave diffusion and fast decorrelation in tissue, revolutionary approaches such as fluorescence photo-activated localization microscopy led to a striking increase in resolution by more than an order of magnitude in the last decade. In contrast with optics, ultrasonic waves propagate deep into organs without losing their coherence and are much less affected by in vivo decorrelation processes. However, their resolution is impeded by the fundamental limits of diffraction, which impose a long-standing trade-off between resolution and penetration. This limits clinical and preclinical ultrasound imaging to a sub-millimetre scale. Here we demonstrate in vivo that ultrasound imaging at ultrafast frame rates (more than 500 frames per second) provides an analogue to optical localization microscopy by capturing the transient signal decorrelation of contrast agents—inert gas microbubbles. Ultrafast ultrasound localization microscopy allowed both non-invasive sub-wavelength structural imaging and haemodynamic quantification of rodent cerebral microvessels (less than ten micrometres in diameter) more than ten millimetres below the tissue surface, leading to transcranial whole-brain imaging within short acquisition times (tens of seconds). After intravenous injection, single echoes from individual microbubbles were detected through ultrafast imaging. Their localization, not limited by diffraction, was accumulated over 75,000 images, yielding 1,000,000 events per coronal plane and statistically independent pixels of ten micrometres in size. Precise temporal tracking of microbubble positions allowed us to extract accurately in-plane velocities of the blood flow with a large dynamic range (from one millimetre per second to several centimetres per second). These results pave the way for deep non

Super-resolution microscopy as a potential approach to diagnosis of platelet granule disorders.

Science.gov (United States)

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.

Optimization of CT image reconstruction algorithms for the lung tissue research consortium (LTRC)

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McCollough, Cynthia; Zhang, Jie; Bruesewitz, Michael; Bartholmai, Brian

2006-03-01

To create a repository of clinical data, CT images and tissue samples and to more clearly understand the pathogenetic features of pulmonary fibrosis and emphysema, the National Heart, Lung, and Blood Institute (NHLBI) launched a cooperative effort known as the Lung Tissue Resource Consortium (LTRC). The CT images for the LTRC effort must contain accurate CT numbers in order to characterize tissues, and must have high-spatial resolution to show fine anatomic structures. This study was performed to optimize the CT image reconstruction algorithms to achieve these criteria. Quantitative analyses of phantom and clinical images were conducted. The ACR CT accreditation phantom containing five regions of distinct CT attenuations (CT numbers of approximately -1000 HU, -80 HU, 0 HU, 130 HU and 900 HU), and a high-contrast spatial resolution test pattern, was scanned using CT systems from two manufacturers (General Electric (GE) Healthcare and Siemens Medical Solutions). Phantom images were reconstructed using all relevant reconstruction algorithms. Mean CT numbers and image noise (standard deviation) were measured and compared for the five materials. Clinical high-resolution chest CT images acquired on a GE CT system for a patient with diffuse lung disease were reconstructed using BONE and STANDARD algorithms and evaluated by a thoracic radiologist in terms of image quality and disease extent. The clinical BONE images were processed with a 3 x 3 x 3 median filter to simulate a thicker slice reconstructed in smoother algorithms, which have traditionally been proven to provide an accurate estimation of emphysema extent in the lungs. Using a threshold technique, the volume of emphysema (defined as the percentage of lung voxels having a CT number lower than -950 HU) was computed for the STANDARD, BONE, and BONE filtered. The CT numbers measured in the ACR CT Phantom images were accurate for all reconstruction kernels for both manufacturers. As expected, visual evaluation of the

Algorithms of CT value correction for reconstructing a radiotherapy simulation image through axial CT images

International Nuclear Information System (INIS)

Ogino, Takashi; Egawa, Sunao

1991-01-01

New algorithms of CT value correction for reconstructing a radiotherapy simulation image through axial CT images were developed. One, designated plane weighting method, is to correct CT value in proportion to the position of the beam element passing through the voxel. The other, designated solid weighting method, is to correct CT value in proportion to the length of the beam element passing through the voxel and the volume of voxel. Phantom experiments showed fair spatial resolution in the transverse direction. In the longitudinal direction, however, spatial resolution of under slice thickness could not be obtained. Contrast resolution was equivalent for both methods. In patient studies, the reconstructed radiotherapy simulation image was almost similar in visual perception of the density resolution to a simulation film taken by X-ray simulator. (author)

Refinement procedure for the image alignment in high-resolution electron tomography

International Nuclear Information System (INIS)

Houben, L.; Bar Sadan, M.

