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Sample records for super-resolution image reconstruction

  1. Single Image Super Resolution via Sparse Reconstruction

    NARCIS (Netherlands)

    Kruithof, M.C.; Eekeren, A.W.M. van; Dijk, J.; Schutte, K.

    2012-01-01

    High resolution sensors are required for recognition purposes. Low resolution sensors, however, are still widely used. Software can be used to increase the resolution of such sensors. One way of increasing the resolution of the images produced is using multi-frame super resolution algorithms.

  2. Application of Super-Resolution Image Reconstruction to Digital Holography

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    Zhang Shuqun

    2006-01-01

    Full Text Available We describe a new application of super-resolution image reconstruction to digital holography which is a technique for three-dimensional information recording and reconstruction. Digital holography has suffered from the low resolution of CCD sensors, which significantly limits the size of objects that can be recorded. The existing solution to this problem is to use optics to bandlimit the object to be recorded, which can cause the loss of details. Here super-resolution image reconstruction is proposed to be applied in enhancing the spatial resolution of digital holograms. By introducing a global camera translation before sampling, a high-resolution hologram can be reconstructed from a set of undersampled hologram images. This permits the recording of larger objects and reduces the distance between the object and the hologram. Practical results from real and simulated holograms are presented to demonstrate the feasibility of the proposed technique.

  3. Super-Resolution Image Reconstruction Applied to Medical Ultrasound

    Science.gov (United States)

    Ellis, Michael

    Ultrasound is the preferred imaging modality for many diagnostic applications due to its real-time image reconstruction and low cost. Nonetheless, conventional ultrasound is not used in many applications because of limited spatial resolution and soft tissue contrast. Most commercial ultrasound systems reconstruct images using a simple delay-and-sum architecture on receive, which is fast and robust but does not utilize all information available in the raw data. Recently, more sophisticated image reconstruction methods have been developed that make use of far more information in the raw data to improve resolution and contrast. One such method is the Time-Domain Optimized Near-Field Estimator (TONE), which employs a maximum a priori estimation to solve a highly underdetermined problem, given a well-defined system model. TONE has been shown to significantly improve both the contrast and resolution of ultrasound images when compared to conventional methods. However, TONE's lack of robustness to variations from the system model and extremely high computational cost hinder it from being readily adopted in clinical scanners. This dissertation aims to reduce the impact of TONE's shortcomings, transforming it from an academic construct to a clinically viable image reconstruction algorithm. By altering the system model from a collection of individual hypothetical scatterers to a collection of weighted, diffuse regions, dTONE is able to achieve much greater robustness to modeling errors. A method for efficient parallelization of dTONE is presented that reduces reconstruction time by more than an order of magnitude with little loss in image fidelity. An alternative reconstruction algorithm, called qTONE, is also developed and is able to reduce reconstruction times by another two orders of magnitude while simultaneously improving image contrast. Each of these methods for improving TONE are presented, their limitations are explored, and all are used in concert to reconstruct in

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

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

    2017-12-01

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

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

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

    2018-01-01

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

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

    Science.gov (United States)

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

    2017-07-11

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

  7. MAP-MRF-Based Super-Resolution Reconstruction Approach for Coded Aperture Compressive Temporal Imaging

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    Tinghua Zhang

    2018-02-01

    Full Text Available Coded Aperture Compressive Temporal Imaging (CACTI can afford low-cost temporal super-resolution (SR, but limits are imposed by noise and compression ratio on reconstruction quality. To utilize inter-frame redundant information from multiple observations and sparsity in multi-transform domains, a robust reconstruction approach based on maximum a posteriori probability and Markov random field (MAP-MRF model for CACTI is proposed. The proposed approach adopts a weighted 3D neighbor system (WNS and the coordinate descent method to perform joint estimation of model parameters, to achieve the robust super-resolution reconstruction. The proposed multi-reconstruction algorithm considers both total variation (TV and ℓ 2 , 1 norm in wavelet domain to address the minimization problem for compressive sensing, and solves it using an accelerated generalized alternating projection algorithm. The weighting coefficient for different regularizations and frames is resolved by the motion characteristics of pixels. The proposed approach can provide high visual quality in the foreground and background of a scene simultaneously and enhance the fidelity of the reconstruction results. Simulation results have verified the efficacy of our new optimization framework and the proposed reconstruction approach.

  8. Synthetic biology's tall order: Reconstruction of 3D, super resolution images of single molecules in real-time

    CSIR Research Space (South Africa)

    Henriques, R

    2010-08-31

    Full Text Available -to-use reconstruction software coupled with image acquisition. Here, we present QuickPALM, an Image plugin, enabling real-time reconstruction of 3D super-resolution images during acquisition and drift correction. We illustrate its application by reconstructing Cy5...

  9. A novel algorithm of super-resolution image reconstruction based on multi-class dictionaries for natural scene

    Science.gov (United States)

    Wu, Wei; Zhao, Dewei; Zhang, Huan

    2015-12-01

    Super-resolution image reconstruction is an effective method to improve the image quality. It has important research significance in the field of image processing. However, the choice of the dictionary directly affects the efficiency of image reconstruction. A sparse representation theory is introduced into the problem of the nearest neighbor selection. Based on the sparse representation of super-resolution image reconstruction method, a super-resolution image reconstruction algorithm based on multi-class dictionary is analyzed. This method avoids the redundancy problem of only training a hyper complete dictionary, and makes the sub-dictionary more representatives, and then replaces the traditional Euclidean distance computing method to improve the quality of the whole image reconstruction. In addition, the ill-posed problem is introduced into non-local self-similarity regularization. Experimental results show that the algorithm is much better results than state-of-the-art algorithm in terms of both PSNR and visual perception.

  10. Super-Resolution Reconstruction of Remote Sensing Images Using Multifractal Analysis

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    Mao-Gui Hu

    2009-10-01

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

  11. 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.

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

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    Chong Fan

    2017-03-01

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

  13. 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.

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

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

    2018-02-07

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

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

    Science.gov (United States)

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

    2018-01-01

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

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

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    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.

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

    Energy Technology Data Exchange (ETDEWEB)

    Gholipour, Ali, E-mail: ali.gholipour@childrens.harvard.edu; Afacan, Onur; Scherrer, Benoit; Prabhu, Sanjay P.; Warfield, Simon K. [Department of Radiology, Boston Children’s Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115 (United States); Aganj, Iman [Radiology Department, Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Boston, Massachusetts 02129 and Harvard Medical School, Boston, Massachusetts 02115 (United States); Sahin, Mustafa [Department of Neurology, Boston Children’s Hospital, Boston, Massachusetts 02115 and Harvard Medical School, Boston, Massachusetts 02115 (United States)

    2015-12-15

    Purpose: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. Methods: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Results: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in

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

    International Nuclear Information System (INIS)

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

    2015-01-01

    Purpose: To compare and evaluate the use of super-resolution reconstruction (SRR), in frequency, image, and wavelet domains, to reduce through-plane partial voluming effects in magnetic resonance imaging. Methods: The reconstruction of an isotropic high-resolution image from multiple thick-slice scans has been investigated through techniques in frequency, image, and wavelet domains. Experiments were carried out with thick-slice T2-weighted fast spin echo sequence on the Academic College of Radiology MRI phantom, where the reconstructed images were compared to a reference high-resolution scan using peak signal-to-noise ratio (PSNR), structural similarity image metric (SSIM), mutual information (MI), and the mean absolute error (MAE) of image intensity profiles. The application of super-resolution reconstruction was then examined in retrospective processing of clinical neuroimages of ten pediatric patients with tuberous sclerosis complex (TSC) to reduce through-plane partial voluming for improved 3D delineation and visualization of thin radial bands of white matter abnormalities. Results: Quantitative evaluation results show improvements in all evaluation metrics through super-resolution reconstruction in the frequency, image, and wavelet domains, with the highest values obtained from SRR in the image domain. The metric values for image-domain SRR versus the original axial, coronal, and sagittal images were PSNR = 32.26 vs 32.22, 32.16, 30.65; SSIM = 0.931 vs 0.922, 0.924, 0.918; MI = 0.871 vs 0.842, 0.844, 0.831; and MAE = 5.38 vs 7.34, 7.06, 6.19. All similarity metrics showed high correlations with expert ranking of image resolution with MI showing the highest correlation at 0.943. Qualitative assessment of the neuroimages of ten TSC patients through in-plane and out-of-plane visualization of structures showed the extent of partial voluming effect in a real clinical scenario and its reduction using SRR. Blinded expert evaluation of image resolution in

  19. Oblique reconstructions in tomosynthesis. II. Super-resolution

    International Nuclear Information System (INIS)

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

    2013-01-01

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

  20. Oblique reconstructions in tomosynthesis. II. Super-resolution

    Science.gov (United States)

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

    2013-01-01

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

  1. 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.

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

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    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.

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

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    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.

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

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    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.

  5. Super-resolution Microscopy in Plant Cell Imaging.

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

    2015-12-01

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

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

    Directory of Open Access Journals (Sweden)

    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.

  7. 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.

  8. Optimized multiple linear mappings for single image super-resolution

    Science.gov (United States)

    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.

  9. A Super-resolution Reconstruction Algorithm for Surveillance Video

    Directory of Open Access Journals (Sweden)

    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.

  10. Super-resolution imaging applied to moving object tracking

    Science.gov (United States)

    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.

  11. Single image super-resolution based on convolutional neural networks

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2018-03-06

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

  13. Learning-based compressed sensing for infrared image super resolution

    Science.gov (United States)

    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.

  14. 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.

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

    NARCIS (Netherlands)

    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

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

    Directory of Open Access Journals (Sweden)

    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.

  17. 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.

  18. SINGLE FRAME SUPER RESOLUTION OF NONCOOPERATIVE IRIS IMAGES

    Directory of Open Access Journals (Sweden)

    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

  19. 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...

  20. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

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

    Science.gov (United States)

    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.

  3. 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.

  4. Wavelet Filter Banks for Super-Resolution SAR Imaging

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  6. 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

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

    Science.gov (United States)

    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.

  8. 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.

  9. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  11. Droplet Image Super Resolution Based on Sparse Representation and Kernel Regression

    Science.gov (United States)

    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.

  12. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  14. 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.

  15. Effects of whispering gallery mode in microsphere super-resolution imaging

    Science.gov (United States)

    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.

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

    Science.gov (United States)

    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.

  17. A novel super-resolution camera model

    Science.gov (United States)

    Shao, Xiaopeng; Wang, Yi; Xu, Jie; Wang, Lin; Liu, Fei; Luo, Qiuhua; Chen, Xiaodong; Bi, Xiangli

    2015-05-01

    Aiming to realize super resolution(SR) to single image and video reconstruction, a super resolution camera model is proposed for the problem that the resolution of the images obtained by traditional cameras behave comparatively low. To achieve this function we put a certain driving device such as piezoelectric ceramics in the camera. By controlling the driving device, a set of continuous low resolution(LR) images can be obtained and stored instantaneity, which reflect the randomness of the displacements and the real-time performance of the storage very well. The low resolution image sequences have different redundant information and some particular priori information, thus it is possible to restore super resolution image factually and effectively. The sample method is used to derive the reconstruction principle of super resolution, which analyzes the possible improvement degree of the resolution in theory. The super resolution algorithm based on learning is used to reconstruct single image and the variational Bayesian algorithm is simulated to reconstruct the low resolution images with random displacements, which models the unknown high resolution image, motion parameters and unknown model parameters in one hierarchical Bayesian framework. Utilizing sub-pixel registration method, a super resolution image of the scene can be reconstructed. The results of 16 images reconstruction show that this camera model can increase the image resolution to 2 times, obtaining images with higher resolution in currently available hardware levels.

  18. 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

  19. 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.

  20. 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.

  1. 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.

  2. 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.

  3. 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

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

    Science.gov (United States)

    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.

  5. 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.

  6. 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.

  7. 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

  8. 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)

  9. 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.

  10. 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

  11. 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.

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

    Science.gov (United States)

    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.

  13. 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.

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

    Science.gov (United States)

    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.

  15. 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...

  16. 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)

  17. Windowed time-reversal music technique 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.

  18. 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

  19. 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.

  20. 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.

  1. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  3. Efficient document-image super-resolution using convolutional ...

    Indian Academy of Sciences (India)

    Ram Krishna Pandey

    2018-03-06

    Mar 6, 2018 ... of almost 43%, 45% and 57% on 75 dpi Tamil, English and Kannada images, respectively. Keywords. ... In our work, we have used a basic CNN with rectified linear unit (ReLU) and .... 4.3 Dataset used for the study. Since the ...

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.

  9. 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

  10. 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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. 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.

  16. 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.

  17. 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

  18. 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.

  19. 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)

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

    Science.gov (United States)

    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.

  1. 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.

  2. 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.

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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

  9. 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...

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

    Science.gov (United States)

    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.

  11. 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.

  12. 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.

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

    Science.gov (United States)

    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.

  14. 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.

  15. 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.

  16. 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.

  17. 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.

  18. 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.

  19. 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.

  20. 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.

  1. 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.

  2. 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)...

  3. 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.

  4. 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

  5. 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.

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

    Science.gov (United States)

    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

  7. 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.

  8. 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.

  9. 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.

  10. Breast Microcalcification Detection Using Super-Resolution Ultrasound Image Reconstruction

    Science.gov (United States)

    2010-09-01

    tissues. These differences in mechanical properties result in ultrasound scattering. Because the sizes of breast microcalcifications are smaller than...2006). [4] Karssemeijer, N., Bluekens, A. M., Beijerinck, D., Deurenberg, J. J., Beekman, M., Visser, R., van Engen , R., Bartels- Kortland, A., and

  11. 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.

  12. 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).

  13. 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

  14. 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

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. 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...

  1. 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.

  2. 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

  3. 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.

  4. 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.

  5. 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.

  6. 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 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.

  7. Super-resolution imaging of ESCRT-proteins at HIV-1 assembly sites.

    Directory of Open Access Journals (Sweden)

    Jens Prescher

    2015-02-01

    Full Text Available The cellular endosomal sorting complex required for transport (ESCRT machinery is involved in membrane budding processes, such as multivesicular biogenesis and cytokinesis. In HIV-infected cells, HIV-1 hijacks the ESCRT machinery to drive HIV release. Early in the HIV-1 assembly process, the ESCRT-I protein Tsg101 and the ESCRT-related protein ALIX are recruited to the assembly site. Further downstream, components such as the ESCRT-III proteins CHMP4 and CHMP2 form transient membrane associated lattices, which are involved in virus-host membrane fission. Although various geometries of ESCRT-III assemblies could be observed, the actual membrane constriction and fission mechanism is not fully understood. Fission might be driven from inside the HIV-1 budding neck by narrowing the membranes from the outside by larger lattices surrounding the neck, or from within the bud. Here, we use super-resolution fluorescence microscopy to elucidate the size and structure of the ESCRT components Tsg101, ALIX, CHMP4B and CHMP2A during HIV-1 budding below the diffraction limit. To avoid the deleterious effects of using fusion proteins attached to ESCRT components, we performed measurements on the endogenous protein or, in the case of CHMP4B, constructs modified with the small HA tag. Due to the transient nature of the ESCRT interactions, the fraction of HIV-1 assembly sites with colocalizing ESCRT complexes was low (1.5%-3.4%. All colocalizing ESCRT clusters exhibited closed, circular structures with an average size (full-width at half-maximum between 45 and 60 nm or a diameter (determined using a Ripley's L-function analysis of roughly 60 to 100 nm. The size distributions for colocalizing clusters were narrower than for non-colocalizing clusters, and significantly smaller than the HIV-1 bud. Hence, our results support a membrane scission process driven by ESCRT protein assemblies inside a confined structure, such as the bud neck, rather than by large lattices

  8. 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.

  9. 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

  10. 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.

  11. 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

  12. 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

  13. 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).

  14. Image quality assessment for determining efficacy and limitations of Super-Resolution Convolutional Neural Network (SRCNN)

    Science.gov (United States)

    Ward, Chris M.; Harguess, Joshua; Crabb, Brendan; Parameswaran, Shibin

    2017-09-01

    Traditional metrics for evaluating the efficacy of image processing techniques do not lend themselves to under- standing the capabilities and limitations of modern image processing methods - particularly those enabled by deep learning. When applying image processing in engineering solutions, a scientist or engineer has a need to justify their design decisions with clear metrics. By applying blind/referenceless image spatial quality (BRISQUE), Structural SIMilarity (SSIM) index scores, and Peak signal-to-noise ratio (PSNR) to images before and after im- age processing, we can quantify quality improvements in a meaningful way and determine the lowest recoverable image quality for a given method.

  15. 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...

  16. Super-Resolution Imaging of Protein Secretion Systems and the Cell Surface of Gram-Negative Bacteria

    Directory of Open Access Journals (Sweden)

    Sachith D. Gunasinghe

    2017-05-01

    Full Text Available Gram-negative bacteria have a highly evolved cell wall with two membranes composed of complex arrays of integral and peripheral proteins, as well as phospholipids and glycolipids. In order to sense changes in, respond to, and exploit their environmental niches, bacteria rely on structures assembled into or onto the outer membrane. Protein secretion across the cell wall is a key process in virulence and other fundamental aspects of bacterial cell biology. The final stage of protein secretion in Gram-negative bacteria, translocation across the outer membrane, is energetically challenging so sophisticated nanomachines have evolved to meet this challenge. Advances in fluorescence microscopy now allow for the direct visualization of the protein secretion process, detailing the dynamics of (i outer membrane biogenesis and the assembly of protein secretion systems into the outer membrane, (ii the spatial distribution of these and other membrane proteins on the bacterial cell surface, and (iii translocation of effector proteins, toxins and enzymes by these protein secretion systems. Here we review the frontier research imaging the process of secretion, particularly new studies that are applying various modes of super-resolution microscopy.

  17. A new low-complexity patch-based image super-resolution

    DEFF Research Database (Denmark)

    Rasti, Pejman; Nasrollahi, Kamal; Orlova, Olga

    2017-01-01

    through an illumination enhancement process resulting in consistency of illumination between neigh- bour patches. This process is applied to all patches of the LR image. Finally, in order to remove the blocking effect caused by merging the patches, an average of the obtained HR image and the interpolated...

  18. Study on super-resolution three-dimensional range-gated imaging technology

    Science.gov (United States)

    Guo, Huichao; Sun, Huayan; Wang, Shuai; Fan, Youchen; Li, Yuanmiao

    2018-04-01

    Range-gated three dimensional imaging technology is a hotspot in recent years, because of the advantages of high spatial resolution, high range accuracy, long range, and simultaneous reflection of target reflectivity information. Based on the study of the principle of intensity-related method, this paper has carried out theoretical analysis and experimental research. The experimental system adopts the high power pulsed semiconductor laser as light source, gated ICCD as the imaging device, can realize the imaging depth and distance flexible adjustment to achieve different work mode. The imaging experiment of small imaging depth is carried out aiming at building 500m away, and 26 group images were obtained with distance step 1.5m. In this paper, the calculation method of 3D point cloud based on triangle method is analyzed, and 15m depth slice of the target 3D point cloud are obtained by using two frame images, the distance precision is better than 0.5m. The influence of signal to noise ratio, illumination uniformity and image brightness on distance accuracy are analyzed. Based on the comparison with the time-slicing method, a method for improving the linearity of point cloud is proposed.

  19. Improvement of Breast Cancer Detection Using Non-subsampled Contourlet Transform and Super-Resolution Technique in Mammographic Images

    Directory of Open Access Journals (Sweden)

    Fatemeh Pak

    2015-05-01

    Full Text Available Introduction Breast cancer is one of the most life-threatening conditions among women. Early detection of this disease is the only way to reduce the associated mortality rate. Mammography is a standard method for the early detection of breast cancer. Today, considering the importance of breast cancer detection, computer-aided detection techniques have been employed to increase the quality of mammographic images and help physicians reduce false positive rate (FPR. Materials and Methods In this study, a method was proposed for improving the quality of mammographic images to help radiologists establish a prompt and accurate diagnosis. The proposed approach included three major parts including pre-processing, feature extraction, and classification. In the pre-processing stage, the region of interest was determined and the image quality was improved by non-subsampled contourlet transform and super-resolution algorithm. In the feature extraction stage, some features of image components were extracted and skewness of each feature was calculated. Finally, a support vector machine was utilized to classify the features and determine the probability of benignity or malignancy of the disease. Results Based on the obtained results using Mammographic Image Analysis Society (MIAS database, the mean accuracy was estimated at 87.26% and maximum accuracy was 96.29%. Also, the mean and minimum FPRs were estimated at 9.55% and 2.87%, respectively.     Conclusion The results obtained using MIAS database indicated the superiority of the proposed method to other techniques. The reduced FPR in the proposed method was a significant finding in the present article.

  20. 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.

  1. 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.

  2. Ultrafast ultrasound localization microscopy for deep super-resolution vascular imaging

    Science.gov (United States)

    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

  3. Enhanced echolocation via robust statistics and super-resolution of sonar images

    Science.gov (United States)

    Kim, Kio

    Echolocation is a process in which an animal uses acoustic signals to exchange information with environments. In a recent study, Neretti et al. have shown that the use of robust statistics can significantly improve the resiliency of echolocation against noise and enhance its accuracy by suppressing the development of sidelobes in the processing of an echo signal. In this research, the use of robust statistics is extended to problems in underwater explorations. The dissertation consists of two parts. Part I describes how robust statistics can enhance the identification of target objects, which in this case are cylindrical containers filled with four different liquids. Particularly, this work employs a variation of an existing robust estimator called an L-estimator, which was first suggested by Koenker and Bassett. As pointed out by Au et al.; a 'highlight interval' is an important feature, and it is closely related with many other important features that are known to be crucial for dolphin echolocation. A varied L-estimator described in this text is used to enhance the detection of highlight intervals, which eventually leads to a successful classification of echo signals. Part II extends the problem into 2 dimensions. Thanks to the advances in material and computer technology, various sonar imaging modalities are available on the market. By registering acoustic images from such video sequences, one can extract more information on the region of interest. Computer vision and image processing allowed application of robust statistics to the acoustic images produced by forward looking sonar systems, such as Dual-frequency Identification Sonar and ProViewer. The first use of robust statistics for sonar image enhancement in this text is in image registration. Random Sampling Consensus (RANSAC) is widely used for image registration. The registration algorithm using RANSAC is optimized for sonar image registration, and the performance is studied. The second use of robust

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

    Science.gov (United States)

    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

  5. Dark-field hyperlens: Super-resolution imaging of weakly scattering objects

    DEFF Research Database (Denmark)

    Repän, Taavi; Lavrinenko, Andrei; Zhukovsky, Sergei

    2015-01-01

    : We propose a device for subwavelength optical imaging based on a metal-dielectric multilayer hyperlens designed in such a way that only large-wavevector (evanescent) waves are transmitted while all propagating (small-wavevector) waves from the object area are blocked by the hyperlens. We...... numerically demonstrate that as the result of such filtering, the image plane only contains scattered light from subwavelength features of the objects and is completely free from background illumination. Similar in spirit to conventional dark-field microscopy, the proposed dark-field hyperlens is shown...

  6. 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.

  7. Instant live-cell super-resolution imaging of cellular structures by nanoinjection of fluorescent probes.

    Science.gov (United States)

    Hennig, Simon; van de Linde, Sebastian; Lummer, Martina; Simonis, Matthias; Huser, Thomas; Sauer, Markus

    2015-02-11

    Labeling internal structures within living cells with standard fluorescent probes is a challenging problem. Here, we introduce a novel intracellular staining method that enables us to carefully control the labeling process and provides instant access to the inner structures of living cells. Using a hollow glass capillary with a diameter of <100 nm, we deliver functionalized fluorescent probes directly into the cells by (di)electrophoretic forces. The label density can be adjusted and traced directly during the staining process by fluorescence microscopy. We demonstrate the potential of this technique by delivering and imaging a range of commercially available cell-permeable and nonpermeable fluorescent probes to cells.

  8. 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.

  9. 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.

  10. 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

  11. 3D range-gated super-resolution imaging based on stereo matching for moving platforms and targets

    Science.gov (United States)

    Sun, Liang; Wang, Xinwei; Zhou, Yan

    2017-11-01

    3D range-gated superresolution imaging is a novel 3D reconstruction technique for target detection and recognition with good real-time performance. However, for moving targets or platforms such as airborne, shipborne, remote operated vehicle and autonomous vehicle, 3D reconstruction has a large error or failure. In order to overcome this drawback, we propose a method of stereo matching for 3D range-gated superresolution reconstruction algorithm. In experiment, the target is a doll of Mario with a height of 38cm at the location of 34m, and we obtain two successive frame images of the Mario. To confirm our method is effective, we transform the original images with translation, rotation, scale and perspective, respectively. The experimental result shows that our method has a good result of 3D reconstruction for moving targets or platforms.

  12. 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.

  13. 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

  14. 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.

  15. Development of targeted STORM for super resolution imaging of biological samples using digital micro-mirror device

    Science.gov (United States)

    Valiya Peedikakkal, Liyana; Steventon, Victoria; Furley, Andrew; Cadby, Ashley J.

    2017-12-01

    We demonstrate a simple illumination system based on a digital mirror device which allows for fine control over the power and pattern of illumination. We apply this to localization microscopy (LM), specifically stochastic optical reconstruction microscopy (STORM). Using this targeted STORM, we were able to image a selected area of a labelled cell without causing photo-damage to the surrounding areas of the cell.

  16. Combination of single image super resolution and digital Inpainting algorithms based on GANS for robust image completion

    Directory of Open Access Journals (Sweden)

    Hayrapetyan Sparik

    2017-01-01

    Full Text Available Image inpainting, a technique of completing missing or corrupted image regions in undetected form, is an open problem in digital image processing. Inpainting of large regions using Deep Convolutional Generative Adversarial Nets (DCGAN is a new and powerful approach. In described approaches the size of generated image and size of input image should be the same. In this paper we propose a new method where the size of input image with corrupted region can be up to 4 times larger than generated image.

  17. 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.

  18. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  20. 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.

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

    Science.gov (United States)

    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.

  2. Super-resolution inpainting

    Institute of Scientific and Technical Information of China (English)

    SHIH Timothy K; CHANG Rong-chi

    2005-01-01

    Image or video resources are often received in poor condition, mostly with noise or defects making the resources hard to read. We propose an effective algorithm based on digital image inpainting. The mechanism can be used in restoring images or video frames with very high noise or defect ratio (e.g., 90%). The algorithm is based on the concept of image subdivision and estimation of color variations. Noises inside blocks of different sizes are inpainted with different levels of surrounding information.The results showed that an almost unrecognizable image can be recovered with visually good result. The algorithm can be further extended for processing motion picture with high percentage of noise.

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

    Science.gov (United States)

    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.

  4. Live-cell and super-resolution imaging reveal that the distribution of wall-associated protein A is correlated with the cell chain integrity of Streptococcus mutans.

    Science.gov (United States)

    Li, Y; Liu, Z; Zhang, Y; Su, Q P; Xue, B; Shao, S; Zhu, Y; Xu, X; Wei, S; Sun, Y

    2015-10-01

    Streptococcus mutans is a primary pathogen responsible for dental caries. It has an outstanding ability to form biofilm, which is vital for virulence. Previous studies have shown that knockout of Wall-associated protein A (WapA) affects cell chain and biofilm formation of S. mutans. As a surface protein, the distribution of WapA remains unknown, but it is important to understand the mechanism underlying the function of WapA. This study applied the fluorescence protein mCherry as a reporter gene to characterize the dynamic distribution of WapA in S. mutans via time-lapse and super-resolution fluorescence imaging. The results revealed interesting subcellular distribution patterns of WapA in single, dividing and long chains of S. mutans cells. It appears at the middle of the cell and moves to the poles as the cell grows and divides. In a cell chain, after each round of cell division, such dynamic relocation results in WapA distribution at the previous cell division sites, resulting in a pattern where WapA is located at the boundary of two adjacent cell pairs. This WapA distribution pattern corresponds to the breaking segmentation of wapA deletion cell chains. The dynamic relocation of WapA through the cell cycle increases our understanding of the mechanism of WapA in maintaining cell chain integrity and biofilm formation. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  5. 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.

  6. Revealing dynamically-organized receptor ion channel clusters in live cells by a correlated electric recording and super-resolution single-molecule imaging approach.

    Science.gov (United States)

    Yadav, Rajeev; Lu, H Peter

    2018-03-28

    The N-methyl-d-aspartate (NMDA) receptor ion-channel is activated by the binding of ligands, along with the application of action potential, important for synaptic transmission and memory functions. Despite substantial knowledge of the structure and function, the gating mechanism of the NMDA receptor ion channel for electric on-off signals is still a topic of debate. We investigate the NMDA receptor partition distribution and the associated channel's open-close electric signal trajectories using a combined approach of correlating single-molecule fluorescence photo-bleaching, single-molecule super-resolution imaging, and single-channel electric patch-clamp recording. Identifying the compositions of NMDA receptors, their spatial organization and distributions over live cell membranes, we observe that NMDA receptors are organized inhomogeneously: nearly half of the receptor proteins are individually dispersed; whereas others exist in heterogeneous clusters of around 50 nm in size as well as co-localized within the diffraction limited imaging area. We demonstrate that inhomogeneous interactions and partitions of the NMDA receptors can be a cause of the heterogeneous gating mechanism of NMDA receptors in living cells. Furthermore, comparing the imaging results with the ion-channel electric current recording, we propose that the clustered NMDA receptors may be responsible for the variation in the current amplitude observed in the on-off two-state ion-channel electric signal trajectories. Our findings shed new light on the fundamental structure-function mechanism of NMDA receptors and present a conceptual advancement of the ion-channel mechanism in living cells.

  7. Nanobodies: site-specific labeling for super-resolution imaging, rapid epitope-mapping and native protein complex isolation

    Science.gov (United States)

    Pleiner, Tino; Bates, Mark; Trakhanov, Sergei; Lee, Chung-Tien; Schliep, Jan Erik; Chug, Hema; Böhning, Marc; Stark, Holger; Urlaub, Henning; Görlich, Dirk

    2015-01-01

    Nanobodies are single-domain antibodies of camelid origin. We generated nanobodies against the vertebrate nuclear pore complex (NPC) and used them in STORM imaging to locate individual NPC proteins with nanobody sequence and labeled the resulting proteins with fluorophore-maleimides. As nanobodies are normally stabilized by disulfide-bonded cysteines, this appears counterintuitive. Yet, our analysis showed that this caused no folding problems. Compared to traditional NHS ester-labeling of lysines, the cysteine-maleimide strategy resulted in far less background in fluorescence imaging, it better preserved epitope recognition and it is site-specific. We also devised a rapid epitope-mapping strategy, which relies on crosslinking mass spectrometry and the introduced ectopic cysteines. Finally, we used different anti-nucleoporin nanobodies to purify the major NPC building blocks – each in a single step, with native elution and, as demonstrated, in excellent quality for structural analysis by electron microscopy. The presented strategies are applicable to any nanobody and nanobody-target. DOI: http://dx.doi.org/10.7554/eLife.11349.001 PMID:26633879

  8. 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

  9. In Vivo Optical Imaging for Targeted Drug Kinetics and Localization for Oral Surgery and Super-Resolution, Facilitated by Printed Phantoms

    Science.gov (United States)

    Bentz, Brian Z.

    Many human cancer cell types over-express folate receptors, and this provides an opportunity to develop targeted anti-cancer drugs. For these drugs to be effective, their kinetics must be well understood in vivo and in deep tissue where tumors occur. We demonstrate a method for imaging these parameters by incorporating a kinetic compartment model and fluorescence into optical diffusion tomography (ODT). The kinetics were imaged in a live mouse, and found to be in agreement with previous in vitro studies, demonstrating the validity of the method and its feasibility as an effective tool in preclinical drug development studies. Progress in developing optical imaging for biomedical applications requires customizable and often complex objects known as "phantoms" for testing and evaluation. We present new optical phantoms fabricated using inexpensive 3D printing methods with multiple materials, allowing for the placement of complex inhomogeneities in heterogeneous or anatomically realistic geometries, as opposed to previous phantoms which were limited to simple shapes formed by molds or machining. Furthermore, we show that Mie theory can be used to design the optical properties to match a target tissue. The phantom fabrication methods are versatile, can be applied to optical imaging methods besides diffusive imaging, and can be used in the calibration of live animal imaging data. Applications of diffuse optical imaging in the operating theater have been limited in part due to computational burden. We present an approach for the fast localization of arteries in the roof of the mouth that has the potential to reduce complications. Furthermore, we use the extracted position information to fabricate a custom surgical guide using 3D printing that could protect the arteries during surgery. The resolution of ODT is severely limited by the attenuation of high spatial frequencies. We present a super-resolution method achieved through the point localization of fluorescent

  10. 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.

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

    Directory of Open Access Journals (Sweden)

    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.

  12. 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.

  13. 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.

  14. 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

  15. 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...

  16. 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....

  17. 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...

  18. 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.

  19. 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.

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

    NARCIS (Netherlands)

    Dzyubachyk, O.; Khmelinskii, A.; Plenge, E.; Kok, P.; Snoeks, T.J.; Poot, D.H.; Löwik, C.W.; Botha, C.P.; Niessen, W.J.; Van der Weerd, L.; Meijering, E.; Lelieveldt, B.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

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

    NARCIS (Netherlands)

    O.M. Dzyubachyk (Oleh); A. Khmelinskii (Artem); E. Plenge (Esben); P. Kok (Peter); T.J.A. Snoeks (Thomas); D.H.J. Poot; C.W.G.M. Löwik (Clemens); C.P. Botha (Charl); W.J. Niessen (Wiro); L. van der Weerd; E. Meijering (Erik); B.P.F. Lelieveldt (Boudewijn)

    2014-01-01

    textabstractIn 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

  2. 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)

  3. 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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. 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.)

  9. 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.

  10. Super Resolution Algorithm for CCTVs

    Science.gov (United States)

    Gohshi, Seiichi

    2015-03-01

    Recently, security cameras and CCTV systems have become an important part of our daily lives. The rising demand for such systems has created business opportunities in this field, especially in big cities. Analogue CCTV systems are being replaced by digital systems, and HDTV CCTV has become quite common. HDTV CCTV can achieve images with high contrast and decent quality if they are clicked in daylight. However, the quality of an image clicked at night does not always have sufficient contrast and resolution because of poor lighting conditions. CCTV systems depend on infrared light at night to compensate for insufficient lighting conditions, thereby producing monochrome images and videos. However, these images and videos do not have high contrast and are blurred. We propose a nonlinear signal processing technique that significantly improves visual and image qualities (contrast and resolution) of low-contrast infrared images. The proposed method enables the use of infrared cameras for various purposes such as night shot and poor lighting environments under poor lighting conditions.

  11. 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.

  12. 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.

  13. Super-resolution imaging of ciliary microdomains in isolated olfactory sensory neurons using a custom two-color stimulated emission depletion microscope

    Science.gov (United States)

    Meyer, Stephanie A.; Ozbay, Baris N.; Potcoava, Mariana; Salcedo, Ernesto; Restrepo, Diego; Gibson, Emily A.

    2016-06-01

    We performed stimulated emission depletion (STED) imaging of isolated olfactory sensory neurons (OSNs) using a custom-built microscope. The STED microscope uses a single pulsed laser to excite two separate fluorophores, Atto 590 and Atto 647N. A gated timing circuit combined with temporal interleaving of the different color excitation/STED laser pulses filters the two channel detection and greatly minimizes crosstalk. We quantified the instrument resolution to be ˜81 and ˜44 nm, for the Atto 590 and Atto 647N channels. The spatial separation between the two channels was measured to be under 10 nm, well below the resolution limit. The custom-STED microscope is incorporated onto a commercial research microscope allowing brightfield, differential interference contrast, and epifluorescence imaging on the same field of view. We performed immunolabeling of OSNs in mice to image localization of ciliary membrane proteins involved in olfactory transduction. We imaged Ca2+-permeable cyclic nucleotide gated (CNG) channel (Atto 594) and adenylyl cyclase type III (ACIII) (Atto 647N) in distinct cilia. STED imaging resolved well-separated subdiffraction limited clusters for each protein. We quantified the size of each cluster to have a mean value of 88±48 nm and 124±43 nm, for CNG and ACIII, respectively. STED imaging showed separated clusters that were not resolvable in confocal images.

  14. 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

  15. 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...

  16. 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,

  17. 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...

  18. 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).

  19. 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.

  20. 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.

  1. Unique Microstructural Changes in the Brain Associated with Urological Chronic Pelvic Pain Syndrome (UCPPS Revealed by Diffusion Tensor MRI, Super-Resolution Track Density Imaging, and Statistical Parameter Mapping: A MAPP Network Neuroimaging Study.

    Directory of Open Access Journals (Sweden)

    Davis Woodworth

    Full Text Available Studies have suggested chronic pain syndromes are associated with neural reorganization in specific regions associated with perception, processing, and integration of pain. Urological chronic pelvic pain syndrome (UCPPS represents a collection of pain syndromes characterized by pelvic pain, namely Chronic Prostatitis/Chronic Pelvic Pain Syndrome (CP/CPPS and Interstitial Cystitis/Painful Bladder Syndrome (IC/PBS, that are both poorly understood in their pathophysiology, and treated ineffectively. We hypothesized patients with UCPPS may have microstructural differences in the brain compared with healthy control subjects (HCs, as well as patients with irritable bowel syndrome (IBS, a common gastrointestinal pain disorder. In the current study we performed population-based voxel-wise DTI and super-resolution track density imaging (TDI in a large, two-center sample of phenotyped patients from the multicenter cohort with UCPPS (N = 45, IBS (N = 39, and HCs (N = 56 as part of the MAPP Research Network. Compared with HCs, UCPPS patients had lower fractional anisotropy (FA, lower generalized anisotropy (GA, lower track density, and higher mean diffusivity (MD in brain regions commonly associated with perception and integration of pain information. Results also showed significant differences in specific anatomical regions in UCPPS patients when compared with IBS patients, consistent with microstructural alterations specific to UCPPS. While IBS patients showed clear sex related differences in FA, MD, GA, and track density consistent with previous reports, few such differences were observed in UCPPS patients. Heat maps illustrating the correlation between specific regions of interest and various pain and urinary symptom scores showed clustering of significant associations along the cortico-basal ganglia-thalamic-cortical loop associated with pain integration, modulation, and perception. Together, results suggest patients with UCPPS have extensive

  2. 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

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

    Science.gov (United States)

    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.

  4. 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.

  5. 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.

  6. 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.

  7. 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.

  8. Image Reconstruction. Chapter 13

    Energy Technology Data Exchange (ETDEWEB)

    Nuyts, J. [Department of Nuclear Medicine and Medical Imaging Research Center, Katholieke Universiteit Leuven, Leuven (Belgium); Matej, S. [Medical Image Processing Group, Department of Radiology, University of Pennsylvania, Philadelphia, PA (United States)

    2014-12-15

    This chapter discusses how 2‑D or 3‑D images of tracer distribution can be reconstructed from a series of so-called projection images acquired with a gamma camera or a positron emission tomography (PET) system [13.1]. This is often called an ‘inverse problem’. The reconstruction is the inverse of the acquisition. The reconstruction is called an inverse problem because making software to compute the true tracer distribution from the acquired data turns out to be more difficult than the ‘forward’ direction, i.e. making software to simulate the acquisition. There are basically two approaches to image reconstruction: analytical reconstruction and iterative reconstruction. The analytical approach is based on mathematical inversion, yielding efficient, non-iterative reconstruction algorithms. In the iterative approach, the reconstruction problem is reduced to computing a finite number of image values from a finite number of measurements. That simplification enables the use of iterative instead of mathematical inversion. Iterative inversion tends to require more computer power, but it can cope with more complex (and hopefully more accurate) models of the acquisition process.

  9. Overview of image reconstruction

    International Nuclear Information System (INIS)

    Marr, R.B.

    1980-04-01

    Image reconstruction (or computerized tomography, etc.) is any process whereby a function, f, on R/sup n/ is estimated from empirical data pertaining to its integrals, ∫f(x) dx, for some collection of hyperplanes of dimension k < n. The paper begins with background information on how image reconstruction problems have arisen in practice, and describes some of the application areas of past or current interest; these include radioastronomy, optics, radiology and nuclear medicine, electron microscopy, acoustical imaging, geophysical tomography, nondestructive testing, and NMR zeugmatography. Then the various reconstruction algorithms are discussed in five classes: summation, or simple back-projection; convolution, or filtered back-projection; Fourier and other functional transforms; orthogonal function series expansion; and iterative methods. Certain more technical mathematical aspects of image reconstruction are considered from the standpoint of uniqueness, consistency, and stability of solution. The paper concludes by presenting certain open problems. 73 references

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

    Science.gov (United States)

    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.

  11. 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.

  12. 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.

  13. 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.

  14. 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.

  15. Super-resolution for a point source using positive refraction

    Science.gov (United States)

    Miñano, Juan C.; Benítez, Pablo; González, Juan C.; Grabovičkić, Dejan; Ahmadpanahi, Hamed

    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 receptor called "perfect drain" (PD) located at the corresponding MFE image point. The PD has the property of absorbing the complete radiation without radiation or scattering and it has been claimed as necessary to obtain super-resolution (SR) in the MFE. However, a prototype using a "drain" different from the PD has shown λ/5 resolution for microwave frequencies (Ma et al, 2010). Recently, the SR properties of a device equivalent to the MFE, called the Spherical Geodesic Waveguide (SGW) (Miñano et al, 2012) have been analyzed. The reported results show resolution up to λ /3000, for the SGW loaded with the perfect drain, and up to λ /500 for the SGW without perfect drain. The perfect drain was realized as a coaxial probe loaded with properly calculated impedance. The SGW provides SR only in a narrow band of frequencies close to the resonance Schumann frequencies. Here we analyze the SGW loaded with a small "perfect drain region" (González et al, 2011). This drain is designed as a region made of a material with complex permittivity. The comparative results show that there is no significant difference in the SR properties for both perfect drain designs.

  16. 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.

  17. 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.

  18. 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.

  19. 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)

  20. 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)

  1. 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.

  2. Deep Learning based Super-Resolution for Improved Action Recognition

    DEFF Research Database (Denmark)

    Nasrollahi, Kamal; Guerrero, Sergio Escalera; Rasti, Pejman

    2015-01-01

    with results of a state-of- the-art deep learning-based super-resolution algorithm, through an alpha-blending approach. The experimental results obtained on down-sampled version of a large subset of Hoolywood2 benchmark database show the importance of the proposed system in increasing the recognition rate...

  3. Pixel super resolution using wavelength scanning

    Science.gov (United States)

    2016-04-08

    13 Celebi ME, Schaefer G. Color Medical Image Analysis. Netherlands: Springer. 2013. 14 Yamaguchi I, Matsumura T, Kato J. Phase-shifting color...2016.60 15 Kato J, Yamaguchi I, Matsumura T. Multicolor digital holography with an achromatic phase shifter. Opt Lett 2002; 27: 1403–1405. 16 Ferraro P

  4. 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.

  5. 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

  6. 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.

  7. 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

  8. 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.

  9. 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

  10. Super-Resolution Algorithm in Cumulative Virtual Blanking

    Science.gov (United States)

    Montillet, J. P.; Meng, X.; Roberts, G. W.; Woolfson, M. S.

    2008-11-01

    The proliferation of mobile devices and the emergence of wireless location-based services have generated consumer demand for precise location. In this paper, the MUSIC super-resolution algorithm is applied to time delay estimation for positioning purposes in cellular networks. The goal is to position a Mobile Station with UMTS technology. The problem of Base-Stations herability is solved using Cumulative Virtual Blanking. A simple simulator is presented using DS-SS signal. The results show that MUSIC algorithm improves the time delay estimation in both the cases whether or not Cumulative Virtual Blanking was carried out.

  11. 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.

  12. Tomographic image reconstruction using training images

    DEFF Research Database (Denmark)

    Soltani, Sara; Andersen, Martin Skovgaard; Hansen, Per Christian

    2017-01-01

    We describe and examine an algorithm for tomographic image reconstruction where prior knowledge about the solution is available in the form of training images. We first construct a non-negative dictionary based on prototype elements from the training images; this problem is formulated within...

  13. 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.

  14. 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.

  15. Current limitations in super-resolution fluorescence microscopy for biological specimens: How deep can we go from the cover glass?

    Science.gov (United States)

    Okada, Yasushi

    2017-04-01

    Diffraction limit of resolution has been one of the biggest limitations in the optical microscopy. Super-resolution fluorescence microscopy has enabled us to break this limit. However, for the observations of real biological specimens, especially for the imaging of tissues or whole body, the target structures of interest are often embedded deep inside the specimen. Here, we would present our results to extend the target of the super-resolution microscopy deeper into the cells. Confocal microscope optics work effectively to minimize the effect by the aberrations by the cellular components, but at the expense of the signal intensities. Spherical aberrations by the refractive index mismatch between the cellular environment and the immersion liquid can be much larger, but can be reduced by adjusting the correction collar at the objective lens.

  16. 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.

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

    Science.gov (United States)

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

    2016-01-26

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

  18. 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.

  19. 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.

  20. Colour reconstruction of underwater images

    OpenAIRE

    Hoth, Julian; Kowalczyk, Wojciech

    2017-01-01

    Objects look very different in the underwater environment compared to their appearance in sunlight. Images with correct colouring simplify the detection of underwater objects and may allow the use of visual SLAM algorithms developed for land-based robots underwater. Hence, image processing is required. Current algorithms focus on the colour reconstruction of scenery at diving depth where different colours can still be distinguished. At greater depth this is not the case. In this study it is i...

  1. Correlative Super-Resolution Microscopy: New Dimensions and New Opportunities.

    Science.gov (United States)

    Hauser, Meghan; Wojcik, Michal; Kim, Doory; Mahmoudi, Morteza; Li, Wan; Xu, Ke

    2017-06-14

    Correlative microscopy, the integration of two or more microscopy techniques performed on the same sample, produces results that emphasize the strengths of each technique while offsetting their individual weaknesses. Light microscopy has historically been a central method in correlative microscopy due to its widespread availability, compatibility with hydrated and live biological samples, and excellent molecular specificity through fluorescence labeling. However, conventional light microscopy can only achieve a resolution of ∼300 nm, undercutting its advantages in correlations with higher-resolution methods. The rise of super-resolution microscopy (SRM) over the past decade has drastically improved the resolution of light microscopy to ∼10 nm, thus creating exciting new opportunities and challenges for correlative microscopy. Here we review how these challenges are addressed to effectively correlate SRM with other microscopy techniques, including light microscopy, electron microscopy, cryomicroscopy, atomic force microscopy, and various forms of spectroscopy. Though we emphasize biological studies, we also discuss the application of correlative SRM to materials characterization and single-molecule reactions. Finally, we point out current limitations and discuss possible future improvements and advances. We thus demonstrate how a correlative approach adds new dimensions of information and provides new opportunities in the fast-growing field of SRM.

  2. Application of spectroscopy and super-resolution microscopy: Excited state

    Energy Technology Data Exchange (ETDEWEB)

    Bhattacharjee, Ujjal [Iowa State Univ., Ames, IA (United States)

    2016-02-19

    Photophysics of inorganic materials and organic molecules in complex systems have been extensively studied with absorption and emission spectroscopy.1-4 Steady-state and time-resolved fluorescence studies are commonly carried out to characterize excited-state properties of fluorophores. Although steady-state fluorescence measurements are widely used for analytical applications, time-resolved fluorescence measurements provide more detailed information about excited-state properties and the environment in the vicinity of the fluorophore. Many photophysical processes, such as photoinduced electron transfer (PET), rotational reorientation, solvent relaxation, and energy transfer, occur on a nanosecond (10-9 s) timescale, thus affecting the lifetime of the fluorophores. Moreover, time-resolved microscopy methods, such as lifetimeimaging, combine the benefits of the microscopic measurement and information-rich, timeresolved data. Thus, time-resolved fluorescence spectroscopy combined with microscopy can be used to quantify these processes and to obtain a deeper understanding of the chemical surroundings of the fluorophore in a small area under investigation. This thesis discusses various photophysical and super-resolution microscopic studies of organic and inorganic materials, which have been outlined below.

  3. 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.

  4. Impact of detector-element active-area shape and fill factor on super-resolution

    Directory of Open Access Journals (Sweden)

    Russell Craig Hardie

    2015-05-01

    Full Text Available In many undersampled imaging systems, spatial integration from the individual detector elements is the dominant component of the system point spread function (PSF. Conventional focal plane arrays (FPAs utilize square detector elements with a nearly 100% fill factor, where fill factor is defined as the fraction of the detector element area that is active in light detection. A large fill factor is generally considered to be desirable because more photons are collected for a given pitch, and this leads to a higher signal-to-noise-ratio (SNR. However, the large active area works against super-resolution (SR image restoration by acting as an additional low pass filter in the overall PSF when modeled on the SR sampling grid. A high fill factor also tends to increase blurring from pixel cross-talk. In this paper, we study the impact of FPA detector-element shape and fill factor on SR. A detailed modulation transfer function analysis is provided along with a number of experimental results with both simulated data and real data acquired with a midwave infrared (MWIR imaging system. We demonstrate the potential advantage of low fill factor detector elements when combined with SR image restoration. Our results suggest that low fill factor circular detector elements may be the best choice. New video results are presented using robust adaptive Wiener filter SR processing applied to data from a commercial MWIR imaging system with both high and low detector element fill factors.

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

    Directory of Open Access Journals (Sweden)

    Aoran Xiao

    2018-04-01

    Full Text Available 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.

  6. 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.

  7. 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.