2011-01-01

High-resolution electron tomography from a tilt series of transmission electron microscopy images requires an accurate image alignment procedure in order to maximise the resolution of the tomogram. This is the case in particular for ultra-high resolution where even very small misalignments between individual images can dramatically reduce the fidelity of the resultant reconstruction. A tomographic-reconstruction based and marker-free method is proposed, which uses an iterative optimisation of the tomogram resolution. The method utilises a search algorithm that maximises the contrast in tomogram sub-volumes. Unlike conventional cross-correlation analysis it provides the required correlation over a large tilt angle separation and guarantees a consistent alignment of images for the full range of object tilt angles. An assessment based on experimental reconstructions shows that the marker-free procedure is competitive to the reference of marker-based procedures at lower resolution and yields sub-pixel accuracy even for simulated high-resolution data. -- Highlights: → Alignment procedure for electron tomography based on iterative tomogram contrast optimisation. → Marker-free, independent of object, little user interaction. → Accuracy competitive with fiducial marker methods and suited for high-resolution tomography.

Three-dimensional breast image reconstruction from a limited number of views

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McCauley, Thomas G.; Stewart, Alexander X.; Stanton, Martin J.; Wu, Tao; Phillips, Walter C.

2000-04-01

Typically in three-dimensional (3D) computed tomography (CT) imaging, hundreds or thousands of x-ray projection images are recorded. The image-collection time and patient dose required rule out conventional CT as a tool for screening mammography. We have developed a CT method that overcomes these limitations by using (1) a novel image collection geometry, (2) new digital electronic x-ray detector technology, and (3) modern image reconstruction procedures. The method, which we call Computed Planar Mammography (CPM), is made possible by the full-field, low-noise, high-resolution CCD-based detector design that we have previously developed. With this method, we need to record only a limited number (10 - 50) of low-dose x- ray images of the breast. The resulting 3D full breast image has a resolution in two orientations equal to the full detector resolution (47 microns), and a lower, variable resolution (0.5 - 10 mm) in the third orientation. This 3D reconstructed image can then be viewed as a series of cross- sectional layers, or planes, each at the full detector resolution. Features due to overlapping tissue, which could not be differentiated in a conventional mammogram, are separated into layers at different depths. We demonstrate the features and capabilities of this method by presenting reconstructed images of phantoms and mastectomy specimens. Finally, we discuss outstanding issues related to the further development of this procedure, as well as considerations for its clinical implementation.

Low-Power Super-resolution Readout with Antimony Bismuth Alloy Film as Mask layer

International Nuclear Information System (INIS)

Lai-Xin, Jiang; Yi-Qun, Wu; Yang, Wang; Jing-Song, Wei; Fu-Xi, Gan

2009-01-01

Sb–Bi alloy films are proposed as a new kind of super-resolution mask layer with low readout threshold power. Using the Sb–Bi alloy film as a mask layer and SiN as a protective layer in a read-only memory disc, the super-resolution pits with diameters of 380 nm are read out by a dynamic setup, the laser wavelength is 780 nm and the numerical aperture of pickup lens is 0.45. The effects of the Sb–Bi thin film thickness, laser readout power and disc rotating velocity on the readout signal are investigated. The results show that the threshold laser power of super-resolution readout of the Sb–Bi mask layer is about 0.5 mW, and the corresponding carrier-to-noise ratio is about 20 dB at the film thickness of 50 nm. The super-resolution mechanism of the Sb–Bi alloy mask layer is discussed based on its temperature dependence of reflection