  8. 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

  9. Method for position emission mammography image reconstruction

    Science.gov (United States)

    Smith, Mark Frederick

    2004-10-12

    An image reconstruction method comprising accepting coincidence datat from either a data file or in real time from a pair of detector heads, culling event data that is outside a desired energy range, optionally saving the desired data for each detector position or for each pair of detector pixels on the two detector heads, and then reconstructing the image either by backprojection image reconstruction or by iterative image reconstruction. In the backprojection image reconstruction mode, rays are traced between centers of lines of response (LOR's), counts are then either allocated by nearest pixel interpolation or allocated by an overlap method and then corrected for geometric effects and attenuation and the data file updated. If the iterative image reconstruction option is selected, one implementation is to compute a grid Siddon retracing, and to perform maximum likelihood expectation maiximization (MLEM) computed by either: a) tracing parallel rays between subpixels on opposite detector heads; or b) tracing rays between randomized endpoint locations on opposite detector heads.

  10. 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.

  11. 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.

  12. Tomographic image reconstruction using Artificial Neural Networks

    International Nuclear Information System (INIS)

    Paschalis, P.; Giokaris, N.D.; Karabarbounis, A.; Loudos, G.K.; Maintas, D.; Papanicolas, C.N.; Spanoudaki, V.; Tsoumpas, Ch.; Stiliaris, E.

    2004-01-01

    A new image reconstruction technique based on the usage of an Artificial Neural Network (ANN) is presented. The most crucial factor in designing such a reconstruction system is the network architecture and the number of the input projections needed to reconstruct the image. Although the training phase requires a large amount of input samples and a considerable CPU time, the trained network is characterized by simplicity and quick response. The performance of this ANN is tested using several image patterns. It is intended to be used together with a phantom rotating table and the γ-camera of IASA for SPECT image reconstruction

  13. Optoelectronic Computer Architecture Development for Image Reconstruction

    National Research Council Canada - National Science Library

    Forber, Richard

    1996-01-01

    .... Specifically, we collaborated with UCSD and ERIM on the development of an optically augmented electronic computer for high speed inverse transform calculations to enable real time image reconstruction...

  14. 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.

  15. Extending the Capture Volume of an Iris Recognition System Using Wavefront Coding and Super-Resolution.

    Science.gov (United States)

    Hsieh, Sheng-Hsun; Li, Yung-Hui; Tien, Chung-Hao; Chang, Chin-Chen

    2016-12-01

    Iris recognition has gained increasing popularity over the last few decades; however, the stand-off distance in a conventional iris recognition system is too short, which limits its application. In this paper, we propose a novel hardware-software hybrid method to increase the stand-off distance in an iris recognition system. When designing the system hardware, we use an optimized wavefront coding technique to extend the depth of field. To compensate for the blurring of the image caused by wavefront coding, on the software side, the proposed system uses a local patch-based super-resolution method to restore the blurred image to its clear version. The collaborative effect of the new hardware design and software post-processing showed great potential in our experiment. The experimental results showed that such improvement cannot be achieved by using a hardware-or software-only design. The proposed system can increase the capture volume of a conventional iris recognition system by three times and maintain the system's high recognition rate.

  16. 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.

  17. Revealing t-tubules in striated muscle with new optical super-resolution microscopy techniques

    Directory of Open Access Journals (Sweden)

    Isuru D. Jayasinghe

    2014-12-01

    Full Text Available The t-tubular system plays a central role in the synchronisation of calcium signalling and excitation-contraction coupling in most striated muscle cells. Light microscopy has been used for imaging t-tubules for well over 100 years and together with electron microscopy (EM, has revealed the three-dimensional complexities of the t-system topology within cardiomyocytes and skeletal muscle fibres from a range of species. The emerging super-resolution single molecule localisation microscopy (SMLM techniques are offering a near 10-fold improvement over the resolution of conventional fluorescence light microscopy methods, with the ability to spectrally resolve nanometre scale distributions of multiple molecular targets. In conjunction with the next generation of electron microscopy, SMLM has allowed the visualisation and quantification of intricate t-tubule morphologies within large areas of muscle cells at an unprecedented level of detail. In this paper, we review recent advancements in the t-tubule structural biology with the utility of various microscopy techniques. We outline the technical considerations in adapting SMLM to study t-tubules and its potential to further our understanding of the molecular processes that underlie the sub-micron scale structural alterations observed in a range of muscle pathologies.

  18. Super-resolution optical microscopy resolves network morphology of smart colloidal microgels.

    Science.gov (United States)

    Bergmann, Stephan; Wrede, Oliver; Huser, Thomas; Hellweg, Thomas

    2018-02-14

    We present a new method to resolve the network morphology of colloidal particles in an aqueous environment via super-resolution microscopy. By localization of freely diffusing fluorophores inside the particle network we can resolve the three dimensional structure of one species of colloidal particles (thermoresponsive microgels) without altering their chemical composition through copolymerization with fluorescent monomers. Our approach utilizes the interaction of the fluorescent dye rhodamine 6G with the polymer network to achieve an indirect labeling. We calculate the 3D structure from the 2D images and compare the structure to previously published models for the microgel morphology, e.g. the fuzzy sphere model. To describe the differences in the data an extension of this model is suggested. Our method enables the tailor-made fabrication of colloidal particles which are used in various applications, such as paints or cosmetics, and are promising candidates for drug delivery, smart surface coatings, and nanocatalysis. With the precise knowledge of the particle morphology an understanding of the underlying structure-property relationships for various colloidal systems is possible.

  19. Iterative image reconstruction in ECT

    International Nuclear Information System (INIS)

    Chintu Chen; Ordonez, C.E.; Wernick, M.N.; Aarsvold, J.N.; Gunter, D.L.; Wong, W.H.; Kapp, O.H.; Xiaolong Ouyang; Levenson, M.; Metz, C.E.

    1992-01-01

    A series of preliminary studies has been performed in the authors laboratories to explore the use of a priori information in Bayesian image restoration and reconstruction. One piece of a priori information is the fact that intensities of neighboring pixels tend to be similar if they belong to the same region within which similar tissue characteristics are exhibited. this property of local continuity can be modeled by the use of Gibbs priors, as first suggested by German and Geman. In their investigation, they also included line sites between each pair of neighboring pixels in the Gibbs prior and used discrete binary numbers to indicate the absence or presence of boundaries between regions. These two features of the a priori model permit averaging within boundaries of homogeneous regions to alleviate the degradation caused by Poisson noise. with the use of this Gibbs prior in combination with the technique of stochastic relaxation, German and Geman demonstrated that noise levels can be reduced significantly in 2-D image restoration. They have developed a Bayesian method that utilizes a Gibbs prior to describe the spatial correlation of neighboring regions and takes into account the effect of limited spatial resolution as well. The statistical framework of the proposed approach is based on the data augmentation scheme suggested by Tanner and Wong. Briefly outlined here, this Bayesian method is based on Geman and Geman's approach

  20. 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.

  1. Sparse Image Reconstruction in Computed Tomography

    DEFF Research Database (Denmark)

    Jørgensen, Jakob Sauer

    In recent years, increased focus on the potentially harmful effects of x-ray computed tomography (CT) scans, such as radiation-induced cancer, has motivated research on new low-dose imaging techniques. Sparse image reconstruction methods, as studied for instance in the field of compressed sensing...... applications. This thesis takes a systematic approach toward establishing quantitative understanding of conditions for sparse reconstruction to work well in CT. A general framework for analyzing sparse reconstruction methods in CT is introduced and two sets of computational tools are proposed: 1...... contributions to a general set of computational characterization tools. Thus, the thesis contributions help advance sparse reconstruction methods toward routine use in...

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

    Science.gov (United States)

    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.

  3. 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....

  4. Medical image reconstruction. A conceptual tutorial

    International Nuclear Information System (INIS)

    Zeng, Gengsheng Lawrence

    2010-01-01

    ''Medical Image Reconstruction: A Conceptual Tutorial'' introduces the classical and modern image reconstruction technologies, such as two-dimensional (2D) parallel-beam and fan-beam imaging, three-dimensional (3D) parallel ray, parallel plane, and cone-beam imaging. This book presents both analytical and iterative methods of these technologies and their applications in X-ray CT (computed tomography), SPECT (single photon emission computed tomography), PET (positron emission tomography), and MRI (magnetic resonance imaging). Contemporary research results in exact region-of-interest (ROI) reconstruction with truncated projections, Katsevich's cone-beam filtered backprojection algorithm, and reconstruction with highly undersampled data with l 0 -minimization are also included. (orig.)

  5. Algorithms for reconstructing images for industrial applications

    International Nuclear Information System (INIS)

    Lopes, R.T.; Crispim, V.R.

    1986-01-01

    Several algorithms for reconstructing objects from their projections are being studied in our Laboratory, for industrial applications. Such algorithms are useful locating the position and shape of different composition of materials in the object. A Comparative study of two algorithms is made. The two investigated algorithsm are: The MART (Multiplicative - Algebraic Reconstruction Technique) and the Convolution Method. The comparison are carried out from the point view of the quality of the image reconstructed, number of views and cost. (Author) [pt

  6. Parallel Algorithm for Reconstruction of TAC Images

    International Nuclear Information System (INIS)

    Vidal Gimeno, V.

    2012-01-01

    The algebraic reconstruction methods are based on solving a system of linear equations. In a previous study, was used and showed as the PETSc library, was and is a scientific computing tool, which facilitates and enables the optimal use of a computer system in the image reconstruction process.

  7. 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...

  8. Parallel CT image reconstruction based on GPUs

    International Nuclear Information System (INIS)

    Flores, Liubov A.; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo

    2014-01-01

    In X-ray computed tomography (CT) iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions from a small number of projections. However, in practice, these methods are not widely used due to the high computational cost of their implementation. Nowadays technology provides the possibility to reduce effectively this drawback. It is the goal of this work to develop a fast GPU-based algorithm to reconstruct high quality images from under sampled and noisy projection data. - Highlights: • We developed GPU-based iterative algorithm to reconstruct images. • Iterative algorithms are capable to reconstruct images from under sampled set of projections. • The computer cost of the implementation of the developed algorithm is low. • The efficiency of the algorithm increases for the large scale problems

  9. Reconstruction Algorithms in Undersampled AFM Imaging

    DEFF Research Database (Denmark)

    Arildsen, Thomas; Oxvig, Christian Schou; Pedersen, Patrick Steffen

    2016-01-01

    This paper provides a study of spatial undersampling in atomic force microscopy (AFM) imaging followed by different image reconstruction techniques based on sparse approximation as well as interpolation. The main reasons for using undersampling is that it reduces the path length and thereby...... the scanning time as well as the amount of interaction between the AFM probe and the specimen. It can easily be applied on conventional AFM hardware. Due to undersampling, it is then necessary to further process the acquired image in order to reconstruct an approximation of the image. Based on real AFM cell...... images, our simulations reveal that using a simple raster scanning pattern in combination with conventional image interpolation performs very well. Moreover, this combination enables a reduction by a factor 10 of the scanning time while retaining an average reconstruction quality around 36 dB PSNR...

  10. 3D Reconstruction of NMR Images

    Directory of Open Access Journals (Sweden)

    Peter Izak

    2007-01-01

    Full Text Available This paper introduces experiment of 3D reconstruction NMR images scanned from magnetic resonance device. There are described methods which can be used for 3D reconstruction magnetic resonance images in biomedical application. The main idea is based on marching cubes algorithm. For this task was chosen sophistication method by program Vision Assistant, which is a part of program LabVIEW.

  11. Super-resolution structure of DNA significantly differs in buccal cells of controls and Alzheimer's patients.

    Science.gov (United States)

    Garcia, Angeles; Huang, David; Righolt, Amanda; Righolt, Christiaan; Kalaw, Maria Carmela; Mathur, Shubha; McAvoy, Elizabeth; Anderson, James; Luedke, Angela; Itorralba, Justine; Mai, Sabine

    2017-09-01

    The advent of super-resolution microscopy allowed for new insights into cellular and physiological processes of normal and diseased cells. In this study, we report for the first time on the super-resolved DNA structure of buccal cells from patients with Alzheimer's disease (AD) versus age- and gender-matched healthy, non-caregiver controls. In this super-resolution study cohort of 74 participants, buccal cells were collected and their spatial DNA organization in the nucleus examined by 3D Structured Illumination Microscopy (3D-SIM). Quantitation of the super-resolution DNA structure revealed that the nuclear super-resolution DNA structure of individuals with AD significantly differs from that of their controls (p structure of AD significantly differs in mild, moderate, and severe disease with respect to the DNA-containing and DNA-free/poor spaces. We conclude that whole genome remodeling is a feature of buccal cells in AD. © 2016 The Authors. Journal of Cellular Physiology Published by Wiley Periodicals, Inc.

  12. 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...

  13. 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

  14. 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.

  15. 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

  16. Fast parallel algorithm for CT image reconstruction.

    Science.gov (United States)

    Flores, Liubov A; Vidal, Vicent; Mayo, Patricia; Rodenas, Francisco; Verdú, Gumersindo

    2012-01-01

    In X-ray computed tomography (CT) the X rays are used to obtain the projection data needed to generate an image of the inside of an object. The image can be generated with different techniques. Iterative methods are more suitable for the reconstruction of images with high contrast and precision in noisy conditions and from a small number of projections. Their use may be important in portable scanners for their functionality in emergency situations. However, in practice, these methods are not widely used due to the high computational cost of their implementation. In this work we analyze iterative parallel image reconstruction with the Portable Extensive Toolkit for Scientific computation (PETSc).

  17. Photoacoustic image reconstruction via deep learning

    Science.gov (United States)

    Antholzer, Stephan; Haltmeier, Markus; Nuster, Robert; Schwab, Johannes

    2018-02-01

    Applying standard algorithms to sparse data problems in photoacoustic tomography (PAT) yields low-quality images containing severe under-sampling artifacts. To some extent, these artifacts can be reduced by iterative image reconstruction algorithms which allow to include prior knowledge such as smoothness, total variation (TV) or sparsity constraints. These algorithms tend to be time consuming as the forward and adjoint problems have to be solved repeatedly. Further, iterative algorithms have additional drawbacks. For example, the reconstruction quality strongly depends on a-priori model assumptions about the objects to be recovered, which are often not strictly satisfied in practical applications. To overcome these issues, in this paper, we develop direct and efficient reconstruction algorithms based on deep learning. As opposed to iterative algorithms, we apply a convolutional neural network, whose parameters are trained before the reconstruction process based on a set of training data. For actual image reconstruction, a single evaluation of the trained network yields the desired result. Our presented numerical results (using two different network architectures) demonstrate that the proposed deep learning approach reconstructs images with a quality comparable to state of the art iterative reconstruction methods.

  18. MR image reconstruction via guided filter.

    Science.gov (United States)

    Huang, Heyan; Yang, Hang; Wang, Kang

    2018-04-01

    Magnetic resonance imaging (MRI) reconstruction from the smallest possible set of Fourier samples has been a difficult problem in medical imaging field. In our paper, we present a new approach based on a guided filter for efficient MRI recovery algorithm. The guided filter is an edge-preserving smoothing operator and has better behaviors near edges than the bilateral filter. Our reconstruction method is consist of two steps. First, we propose two cost functions which could be computed efficiently and thus obtain two different images. Second, the guided filter is used with these two obtained images for efficient edge-preserving filtering, and one image is used as the guidance image, the other one is used as a filtered image in the guided filter. In our reconstruction algorithm, we can obtain more details by introducing guided filter. We compare our reconstruction algorithm with some competitive MRI reconstruction techniques in terms of PSNR and visual quality. Simulation results are given to show the performance of our new method.

  19. 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.

  20. 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.

  1. Computational acceleration for MR image reconstruction in partially parallel imaging.

    Science.gov (United States)

    Ye, Xiaojing; Chen, Yunmei; Huang, Feng

    2011-05-01

    In this paper, we present a fast numerical algorithm for solving total variation and l(1) (TVL1) based image reconstruction with application in partially parallel magnetic resonance imaging. Our algorithm uses variable splitting method to reduce computational cost. Moreover, the Barzilai-Borwein step size selection method is adopted in our algorithm for much faster convergence. Experimental results on clinical partially parallel imaging data demonstrate that the proposed algorithm requires much fewer iterations and/or less computational cost than recently developed operator splitting and Bregman operator splitting methods, which can deal with a general sensing matrix in reconstruction framework, to get similar or even better quality of reconstructed images.

  2. 3-D image reconstruction in radiology

    International Nuclear Information System (INIS)

    Grangeat, P.

    1999-01-01

    In this course, we present highlights on fully 3-D image reconstruction algorithms used in 3-D X-ray Computed Tomography (3-D-CT) and 3-D Rotational Radiography (3-D-RR). We first consider the case of spiral CT with a one-row detector. Starting from the 2-D fan-beam inversion formula for a circular trajectory, we introduce spiral CT 3-D image reconstruction algorithm using axial interpolation for each transverse slice. In order to improve the X-ray detection efficiency and to speed the acquisition process, the future is to use multi-row detectors associated with small angle cone-beam geometry. The generalization of the 2-D fan-beam image reconstruction algorithm to cone beam defined direct inversion formula referred as Feldkamp's algorithm for a circular trajectory and Wang's algorithm for a spiral trajectory. However, large area detectors does exist such as Radiological Image Intensifiers or in a near future solid state detectors. To get a larger zoom effect, it defines a cone-beam geometry associated with a large aperture angle. For this case, we introduce indirect image reconstruction algorithm by plane re-binning in the Radon domain. We will present some results from a prototype MORPHOMETER device using the RADON reconstruction software. Lastly, we consider the special case of 3-D Rotational Digital Subtraction Angiography with a restricted number of views. We introduce constraint optimization algorithm using quadratic, entropic or half-quadratic constraints. Generalized ART (Algebraic Reconstruction Technique) iterative reconstruction algorithm can be derived from the Bregman algorithm. We present reconstructed vascular trees from a prototype MORPHOMETER device. (author)

  3. A combinational fast algorithm for image reconstruction

    International Nuclear Information System (INIS)

    Wu Zhongquan

    1987-01-01

    A combinational fast algorithm has been developed in order to increase the speed of reconstruction. First, an interpolation method based on B-spline functions is used in image reconstruction. Next, the influence of the boundary conditions assumed here on the interpolation of filtered projections and on the image reconstruction is discussed. It is shown that this boundary condition has almost no influence on the image in the central region of the image space, because the error of interpolation rapidly decreases by a factor of ten in shifting two pixels from the edge toward the center. In addition, a fast algorithm for computing the detecting angle has been used with the mentioned interpolation algorithm, and the cost for detecting angle computaton is reduced by a factor of two. The implementation results show that in the same subjective and objective fidelity, the computational cost for the interpolation using this algorithm is about one-twelfth of the conventional algorithm

  4. Image reconstruction methods in positron tomography

    International Nuclear Information System (INIS)

    Townsend, D.W.; Defrise, M.

    1993-01-01

    In the two decades since the introduction of the X-ray scanner into radiology, medical imaging techniques have become widely established as essential tools in the diagnosis of disease. As a consequence of recent technological and mathematical advances, the non-invasive, three-dimensional imaging of internal organs such as the brain and the heart is now possible, not only for anatomical investigations using X-ray but also for studies which explore the functional status of the body using positron-emitting radioisotopes. This report reviews the historical and physical basis of medical imaging techniques using positron-emitting radioisotopes. Mathematical methods which enable three-dimensional distributions of radioisotopes to be reconstructed from projection data (sinograms) acquired by detectors suitably positioned around the patient are discussed. The extension of conventional two-dimensional tomographic reconstruction algorithms to fully three-dimensional reconstruction is described in detail. (orig.)

  5. Research of ART method in CT image reconstruction

    International Nuclear Information System (INIS)

    Li Zhipeng; Cong Peng; Wu Haifeng

    2005-01-01

    This paper studied Algebraic Reconstruction Technique (ART) in CT image reconstruction. Discussed the ray number influence on image quality. And the adopting of smooth method got high quality CT image. (authors)

  6. Super-resolution biomolecular crystallography with low-resolution data.

    Science.gov (United States)

    Schröder, Gunnar F; Levitt, Michael; Brunger, Axel T

    2010-04-22

    -ray crystallography and cryo-electron microscopy: as optical imaging advances to subnanometre resolution, it can use similar tools.

  7. Fabrication of optical multilayer for two-color phase plate in super-resolution microscope.

    Science.gov (United States)

    Iketaki, Yoshinori; Kitagawa, Katsuichi; Hidaka, Kohjiro; Kato, Naoki; Hirabayashi, Akira; Bokor, Nandor

    2014-07-01

    In super-resolution microscopy based on fluorescence depletion, the two-color phase plate (TPP) is an indispensable optical element, which can independently control the phase shifts for two beams of different color, i.e., the pump and erase beams. By controlling a phase shift of the erase beam through the TPP, the erase beam can be modulated into a doughnut shape, while the pump beam maintains the initial Gaussian shape. To obtain a reliable optical multiplayer (ML) for the TPP, we designed a ML with only two optical layers by performing numerical optimization. The measured phase shifts generated by the fabricated ML using interferometry correspond to the design values. The beam profiles in the focal plane are also consistent with theoretical results. Although the fabricated ML consists of only two optical layers, the ML can provide a suitable phase modulation function for the TPP in a practical super-resolution microscope.

  8. Fabrication of optical multilayer for two-color phase plate in super-resolution microscope

    International Nuclear Information System (INIS)

    Iketaki, Yoshinori; Kitagawa, Katsuichi; Hidaka, Kohjiro; Kato, Naoki; Hirabayashi, Akira; Bokor, Nandor

    2014-01-01

    In super-resolution microscopy based on fluorescence depletion, the two-color phase plate (TPP) is an indispensable optical element, which can independently control the phase shifts for two beams of different color, i.e., the pump and erase beams. By controlling a phase shift of the erase beam through the TPP, the erase beam can be modulated into a doughnut shape, while the pump beam maintains the initial Gaussian shape. To obtain a reliable optical multiplayer (ML) for the TPP, we designed a ML with only two optical layers by performing numerical optimization. The measured phase shifts generated by the fabricated ML using interferometry correspond to the design values. The beam profiles in the focal plane are also consistent with theoretical results. Although the fabricated ML consists of only two optical layers, the ML can provide a suitable phase modulation function for the TPP in a practical super-resolution microscope

  9. Super-resolution microscopy reveals cell wall dynamics and peptidoglycan architecture in ovococcal bacteria.

    Science.gov (United States)

    Wheeler, Richard; Mesnage, Stéphane; Boneca, Ivo G; Hobbs, Jamie K; Foster, Simon J

    2011-12-01

    Cell morphology and viability in Eubacteria is dictated by the architecture of peptidoglycan, the major and essential structural component of the cell wall. Although the biochemical composition of peptidoglycan is well understood, how the peptidoglycan architecture can accommodate the dynamics of growth and division while maintaining cell shape remains largely unknown. Here, we elucidate the peptidoglycan architecture and dynamics of bacteria with ovoid cell shape (ovococci), which includes a number of important pathogens, by combining biochemical analyses with atomic force and super-resolution microscopies. Atomic force microscopy analysis showed preferential orientation of the peptidoglycan network parallel to the short axis of the cell, with distinct architectural features associated with septal and peripheral wall synthesis. Super-resolution three-dimensional structured illumination fluorescence microscopy was applied for the first time in bacteria to unravel the dynamics of peptidoglycan assembly in ovococci. The ovococci have a unique peptidoglycan architecture and growth mode not observed in other model organisms. © 2011 Blackwell Publishing Ltd.

  10. Graphene-enabled electron microscopy and correlated super-resolution microscopy of wet cells.

    Science.gov (United States)

    Wojcik, Michal; Hauser, Margaret; Li, Wan; Moon, Seonah; Xu, Ke

    2015-06-11

    The application of electron microscopy to hydrated biological samples has been limited by high-vacuum operating conditions. Traditional methods utilize harsh and laborious sample dehydration procedures, often leading to structural artefacts and creating difficulties for correlating results with high-resolution fluorescence microscopy. Here, we utilize graphene, a single-atom-thick carbon meshwork, as the thinnest possible impermeable and conductive membrane to protect animal cells from vacuum, thus enabling high-resolution electron microscopy of wet and untreated whole cells with exceptional ease. Our approach further allows for facile correlative super-resolution and electron microscopy of wet cells directly on the culturing substrate. In particular, individual cytoskeletal actin filaments are resolved in hydrated samples through electron microscopy and well correlated with super-resolution results.

  11. Image reconstruction under non-Gaussian noise

    DEFF Research Database (Denmark)

    Sciacchitano, Federica

    During acquisition and transmission, images are often blurred and corrupted by noise. One of the fundamental tasks of image processing is to reconstruct the clean image from a degraded version. The process of recovering the original image from the data is an example of inverse problem. Due...... to the ill-posedness of the problem, the simple inversion of the degradation model does not give any good reconstructions. Therefore, to deal with the ill-posedness it is necessary to use some prior information on the solution or the model and the Bayesian approach. Additive Gaussian noise has been......D thesis intends to solve some of the many open questions for image restoration under non-Gaussian noise. The two main kinds of noise studied in this PhD project are the impulse noise and the Cauchy noise. Impulse noise is due to for instance the malfunctioning pixel elements in the camera sensors, errors...

  12. 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.

  13. A simple model explaining super-resolution in absolute optical instruments

    Science.gov (United States)

    Leonhardt, Ulf; Sahebdivan, Sahar; Kogan, Alex; Tyc, Tomáš

    2015-05-01

    We develop a simple, one-dimensional model for super-resolution in absolute optical instruments that is able to describe the interplay between sources and detectors. Our model explains the subwavelength sensitivity of a point detector to a point source reported in previous computer simulations and experiments (Miñano 2011 New J. Phys.13 125009; Miñano 2014 New J. Phys.16 033015).

  14. Accelerated Compressed Sensing Based CT Image Reconstruction.

    Science.gov (United States)

    Hashemi, SayedMasoud; Beheshti, Soosan; Gill, Patrick R; Paul, Narinder S; Cobbold, Richard S C

    2015-01-01

    In X-ray computed tomography (CT) an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS) enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  15. Accelerated Compressed Sensing Based CT Image Reconstruction

    Directory of Open Access Journals (Sweden)

    SayedMasoud Hashemi

    2015-01-01

    Full Text Available In X-ray computed tomography (CT an important objective is to reduce the radiation dose without significantly degrading the image quality. Compressed sensing (CS enables the radiation dose to be reduced by producing diagnostic images from a limited number of projections. However, conventional CS-based algorithms are computationally intensive and time-consuming. We propose a new algorithm that accelerates the CS-based reconstruction by using a fast pseudopolar Fourier based Radon transform and rebinning the diverging fan beams to parallel beams. The reconstruction process is analyzed using a maximum-a-posterior approach, which is transformed into a weighted CS problem. The weights involved in the proposed model are calculated based on the statistical characteristics of the reconstruction process, which is formulated in terms of the measurement noise and rebinning interpolation error. Therefore, the proposed method not only accelerates the reconstruction, but also removes the rebinning and interpolation errors. Simulation results are shown for phantoms and a patient. For example, a 512 × 512 Shepp-Logan phantom when reconstructed from 128 rebinned projections using a conventional CS method had 10% error, whereas with the proposed method the reconstruction error was less than 1%. Moreover, computation times of less than 30 sec were obtained using a standard desktop computer without numerical optimization.

  16. A Novel Method to Implement the Matrix Pencil Super Resolution Algorithm for Indoor Positioning

    Directory of Open Access Journals (Sweden)

    Tariq Jamil Saifullah Khanzada

    2011-10-01

    Full Text Available This article highlights the estimation of the results for the algorithms implemented in order to estimate the delays and distances for the indoor positioning system. The data sets for the transmitted and received signals are captured at a typical outdoor and indoor area. The estimation super resolution algorithms are applied. Different state of art and super resolution techniques based algorithms are applied to avail the optimal estimates of the delays and distances between the transmitted and received signals and a novel method for matrix pencil algorithm is devised. The algorithms perform variably at different scenarios of transmitted and received positions. Two scenarios are experienced, for the single antenna scenario the super resolution techniques like ESPRIT (Estimation of Signal Parameters via Rotational Invariance Technique and theMatrix Pencil algorithms give optimal performance compared to the conventional techniques. In two antenna scenario RootMUSIC and Matrix Pencil algorithm performed better than other algorithms for the distance estimation, however, the accuracy of all the algorithms is worst than the single antenna scenario. In all cases our devised Matrix Pencil algorithm achieved the best estimation results.

  17. An introduction to optical super-resolution microscopy for the adventurous biologist

    Science.gov (United States)

    Vangindertael, J.; Camacho, R.; Sempels, W.; Mizuno, H.; Dedecker, P.; Janssen, K. P. F.

    2018-04-01

    Ever since the inception of light microscopy, the laws of physics have seemingly thwarted every attempt to visualize the processes of life at its most fundamental, sub-cellular, level. The diffraction limit has restricted our view to length scales well above 250 nm and in doing so, severely compromised our ability to gain true insights into many biological systems. Fortunately, continuous advancements in optics, electronics and mathematics have since provided the means to once again make physics work to our advantage. Even though some of the fundamental concepts enabling super-resolution light microscopy have been known for quite some time, practically feasible implementations have long remained elusive. It should therefore not come as a surprise that the 2014 Nobel Prize in Chemistry was awarded to the scientists who, each in their own way, contributed to transforming super-resolution microscopy from a technological tour de force to a staple of the biologist’s toolkit. By overcoming the diffraction barrier, light microscopy could once again be established as an indispensable tool in an age where the importance of understanding life at the molecular level cannot be overstated. This review strives to provide the aspiring life science researcher with an introduction to optical microscopy, starting from the fundamental concepts governing compound and fluorescent confocal microscopy to the current state-of-the-art of super-resolution microscopy techniques and their applications.

  18. On an image reconstruction method for ECT

    Science.gov (United States)

    Sasamoto, Akira; Suzuki, Takayuki; Nishimura, Yoshihiro

    2007-04-01

    An image by Eddy Current Testing(ECT) is a blurred image to original flaw shape. In order to reconstruct fine flaw image, a new image reconstruction method has been proposed. This method is based on an assumption that a very simple relationship between measured data and source were described by a convolution of response function and flaw shape. This assumption leads to a simple inverse analysis method with deconvolution.In this method, Point Spread Function (PSF) and Line Spread Function(LSF) play a key role in deconvolution processing. This study proposes a simple data processing to determine PSF and LSF from ECT data of machined hole and line flaw. In order to verify its validity, ECT data for SUS316 plate(200x200x10mm) with artificial machined hole and notch flaw had been acquired by differential coil type sensors(produced by ZETEC Inc). Those data were analyzed by the proposed method. The proposed method restored sharp discrete multiple hole image from interfered data by multiple holes. Also the estimated width of line flaw has been much improved compared with original experimental data. Although proposed inverse analysis strategy is simple and easy to implement, its validity to holes and line flaw have been shown by many results that much finer image than original image have been reconstructed.

  19. 3D EIT image reconstruction with GREIT.

    Science.gov (United States)

    Grychtol, Bartłomiej; Müller, Beat; Adler, Andy

    2016-06-01

    Most applications of thoracic EIT use a single plane of electrodes on the chest from which a transverse image 'slice' is calculated. However, interpretation of EIT images is made difficult by the large region above and below the electrode plane to which EIT is sensitive. Volumetric EIT images using two (or more) electrode planes should help compensate, but are little used currently. The Graz consensus reconstruction algorithm for EIT (GREIT) has become popular in lung EIT. One shortcoming of the original formulation of GREIT is its restriction to reconstruction onto a 2D planar image. We present an extension of the GREIT algorithm to 3D and develop open-source tools to evaluate its performance as a function of the choice of stimulation and measurement pattern. Results show 3D GREIT using two electrode layers has significantly more uniform sensitivity profiles through the chest region. Overall, the advantages of 3D EIT are compelling.

  20. Reconstructing building mass models from UAV images

    KAUST Repository

    Li, Minglei; Nan, Liangliang; Smith, Neil; Wonka, Peter

    2015-01-01

    We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first

  1. Connections model for tomographic images reconstruction

    International Nuclear Information System (INIS)

    Rodrigues, R.G.S.; Pela, C.A.; Roque, S.F. A.C.

    1998-01-01

    This paper shows an artificial neural network with an adequately topology for tomographic image reconstruction. The associated error function is derived and the learning algorithm is make. The simulated results are presented and demonstrate the existence of a generalized solution for nets with linear activation function. (Author)

  2. Non-Cartesian parallel imaging reconstruction.

    Science.gov (United States)

    Wright, Katherine L; Hamilton, Jesse I; Griswold, Mark A; Gulani, Vikas; Seiberlich, Nicole

    2014-11-01

    Non-Cartesian parallel imaging has played an important role in reducing data acquisition time in MRI. The use of non-Cartesian trajectories can enable more efficient coverage of k-space, which can be leveraged to reduce scan times. These trajectories can be undersampled to achieve even faster scan times, but the resulting images may contain aliasing artifacts. Just as Cartesian parallel imaging can be used to reconstruct images from undersampled Cartesian data, non-Cartesian parallel imaging methods can mitigate aliasing artifacts by using additional spatial encoding information in the form of the nonhomogeneous sensitivities of multi-coil phased arrays. This review will begin with an overview of non-Cartesian k-space trajectories and their sampling properties, followed by an in-depth discussion of several selected non-Cartesian parallel imaging algorithms. Three representative non-Cartesian parallel imaging methods will be described, including Conjugate Gradient SENSE (CG SENSE), non-Cartesian generalized autocalibrating partially parallel acquisition (GRAPPA), and Iterative Self-Consistent Parallel Imaging Reconstruction (SPIRiT). After a discussion of these three techniques, several potential promising clinical applications of non-Cartesian parallel imaging will be covered. © 2014 Wiley Periodicals, Inc.

  3. 3-D Reconstruction From Satellite Images

    DEFF Research Database (Denmark)

    Denver, Troelz

    1999-01-01

    of planetary surfaces, but other purposes is considered as well. The system performance is measured with respect to the precision and the time consumption.The reconstruction process is divided into four major areas: Acquisition, calibration, matching/reconstruction and presentation. Each of these areas...... are treated individually. A detailed treatment of various lens distortions is required, in order to correct for these problems. This subject is included in the acquisition part. In the calibration part, the perspective distortion is removed from the images. Most attention has been paid to the matching problem...

  4. Quantum phase amplification for temporal pulse shaping and super-resolution in remote sensing

    Science.gov (United States)

    Yin, Yanchun

    QPA in the spatial domain has also been studied as a method to enhance the spatial resolution of imaging systems. A detailed model has been developed for achieving both super-resolution and detection of phase-amplified light. The imaging resolution problem considered here is treated as a binary hypotheses testing problem. Resolution enhancement is achieved by magnification of the angular separation of two targets in the sub-Rayleigh regime. The detection model includes optimization of detector segmentation, detector noise, and detection in both the spatial and the spatial frequency domain, which provide strategies for the optimization of the signal-to-noise ratio that take advantage of both the change of the field distribution and the change of energy of the signal in the QPA process. Proof-of-principle experiments have been conducted in the spatial domain. For the first time, beam angular amplification has been demonstrated, and the experimental result is in good agreement with simulations. The experimental demonstration has been achieved by observing the correlation of amplitude and angular phase in the phase-sensitive three-wave mixing process using ultrashort laser pulses and utilizing a type I three-wave mixing process. Several diagnostics have been developed and employed in the experimental measurements, including the near-field diagnostic, the far-field diagnostic, and the interferometry diagnostic. They have all been used to confirm the existence and study the properties of the QPA process on a shot-to-shot basis. Specifically, amplitude was measured in the near-field diagnostic, while the angular phase was indirectly measured in the far-field diagnostic by determining the position of the beam centroid. Interferometric measurements have been found to be of insufficient accuracy for this measurement in the way they were implemented. The demonstration of beam angular amplification by use of QPA lays the foundation for future integrated demonstration of imaging

  5. Reconstructing building mass models from UAV images

    KAUST Repository

    Li, Minglei

    2015-07-26

    We present an automatic reconstruction pipeline for large scale urban scenes from aerial images captured by a camera mounted on an unmanned aerial vehicle. Using state-of-the-art Structure from Motion and Multi-View Stereo algorithms, we first generate a dense point cloud from the aerial images. Based on the statistical analysis of the footprint grid of the buildings, the point cloud is classified into different categories (i.e., buildings, ground, trees, and others). Roof structures are extracted for each individual building using Markov random field optimization. Then, a contour refinement algorithm based on pivot point detection is utilized to refine the contour of patches. Finally, polygonal mesh models are extracted from the refined contours. Experiments on various scenes as well as comparisons with state-of-the-art reconstruction methods demonstrate the effectiveness and robustness of the proposed method.

  6. Super-resolution optical microscopy for studying membrane structure and dynamics.

    Science.gov (United States)

    Sezgin, Erdinc

    2017-07-12

    Investigation of cell membrane structure and dynamics requires high spatial and temporal resolution. The spatial resolution of conventional light microscopy is limited due to the diffraction of light. However, recent developments in microscopy enabled us to access the nano-scale regime spatially, thus to elucidate the nanoscopic structures in the cellular membranes. In this review, we will explain the resolution limit, address the working principles of the most commonly used super-resolution microscopy techniques and summarise their recent applications in the biomembrane field.

  7. Homotopy Based Reconstruction from Acoustic Images

    DEFF Research Database (Denmark)

    Sharma, Ojaswa

    of the inherent arrangement. The problem of reconstruction from arbitrary cross sections is a generic problem and is also shown to be solved here using the mathematical tool of continuous deformations. As part of a complete processing, segmentation using level set methods is explored for acoustic images and fast...... GPU (Graphics Processing Unit) based methods are suggested for a streaming computation on large volumes of data. Validation of results for acoustic images is not straightforward due to unavailability of ground truth. Accuracy figures for the suggested methods are provided using phantom object...

  8. Image reconstruction of dynamic infrared single-pixel imaging system

    Science.gov (United States)

    Tong, Qi; Jiang, Yilin; Wang, Haiyan; Guo, Limin

    2018-03-01

    Single-pixel imaging technique has recently received much attention. Most of the current single-pixel imaging is aimed at relatively static targets or the imaging system is fixed, which is limited by the number of measurements received through the single detector. In this paper, we proposed a novel dynamic compressive imaging method to solve the imaging problem, where exists imaging system motion behavior, for the infrared (IR) rosette scanning system. The relationship between adjacent target images and scene is analyzed under different system movement scenarios. These relationships are used to build dynamic compressive imaging models. Simulation results demonstrate that the proposed method can improve the reconstruction quality of IR image and enhance the contrast between the target and the background in the presence of system movement.

  9. Spectrally Resolved and Functional Super-resolution Microscopy via Ultrahigh-Throughput Single-Molecule Spectroscopy.

    Science.gov (United States)

    Yan, Rui; Moon, Seonah; Kenny, Samuel J; Xu, Ke

    2018-03-20

    As an elegant integration of the spatial and temporal dimensions of single-molecule fluorescence, single-molecule localization microscopy (SMLM) overcomes the diffraction-limited resolution barrier of optical microscopy by localizing single molecules that stochastically switch between fluorescent and dark states over time. While this type of super-resolution microscopy (SRM) technique readily achieves remarkable spatial resolutions of ∼10 nm, it typically provides no spectral information. Meanwhile, current scanning-based single-location approaches for mapping the positions and spectra of single molecules are limited by low throughput and are difficult to apply to densely labeled (bio)samples. In this Account, we summarize the rationale, design, and results of our recent efforts toward the integration of the spectral dimension of single-molecule fluorescence with SMLM to achieve spectrally resolved SMLM (SR-SMLM) and functional SRM ( f-SRM). By developing a wide-field scheme for spectral measurement and implementing single-molecule fluorescence on-off switching typical of SMLM, we first showed that in densely labeled (bio)samples it is possible to record the fluorescence spectra and positions of millions of single molecules synchronously within minutes, giving rise to ultrahigh-throughput single-molecule spectroscopy and SR-SMLM. This allowed us to first show statistically that for many dyes, single molecules of the same species exhibit near identical emission in fixed cells. This narrow distribution of emission wavelengths, which contrasts markedly with previous results at solid surfaces, allowed us to unambiguously identify single molecules of spectrally similar dyes. Crosstalk-free, multiplexed SRM was thus achieved for four dyes that were merely 10 nm apart in emission spectrum, with the three-dimensional SRM images of all four dyes being automatically aligned within one image channel. The ability to incorporate single-molecule fluorescence measurement with

  10. Image-reconstruction methods in positron tomography

    CERN Document Server

    Townsend, David W; CERN. Geneva

    1993-01-01

    Physics and mathematics for medical imaging In the two decades since the introduction of the X-ray scanner into radiology, medical imaging techniques have become widely established as essential tools in the diagnosis of disease. As a consequence of recent technological and mathematical advances, the non-invasive, three-dimensional imaging of internal organs such as the brain and the heart is now possible, not only for anatomical investigations using X-rays but also for studies which explore the functional status of the body using positron-emitting radioisotopes and nuclear magnetic resonance. Mathematical methods which enable three-dimentional distributions to be reconstructed from projection data acquired by radiation detectors suitably positioned around the patient will be described in detail. The lectures will trace the development of medical imaging from simpleradiographs to the present-day non-invasive measurement of in vivo boichemistry. Powerful techniques to correlate anatomy and function that are cur...

  11. Three-dimensional reconstruction of CT images

    Energy Technology Data Exchange (ETDEWEB)

    Watanabe, Toshiaki; Kattoh, Keiichi; Kawakami, Genichiroh; Igami, Isao; Mariya, Yasushi; Nakamura, Yasuhiko; Saitoh, Yohko; Tamura, Koreroku; Shinozaki, Tatsuyo

    1986-09-01

    Computed tomography (CT) has the ability to provide sensitive visualization of organs and lesions. Owing to the nature of CT to be transaxial images, a structure which is greater than a certain size appears as several serial CT images. Consequently each observer must reconstruct those images into a three-dimensional (3-D) form mentally. It has been supposed to be of great use if such a 3-D form can be described as a definite figure. A new computer program has been developed which can produce 3-D figures from the profiles of organs and lesions on CT images using spline curves. The figures obtained through this method are regarded to have practical applications.

  12. Simulated annealing image reconstruction for positron emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Sundermann, E; Lemahieu, I; Desmedt, P [Department of Electronics and Information Systems, University of Ghent, St. Pietersnieuwstraat 41, B-9000 Ghent, Belgium (Belgium)

    1994-12-31

    In Positron Emission Tomography (PET) images have to be reconstructed from moisy projection data. The noise on the PET data can be modeled by a Poison distribution. In this paper, we present the results of using the simulated annealing technique to reconstruct PET images. Various parameter settings of the simulated annealing algorithm are discussed and optimized. The reconstructed images are of good quality and high contrast, in comparison to other reconstruction techniques. (authors). 11 refs., 2 figs.

  13. Simulated annealing image reconstruction for positron emission tomography

    International Nuclear Information System (INIS)

    Sundermann, E.; Lemahieu, I.; Desmedt, P.

    1994-01-01

    In Positron Emission Tomography (PET) images have to be reconstructed from moisy projection data. The noise on the PET data can be modeled by a Poison distribution. In this paper, we present the results of using the simulated annealing technique to reconstruct PET images. Various parameter settings of the simulated annealing algorithm are discussed and optimized. The reconstructed images are of good quality and high contrast, in comparison to other reconstruction techniques. (authors)

  14. Fluorescent dyes with large Stokes shifts for super-resolution optical microscopy of biological objects: a review

    International Nuclear Information System (INIS)

    Sednev, Maksim V; Belov, Vladimir N; Hell, Stefan W

    2015-01-01

    The review deals with commercially available organic dyes possessing large Stokes shifts and their applications as fluorescent labels in optical microscopy based on stimulated emission depletion (STED). STED microscopy breaks Abbe’s diffraction barrier and provides optical resolution beyond the diffraction limit. STED microscopy is non-invasive and requires photostable fluorescent markers attached to biomolecules or other objects of interest. Up to now, in most biology-related STED experiments, bright and photoresistant dyes with small Stokes shifts of 20–40 nm were used. The rapid progress in STED microscopy showed that organic fluorophores possessing large Stokes shifts are indispensable in multi-color super-resolution techniques. The ultimate result of the imaging relies on the optimal combination of a dye, the bio-conjugation procedure and the performance of the optical microscope. Modern bioconjugation methods, basics of STED microscopy, as well as structures and spectral properties of the presently available fluorescent markers are reviewed and discussed. In particular, the spectral properties of the commercial dyes are tabulated and correlated with the available depletion wavelengths found in STED microscopes produced by LEICA Microsytems, Abberior Instruments and Picoquant GmbH. (topical review)

  15. Super-resolution by elliptical bubble formation with PtOx and AgInSbTe layers

    International Nuclear Information System (INIS)

    Kim, Jooho; Hwang, Inoh; Yoon, Duseop; Park, Insik; Shin, Dongho; Kikukawa, Takashi; Shima, Takayuki; Tominaga, Junji

    2003-01-01

    The recording and retrieval of signals below 100 nm mark length were attempted with elliptical bubble-type super-resolution technology with platinum oxide (PtO x ) and ductile AgInSbTe layers, using the same optical system as that of a digital versatile disk (a 635 nm wavelength red laser system). The carrier-to-noise ratio (CNR) of over 47 dB for 100 nm mark length signals (over 43 dB for 80 nm mark length signals) was obtained, which can be considered as a commercially acceptable level of CNR. The recording mechanism of the sample disk was shown through the transmission electron microscopy cross-section image observation to be by rigid elliptical bubble formation at the PtO x layer located between the AgInSbTe layers. The results of this report represent the potential for a much higher-density storage using the red laser system and a subterabyte optical storage using the blue laser system

  16. Light-Induced Fluorescence Modulation of Quantum Dot-Crystal Violet Conjugates: Stochastic Off-On-Off Cycles for Multicolor Patterning and Super-Resolution.

    Science.gov (United States)

    Jung, Sungwook; Park, Joonhyuck; Bang, Jiwon; Kim, Jae-Yeol; Kim, Cheolhee; Jeon, Yongmoon; Lee, Seung Hwan; Jin, Ho; Choi, Sukyung; Kim, Bomi; Lee, Woo Jin; Pack, Chan-Gi; Lee, Jong-Bong; Lee, Nam Ki; Kim, Sungjee

    2017-06-07

    Photoswitching or modulation of quantum dots (QDs) can be promising for many fields that include display, memory, and super-resolution imaging. However, such modulations have mostly relied on photomodulations of conjugated molecules in QD vicinity, which typically require high power of high energy photons at UV. We report a visible light-induced facile modulation route for QD-dye conjugates. QD crystal violets conjugates (QD-CVs) were prepared and the crystal violet (CV) molecules on QD quenched the fluorescence efficiently. The fluorescence of QD-CVs showed a single cycle of emission burst as they go through three stages of (i) initially quenched "off" to (ii) photoactivated "on" as the result of chemical change of CVs induced by photoelectrons from QD and (iii) back to photodarkened "off" by radical-associated reactions. Multicolor on-demand photopatterning was demonstrated using QD-CV solid films. QD-CVs were introduced into cells, and excitation with visible light yielded photomodulation from "off" to "on" and "off" by nearly ten fold. Individual photoluminescence dynamics of QD-CVs was investigated using fluorescence correlation spectroscopy and single QD emission analysis, which revealed temporally stochastic photoactivations and photodarkenings. Exploiting the stochastic fluorescence burst of QD-CVs, simultaneous multicolor super-resolution localizations were demonstrated.

  17. Image reconstruction. Application to transverse axial tomography

    International Nuclear Information System (INIS)

    Aubry, Florent.

    1977-09-01

    A method of computerized tridimensional image reconstruction from their projection, especially in the computerized transverse axial tomography is suggested. First, the different techniques actually developped and presented in the literature are analyzed. Then, the equipment used is briefly described. The reconstruction algorithm developped is presented. This algorithm is based on the convolution method, well adapted to the real conditions of exploitation. It is an extension of SHEPP and LOGAN's algorithm. A correction of the self absorption and of the detector's response is proposed. Finally, the first results obtained which are satisfactory are given. The simplicity of the method which does not need a too long computation time makes possible the implementation of the algorithm on a mini-computer [fr

  18. Reconstruction of Novel Viewpoint Image Using GRNN

    Institute of Scientific and Technical Information of China (English)

    李战委; 孙济洲; 张志强

    2003-01-01

    A neural-statistical approach to the reconstruction of novel viewpoint image using general regression neural networks(GRNN) is presented. Different color value will be obtained by watching the same surface point of an object from different viewpoints due to specular reflection, and the difference is related to the position of viewpoint. The relationship between the position of viewpoint and the color of image is non-linear, neural network is introduced to make curve fitting, where the inputs of neural network are only a few calibrated images with obvious specular reflection. By training the neural network, network model is obtained. By inputing an arbitrary virtual viewpoint to the model, the image of the virtual viewpoint can be computed. By using the method presented here, novel viewpoint image with photo-realistic property can be obtained, especially images with obvious specular reflection can accurately be generated. The method is an image-based rendering method, geometric model of the scene and position of lighting are not needed.

  19. Hypotonic activation of the myo-inositol transporter SLC5A3 in HEK293 cells probed by cell volumetry, confocal and super-resolution microscopy.

    Directory of Open Access Journals (Sweden)

    Joseph Andronic

    Full Text Available Swelling-activated pathways for myo-inositol, one of the most abundant organic osmolytes in mammalian cells, have not yet been identified. The present study explores the SLC5A3 protein as a possible transporter of myo-inositol in hyponically swollen HEK293 cells. To address this issue, we examined the relationship between the hypotonicity-induced changes in plasma membrane permeability to myo-inositol P ino [m/s] and expression/localization of SLC5A3. P ino values were determined by cell volumetry over a wide tonicity range (100-275 mOsm in myo-inositol-substituted solutions. While being negligible under mild hypotonicity (200-275 mOsm, P ino grew rapidly at osmolalities below 200 mOsm to reach a maximum of ∼ 3 nm/s at 100-125 mOsm, as indicated by fast cell swelling due to myo-inositol influx. The increase in P ino resulted most likely from the hypotonicity-mediated incorporation of cytosolic SLC5A3 into the plasma membrane, as revealed by confocal fluorescence microscopy of cells expressing EGFP-tagged SLC5A3 and super-resolution imaging of immunostained SLC5A3 by direct stochastic optical reconstruction microscopy (dSTORM. dSTORM in hypotonic cells revealed a surface density of membrane-associated SLC5A3 proteins of 200-2000 localizations/μm2. Assuming SLC5A3 to be the major path for myo-inositol, a turnover rate of 80-800 myo-inositol molecules per second for a single transporter protein was estimated from combined volumetric and dSTORM data. Hypotonic stress also caused a significant upregulation of SLC5A3 gene expression as detected by semiquantitative RT-PCR and Western blot analysis. In summary, our data provide first evidence for swelling-mediated activation of SLC5A3 thus suggesting a functional role of this transporter in hypotonic volume regulation of mammalian cells.