Developing a New Biophysical Tool to Combine Magneto-Optical Tweezers with Super-Resolution Fluorescence Microscopy

Directory of Open Access Journals (Sweden)

Zhaokun Zhou

2015-06-01

Full Text Available We present a novel experimental setup in which magnetic and optical tweezers are combined for torque and force transduction onto single filamentous molecules in a transverse configuration to allow simultaneous mechanical measurement and manipulation. Previously we have developed a super-resolution imaging module which, in conjunction with advanced imaging techniques such as Blinking assisted Localisation Microscopy (BaLM, achieves localisation precision of single fluorescent dye molecules bound to DNA of ~30 nm along the contour of the molecule; our work here describes developments in producing a system which combines tweezing and super-resolution fluorescence imaging. The instrument also features an acousto-optic deflector that temporally divides the laser beam to form multiple traps for high throughput statistics collection. Our motivation for developing the new tool is to enable direct observation of detailed molecular topological transformation and protein binding event localisation in a stretching/twisting mechanical assay that previously could hitherto only be deduced indirectly from the end-to-end length variation of DNA. Our approach is simple and robust enough for reproduction in the lab without the requirement of precise hardware engineering, yet is capable of unveiling the elastic and dynamic properties of filamentous molecules that have been hidden using traditional tools.

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.

Science.gov (United States)

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.

Designing sparse sensing matrix for compressive sensing to reconstruct high resolution medical images

Directory of Open Access Journals (Sweden)

Vibha Tiwari

2015-12-01

Full Text Available Compressive sensing theory enables faithful reconstruction of signals, sparse in domain $ \\Psi $, at sampling rate lesser than Nyquist criterion, while using sampling or sensing matrix $ \\Phi $ which satisfies restricted isometric property. The role played by sensing matrix $ \\Phi $ and sparsity matrix $ \\Psi $ is vital in faithful reconstruction. If the sensing matrix is dense then it takes large storage space and leads to high computational cost. In this paper, effort is made to design sparse sensing matrix with least incurred computational cost while maintaining quality of reconstructed image. The design approach followed is based on sparse block circulant matrix (SBCM with few modifications. The other used sparse sensing matrix consists of 15 ones in each column. The medical images used are acquired from US, MRI and CT modalities. The image quality measurement parameters are used to compare the performance of reconstructed medical images using various sensing matrices. It is observed that, since Gram matrix of dictionary matrix ($ \\Phi \\Psi \\mathrm{} $ is closed to identity matrix in case of proposed modified SBCM, therefore, it helps to reconstruct the medical images of very good quality.

Algebraic 2D PET image reconstruction using depth-of-interaction information

International Nuclear Information System (INIS)

Yamaya, Taiga; Obi, Takashi; Yamaguchi, Masahiro; Kita, Kouichi

2001-01-01

Recently a high-performance PET scanner, which measures depth-of-interaction (DOI) information, is being developed for molecular imaging. DOI measurement of multi-layered thin crystals can improve spatial resolution and scanner sensitivity simultaneously. In this paper, we apply an algebraic image reconstruction method to 2-dimensional (2D) DOI-PET scanners using accurate system modeling, in order to evaluate the effects of using DOI information on PET image quality. Algebraic image reconstruction methods have been successfully used to improve PET image quality, compared with the conventional filtered backprojection method. The proposed method is applied to simulated data for a small 2D DOI-PET scanner. The results show that accurate system modeling improves spatial resolution without noise emphasis, and that DOI information improves uniformity of spatial resolution. (author)

Three dimensional image reconstruction in the Fourier domain

International Nuclear Information System (INIS)

Stearns, C.W.; Chesler, D.A.; Brownell, G.L.