  20. 2D Unitary ESPRIT Based Super-Resolution Channel Estimation for Millimeter-Wave Massive MIMO with Hybrid Precoding

    KAUST Repository

    Liao, Anwen

    2017-11-01

    Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) with hybrid precoding is a promising technique for the future 5G wireless communications. Due to a large number of antennas but a much smaller number of radio frequency (RF) chains, estimating the high-dimensional mmWave massive MIMO channel will bring the large pilot overhead. To overcome this challenge, this paper proposes a super-resolution channel estimation scheme based on two-dimensional (2D) unitary ESPRIT algorithm. By exploiting the angular sparsity of mmWave channels, the continuously distributed angle of arrivals/departures (AoAs/AoDs) can be jointly estimated with high accuracy. Specifically, by designing the uplink training signals at both base station (BS) and mobile station (MS), we first use low pilot overhead to estimate a low-dimensional effective channel, which has the same shift-invariance of array response as the high-dimensional mmWave MIMO channel to be estimated. From the low-dimensional effective channel, the superresolution estimates of AoAs and AoDs can be jointly obtained by exploiting the 2D unitary ESPRIT channel estimation algorithm. Furthermore, the associated path gains can be acquired based on the least squares (LS) criterion. Finally, we can reconstruct the high-dimensional mmWave MIMO channel according to the obtained AoAs, AoDs, and path gains. Simulation results have confirmed that the proposed scheme is superior to conventional schemes with a much lower pilot overhead.

  1. 2D Unitary ESPRIT Based Super-Resolution Channel Estimation for Millimeter-Wave Massive MIMO with Hybrid Precoding

    KAUST Repository

    Liao, Anwen; Gao, Zhen; Wu, Yongpeng; Wang, Hua; Alouini, Mohamed-Slim

    2017-01-01

    Millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) with hybrid precoding is a promising technique for the future 5G wireless communications. Due to a large number of antennas but a much smaller number of radio frequency (RF) chains, estimating the high-dimensional mmWave massive MIMO channel will bring the large pilot overhead. To overcome this challenge, this paper proposes a super-resolution channel estimation scheme based on two-dimensional (2D) unitary ESPRIT algorithm. By exploiting the angular sparsity of mmWave channels, the continuously distributed angle of arrivals/departures (AoAs/AoDs) can be jointly estimated with high accuracy. Specifically, by designing the uplink training signals at both base station (BS) and mobile station (MS), we first use low pilot overhead to estimate a low-dimensional effective channel, which has the same shift-invariance of array response as the high-dimensional mmWave MIMO channel to be estimated. From the low-dimensional effective channel, the superresolution estimates of AoAs and AoDs can be jointly obtained by exploiting the 2D unitary ESPRIT channel estimation algorithm. Furthermore, the associated path gains can be acquired based on the least squares (LS) criterion. Finally, we can reconstruct the high-dimensional mmWave MIMO channel according to the obtained AoAs, AoDs, and path gains. Simulation results have confirmed that the proposed scheme is superior to conventional schemes with a much lower pilot overhead.

  2. Prior image constrained image reconstruction in emerging computed tomography applications

    Science.gov (United States)

    Brunner, Stephen T.

    Advances have been made in computed tomography (CT), especially in the past five years, by incorporating prior images into the image reconstruction process. In this dissertation, we investigate prior image constrained image reconstruction in three emerging CT applications: dual-energy CT, multi-energy photon-counting CT, and cone-beam CT in image-guided radiation therapy. First, we investigate the application of Prior Image Constrained Compressed Sensing (PICCS) in dual-energy CT, which has been called "one of the hottest research areas in CT." Phantom and animal studies are conducted using a state-of-the-art 64-slice GE Discovery 750 HD CT scanner to investigate the extent to which PICCS can enable radiation dose reduction in material density and virtual monochromatic imaging. Second, we extend the application of PICCS from dual-energy CT to multi-energy photon-counting CT, which has been called "one of the 12 topics in CT to be critical in the next decade." Numerical simulations are conducted to generate multiple energy bin images for a photon-counting CT acquisition and to investigate the extent to which PICCS can enable radiation dose efficiency improvement. Third, we investigate the performance of a newly proposed prior image constrained scatter correction technique to correct scatter-induced shading artifacts in cone-beam CT, which, when used in image-guided radiation therapy procedures, can assist in patient localization, and potentially, dose verification and adaptive radiation therapy. Phantom studies are conducted using a Varian 2100 EX system with an on-board imager to investigate the extent to which the prior image constrained scatter correction technique can mitigate scatter-induced shading artifacts in cone-beam CT. Results show that these prior image constrained image reconstruction techniques can reduce radiation dose in dual-energy CT by 50% in phantom and animal studies in material density and virtual monochromatic imaging, can lead to radiation

  3. Hyperspectral image processing

    CERN Document Server

    Wang, Liguo

    2016-01-01

    Based on the authors’ research, this book introduces the main processing techniques in hyperspectral imaging. In this context, SVM-based classification, distance comparison-based endmember extraction, SVM-based spectral unmixing, spatial attraction model-based sub-pixel mapping, and MAP/POCS-based super-resolution reconstruction are discussed in depth. Readers will gain a comprehensive understanding of these cutting-edge hyperspectral imaging techniques. Researchers and graduate students in fields such as remote sensing, surveying and mapping, geosciences and information systems will benefit from this valuable resource.

  4. Optimized Quasi-Interpolators for Image Reconstruction.

    Science.gov (United States)

    Sacht, Leonardo; Nehab, Diego

    2015-12-01

    We propose new quasi-interpolators for the continuous reconstruction of sampled images, combining a narrowly supported piecewise-polynomial kernel and an efficient digital filter. In other words, our quasi-interpolators fit within the generalized sampling framework and are straightforward to use. We go against standard practice and optimize for approximation quality over the entire Nyquist range, rather than focusing exclusively on the asymptotic behavior as the sample spacing goes to zero. In contrast to previous work, we jointly optimize with respect to all degrees of freedom available in both the kernel and the digital filter. We consider linear, quadratic, and cubic schemes, offering different tradeoffs between quality and computational cost. Experiments with compounded rotations and translations over a range of input images confirm that, due to the additional degrees of freedom and the more realistic objective function, our new quasi-interpolators perform better than the state of the art, at a similar computational cost.

  5. Managing the Introduction of Super-Resolution Microscopy into a Core Facility.

    Science.gov (United States)

    Kamykowski, Jeffrey A; Storrie, Brian

    2017-01-01

    Super resolution techniques place the resolution of fluorescence microscopy closer to the size of the underlying cell structure or molecular machine being studied. Structured illumination techniques will give users a set of tools that are close to their past experience and relatively simple and quick to learn. The present dyes can be used. Resolution approaching 100 nm XY can be achieved. In contrast, stochastic methods such as PALM/STORM typically require the choice of new dyes and a much greater learning curve to master the technology and calculations. However, a further fivefold resolution improvement is possible. Stimulated depletion techniques such as STED offer a third set of approaches that will again require the use of new dyes. All these approaches require substantial investment in new equipment and in user training. There is no free lunch in the search for better resolution.

  6. Image reconstruction design of industrial CT instrument for teaching

    International Nuclear Information System (INIS)

    Zou Yongning; Cai Yufang

    2009-01-01

    Industrial CT instrument for teaching is applied to teaching and study in field of physics and radiology major, image reconstruction is an important part of software on CT instrument. The paper expatiate on CT physical theory and first generation CT reconstruction algorithm, describe scan process of industrial CT instrument for teaching; analyze image artifact as result of displacement of rotation center, implement method of center displacement correcting, design and complete image reconstruction software, application shows that reconstructed image is very clear and qualitatively high. (authors)

  7. Sparse BLIP: BLind Iterative Parallel imaging reconstruction using compressed sensing.

    Science.gov (United States)

    She, Huajun; Chen, Rong-Rong; Liang, Dong; DiBella, Edward V R; Ying, Leslie

    2014-02-01

    To develop a sensitivity-based parallel imaging reconstruction method to reconstruct iteratively both the coil sensitivities and MR image simultaneously based on their prior information. Parallel magnetic resonance imaging reconstruction problem can be formulated as a multichannel sampling problem where solutions are sought analytically. However, the channel functions given by the coil sensitivities in parallel imaging are not known exactly and the estimation error usually leads to artifacts. In this study, we propose a new reconstruction algorithm, termed Sparse BLind Iterative Parallel, for blind iterative parallel imaging reconstruction using compressed sensing. The proposed algorithm reconstructs both the sensitivity functions and the image simultaneously from undersampled data. It enforces the sparseness constraint in the image as done in compressed sensing, but is different from compressed sensing in that the sensing matrix is unknown and additional constraint is enforced on the sensitivities as well. Both phantom and in vivo imaging experiments were carried out with retrospective undersampling to evaluate the performance of the proposed method. Experiments show improvement in Sparse BLind Iterative Parallel reconstruction when compared with Sparse SENSE, JSENSE, IRGN-TV, and L1-SPIRiT reconstructions with the same number of measurements. The proposed Sparse BLind Iterative Parallel algorithm reduces the reconstruction errors when compared to the state-of-the-art parallel imaging methods. Copyright © 2013 Wiley Periodicals, Inc.

  8. Blind compressed sensing image reconstruction based on alternating direction method

    Science.gov (United States)

    Liu, Qinan; Guo, Shuxu

    2018-04-01

    In order to solve the problem of how to reconstruct the original image under the condition of unknown sparse basis, this paper proposes an image reconstruction method based on blind compressed sensing model. In this model, the image signal is regarded as the product of a sparse coefficient matrix and a dictionary matrix. Based on the existing blind compressed sensing theory, the optimal solution is solved by the alternative minimization method. The proposed method solves the problem that the sparse basis in compressed sensing is difficult to represent, which restrains the noise and improves the quality of reconstructed image. This method ensures that the blind compressed sensing theory has a unique solution and can recover the reconstructed original image signal from a complex environment with a stronger self-adaptability. The experimental results show that the image reconstruction algorithm based on blind compressed sensing proposed in this paper can recover high quality image signals under the condition of under-sampling.

  9. 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.

  10. Image reconstruction by domain-transform manifold learning

    Science.gov (United States)

    Zhu, Bo; Liu, Jeremiah Z.; Cauley, Stephen F.; Rosen, Bruce R.; Rosen, Matthew S.

    2018-03-01

    Image reconstruction is essential for imaging applications across the physical and life sciences, including optical and radar systems, magnetic resonance imaging, X-ray computed tomography, positron emission tomography, ultrasound imaging and radio astronomy. During image acquisition, the sensor encodes an intermediate representation of an object in the sensor domain, which is subsequently reconstructed into an image by an inversion of the encoding function. Image reconstruction is challenging because analytic knowledge of the exact inverse transform may not exist a priori, especially in the presence of sensor non-idealities and noise. Thus, the standard reconstruction approach involves approximating the inverse function with multiple ad hoc stages in a signal processing chain, the composition of which depends on the details of each acquisition strategy, and often requires expert parameter tuning to optimize reconstruction performance. Here we present a unified framework for image reconstruction—automated transform by manifold approximation (AUTOMAP)—which recasts image reconstruction as a data-driven supervised learning task that allows a mapping between the sensor and the image domain to emerge from an appropriate corpus of training data. We implement AUTOMAP with a deep neural network and exhibit its flexibility in learning reconstruction transforms for various magnetic resonance imaging acquisition strategies, using the same network architecture and hyperparameters. We further demonstrate that manifold learning during training results in sparse representations of domain transforms along low-dimensional data manifolds, and observe superior immunity to noise and a reduction in reconstruction artefacts compared with conventional handcrafted reconstruction methods. In addition to improving the reconstruction performance of existing acquisition methodologies, we anticipate that AUTOMAP and other learned reconstruction approaches will accelerate the development

  11. A fast image reconstruction technique based on ART

    International Nuclear Information System (INIS)

    Zhang Shunli; Zhang Dinghua; Wang Kai; Huang Kuidong; Li Weibin

    2007-01-01

    Algebraic Reconstruction Technique (ART) is an iterative method for image reconstruction. Improving its reconstruction speed has been one of the important researching aspects of ART. For the simplified weight coefficients reconstruction model of ART, a fast grid traverse algorithm is proposed, which can determine the grid index by simple operations such as addition, subtraction and comparison. Since the weight coefficients are calculated at real time during iteration, large amount of storage is saved and the reconstruction speed is greatly increased. Experimental results show that the new algorithm is very effective and the reconstruction speed is improved about 10 times compared with the traditional algorithm. (authors)

  12. Photogrammetric 3D reconstruction using mobile imaging

    Science.gov (United States)

    Fritsch, Dieter; Syll, Miguel

    2015-03-01

    In our paper we demonstrate the development of an Android Application (AndroidSfM) for photogrammetric 3D reconstruction that works on smartphones and tablets likewise. The photos are taken with mobile devices, and can thereafter directly be calibrated using standard calibration algorithms of photogrammetry and computer vision, on that device. Due to still limited computing resources on mobile devices, a client-server handshake using Dropbox transfers the photos to the sever to run AndroidSfM for the pose estimation of all photos by Structure-from-Motion and, thereafter, uses the oriented bunch of photos for dense point cloud estimation by dense image matching algorithms. The result is transferred back to the mobile device for visualization and ad-hoc on-screen measurements.

  13. Reconstruction from gamma radiography and ultrasonic images

    International Nuclear Information System (INIS)

    Gautier, S.; Lavayssiere, B.; Idier, J.; Mohammad-Djafari, A.

    1998-02-01

    This work deals with the three-dimensional reconstruction from gamma radiographic and ultrasonic images. Such an issue belongs to the field of data fusion since the data provide complementary information. The two sets of data are independently related to two sets of parameters: gamma ray attenuation and ultrasonic reflectivity. The fusion problem is addressed in a Bayesian framework; the kingpin of the task is then to define a joint a priori model for both attenuation and reflectivity. Thus, the developing of this model and the entailed joint estimation constitute the principal contribution of this work. The results of real data treatments demonstrate the validity of this method as compared to a sequential approach of the two sets of data

  14. Model-Based Reconstructive Elasticity Imaging Using Ultrasound

    Directory of Open Access Journals (Sweden)

    Salavat R. Aglyamov

    2007-01-01

    Full Text Available Elasticity imaging is a reconstructive imaging technique where tissue motion in response to mechanical excitation is measured using modern imaging systems, and the estimated displacements are then used to reconstruct the spatial distribution of Young's modulus. Here we present an ultrasound elasticity imaging method that utilizes the model-based technique for Young's modulus reconstruction. Based on the geometry of the imaged object, only one axial component of the strain tensor is used. The numerical implementation of the method is highly efficient because the reconstruction is based on an analytic solution of the forward elastic problem. The model-based approach is illustrated using two potential clinical applications: differentiation of liver hemangioma and staging of deep venous thrombosis. Overall, these studies demonstrate that model-based reconstructive elasticity imaging can be used in applications where the geometry of the object and the surrounding tissue is somewhat known and certain assumptions about the pathology can be made.

  15. An efficient algorithm for MR image reconstruction and compression

    International Nuclear Information System (INIS)

    Wang, Hang; Rosenfeld, D.; Braun, M.; Yan, Hong

    1992-01-01

    In magnetic resonance imaging (MRI), the original data are sampled in the spatial frequency domain. The sampled data thus constitute a set of discrete Fourier transform (DFT) coefficients. The image is usually reconstructed by taking inverse DFT. The image data may then be efficiently compressed using the discrete cosine transform (DCT). A method of using DCT to treat the sampled data is presented which combines two procedures, image reconstruction and data compression. This method may be particularly useful in medical picture archiving and communication systems where both image reconstruction and compression are important issues. 11 refs., 3 figs

  16. TREE STEM RECONSTRUCTION USING VERTICAL FISHEYE IMAGES: A PRELIMINARY STUDY

    Directory of Open Access Journals (Sweden)

    A. Berveglieri

    2016-06-01

    Full Text Available A preliminary study was conducted to assess a tree stem reconstruction technique with panoramic images taken with fisheye lenses. The concept is similar to the Structure from Motion (SfM technique, but the acquisition and data preparation rely on fisheye cameras to generate a vertical image sequence with height variations of the camera station. Each vertical image is rectified to four vertical planes, producing horizontal lateral views. The stems in the lateral view are rectified to the same scale in the image sequence to facilitate image matching. Using bundle adjustment, the stems are reconstructed, enabling later measurement and extraction of several attributes. The 3D reconstruction was performed with the proposed technique and compared with SfM. The preliminary results showed that the stems were correctly reconstructed by using the lateral virtual images generated from the vertical fisheye images and with the advantage of using fewer images and taken from one single station.

  17. Superiority of CT imaging reconstruction on Linux OS

    International Nuclear Information System (INIS)

    Lin Shaochun; Yan Xufeng; Wu Tengfang; Luo Xiaomei; Cai Huasong

    2010-01-01

    Objective: To compare the speed of CT reconstruction using the Linux and Windows OS. Methods: Shepp-Logan head phantom in different pixel size was projected to obtain the sinogram by using the inverse Fourier transformation, filtered back projection and Radon transformation on both Linux and Windows OS. Results: CT image reconstruction using the Linux operating system was significantly better and more efficient than Windows. Conclusion: CT image reconstruction using the Linux operating system is more efficient. (authors)

  18. 3D Reconstruction of NMR Images by LabVIEW

    Directory of Open Access Journals (Sweden)

    Peter IZAK

    2007-01-01

    Full Text Available This paper introduces the experiment of 3D reconstruction NMR images via virtual instrumentation - LabVIEW. The main idea is based on marching cubes algorithm and image processing implemented by module of Vision assistant. The two dimensional images shot by the magnetic resonance device provide information about the surface properties of human body. There is implemented algorithm which can be used for 3D reconstruction of magnetic resonance images in biomedical application.

  19. Reconstruction of Optical Thickness from Hoffman Modulation Contrast Images

    DEFF Research Database (Denmark)

    Olsen, Niels Holm; Sporring, Jon; Nielsen, Mads

    2003-01-01

    Hoffman microscopy imaging systems are part of numerous fertility clinics world-wide. We discuss the physics of the Hoffman imaging system from optical thickness to image intensity, implement a simple, yet fast, reconstruction algorithm using Fast Fourier Transformation and discuss the usability...... of the method on a number of cells from a human embryo. Novelty is identifying the non-linearity of a typical Hoffman imaging system, and the application of Fourier Transformation to reconstruct the optical thickness....

  20. 3D reconstruction based on light field images

    Science.gov (United States)

    Zhu, Dong; Wu, Chunhong; Liu, Yunluo; Fu, Dongmei

    2018-04-01

    This paper proposed a method of reconstructing three-dimensional (3D) scene from two light field images capture by Lytro illium. The work was carried out by first extracting the sub-aperture images from light field images and using the scale-invariant feature transform (SIFT) for feature registration on the selected sub-aperture images. Structure from motion (SFM) algorithm is further used on the registration completed sub-aperture images to reconstruct the three-dimensional scene. 3D sparse point cloud was obtained in the end. The method shows that the 3D reconstruction can be implemented by only two light field camera captures, rather than at least a dozen times captures by traditional cameras. This can effectively solve the time-consuming, laborious issues for 3D reconstruction based on traditional digital cameras, to achieve a more rapid, convenient and accurate reconstruction.

  1. 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.

  2. Low dose reconstruction algorithm for differential phase contrast imaging.

    Science.gov (United States)

    Wang, Zhentian; Huang, Zhifeng; Zhang, Li; Chen, Zhiqiang; Kang, Kejun; Yin, Hongxia; Wang, Zhenchang; Marco, Stampanoni

    2011-01-01

    Differential phase contrast imaging computed tomography (DPCI-CT) is a novel x-ray inspection method to reconstruct the distribution of refraction index rather than the attenuation coefficient in weakly absorbing samples. In this paper, we propose an iterative reconstruction algorithm for DPCI-CT which benefits from the new compressed sensing theory. We first realize a differential algebraic reconstruction technique (DART) by discretizing the projection process of the differential phase contrast imaging into a linear partial derivative matrix. In this way the compressed sensing reconstruction problem of DPCI reconstruction can be transformed to a resolved problem in the transmission imaging CT. Our algorithm has the potential to reconstruct the refraction index distribution of the sample from highly undersampled projection data. Thus it can significantly reduce the dose and inspection time. The proposed algorithm has been validated by numerical simulations and actual experiments.

  3. Longitudinal and transverse digital image reconstruction with a tomographic scanner

    International Nuclear Information System (INIS)

    Pickens, D.R.; Price, R.R.; Erickson, J.J.; Patton, J.A.; Partain, C.L.; Rollo, F.D.

    1981-01-01

    A Siemens Gammasonics PHO/CON-192 Multiplane Imager is interfaced to a digital computer for the purpose of performing tomographic reconstructions from the data collected during a single scan. Data from the two moving gamma cameras as well as camera position information are sent to the computer by an interface designed in the authors' laboratory. Backprojection reconstruction is implemented by the computer. Longitudinal images in whole-body format as well as smaller formats are reconstructed for up to six planes simultaneously from the list mode data. Transverse reconstructions are demonstrated for 201 T1 myocardial scans. Post-reconstruction deconvolution processing to remove the blur artifact (characteristic of focal plane tomography) is applied to a multiplane phantom. Digital data acquisition of data and reconstruction of images are practical, and can extend the usefulness of the machine when compared with the film output (author)

  4. Gadgetron: An Open Source Framework for Medical Image Reconstruction

    DEFF Research Database (Denmark)

    Hansen, Michael Schacht; Sørensen, Thomas Sangild

    2013-01-01

    This work presents a new open source framework for medical image reconstruction called the “Gadgetron.” The framework implements a flexible system for creating streaming data processing pipelines where data pass through a series of modules or “Gadgets” from raw data to reconstructed images...... with a set of dedicated toolboxes in shared libraries for medical image reconstruction. This includes generic toolboxes for data-parallel (e.g., GPU-based) execution of compute-intensive components. The basic framework architecture is independent of medical imaging modality, but this article focuses on its...

  5. Cortical actin nodes: Their dynamics and recruitment of podosomal proteins as revealed by super-resolution and single-molecule microscopy

    Science.gov (United States)

    Shirai, Yuki M.; Tsunoyama, Taka A.; Hiramoto-Yamaki, Nao; Hirosawa, Koichiro M.; Shibata, Akihiro C. E.; Kondo, Kenichi; Tsurumune, Atsushi; Ishidate, Fumiyoshi; Kusumi, Akihiro

    2017-01-01

    Electron tomography of the plasma membrane (PM) identified several layers of cortical actin meshwork running parallel to the PM cytoplasmic surface throughout the PM. Here, cortical actin structures and dynamics were examined in living cells, using super-resolution microscopy, with (x,y)- and z-resolutions of ~140 and ~400 nm, respectively, and single-molecule imaging. The super-resolution microscopy identified sub-micron-sized actin clusters that appeared identical by both phalloidin post-fixation staining and Lifeact-mGFP expression followed by fixation, and therefore, these actin clusters were named “actin-pl-clusters”. In live cells, the actin-pl-clusters visualized by Lifeact-mGFP linked two or more actin filaments in the fine actin meshwork, acting as a node of the meshwork, and dynamically moved on/along the meshwork in a myosin II-dependent manner. Their formation depended on the Arp2/3 activities, suggesting that the movements could involve both the myosin motor activity and actin polymerization-depolymerization. The actin-pl-clusters differ from the actin nodes/asters found previously after latrunculin treatments, since myosin II and filamin A were not colocalized with the actin-pl-clusters, and the actin-pl-clusters were much smaller than the previously reported nodes/asters. The Lifeact linked to a fluorescently-labeled transmembrane peptide from syntaxin4 (Lifeact-TM) expressed in the PM exhibited temporary immobilization in the PM regions on which actin-pl-clusters and stress fibers were projected, showing that ≥66% of actin-pl-clusters and 89% of stress fibers were located in close proximity (within 3.5 nm) to the PM cytoplasmic surface. Podosome-associated cytoplasmic proteins, Tks4, Tks5, cortactin, and N-WASP, were transiently recruited to actin-pl-clusters, and thus, we propose that actin-pl-clusters also represent “actin podosome-like clusters”. PMID:29190677

  6. Super-Resolution Microscopy Reveals the Native Ultrastructure of the Erythrocyte Cytoskeleton

    Directory of Open Access Journals (Sweden)

    Leiting Pan

    2018-01-01

    Full Text Available The erythrocyte cytoskeleton is a textbook prototype for the submembrane cytoskeleton of metazoan cells. While early experiments suggest a triangular network of actin-based junctional complexes connected by ∼200-nm-long spectrin tetramers, later studies indicate much smaller junction-to-junction distances in the range of 25-60 nm. Through super-resolution microscopy, we resolve the native ultrastructure of the cytoskeleton of membrane-preserved erythrocytes for the N and C termini of β-spectrin, F-actin, protein 4.1, tropomodulin, and adducin. This allows us to determine an ∼80-nm junction-to-junction distance, a length consistent with relaxed spectrin tetramers and theories based on spectrin abundance. Through two-color data, we further show that the cytoskeleton meshwork often contains nanoscale voids where the cell membrane remains intact and that actin filaments and capping proteins localize to a subset of, but not all, junctional complexes. Together, our results call for a reassessment of the structure and function of the submembrane cytoskeleton.

  7. Measurement of replication structures at the nanometer scale using super-resolution light microscopy.

    Science.gov (United States)

    Baddeley, D; Chagin, V O; Schermelleh, L; Martin, S; Pombo, A; Carlton, P M; Gahl, A; Domaing, P; Birk, U; Leonhardt, H; Cremer, C; Cardoso, M C

    2010-01-01

    DNA replication, similar to other cellular processes, occurs within dynamic macromolecular structures. Any comprehensive understanding ultimately requires quantitative data to establish and test models of genome duplication. We used two different super-resolution light microscopy techniques to directly measure and compare the size and numbers of replication foci in mammalian cells. This analysis showed that replication foci vary in size from 210 nm down to 40 nm. Remarkably, spatially modulated illumination (SMI) and 3D-structured illumination microscopy (3D-SIM) both showed an average size of 125 nm that was conserved throughout S-phase and independent of the labeling method, suggesting a basic unit of genome duplication. Interestingly, the improved optical 3D resolution identified 3- to 5-fold more distinct replication foci than previously reported. These results show that optical nanoscopy techniques enable accurate measurements of cellular structures at a level previously achieved only by electron microscopy and highlight the possibility of high-throughput, multispectral 3D analyses.

  8. Newmark-Beta-FDTD method for super-resolution analysis of time reversal waves

    Science.gov (United States)

    Shi, Sheng-Bing; Shao, Wei; Ma, Jing; Jin, Congjun; Wang, Xiao-Hua

    2017-09-01

    In this work, a new unconditionally stable finite-difference time-domain (FDTD) method with the split-field perfectly matched layer (PML) is proposed for the analysis of time reversal (TR) waves. The proposed method is very suitable for multiscale problems involving microstructures. The spatial and temporal derivatives in this method are discretized by the central difference technique and Newmark-Beta algorithm, respectively, and the derivation results in the calculation of a banded-sparse matrix equation. Since the coefficient matrix keeps unchanged during the whole simulation process, the lower-upper (LU) decomposition of the matrix needs to be performed only once at the beginning of the calculation. Moreover, the reverse Cuthill-Mckee (RCM) technique, an effective preprocessing technique in bandwidth compression of sparse matrices, is used to improve computational efficiency. The super-resolution focusing of TR wave propagation in two- and three-dimensional spaces is included to validate the accuracy and efficiency of the proposed method.

  9. Ensemble variational Bayes tensor factorization for super resolution of CFRP debond detection

    Science.gov (United States)

    Lu, Peng; Gao, Bin; Feng, Qizhi; Yang, Yang; Woo, W. L.; Tian, Gui Yun

    2017-09-01

    The carbon fiber reinforced polymer (CFRP) is widely used in aircraft and wind turbine blades. The common type of CFRP defect is debond. Optical pulse thermographic nondestructive evaluation (OPTNDE) and relevant thermal feature extraction algorithms are generally used to detect the debond. However, the resolution of detection performance remain as challenges. In this paper, the ensemble variational Bayes tensor factorization has been proposed to conduct super resolution of the debond detection. The algorithm is based on the framework of variational Bayes tensor factorization and it constructs spatial-transient multi-layer mining structure which can significantly enhance the contrast ratio between the defective regions and sound regions. In order to quantitatively evaluate the results, the event based F-score is computed. The different information regions of the extracted thermal patterns are considered as different events and the purpose is to objectively evaluate the detectability for different algorithms. Experimental tests and comparative studies have been conducted to prove the efficacy of the proposed method.

  10. Super-resolution with an optically-addressable liquid crystal spatial light modulator

    International Nuclear Information System (INIS)

    McOrist, J.; Sharma, M.D.; Sheppard, C.J.R.

    2002-01-01

    Full text: An optically-addressable liquid crystal spatial light modulator has been used to generate super-resolving masks. This approach avoids problems of low efficiency and coupling between amplitude and phase modulation, that occur when using conventional liquid crystal modulators. When addressed by a programmed light intensity distribution, it allows filters to be changed rapidly to modify the response of a system or permit the investigation of different filter designs. The device used is not pixellated, with a spatial resolution of 30 line pairs/mm over an area 18mm X 18mm, and can achieve continuously-variable phase modulation up to 1.5 wavelengths. The system consists of a write-beam that is collimated from a white-light source. An input mask was used in our experiments determines the modulation pattern of the read-beam. The read-beam from a HeNe laser reflects from the modulator and is focused by a microscope objective. The value of the phase change induced by the transparent regions of the mask can be altered continuously by adjusting the brightness of the write-beam. We have used this system to attain super-resolution by simple Toraldo filters, consisting of arrays of rings. Copyright (2002) Australian Society for Electron Microscopy Inc

  11. Super-resolution mapping of scaffold nucleoporins in the nuclear pore complex.

    Science.gov (United States)

    Ma, Jiong; Kelich, Joseph M; Junod, Samuel L; Yang, Weidong

    2017-04-01

    The nuclear pore complex (NPC), composed of ∼30 different nucleoporins (Nups), is one of the largest supramolecular structures in eukaryotic cells. Its octagonal ring scaffold perforates the nuclear envelope and features a unique molecular machinery that regulates nucleocytoplasmic transport. However, the precise copy number and the spatial location of each Nup in the native NPC remain obscure due to the inherent difficulty of counting and localizing proteins inside of the sub-micrometer supramolecular complex. Here, we combined super-resolution single-point edge-excitation subdiffraction (SPEED) microscopy and nanobody-specific labeling to reveal the spatial distribution of scaffold Nups within three separate layers in the native NPC with a precision of ∼3 nm. Our data reveal both the radial and axial spatial distributions for Pom121, Nup37 and Nup35 and provide evidence for their copy numbers of 8, 32 and 16, respectively, per NPC. This approach can help pave the path for mapping the entirety of Nups in native NPCs and also other structural components of macromolecular complexes. © 2017. Published by The Company of Biologists Ltd.

  12. Radial super-resolution in digital holographic microscopy using structured illumination with circular symmetry

    Science.gov (United States)

    Yin, Yujian; Su, Ping; Ma, Jianshe

    2018-01-01

    A method to improve the radial resolution using special structured light is proposed in the field of digital holographic microscopy (DHM). A specimen is illuminated with circular symmetrical structured light that makes the spectrum have radial movement, so that high frequency components of the specimen are moved into the passband of the receiver to overcome the diffraction limit. In the DHM imaging system, Computer Generated Hologram (CGH) technology is used to generate the required structured light grating. Then the grating is loaded into a spatial light modulator (SLM) to obtain specific structured illumination. After recording the hologram, digital reconstruction, for the microstructure of a binary optical element that needs to observe radial distribution, the radial resolution of the specimen is improved experimentally compare it with the result of one-dimensional sinusoidal structured light imaging. And a method of designing structured light is presented.

  13. Reconstruction CT imaging of the hypopharynx and the larynx

    International Nuclear Information System (INIS)

    Okuno, Tetsuji; Fujimura, Akiko; Murakami, Yasushi; Shiga, Hayao

    1986-01-01

    The multiplanar reconstruction CT imaging of the hypopharynx and the larynx was performed on a total of 20 cases: 8 with laryngeal carcinomas, 6 with hypopharyngeal carcinomas, 4 with vocal cord paralyses due to various causes, 1 with laryngeal amyloidosis, 1 with inflammatory granuloma of the hypopharynx. Coronal, segittal, and parasagittal reconstruction images were obtained from either 1 or 2 mm overlapping axial scans with 4 or 5 mm slice thickness (3 cases) using 5 sec scan times during queit breathing. In 15 cases with coronal reconstruction imaging, the anatomical derangements of the laryngopharyngeal structures especially along the undersurface of the true vocal cord to the false cord level, the lateral wall of the pyriform sinus, and the paraglottic space were demonstrated more clearly than the axial CT imaging. In 5 cases with sagittal reconstruction imaging, the vertical extension of the lesions through the anterior commisure was more clearly depicted than the axial CT imaging. In 8 cases with parasagittal reconstruction imaging, which is along the vocal fold or across the aryepiglottic fold, pathological changes along the aryepiglottic fold, the arytenoid-corniculate cartilage complex, and the tip of the pyriform sinus were more clearly demonstrated than the axial CT imaging. In determining the feasibility of conservation surgery of the larynx and the hypopharynx, reconstruction CT imaging is recommended as the diagnostic procedure of a choice, which would supplement the findings of the routine axial CT imaging. (author)

  14. Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU.

    Science.gov (United States)

    Arefan, D; Talebpour, A; Ahmadinejhad, N; Kamali Asl, A

    2015-06-01

    Digital Breast Tomosynthesis (DBT) is a technology that creates three dimensional (3D) images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU). At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU) card and the Graphics Processing Unit (GPU). It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU).

  15. 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

  16. 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

  17. Quantification of resolution in multiplanar reconstructions for digital breast tomosynthesis

    Science.gov (United States)

    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.

  18. 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.

  19. Reconstruction of a ring applicator using CT imaging: impact of the reconstruction method and applicator orientation

    DEFF Research Database (Denmark)

    Hellebust, Taran Paulsen; Tanderup, Kari; Bergstrand, Eva Stabell

    2007-01-01

    in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method...

  20. Reconstitution radicicol containing apolipoprotein B lipoparticle and tracing its cell uptake process by super resolution fluorescent microscopy.

    Science.gov (United States)

    Lin, Chung Ching; Lin, Po-Yen; Chang, Chia-Ching

    Apolipoprotein B (apoB) is the only protein of LDL. LDL delivers cholesterol, triacylglycerides and lipids to the target cells. Reconstitute apoB lipoparticle (rABL) will be an idea drug delivery vehicle for hydrophobic and amphiphilic materials delivery. It is challenged to renature ApoB into its functional state from denatured state. By using modified bile salt and radicicol (Rad) added over-critical refolding process, apoB can be restored into its native like state. The intrinsic fluorescence of apoB increased during the refolding process. Moreover, radicicol (Rad) molecules have been encapsulated into reconstitute rABL (Rad@rABL). To investigate the cell uptake mechanism of Rad@rABL, a super resolution ground state depletion (GSD) microscopy is used in this research. Fluorescence labeled Rad@rABL can be traced within the tumor cell. Key words: LDL, radicicol, protein refolding, super resolution microscopy.

  1. Simbol-X Formation Flight and Image Reconstruction

    Science.gov (United States)

    Civitani, M.; Djalal, S.; Le Duigou, J. M.; La Marle, O.; Chipaux, R.

    2009-05-01

    Simbol-X is the first operational mission relying on two satellites flying in formation. The dynamics of the telescope, due to the formation flight concept, raises a variety of problematic, like image reconstruction, that can be better evaluated via a simulation tools. We present here the first results obtained with Simulos, simulation tool aimed to study the relative spacecrafts navigation and the weight of the different parameters in image reconstruction and telescope performance evaluation. The simulation relies on attitude and formation flight sensors models, formation flight dynamics and control, mirror model and focal plane model, while the image reconstruction is based on the Line of Sight (LOS) concept.

  2. 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

  3. Quantum Dot Immunocytochemical Localization of Somatostatin in Somatostatinoma by Widefield Epifluorescence, Super-resolution Light, and Immunoelectron Microscopy

    Science.gov (United States)

    Lai, Ken; Wu, Xiaojuan; Yong, Jim L. C.; Lee, C. Soon

    2012-01-01

    Quantum dot nanocrystal probes (QDs) have been used for detection of somatostatin hormone in secretory granules of somatostatinoma tumor cells by immunofluorescence light microscopy, super-resolution light microscopy, and immunoelectron microscopy. Immunostaining for all modalities was done using sections taken from an epoxy resin-embedded tissue specimen and a similar labeling protocol. This approach allowed assessment of labeling at light microscopy level before examination at super-resolution and electron microscopy level and was a significant aid in interpretation. Etching of ultrathin sections with saturated sodium metaperiodate was a critical step presumably able to retrieve some tissue antigenicity masked by processing in epoxy resin. Immunofluorescence microscopy of QD-immunolabeled sections showed somatostatin hormone localization in cytoplasmic granules. Some variable staining of tumor gland-like structures appeared related to granule maturity and dispersal of granule contents within the tumor cell cytoplasm. Super-resolution light microscopy demonstrated localization of somatostatin within individual secretory granules to be heterogeneous, and this staining pattern was confirmed by immunoelectron microscopy. PMID:22899862

  4. Quantum dot immunocytochemical localization of somatostatin in somatostatinoma by Widefield Epifluorescence, super-resolution light, and immunoelectron microscopy.

    Science.gov (United States)

    Killingsworth, Murray C; Lai, Ken; Wu, Xiaojuan; Yong, Jim L C; Lee, C Soon

    2012-11-01

    Quantum dot nanocrystal probes (QDs) have been used for detection of somatostatin hormone in secretory granules of somatostatinoma tumor cells by immunofluorescence light microscopy, super-resolution light microscopy, and immunoelectron microscopy. Immunostaining for all modalities was done using sections taken from an epoxy resin-embedded tissue specimen and a similar labeling protocol. This approach allowed assessment of labeling at light microscopy level before examination at super-resolution and electron microscopy level and was a significant aid in interpretation. Etching of ultrathin sections with saturated sodium metaperiodate was a critical step presumably able to retrieve some tissue antigenicity masked by processing in epoxy resin. Immunofluorescence microscopy of QD-immunolabeled sections showed somatostatin hormone localization in cytoplasmic granules. Some variable staining of tumor gland-like structures appeared related to granule maturity and dispersal of granule contents within the tumor cell cytoplasm. Super-resolution light microscopy demonstrated localization of somatostatin within individual secretory granules to be heterogeneous, and this staining pattern was confirmed by immunoelectron microscopy.

  5. Simultaneous maximum a posteriori longitudinal PET image reconstruction

    Science.gov (United States)

    Ellis, Sam; Reader, Andrew J.

    2017-09-01

    Positron emission tomography (PET) is frequently used to monitor functional changes that occur over extended time scales, for example in longitudinal oncology PET protocols that include routine clinical follow-up scans to assess the efficacy of a course of treatment. In these contexts PET datasets are currently reconstructed into images using single-dataset reconstruction methods. Inspired by recently proposed joint PET-MR reconstruction methods, we propose to reconstruct longitudinal datasets simultaneously by using a joint penalty term in order to exploit the high degree of similarity between longitudinal images. We achieved this by penalising voxel-wise differences between pairs of longitudinal PET images in a one-step-late maximum a posteriori (MAP) fashion, resulting in the MAP simultaneous longitudinal reconstruction (SLR) method. The proposed method reduced reconstruction errors and visually improved images relative to standard maximum likelihood expectation-maximisation (ML-EM) in simulated 2D longitudinal brain tumour scans. In reconstructions of split real 3D data with inserted simulated tumours, noise across images reconstructed with MAP-SLR was reduced to levels equivalent to doubling the number of detected counts when using ML-EM. Furthermore, quantification of tumour activities was largely preserved over a variety of longitudinal tumour changes, including changes in size and activity, with larger changes inducing larger biases relative to standard ML-EM reconstructions. Similar improvements were observed for a range of counts levels, demonstrating the robustness of the method when used with a single penalty strength. The results suggest that longitudinal regularisation is a simple but effective method of improving reconstructed PET images without using resolution degrading priors.

  6. 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.

  7. Surface Reconstruction and Image Enhancement via $L^1$-Minimization

    KAUST Repository

    Dobrev, Veselin

    2010-01-01

    A surface reconstruction technique based on minimization of the total variation of the gradient is introduced. Convergence of the method is established, and an interior-point algorithm solving the associated linear programming problem is introduced. The reconstruction algorithm is illustrated on various test cases including natural and urban terrain data, and enhancement oflow-resolution or aliased images. Copyright © by SIAM.

  8. Fast implementations of reconstruction-based scatter compensation in fully 3D SPECT image reconstruction

    International Nuclear Information System (INIS)

    Kadrmas, Dan J.; Karimi, Seemeen S.; Frey, Eric C.; Tsui, Benjamin M.W.

    1998-01-01

    Accurate scatter compensation in SPECT can be performed by modelling the scatter response function during the reconstruction process. This method is called reconstruction-based scatter compensation (RBSC). It has been shown that RBSC has a number of advantages over other methods of compensating for scatter, but using RBSC for fully 3D compensation has resulted in prohibitively long reconstruction times. In this work we propose two new methods that can be used in conjunction with existing methods to achieve marked reductions in RBSC reconstruction times. The first method, coarse-grid scatter modelling, significantly accelerates the scatter model by exploiting the fact that scatter is dominated by low-frequency information. The second method, intermittent RBSC, further accelerates the reconstruction process by limiting the number of iterations during which scatter is modelled. The fast implementations were evaluated using a Monte Carlo simulated experiment of the 3D MCAT phantom with 99m Tc tracer, and also using experimentally acquired data with 201 Tl tracer. Results indicated that these fast methods can reconstruct, with fully 3D compensation, images very similar to those obtained using standard RBSC methods, and in reconstruction times that are an order of magnitude shorter. Using these methods, fully 3D iterative reconstruction with RBSC can be performed well within the realm of clinically realistic times (under 10 minutes for 64x64x24 image reconstruction). (author)

  9. Reconstruction of a ring applicator using CT imaging: impact of the reconstruction method and applicator orientation

    International Nuclear Information System (INIS)

    Hellebust, Taran Paulsen; Tanderup, Kari; Bergstrand, Eva Stabell; Knutsen, Bjoern Helge; Roeislien, Jo; Olsen, Dag Rune

    2007-01-01

    The purpose of this study is to investigate whether the method of applicator reconstruction and/or the applicator orientation influence the dose calculation to points around the applicator for brachytherapy of cervical cancer with CT-based treatment planning. A phantom, containing a fixed ring applicator set and six lead pellets representing dose points, was used. The phantom was CT scanned with the ring applicator at four different angles related to the image plane. In each scan the applicator was reconstructed by three methods: (1) direct reconstruction in each image (DR) (2) reconstruction in multiplanar reconstructed images (MPR) and (3) library plans, using pre-defined applicator geometry (LIB). The doses to the lead pellets were calculated. The relative standard deviation (SD) for all reconstruction methods was less than 3.7% in the dose points. The relative SD for the LIB method was significantly lower (p < 0.05) than for the DR and MPR methods for all but two points. All applicator orientations had similar dose calculation reproducibility. Using library plans for applicator reconstruction gives the most reproducible dose calculation. However, with restrictive guidelines for applicator reconstruction the uncertainties for all methods are low compared to other factors influencing the accuracy of brachytherapy

  10. Compressively sampled MR image reconstruction using generalized thresholding iterative algorithm

    Science.gov (United States)

    Elahi, Sana; kaleem, Muhammad; Omer, Hammad

    2018-01-01

    Compressed sensing (CS) is an emerging area of interest in Magnetic Resonance Imaging (MRI). CS is used for the reconstruction of the images from a very limited number of samples in k-space. This significantly reduces the MRI data acquisition time. One important requirement for signal recovery in CS is the use of an appropriate non-linear reconstruction algorithm. It is a challenging task to choose a reconstruction algorithm that would accurately reconstruct the MR images from the under-sampled k-space data. Various algorithms have been used to solve the system of non-linear equations for better image quality and reconstruction speed in CS. In the recent past, iterative soft thresholding algorithm (ISTA) has been introduced in CS-MRI. This algorithm directly cancels the incoherent artifacts produced because of the undersampling in k -space. This paper introduces an improved iterative algorithm based on p -thresholding technique for CS-MRI image reconstruction. The use of p -thresholding function promotes sparsity in the image which is a key factor for CS based image reconstruction. The p -thresholding based iterative algorithm is a modification of ISTA, and minimizes non-convex functions. It has been shown that the proposed p -thresholding iterative algorithm can be used effectively to recover fully sampled image from the under-sampled data in MRI. The performance of the proposed method is verified using simulated and actual MRI data taken at St. Mary's Hospital, London. The quality of the reconstructed images is measured in terms of peak signal-to-noise ratio (PSNR), artifact power (AP), and structural similarity index measure (SSIM). The proposed approach shows improved performance when compared to other iterative algorithms based on log thresholding, soft thresholding and hard thresholding techniques at different reduction factors.

  11. Challenges for Super-Resolution Localization Microscopy and Biomolecular Fluorescent Nano-Probing in Cancer Research

    Science.gov (United States)

    Ilić, Nataša; Pilarczyk, Götz; Lee, Jin-Ho; Logeswaran, Abiramy; Borroni, Aurora Paola; Krufczik, Matthias; Theda, Franziska; Waltrich, Nadine; Bestvater, Felix; Hildenbrand, Georg; Cremer, Christoph; Blank, Michael

    2017-01-01

    Understanding molecular interactions and regulatory mechanisms in tumor initiation, progression, and treatment response are key requirements towards advanced cancer diagnosis and novel treatment procedures in personalized medicine. Beyond decoding the gene expression, malfunctioning and cancer-related epigenetic pathways, investigations of the spatial receptor arrangements in membranes and genome organization in cell nuclei, on the nano-scale, contribute to elucidating complex molecular mechanisms in cells and tissues. By these means, the correlation between cell function and spatial organization of molecules or molecular complexes can be studied, with respect to carcinogenesis, tumor sensitivity or tumor resistance to anticancer therapies, like radiation or antibody treatment. Here, we present several new applications for bio-molecular nano-probes and super-resolution, laser fluorescence localization microscopy and their potential in life sciences, especially in biomedical and cancer research. By means of a tool-box of fluorescent antibodies, green fluorescent protein (GFP) tagging, or specific oligonucleotides, we present tumor relevant re-arrangements of Erb-receptors in membranes, spatial organization of Smad specific ubiquitin protein ligase 2 (Smurf2) in the cytosol, tumor cell characteristic heterochromatin organization, and molecular re-arrangements induced by radiation or antibody treatment. The main purpose of this article is to demonstrate how nano-scaled distance measurements between bio-molecules, tagged by appropriate nano-probes, can be applied to elucidate structures and conformations of molecular complexes which are characteristic of tumorigenesis and treatment responses. These applications open new avenues towards a better interpretation of the spatial organization and treatment responses of functionally relevant molecules, at the single cell level, in normal and cancer cells, offering new potentials for individualized medicine. PMID:28956810

  12. Challenges for Super-Resolution Localization Microscopy and Biomolecular Fluorescent Nano-Probing in Cancer Research

    Directory of Open Access Journals (Sweden)

    Michael Hausmann

    2017-09-01

    Full Text Available Understanding molecular interactions and regulatory mechanisms in tumor initiation, progression, and treatment response are key requirements towards advanced cancer diagnosis and novel treatment procedures in personalized medicine. Beyond decoding the gene expression, malfunctioning and cancer-related epigenetic pathways, investigations of the spatial receptor arrangements in membranes and genome organization in cell nuclei, on the nano-scale, contribute to elucidating complex molecular mechanisms in cells and tissues. By these means, the correlation between cell function and spatial organization of molecules or molecular complexes can be studied, with respect to carcinogenesis, tumor sensitivity or tumor resistance to anticancer therapies, like radiation or antibody treatment. Here, we present several new applications for bio-molecular nano-probes and super-resolution, laser fluorescence localization microscopy and their potential in life sciences, especially in biomedical and cancer research. By means of a tool-box of fluorescent antibodies, green fluorescent protein (GFP tagging, or specific oligonucleotides, we present tumor relevant re-arrangements of Erb-receptors in membranes, spatial organization of Smad specific ubiquitin protein ligase 2 (Smurf2 in the cytosol, tumor cell characteristic heterochromatin organization, and molecular re-arrangements induced by radiation or antibody treatment. The main purpose of this article is to demonstrate how nano-scaled distance measurements between bio-molecules, tagged by appropriate nano-probes, can be applied to elucidate structures and conformations of molecular complexes which are characteristic of tumorigenesis and treatment responses. These applications open new avenues towards a better interpretation of the spatial organization and treatment responses of functionally relevant molecules, at the single cell level, in normal and cancer cells, offering new potentials for individualized medicine.