1987-01-01

Filtered backprojection reconstruction algorithms are based upon the relationship between the Fourier transform of the imaged object and the Fourier transforms of its projections. A new reconstruction algorithm has been developed which performs the image assembly operation in Fourier space, rather than in image space by backprojection. This represents a significant decrease in the number of operations required to assemble the image. The new Fourier domain algorithm has resolution comparable to the filtered backprojection algorithm, and, after correction by a pointwise multiplication, demonstrates proper recovery throughout image space. Although originally intended for three-dimensional imaging applications, the Fourier domain algorithm can also be developed for two-dimensional imaging applications such as planar positron imaging systems

Practical considerations for image-based PSF and blobs reconstruction in PET

International Nuclear Information System (INIS)

Stute, Simon; Comtat, Claude

2013-01-01

Iterative reconstructions in positron emission tomography (PET) need a model relating the recorded data to the object/patient being imaged, called the system matrix (SM). The more realistic this model, the better the spatial resolution in the reconstructed images. However, a serious concern when using a SM that accurately models the resolution properties of the PET system is the undesirable edge artefact, visible through oscillations near sharp discontinuities in the reconstructed images. This artefact is a natural consequence of solving an ill-conditioned inverse problem, where the recorded data are band-limited. In this paper, we focus on practical aspects when considering image-based point-spread function (PSF) reconstructions. To remove the edge artefact, we propose to use a particular case of the method of sieves (Grenander 1981 Abstract Inference New York: Wiley), which simply consists in performing a standard PSF reconstruction, followed by a post-smoothing using the PSF as the convolution kernel. Using analytical simulations, we investigate the impact of different reconstruction and PSF modelling parameters on the edge artefact and its suppression, in the case of noise-free data and an exactly known PSF. Using Monte-Carlo simulations, we assess the proposed method of sieves with respect to the choice of the geometric projector and the PSF model used in the reconstruction. When the PSF model is accurately known, we show that the proposed method of sieves succeeds in completely suppressing the edge artefact, though after a number of iterations higher than typically used in practice. When applying the method to realistic data (i.e. unknown true SM and noisy data), we show that the choice of the geometric projector and the PSF model does not impact the results in terms of noise and contrast recovery, as long as the PSF has a width close to the true PSF one. Equivalent results were obtained using either blobs or voxels in the same conditions (i.e. the blob�

Influence of the partial volume correction method on (18)F-fluorodeoxyglucose brain kinetic modelling from dynamic PET images reconstructed with resolution model based OSEM.

Science.gov (United States)

Bowen, Spencer L; Byars, Larry G; Michel, Christian J; Chonde, Daniel B; Catana, Ciprian

2013-10-21

Kinetic parameters estimated from dynamic (18)F-fluorodeoxyglucose ((18)F-FDG) PET acquisitions have been used frequently to assess brain function in humans. Neglecting partial volume correction (PVC) for a dynamic series has been shown to produce significant bias in model estimates. Accurate PVC requires a space-variant model describing the reconstructed image spatial point spread function (PSF) that accounts for resolution limitations, including non-uniformities across the field of view due to the parallax effect. For ordered subsets expectation maximization (OSEM), image resolution convergence is local and influenced significantly by the number of iterations, the count density, and background-to-target ratio. As both count density and background-to-target values for a brain structure can change during a dynamic scan, the local image resolution may also concurrently vary. When PVC is applied post-reconstruction the kinetic parameter estimates may be biased when neglecting the frame-dependent resolution. We explored the influence of the PVC method and implementation on kinetic parameters estimated by fitting (18)F-FDG dynamic data acquired on a dedicated brain PET scanner and reconstructed with and without PSF modelling in the OSEM algorithm. The performance of several PVC algorithms was quantified with a phantom experiment, an anthropomorphic Monte Carlo simulation, and a patient scan. Using the last frame reconstructed image only for regional spread function (RSF) generation, as opposed to computing RSFs for each frame independently, and applying perturbation geometric transfer matrix PVC with PSF based OSEM produced the lowest magnitude bias kinetic parameter estimates in most instances, although at the cost of increased noise compared to the PVC methods utilizing conventional OSEM. Use of the last frame RSFs for PVC with no PSF modelling in the OSEM algorithm produced the lowest bias in cerebral metabolic rate of glucose estimates, although by less than 5% in

SuperAGILE: The hard X-ray imager for the AGILE space mission

International Nuclear Information System (INIS)

Feroci, M.; Costa, E.; Soffitta, P.; Del Monte, E.; Di Persio, G.; Donnarumma, I.; Evangelista, Y.; Frutti, M.; Lapshov, I.; Lazzarotto, F.; Mastropietro, M.; Morelli, E.; Pacciani, L.; Porrovecchio, G.; Rapisarda, M.; Rubini, A.; Tavani, M.; Argan, A.

2007-01-01

SuperAGILE is a coded mask experiment based on silicon microstrip detectors. It operates in the 15-45 keV nominal energy range, providing crossed one-dimensional images of the X-ray sky with an on-axis angular resolution of 6 arcmin, over a field of view in excess of 1 sr. It was designed as the hard X-ray monitor of the AGILE space mission, a small satellite of the Italian Space Agency devoted to image the gamma-ray sky in the 30 MeV-50 GeV energy band. The AGILE mission was launched in a low-earth orbit on 23rd April 2007. In this paper we describe the SuperAGILE experiment, its construction and test processes, and its performance before flight, based on the on-ground test and calibrations

Noise and physical limits to maximum resolution of PET images

Energy Technology Data Exchange (ETDEWEB)

Herraiz, J.L.; Espana, S. [Dpto. Fisica Atomica, Molecular y Nuclear, Facultad de Ciencias Fisicas, Universidad Complutense de Madrid, Avda. Complutense s/n, E-28040 Madrid (Spain); Vicente, E.; Vaquero, J.J.; Desco, M. [Unidad de Medicina y Cirugia Experimental, Hospital GU ' Gregorio Maranon' , E-28007 Madrid (Spain); Udias, J.M. [Dpto. Fisica Atomica, Molecular y Nuclear, Facultad de Ciencias Fisicas, Universidad Complutense de Madrid, Avda. Complutense s/n, E-28040 Madrid (Spain)], E-mail: jose@nuc2.fis.ucm.es

2007-10-01

In this work we show that there is a limit for the maximum resolution achievable with a high resolution PET scanner, as well as for the best signal-to-noise ratio, which are ultimately related to the physical effects involved in the emission and detection of the radiation and thus they cannot be overcome with any particular reconstruction method. These effects prevent the spatial high frequency components of the imaged structures to be recorded by the scanner. Therefore, the information encoded in these high frequencies cannot be recovered by any reconstruction technique. Within this framework, we have determined the maximum resolution achievable for a given acquisition as a function of data statistics and scanner parameters, like the size of the crystals or the inter-crystal scatter. In particular, the noise level in the data as a limitation factor to yield high-resolution images in tomographs with small crystal sizes is outlined. These results have implications regarding how to decide the optimal number of voxels of the reconstructed image or how to design better PET scanners.

Noise and physical limits to maximum resolution of PET images

International Nuclear Information System (INIS)

Herraiz, J.L.; Espana, S.; Vicente, E.; Vaquero, J.J.; Desco, M.; Udias, J.M.

2007-01-01

In this work we show that there is a limit for the maximum resolution achievable with a high resolution PET scanner, as well as for the best signal-to-noise ratio, which are ultimately related to the physical effects involved in the emission and detection of the radiation and thus they cannot be overcome with any particular reconstruction method. These effects prevent the spatial high frequency components of the imaged structures to be recorded by the scanner. Therefore, the information encoded in these high frequencies cannot be recovered by any reconstruction technique. Within this framework, we have determined the maximum resolution achievable for a given acquisition as a function of data statistics and scanner parameters, like the size of the crystals or the inter-crystal scatter. In particular, the noise level in the data as a limitation factor to yield high-resolution images in tomographs with small crystal sizes is outlined. These results have implications regarding how to decide the optimal number of voxels of the reconstructed image or how to design better PET scanners

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