  13. Super-Resolution Community Detection for Layer-Aggregated Multilayer Networks

    Directory of Open Access Journals (Sweden)

    Dane Taylor

    2017-09-01

    Full Text Available Applied network science often involves preprocessing network data before applying a network-analysis method, and there is typically a theoretical disconnect between these steps. For example, it is common to aggregate time-varying network data into windows prior to analysis, and the trade-offs of this preprocessing are not well understood. Focusing on the problem of detecting small communities in multilayer networks, we study the effects of layer aggregation by developing random-matrix theory for modularity matrices associated with layer-aggregated networks with N nodes and L layers, which are drawn from an ensemble of Erdős–Rényi networks with communities planted in subsets of layers. We study phase transitions in which eigenvectors localize onto communities (allowing their detection and which occur for a given community provided its size surpasses a detectability limit K^{*}. When layers are aggregated via a summation, we obtain K^{*}∝O(sqrt[NL]/T, where T is the number of layers across which the community persists. Interestingly, if T is allowed to vary with L, then summation-based layer aggregation enhances small-community detection even if the community persists across a vanishing fraction of layers, provided that T/L decays more slowly than O(L^{-1/2}. Moreover, we find that thresholding the summation can, in some cases, cause K^{*} to decay exponentially, decreasing by orders of magnitude in a phenomenon we call super-resolution community detection. In other words, layer aggregation with thresholding is a nonlinear data filter enabling detection of communities that are otherwise too small to detect. Importantly, different thresholds generally enhance the detectability of communities having different properties, illustrating that community detection can be obscured if one analyzes network data using a single threshold.

  14. Super-Resolution Community Detection for Layer-Aggregated Multilayer Networks.

    Science.gov (United States)

    Taylor, Dane; Caceres, Rajmonda S; Mucha, Peter J

    2017-01-01

    Applied network science often involves preprocessing network data before applying a network-analysis method, and there is typically a theoretical disconnect between these steps. For example, it is common to aggregate time-varying network data into windows prior to analysis, and the trade-offs of this preprocessing are not well understood. Focusing on the problem of detecting small communities in multilayer networks, we study the effects of layer aggregation by developing random-matrix theory for modularity matrices associated with layer-aggregated networks with N nodes and L layers, which are drawn from an ensemble of Erdős-Rényi networks with communities planted in subsets of layers. We study phase transitions in which eigenvectors localize onto communities (allowing their detection) and which occur for a given community provided its size surpasses a detectability limit K * . When layers are aggregated via a summation, we obtain [Formula: see text], where T is the number of layers across which the community persists. Interestingly, if T is allowed to vary with L , then summation-based layer aggregation enhances small-community detection even if the community persists across a vanishing fraction of layers, provided that T/L decays more slowly than ( L -1/2 ). Moreover, we find that thresholding the summation can, in some cases, cause K * to decay exponentially, decreasing by orders of magnitude in a phenomenon we call super-resolution community detection. In other words, layer aggregation with thresholding is a nonlinear data filter enabling detection of communities that are otherwise too small to detect. Importantly, different thresholds generally enhance the detectability of communities having different properties, illustrating that community detection can be obscured if one analyzes network data using a single threshold.

  15. Algorithms for Reconstruction of Undersampled Atomic Force Microscopy Images Supplementary Material

    DEFF Research Database (Denmark)

    2017-01-01

    Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods.......Two Jupyter Notebooks showcasing reconstructions of undersampled atomic force microscopy images. The reconstructions were obtained using a variety of interpolation and reconstruction methods....

  16. A Kalman filter technique applied for medical image reconstruction

    International Nuclear Information System (INIS)

    Goliaei, S.; Ghorshi, S.; Manzuri, M. T.; Mortazavi, M.

    2011-01-01

    Medical images contain information about vital organic tissues inside of human body and are widely used for diagnoses of disease or for surgical purposes. Image reconstruction is essential for medical images for some applications such as suppression of noise or de-blurring the image in order to provide images with better quality and contrast. Due to vital rule of image reconstruction in medical sciences the corresponding algorithms with better efficiency and higher speed is desirable. Most algorithms in image reconstruction are operated on frequency domain such as the most popular one known as filtered back projection. In this paper we introduce a Kalman filter technique which is operated in time domain for medical image reconstruction. Results indicated that as the number of projection increases in both normal collected ray sum and the collected ray sum corrupted by noise the quality of reconstructed image becomes better in terms of contract and transparency. It is also seen that as the number of projection increases the error index decreases.

  17. CT Image Reconstruction in a Low Dimensional Manifold

    OpenAIRE

    Cong, Wenxiang; Wang, Ge; Yang, Qingsong; Hsieh, Jiang; Li, Jia; Lai, Rongjie

    2017-01-01

    Regularization methods are commonly used in X-ray CT image reconstruction. Different regularization methods reflect the characterization of different prior knowledge of images. In a recent work, a new regularization method called a low-dimensional manifold model (LDMM) is investigated to characterize the low-dimensional patch manifold structure of natural images, where the manifold dimensionality characterizes structural information of an image. In this paper, we propose a CT image reconstruc...

  18. A theoretical investigation of super-resolution CARS imaging via coherent and incoherent saturation of transitions

    NARCIS (Netherlands)

    Beeker, W.P.; Beeker, Willem; Lee, Christopher James; Boller, Klaus J.; Gross, Petra; Gross, P.; Cleff, Carsten; Fallnich, Carsten; Offerhaus, Herman L.; Herek, Jennifer Lynn

    2011-01-01

    We review two approaches to achieving sub-diffraction-limited resolution coherent anti-Stokes Raman scattering (CARS) microscopy (Beeker et al., Opt. Express, 2009, 17, 22632 and Beeker et al., J. Herek, Phys. Rev. A, 2010, 81, 012507). We performed a numerical investigation, based on the density

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

    KAUST Repository

    Habuchi, Satoshi

    2014-01-01

    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

  20. Investigating sub-spine actin dynamics in rat hippocampal neurons with super-resolution optical imaging.

    Directory of Open Access Journals (Sweden)

    Vedakumar Tatavarty

    Full Text Available Morphological changes in dendritic spines represent an important mechanism for synaptic plasticity which is postulated to underlie the vital cognitive phenomena of learning and memory. These morphological changes are driven by the dynamic actin cytoskeleton that is present in dendritic spines. The study of actin dynamics in these spines traditionally has been hindered by the small size of the spine. In this study, we utilize a photo-activation localization microscopy (PALM-based single-molecule tracking technique to analyze F-actin movements with approximately 30-nm resolution in cultured hippocampal neurons. We were able to observe the kinematic (physical motion of actin filaments, i.e., retrograde flow and kinetic (F-actin turn-over dynamics of F-actin at the single-filament level in dendritic spines. We found that F-actin in dendritic spines exhibits highly heterogeneous kinematic dynamics at the individual filament level, with simultaneous actin flows in both retrograde and anterograde directions. At the ensemble level, movements of filaments integrate into a net retrograde flow of approximately 138 nm/min. These results suggest a weakly polarized F-actin network that consists of mostly short filaments in dendritic spines.

  1. Investigating sub-spine actin dynamics in rat hippocampal neurons with super-resolution optical imaging.

    Science.gov (United States)

    Tatavarty, Vedakumar; Kim, Eun-Ji; Rodionov, Vladimir; Yu, Ji

    2009-11-09

    Morphological changes in dendritic spines represent an important mechanism for synaptic plasticity which is postulated to underlie the vital cognitive phenomena of learning and memory. These morphological changes are driven by the dynamic actin cytoskeleton that is present in dendritic spines. The study of actin dynamics in these spines traditionally has been hindered by the small size of the spine. In this study, we utilize a photo-activation localization microscopy (PALM)-based single-molecule tracking technique to analyze F-actin movements with approximately 30-nm resolution in cultured hippocampal neurons. We were able to observe the kinematic (physical motion of actin filaments, i.e., retrograde flow) and kinetic (F-actin turn-over) dynamics of F-actin at the single-filament level in dendritic spines. We found that F-actin in dendritic spines exhibits highly heterogeneous kinematic dynamics at the individual filament level, with simultaneous actin flows in both retrograde and anterograde directions. At the ensemble level, movements of filaments integrate into a net retrograde flow of approximately 138 nm/min. These results suggest a weakly polarized F-actin network that consists of mostly short filaments in dendritic spines.

  2. Quantifying protein densities on cell membranes using super-resolution optical fluctuation imaging

    Czech Academy of Sciences Publication Activity Database

    Lukeš, T.; Glatzová, Daniela; Kvíčalová, Zuzana; Levet, F.; Benda, Aleš; Letschert, S.; Sauer, M.; Brdička, Tomáš; Lasser, T.; Cebecauer, Marek

    2017-01-01

    Roč. 8, č. 1 (2017), č. článku 1731. ISSN 2041-1723 R&D Projects: GA ČR GA15-06989S Institutional support: RVO:61388955 ; RVO:68378050 Keywords : quantifying protein densities * membranes * single-molecule localization microscopy Subject RIV: CE - Biochemistry OBOR OECD: Biochemistry and molecular biology Impact factor: 12.124, year: 2016

  3. Diverse Protocols for Correlative Super-Resolution Fluorescence Imaging and Electron Microscopy of Cells and Tissue

    Science.gov (United States)

    2016-05-25

    polymerization36. Finally, we mutated surface residues on mEos2 to remove nucleophilic groups, which are involved in cross-linking with aldehydes and...Sites of Clathrin-Mediated Endocytosis. Current Biology 21, 1167– 1175 (2011). 49. Caplan, J. et al. Correlative Protein Localization in Yeast . (2013

  4. Imaging lipid domains in cell membranes: the advent of super-resolution fluorescence microscopy

    Directory of Open Access Journals (Sweden)

    Dylan Myers Owen

    2013-12-01

    Full Text Available The lipid bilayer of model membranes, liposomes reconstituted from cell lipids, and plasma membrane vesicles and spheres can separate into two distinct liquid phases to yield lipid domains with liquid-ordered and liquid-disordered properties. These observations are the basis of the lipid raft hypothesis that postulates the existence of cholesterol-enriched ordered-phase lipid domains in cell membranes that could regulate protein mobility, localization and interaction. Here we review the evidence that nano-scaled lipid complexes and meso-scaled lipid domains exist in cell membranes and how new fluorescence microscopy techniques that overcome the diffraction limit provide new insights into lipid organization in cell membranes.

  5. Time-of-flight PET image reconstruction using origin ensembles

    Science.gov (United States)

    Wülker, Christian; Sitek, Arkadiusz; Prevrhal, Sven

    2015-03-01

    The origin ensemble (OE) algorithm is a novel statistical method for minimum-mean-square-error (MMSE) reconstruction of emission tomography data. This method allows one to perform reconstruction entirely in the image domain, i.e. without the use of forward and backprojection operations. We have investigated the OE algorithm in the context of list-mode (LM) time-of-flight (TOF) PET reconstruction. In this paper, we provide a general introduction to MMSE reconstruction, and a statistically rigorous derivation of the OE algorithm. We show how to efficiently incorporate TOF information into the reconstruction process, and how to correct for random coincidences and scattered events. To examine the feasibility of LM-TOF MMSE reconstruction with the OE algorithm, we applied MMSE-OE and standard maximum-likelihood expectation-maximization (ML-EM) reconstruction to LM-TOF phantom data with a count number typically registered in clinical PET examinations. We analyzed the convergence behavior of the OE algorithm, and compared reconstruction time and image quality to that of the EM algorithm. In summary, during the reconstruction process, MMSE-OE contrast recovery (CRV) remained approximately the same, while background variability (BV) gradually decreased with an increasing number of OE iterations. The final MMSE-OE images exhibited lower BV and a slightly lower CRV than the corresponding ML-EM images. The reconstruction time of the OE algorithm was approximately 1.3 times longer. At the same time, the OE algorithm can inherently provide a comprehensive statistical characterization of the acquired data. This characterization can be utilized for further data processing, e.g. in kinetic analysis and image registration, making the OE algorithm a promising approach in a variety of applications.

  6. A study of transverse image reconstruction with digital subtraction angiography

    International Nuclear Information System (INIS)

    Sakamoto, Kiyoshi; Kotoura, Noriko; Terasawa, Yuuji; Oda, Masahiko; Gotou, Hiroshi; Nasada, Toshiya; Tanooka, Masao

    1995-01-01

    For digital subtraction angiography (DSA) with C-type equipment, it is possible to radiate an X-ray during rotation and to collect data at different angular settings. We tried to reconstruct transverse image from data obtained by scanning DSA images at different angular settings. 88 projection data were obtained by rotating the object at 180deg during radiation. Reconstruction was made using the convolution method with pixel value distribution for each projection. Similarly, the image quality of the reconstructed images were compared with the unsubtracted and subtracted ones. In case a part object was outside the calculating region, artifacts were generally produced. However, the artifacts were reduced by subtracting the background from the image. In addition, the cupping phenomenon caused by beam hardening was relaxed and high-quality imaging could be achieved. This method will become even more effective, if we will use it with selective angiography in which the limited area is enhanced. (author)

  7. Robust sparse image reconstruction of radio interferometric observations with PURIFY

    Science.gov (United States)

    Pratley, Luke; McEwen, Jason D.; d'Avezac, Mayeul; Carrillo, Rafael E.; Onose, Alexandru; Wiaux, Yves

    2018-01-01

    Next-generation radio interferometers, such as the Square Kilometre Array, will revolutionize our understanding of the Universe through their unprecedented sensitivity and resolution. However, to realize these goals significant challenges in image and data processing need to be overcome. The standard methods in radio interferometry for reconstructing images, such as CLEAN, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we apply and evaluate alternative interferometric reconstruction methods that make use of state-of-the-art sparse image reconstruction algorithms motivated by compressive sensing, which have been implemented in the PURIFY software package. In particular, we implement and apply the proximal alternating direction method of multipliers algorithm presented in a recent article. First, we assess the impact of the interpolation kernel used to perform gridding and degridding on sparse image reconstruction. We find that the Kaiser-Bessel interpolation kernel performs as well as prolate spheroidal wave functions while providing a computational saving and an analytic form. Secondly, we apply PURIFY to real interferometric observations from the Very Large Array and the Australia Telescope Compact Array and find that images recovered by PURIFY are of higher quality than those recovered by CLEAN. Thirdly, we discuss how PURIFY reconstructions exhibit additional advantages over those recovered by CLEAN. The latest version of PURIFY, with developments presented in this work, is made publicly available.

  8. 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)

  9. Fingerprint image reconstruction for swipe sensor using Predictive Overlap Method

    Directory of Open Access Journals (Sweden)

    Mardiansyah Ahmad Zafrullah

    2018-01-01

    Full Text Available Swipe sensor is one of many biometric authentication sensor types that widely applied to embedded devices. The sensor produces an overlap on every pixel block of the image, so the picture requires a reconstruction process before heading to the feature extraction process. Conventional reconstruction methods require extensive computation, causing difficult to apply to embedded devices that have limited computing process. In this paper, image reconstruction is proposed using predictive overlap method, which determines the image block shift from the previous set of change data. The experiments were performed using 36 images generated by a swipe sensor with 128 x 8 pixels size of the area, where each image has an overlap in each block. The results reveal computation can increase up to 86.44% compared with conventional methods, with accuracy decreasing to 0.008% in average.

  10. Quantitative reconstruction from a single diffraction-enhanced image

    International Nuclear Information System (INIS)

    Paganin, D.M.; Lewis, R.A.; Kitchen, M.

    2003-01-01

    Full text: We develop an algorithm for using a single diffraction-enhanced image (DEI) to obtain a quantitative reconstruction of the projected thickness of a single-material sample which is embedded within a substrate of approximately constant thickness. This algorithm is used to quantitatively map inclusions in a breast phantom, from a single synchrotron DEI image. In particular, the reconstructed images quantitatively represent the projected thickness in the bulk of the sample, in contrast to DEI images which greatly emphasise sharp edges (high spatial frequencies). In the context of an ultimate aim of improved methods for breast cancer detection, the reconstructions are potentially of greater diagnostic value compared to the DEI data. Lastly, we point out that the methods of analysis presented here are also applicable to the quantitative analysis of differential interference contrast (DIC) images

  11. Matrix-based image reconstruction methods for tomography

    International Nuclear Information System (INIS)

    Llacer, J.; Meng, J.D.

    1984-10-01

    Matrix methods of image reconstruction have not been used, in general, because of the large size of practical matrices, ill condition upon inversion and the success of Fourier-based techniques. An exception is the work that has been done at the Lawrence Berkeley Laboratory for imaging with accelerated radioactive ions. An extension of that work into more general imaging problems shows that, with a correct formulation of the problem, positron tomography with ring geometries results in well behaved matrices which can be used for image reconstruction with no distortion of the point response in the field of view and flexibility in the design of the instrument. Maximum Likelihood Estimator methods of reconstruction, which use the system matrices tailored to specific instruments and do not need matrix inversion, are shown to result in good preliminary images. A parallel processing computer structure based on multiple inexpensive microprocessors is proposed as a system to implement the matrix-MLE methods. 14 references, 7 figures

  12. 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

  13. Photoelectron holography with improved image reconstruction

    Energy Technology Data Exchange (ETDEWEB)

    Matsushita, Tomohiro, E-mail: matusita@spring8.or.j [Japan Synchrotron Radiation Research Institute (JASRI), SPring-8, 1-1-1 Kouto, Sayo-cho, Sayo-gun Hyogo 679-5198 (Japan); Matsui, Fumihiko; Daimon, Hiroshi [Nara Institute of Science and Technology (NAIST), 8916-5 Takayama, Ikoma, Nara 630-0192 (Japan); Hayashi, Kouichi [Institute for Materials Research, Tohoku University, Sendai 980-8577 (Japan)

    2010-05-15

    Electron holography is a type of atomic structural analysis, and it has unique features such as element selectivity and the ability to analyze the structure around an impurity in a crystal. In this paper, we introduce the measurement system, electron holograms, a theory for the recording process of an electron hologram, and a theory for the reconstruction algorithm. We describe photoelectron holograms, Auger electron holograms, and the inverse mode of an electron hologram. The reconstruction algorithm, scattering pattern extraction algorithm (SPEA), the SPEA with maximum entropy method (SPEA-MEM), and SPEA-MEM with translational operation are also described.

  14. Photoelectron holography with improved image reconstruction

    International Nuclear Information System (INIS)

    Matsushita, Tomohiro; Matsui, Fumihiko; Daimon, Hiroshi; Hayashi, Kouichi

    2010-01-01

    Electron holography is a type of atomic structural analysis, and it has unique features such as element selectivity and the ability to analyze the structure around an impurity in a crystal. In this paper, we introduce the measurement system, electron holograms, a theory for the recording process of an electron hologram, and a theory for the reconstruction algorithm. We describe photoelectron holograms, Auger electron holograms, and the inverse mode of an electron hologram. The reconstruction algorithm, scattering pattern extraction algorithm (SPEA), the SPEA with maximum entropy method (SPEA-MEM), and SPEA-MEM with translational operation are also described.

  15. Super-Resolution Localization Microscopy of γ-H2AX and Heterochromatin after Folate Deficiency.

    Science.gov (United States)

    Bach, Margund; Savini, Claudia; Krufczik, Matthias; Cremer, Christoph; Rösl, Frank; Hausmann, Michael

    2017-08-08

    Folate is an essential water-soluble vitamin in food and nutrition supplements. As a one-carbon source, it is involved in many central regulatory processes, such as DNA, RNA, and protein methylation as well as DNA synthesis and repair. Deficiency in folate is considered to be associated with an increased incidence of several malignancies, including cervical cancer that is etiologically linked to an infection with "high-risk" human papilloma viruses (HPV). However, it is still not known how a recommended increase in dietary folate after its deprivation affects the physiological status of cells. To study the impact of folate depletion and its subsequent reconstitution in single cells, we used quantitative chromatin conformation measurements obtained by super-resolution fluorescence microscopy, i.e., single molecule localization microscopy (SMLM). As a read-out, we examined the levels and the (re)positioning of γ-H2AX tags and histone H3K9me3 heterochromatin tags after immunostaining in three-dimensional (3D)-conserved cell nuclei. As model, we used HPV16 positive immortalized human keratinocytes that were cultivated under normal, folate deficient, and reconstituted conditions for different periods of time. The results were compared to cells continuously cultivated in standard folate medium. After 13 weeks in low folate, an increase in the phosphorylation of the histone H2AX was noted, indicative of an accumulation of DNA double strand breaks. DNA repair activity represented by the formation of those γ-H2AX clusters was maintained during the following 15 weeks of examination. However, the clustered arrangements of tags appeared to relax in a time-dependent manner. Parallel to the repair activity, the chromatin methylation activity increased as detected by H3K9me3 tags. The progress of DNA double strand repair was accompanied by a reduction of the detected nucleosome density around the γ-H2AX clusters, suggesting a shift from hetero- to euchromatin to allow access

  16. 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.

  17. Fast Dictionary-Based Reconstruction for Diffusion Spectrum Imaging

    Science.gov (United States)

    Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F.; Yendiki, Anastasia; Wald, Lawrence L.; Adalsteinsson, Elfar

    2015-01-01

    Diffusion Spectrum Imaging (DSI) reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation (TV) transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using Matlab running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using Principal Component Analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm. PMID:23846466

  18. Fast dictionary-based reconstruction for diffusion spectrum imaging.

    Science.gov (United States)

    Bilgic, Berkin; Chatnuntawech, Itthi; Setsompop, Kawin; Cauley, Stephen F; Yendiki, Anastasia; Wald, Lawrence L; Adalsteinsson, Elfar

    2013-11-01

    Diffusion spectrum imaging reveals detailed local diffusion properties at the expense of substantially long imaging times. It is possible to accelerate acquisition by undersampling in q-space, followed by image reconstruction that exploits prior knowledge on the diffusion probability density functions (pdfs). Previously proposed methods impose this prior in the form of sparsity under wavelet and total variation transforms, or under adaptive dictionaries that are trained on example datasets to maximize the sparsity of the representation. These compressed sensing (CS) methods require full-brain processing times on the order of hours using MATLAB running on a workstation. This work presents two dictionary-based reconstruction techniques that use analytical solutions, and are two orders of magnitude faster than the previously proposed dictionary-based CS approach. The first method generates a dictionary from the training data using principal component analysis (PCA), and performs the reconstruction in the PCA space. The second proposed method applies reconstruction using pseudoinverse with Tikhonov regularization with respect to a dictionary. This dictionary can either be obtained using the K-SVD algorithm, or it can simply be the training dataset of pdfs without any training. All of the proposed methods achieve reconstruction times on the order of seconds per imaging slice, and have reconstruction quality comparable to that of dictionary-based CS algorithm.

  19. Convergence of iterative image reconstruction algorithms for Digital Breast Tomosynthesis

    DEFF Research Database (Denmark)

    Sidky, Emil; Jørgensen, Jakob Heide; Pan, Xiaochuan

    2012-01-01

    Most iterative image reconstruction algorithms are based on some form of optimization, such as minimization of a data-fidelity term plus an image regularizing penalty term. While achieving the solution of these optimization problems may not directly be clinically relevant, accurate optimization s...

  20. Analytic 3D image reconstruction using all detected events

    International Nuclear Information System (INIS)

    Kinahan, P.E.; Rogers, J.G.

    1988-11-01

    We present the results of testing a previously presented algorithm for three-dimensional image reconstruction that uses all gamma-ray coincidence events detected by a PET volume-imaging scanner. By using two iterations of an analytic filter-backprojection method, the algorithm is not constrained by the requirement of a spatially invariant detector point spread function, which limits normal analytic techniques. Removing this constraint allows the incorporation of all detected events, regardless of orientation, which improves the statistical quality of the final reconstructed image

  1. Three-dimensional image reconstruction. I. Determination of pattern orientation

    International Nuclear Information System (INIS)

    Blankenbecler, Richard

    2004-01-01

    The problem of determining the Euler angles of a randomly oriented three-dimensional (3D) object from its 2D Fraunhofer diffraction patterns is discussed. This problem arises in the reconstruction of a positive semidefinite 3D object using oversampling techniques. In such a problem, the data consist of a measured set of magnitudes from 2D tomographic images of the object at several unknown orientations. After the orientation angles are determined, the object itself can then be reconstructed by a variety of methods using oversampling, the magnitude data from the 2D images, physical constraints on the image, and then iteration to determine the phases

  2. Few-view image reconstruction with dual dictionaries

    International Nuclear Information System (INIS)

    Lu Yang; Zhao Jun; Wang Ge

    2012-01-01

    In this paper, we formulate the problem of computed tomography (CT) under sparsity and few-view constraints, and propose a novel algorithm for image reconstruction from few-view data utilizing the simultaneous algebraic reconstruction technique (SART) coupled with dictionary learning, sparse representation and total variation (TV) minimization on two interconnected levels. The main feature of our algorithm is the use of two dictionaries: a transitional dictionary for atom matching and a global dictionary for image updating. The atoms in the global and transitional dictionaries represent the image patches from high-quality and low-quality CT images, respectively. Experiments with simulated and real projections were performed to evaluate and validate the proposed algorithm. The results reconstructed using the proposed approach are significantly better than those using either SART or SART–TV. (paper)

  3. Bayesian image reconstruction for improving detection performance of muon tomography.

    Science.gov (United States)

    Wang, Guobao; Schultz, Larry J; Qi, Jinyi

    2009-05-01

    Muon tomography is a novel technology that is being developed for detecting high-Z materials in vehicles or cargo containers. Maximum likelihood methods have been developed for reconstructing the scattering density image from muon measurements. However, the instability of maximum likelihood estimation often results in noisy images and low detectability of high-Z targets. In this paper, we propose using regularization to improve the image quality of muon tomography. We formulate the muon reconstruction problem in a Bayesian framework by introducing a prior distribution on scattering density images. An iterative shrinkage algorithm is derived to maximize the log posterior distribution. At each iteration, the algorithm obtains the maximum a posteriori update by shrinking an unregularized maximum likelihood update. Inverse quadratic shrinkage functions are derived for generalized Laplacian priors and inverse cubic shrinkage functions are derived for generalized Gaussian priors. Receiver operating characteristic studies using simulated data demonstrate that the Bayesian reconstruction can greatly improve the detection performance of muon tomography.

  4. Evaluation of aortocoronary bypass graft patency by reconstructed CT image

    International Nuclear Information System (INIS)

    Kawakita, Seizaburo; Koide, Takashi; Saito, Yoshio; Yamamoto, Tadao; Iwasaki, Tadaaki

    1982-01-01

    Ten patients were examined in the period of three months from January to March 1981. The patients were operated from 1 month to 7 years before CT. A bypass to the left anterior descending artery (LAD) was grafted in 10 cases, 2 to the right coronary artery (RCA), 4 to an obtuse marginal artery (OM), and 1 to a diagonal artery. Image reconstruction was performed in 10 cases by using an image analytical computer Evaluskop. Appropriate planes for reconstruction were selected by trial and error methods upon observation of CT images. When gained picture of a graft course coincided with surgical records or angiography, the work of building images was concluded. On cross section, grafts to LAD were visualized in all 10 cases: 9 in the entire course and 1 in a proximal part of the graft. Two to RCA, 4 to OM and 1 to a diagonal were also successfully visualized. Reconstruction of graft images succeeded in 9 grafts of 6 cases. The course of a graft could be pursued from the proximal to the distal end adjacent to the cardiac chamber. The picture of a bypass to LAD was visualized in 6 of 10 grafts. Two bypass to RCA could be depicted, and 1 to OM was also found. However 3 to OM and 1 to a diagonal failed to be visualized throughout their courses in reconstructed images. I think that the causes of faillure mainly depended upon the course of the graft. When a graft was running arc-like surrounding the heart chamber, it was very difficult to depict its entire length in reconstructed images, though the graft could be detected in cross sections. These preliminary studies indicated that reconstruction of CT images had some benefits for the pursuit of graft courses. (J.P.N.)

  5. A neural network image reconstruction technique for electrical impedance tomography

    International Nuclear Information System (INIS)

    Adler, A.; Guardo, R.

    1994-01-01

    Reconstruction of Images in Electrical Impedance Tomography requires the solution of a nonlinear inverse problem on noisy data. This problem is typically ill-conditioned and requires either simplifying assumptions or regularization based on a priori knowledge. This paper presents a reconstruction algorithm using neural network techniques which calculates a linear approximation of the inverse problem directly from finite element simulations of the forward problem. This inverse is adapted to the geometry of the medium and the signal-to-noise ratio (SNR) used during network training. Results show good conductivity reconstruction where measurement SNR is similar to the training conditions. The advantages of this method are its conceptual simplicity and ease of implementation, and the ability to control the compromise between the noise performance and resolution of the image reconstruction

  6. Biologically inspired EM image alignment and neural reconstruction.

    Science.gov (United States)

    Knowles-Barley, Seymour; Butcher, Nancy J; Meinertzhagen, Ian A; Armstrong, J Douglas

    2011-08-15

    Three-dimensional reconstruction of consecutive serial-section transmission electron microscopy (ssTEM) images of neural tissue currently requires many hours of manual tracing and annotation. Several computational techniques have already been applied to ssTEM images to facilitate 3D reconstruction and ease this burden. Here, we present an alternative computational approach for ssTEM image analysis. We have used biologically inspired receptive fields as a basis for a ridge detection algorithm to identify cell membranes, synaptic contacts and mitochondria. Detected line segments are used to improve alignment between consecutive images and we have joined small segments of membrane into cell surfaces using a dynamic programming algorithm similar to the Needleman-Wunsch and Smith-Waterman DNA sequence alignment procedures. A shortest path-based approach has been used to close edges and achieve image segmentation. Partial reconstructions were automatically generated and used as a basis for semi-automatic reconstruction of neural tissue. The accuracy of partial reconstructions was evaluated and 96% of membrane could be identified at the cost of 13% false positive detections. An open-source reference implementation is available in the Supplementary information. seymour.kb@ed.ac.uk; douglas.armstrong@ed.ac.uk Supplementary data are available at Bioinformatics online.

  7. Prospective regularization design in prior-image-based reconstruction

    International Nuclear Information System (INIS)

    Dang, Hao; Siewerdsen, Jeffrey H; Stayman, J Webster

    2015-01-01

    Prior-image-based reconstruction (PIBR) methods leveraging patient-specific anatomical information from previous imaging studies and/or sequences have demonstrated dramatic improvements in dose utilization and image quality for low-fidelity data. However, a proper balance of information from the prior images and information from the measurements is required (e.g. through careful tuning of regularization parameters). Inappropriate selection of reconstruction parameters can lead to detrimental effects including false structures and failure to improve image quality. Traditional methods based on heuristics are subject to error and sub-optimal solutions, while exhaustive searches require a large number of computationally intensive image reconstructions. In this work, we propose a novel method that prospectively estimates the optimal amount of prior image information for accurate admission of specific anatomical changes in PIBR without performing full image reconstructions. This method leverages an analytical approximation to the implicitly defined PIBR estimator, and introduces a predictive performance metric leveraging this analytical form and knowledge of a particular presumed anatomical change whose accurate reconstruction is sought. Additionally, since model-based PIBR approaches tend to be space-variant, a spatially varying prior image strength map is proposed to optimally admit changes everywhere in the image (eliminating the need to know change locations a priori). Studies were conducted in both an ellipse phantom and a realistic thorax phantom emulating a lung nodule surveillance scenario. The proposed method demonstrated accurate estimation of the optimal prior image strength while achieving a substantial computational speedup (about a factor of 20) compared to traditional exhaustive search. Moreover, the use of the proposed prior strength map in PIBR demonstrated accurate reconstruction of anatomical changes without foreknowledge of change locations in

  8. Image interface in Java for tomographic reconstruction in nuclear medicine

    International Nuclear Information System (INIS)

    Andrade, M.A.; Silva, A.M. Marques da

    2004-01-01

    The aim of this study is to implement a software for tomographic reconstruction of SPECT data from Nuclear Medicine with a flexible interface design, cross-platform, written in Java. Validation tests were performed based on SPECT simulated data. The results showed that the implemented algorithms and filters agree with the theoretical context. We intend to extend the system by implementing additional tomographic reconstruction techniques and Java threads, in order to provide simultaneously image processing. (author)

  9. Image Reconstruction For Bioluminescence Tomography From Partial Measurement

    OpenAIRE

    Jiang, M.; Zhou, T.; Cheng, J. T.; Cong, W. X.; Wang, Ge

    2007-01-01

    The bioluminescence tomography is a novel molecular imaging technology for small animal studies. Known reconstruction methods require the completely measured data on the external surface, although only partially measured data is available in practice. In this work, we formulate a mathematical model for BLT from partial data and generalize our previous results on the solution uniqueness to the partial data case. Then we extend two of our reconstruction methods for BLT to this case. The first m...

  10. Demosaicing and Superresolution for Color Filter Array via Residual Image Reconstruction and Sparse Representation

    OpenAIRE

    Sun, Guangling

    2012-01-01

    A framework of demosaicing and superresolution for color filter array (CFA) via residual image reconstruction and sparse representation is presented.Given the intermediate image produced by certain demosaicing and interpolation technique, a residual image between the final reconstruction image and the intermediate image is reconstructed using sparse representation.The final reconstruction image has richer edges and details than that of the intermediate image. Specifically, a generic dictionar...

  11. Reconstructing flaw image using dataset of full matrix capture technique

    Energy Technology Data Exchange (ETDEWEB)

    Lee, Tae Hun; Kim, Yong Sik; Lee, Jeong Seok [KHNP Central Research Institute, Daejeon (Korea, Republic of)

    2017-02-15

    A conventional phased array ultrasonic system offers the ability to steer an ultrasonic beam by applying independent time delays of individual elements in the array and produce an ultrasonic image. In contrast, full matrix capture (FMC) is a data acquisition process that collects a complete matrix of A-scans from every possible independent transmit-receive combination in a phased array transducer and makes it possible to reconstruct various images that cannot be produced by conventional phased array with the post processing as well as images equivalent to a conventional phased array image. In this paper, a basic algorithm based on the LLL mode total focusing method (TFM) that can image crack type flaws is described. And this technique was applied to reconstruct flaw images from the FMC dataset obtained from the experiments and ultrasonic simulation.

  12. Image reconstruction in computerized tomography using the convolution method

    International Nuclear Information System (INIS)

    Oliveira Rebelo, A.M. de.

    1984-03-01

    In the present work an algoritin was derived, using the analytical convolution method (filtered back-projection) for two-dimensional or three-dimensional image reconstruction in computerized tomography applied to non-destructive testing and to the medical use. This mathematical model is based on the analytical Fourier transform method for image reconstruction. This model consists of a discontinuous system formed by an NxN array of cells (pixels). The attenuation in the object under study of a colimated gamma ray beam has been determined for various positions and incidence angles (projections) in terms of the interaction of the beam with the intercepted pixels. The contribution of each pixel to beam attenuation was determined using the weight function W ij which was used for simulated tests. Simulated tests using standard objects with attenuation coefficients in the range of 0,2 to 0,7 cm -1 were carried out using cell arrays of up to 25x25. One application was carried out in the medical area simulating image reconstruction of an arm phantom with attenuation coefficients in the range of 0,2 to 0,5 cm -1 using cell arrays of 41x41. The simulated results show that, in objects with a great number of interfaces and great variations of attenuation coefficients at these interfaces, a good reconstruction is obtained with the number of projections equal to the reconstruction matrix dimension. A good reconstruction is otherwise obtained with fewer projections. (author) [pt

  13. 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...

  14. 3D widefield light microscope image reconstruction without dyes

    Science.gov (United States)

    Larkin, S.; Larson, J.; Holmes, C.; Vaicik, M.; Turturro, M.; Jurkevich, A.; Sinha, S.; Ezashi, T.; Papavasiliou, G.; Brey, E.; Holmes, T.

    2015-03-01

    3D image reconstruction using light microscope modalities without exogenous contrast agents is proposed and investigated as an approach to produce 3D images of biological samples for live imaging applications. Multimodality and multispectral imaging, used in concert with this 3D optical sectioning approach is also proposed as a way to further produce contrast that could be specific to components in the sample. The methods avoid usage of contrast agents. Contrast agents, such as fluorescent or absorbing dyes, can be toxic to cells or alter cell behavior. Current modes of producing 3D image sets from a light microscope, such as 3D deconvolution algorithms and confocal microscopy generally require contrast agents. Zernike phase contrast (ZPC), transmitted light brightfield (TLB), darkfield microscopy and others can produce contrast without dyes. Some of these modalities have not previously benefitted from 3D image reconstruction algorithms, however. The 3D image reconstruction algorithm is based on an underlying physical model of scattering potential, expressed as the sample's 3D absorption and phase quantities. The algorithm is based upon optimizing an objective function - the I-divergence - while solving for the 3D absorption and phase quantities. Unlike typical deconvolution algorithms, each microscope modality, such as ZPC or TLB, produces two output image sets instead of one. Contrast in the displayed image and 3D renderings is further enabled by treating the multispectral/multimodal data as a feature set in a mathematical formulation that uses the principal component method of statistics.

  15. Reconstruction of CT images by the Bayes- back projection method

    CERN Document Server

    Haruyama, M; Takase, M; Tobita, H

    2002-01-01

    In the course of research on quantitative assay of non-destructive measurement of radioactive waste, the have developed a unique program based on the Bayesian theory for reconstruction of transmission computed tomography (TCT) image. The reconstruction of cross-section images in the CT technology usually employs the Filtered Back Projection method. The new imaging reconstruction program reported here is based on the Bayesian Back Projection method, and it has a function of iterative improvement images by every step of measurement. Namely, this method has the capability of prompt display of a cross-section image corresponding to each angled projection data from every measurement. Hence, it is possible to observe an improved cross-section view by reflecting each projection data in almost real time. From the basic theory of Baysian Back Projection method, it can be not only applied to CT types of 1st, 2nd, and 3rd generation. This reported deals with a reconstruction program of cross-section images in the CT of ...

  16. Ultra-Fast Image Reconstruction of Tomosynthesis Mammography Using GPU

    Directory of Open Access Journals (Sweden)

    Arefan D

    2015-06-01

    Full Text Available Digital Breast Tomosynthesis (DBT is a technology that creates three dimensional (3D images of breast tissue. Tomosynthesis mammography detects lesions that are not detectable with other imaging systems. If image reconstruction time is in the order of seconds, we can use Tomosynthesis systems to perform Tomosynthesis-guided Interventional procedures. This research has been designed to study ultra-fast image reconstruction technique for Tomosynthesis Mammography systems using Graphics Processing Unit (GPU. At first, projections of Tomosynthesis mammography have been simulated. In order to produce Tomosynthesis projections, it has been designed a 3D breast phantom from empirical data. It is based on MRI data in its natural form. Then, projections have been created from 3D breast phantom. The image reconstruction algorithm based on FBP was programmed with C++ language in two methods using central processing unit (CPU card and the Graphics Processing Unit (GPU. It calculated the time of image reconstruction in two kinds of programming (using CPU and GPU.

  17. Image reconstruction technique using projection data from neutron tomography system

    Directory of Open Access Journals (Sweden)

    Waleed Abd el Bar

    2015-12-01

    Full Text Available Neutron tomography is a very powerful technique for nondestructive evaluation of heavy industrial components as well as for soft hydrogenous materials enclosed in heavy metals which are usually difficult to image using X-rays. Due to the properties of the image acquisition system, the projection images are distorted by several artifacts, and these reduce the quality of the reconstruction. In order to eliminate these harmful effects the projection images should be corrected before reconstruction. This paper gives a description of a filter back projection (FBP technique, which is used for reconstruction of projected data obtained from transmission measurements by neutron tomography system We demonstrated the use of spatial Discrete Fourier Transform (DFT and the 2D Inverse DFT in the formulation of the method, and outlined the theory of reconstruction of a 2D neutron image from a sequence of 1D projections taken at different angles between 0 and π in MATLAB environment. Projections are generated by applying the Radon transform to the original image at different angles.

  18. Optical image reconstruction using DC data: simulations and experiments

    International Nuclear Information System (INIS)

    Huabei Jiang; Paulsen, K.D.; Oesterberg, U.L.

    1996-01-01

    In this paper, we explore optical image formation using a diffusion approximation of light propagation in tissue which is modelled with a finite-element method for optically heterogeneous media. We demonstrate successful image reconstruction based on absolute experimental DC data obtained with a continuous wave 633 nm He-Ne laser system and a 751 nm diode laser system in laboratory phantoms having two optically distinct regions. The experimental systems used exploit a tomographic type of data collection scheme that provides information from which a spatially variable optical property map is deduced. Reconstruction of scattering coefficient only and simultaneous reconstruction of both scattering and absorption profiles in tissue-like phantoms are obtained from measured and simulated data. Images with different contrast levels between the heterogeneity and the background are also reported and the results show that although it is possible to obtain qualitative visual information on the location and size of a heterogeneity, it may not be possible to quantitatively resolve contrast levels or optical properties using reconstructions from DC data only. Sensitivity of image reconstruction to noise in the measurement data is investigated through simulations. The application of boundary constraints has also been addressed. (author)

  19. Block Compressed Sensing of Images Using Adaptive Granular Reconstruction

    Directory of Open Access Journals (Sweden)

    Ran Li

    2016-01-01

    Full Text Available In the framework of block Compressed Sensing (CS, the reconstruction algorithm based on the Smoothed Projected Landweber (SPL iteration can achieve the better rate-distortion performance with a low computational complexity, especially for using the Principle Components Analysis (PCA to perform the adaptive hard-thresholding shrinkage. However, during learning the PCA matrix, it affects the reconstruction performance of Landweber iteration to neglect the stationary local structural characteristic of image. To solve the above problem, this paper firstly uses the Granular Computing (GrC to decompose an image into several granules depending on the structural features of patches. Then, we perform the PCA to learn the sparse representation basis corresponding to each granule. Finally, the hard-thresholding shrinkage is employed to remove the noises in patches. The patches in granule have the stationary local structural characteristic, so that our method can effectively improve the performance of hard-thresholding shrinkage. Experimental results indicate that the reconstructed image by the proposed algorithm has better objective quality when compared with several traditional ones. The edge and texture details in the reconstructed image are better preserved, which guarantees the better visual quality. Besides, our method has still a low computational complexity of reconstruction.

  20. 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

  1. Adaptive reconstructions for magnetic resonance imaging of moving organs

    International Nuclear Information System (INIS)

    Lohezic, Maelene

    2011-01-01

    Magnetic resonance imaging (MRI) is a valuable tool for the clinical diagnosis for brain imaging as well as cardiac and abdominal imaging. For instance, MRI is the only modality that enables the visualization and characterization myocardial edema. However, motion remains a challenging problem for cardiac MRI. Breathing as well as cardiac beating have to be carefully handled during patient examination. Moreover they limit the achievable temporal and spatial resolution of the images. In this work an approach that takes these physiological motions into account during image reconstruction process has been proposed. It allows performing cardiac examination while breathing freely. First, an iterative reconstruction algorithm, that compensates motion estimated from a motion model constrained by physiological signals, is applied to morphological cardiac imaging. A semi-automatic method for edema detection has been tested on reconstructed images. It has also been associated with an adaptive acquisition strategy which enables free-breathing end-systolic imaging. This reconstruction has then been extended to the assessment of transverse relaxation times T2, which is used for myocardial edema characterization. The proposed method, ARTEMIS, enables free-breathing T2 mapping without additional acquisition time. The proposed free breathing approaches take advantage of physiological signals to estimate the motion that occurs during MR acquisitions. Several solutions have been tested to measure this information. Among them, accelerometer-based external sensors allow local measurements at several locations. Another approach consists in the use of k-space based measurements, which are 'embedded' inside the MRI pulse sequence (navigator) and prevent from the requirement of additional recording hardware. Hence, several adaptive reconstruction algorithms were developed to obtain diagnostic information from free breathing acquisitions. These works allow performing efficient and accurate

  2. Improving parallel imaging by jointly reconstructing multi-contrast data.

    Science.gov (United States)

    Bilgic, Berkin; Kim, Tae Hyung; Liao, Congyu; Manhard, Mary Kate; Wald, Lawrence L; Haldar, Justin P; Setsompop, Kawin

    2018-08-01

    To develop parallel imaging techniques that simultaneously exploit coil sensitivity encoding, image phase prior information, similarities across multiple images, and complementary k-space sampling for highly accelerated data acquisition. We introduce joint virtual coil (JVC)-generalized autocalibrating partially parallel acquisitions (GRAPPA) to jointly reconstruct data acquired with different contrast preparations, and show its application in 2D, 3D, and simultaneous multi-slice (SMS) acquisitions. We extend the joint parallel imaging concept to exploit limited support and smooth phase constraints through Joint (J-) LORAKS formulation. J-LORAKS allows joint parallel imaging from limited autocalibration signal region, as well as permitting partial Fourier sampling and calibrationless reconstruction. We demonstrate highly accelerated 2D balanced steady-state free precession with phase cycling, SMS multi-echo spin echo, 3D multi-echo magnetization-prepared rapid gradient echo, and multi-echo gradient recalled echo acquisitions in vivo. Compared to conventional GRAPPA, proposed joint acquisition/reconstruction techniques provide more than 2-fold reduction in reconstruction error. JVC-GRAPPA takes advantage of additional spatial encoding from phase information and image similarity, and employs different sampling patterns across acquisitions. J-LORAKS achieves a more parsimonious low-rank representation of local k-space by considering multiple images as additional coils. Both approaches provide dramatic improvement in artifact and noise mitigation over conventional single-contrast parallel imaging reconstruction. Magn Reson Med 80:619-632, 2018. © 2018 International Society for Magnetic Resonance in Medicine. © 2018 International Society for Magnetic Resonance in Medicine.

  3. 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

  4. Image Reconstruction Algorithm For Electrical Capacitance Tomography (ECT)

    International Nuclear Information System (INIS)

    Arko

    2001-01-01

    ). Most image reconstruction algorithms for electrical capacitance tomography (ECT) use sensitivity maps as weighting factors. The computation is fast, involving a simple multiply-and- accumulate (MAC) operation, but the resulting image suffers from blurring due to the soft-field effect of the sensor. This paper presents a low cost iterative method employing proportional thresholding, which improves image quality dramatically. The strategy for implementation, computational cost, and achievable speed is examined when using a personal computer (PC) and Digital Signal Processor (DSP). For PC implementation, Watcom C++ 10.6 and Visual C++ 5.0 compilers were used. The experimental results are compared to the images reconstructed by commercially available software. The new algorithm improves the image quality significantly at a cost of a few iterations. This technique can be readily exploited for online applications

  5. Silhouette-based approach of 3D image reconstruction for automated image acquisition using robotic arm

    Science.gov (United States)

    Azhar, N.; Saad, W. H. M.; Manap, N. A.; Saad, N. M.; Syafeeza, A. R.

    2017-06-01

    This study presents the approach of 3D image reconstruction using an autonomous robotic arm for the image acquisition process. A low cost of the automated imaging platform is created using a pair of G15 servo motor connected in series to an Arduino UNO as a main microcontroller. Two sets of sequential images were obtained using different projection angle of the camera. The silhouette-based approach is used in this study for 3D reconstruction from the sequential images captured from several different angles of the object. Other than that, an analysis based on the effect of different number of sequential images on the accuracy of 3D model reconstruction was also carried out with a fixed projection angle of the camera. The effecting elements in the 3D reconstruction are discussed and the overall result of the analysis is concluded according to the prototype of imaging platform.

  6. Blockwise conjugate gradient methods for image reconstruction in volumetric CT.

    Science.gov (United States)

    Qiu, W; Titley-Peloquin, D; Soleimani, M

    2012-11-01

    Cone beam computed tomography (CBCT) enables volumetric image reconstruction from 2D projection data and plays an important role in image guided radiation therapy (IGRT). Filtered back projection is still the most frequently used algorithm in applications. The algorithm discretizes the scanning process (forward projection) into a system of linear equations, which must then be solved to recover images from measured projection data. The conjugate gradients (CG) algorithm and its variants can be used to solve (possibly regularized) linear systems of equations Ax=b and linear least squares problems minx∥b-Ax∥2, especially when the matrix A is very large and sparse. Their applications can be found in a general CT context, but in tomography problems (e.g. CBCT reconstruction) they have not widely been used. Hence, CBCT reconstruction using the CG-type algorithm LSQR was implemented and studied in this paper. In CBCT reconstruction, the main computational challenge is that the matrix A usually is very large, and storing it in full requires an amount of memory well beyond the reach of commodity computers. Because of these memory capacity constraints, only a small fraction of the weighting matrix A is typically used, leading to a poor reconstruction. In this paper, to overcome this difficulty, the matrix A is partitioned and stored blockwise, and blockwise matrix-vector multiplications are implemented within LSQR. This implementation allows us to use the full weighting matrix A for CBCT reconstruction without further enhancing computer standards. Tikhonov regularization can also be implemented in this fashion, and can produce significant improvement in the reconstructed images. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

  7. Development of computed tomography system and image reconstruction algorithm

    International Nuclear Information System (INIS)

    Khairiah Yazid; Mohd Ashhar Khalid; Azaman Ahmad; Khairul Anuar Mohd Salleh; Ab Razak Hamzah

    2006-01-01

    Computed tomography is one of the most advanced and powerful nondestructive inspection techniques, which is currently used in many different industries. In several CT systems, detection has been by combination of an X-ray image intensifier and charge -coupled device (CCD) camera or by using line array detector. The recent development of X-ray flat panel detector has made fast CT imaging feasible and practical. Therefore this paper explained the arrangement of a new detection system which is using the existing high resolution (127 μm pixel size) flat panel detector in MINT and the image reconstruction technique developed. The aim of the project is to develop a prototype flat panel detector based CT imaging system for NDE. The prototype consisted of an X-ray tube, a flat panel detector system, a rotation table and a computer system to control the sample motion and image acquisition. Hence this project is divided to two major tasks, firstly to develop image reconstruction algorithm and secondly to integrate X-ray imaging components into one CT system. The image reconstruction algorithm using filtered back-projection method is developed and compared to other techniques. The MATLAB program is the tools used for the simulations and computations for this project. (Author)

  8. Dictionary Approaches to Image Compression and Reconstruction

    Science.gov (United States)

    Ziyad, Nigel A.; Gilmore, Erwin T.; Chouikha, Mohamed F.

    1998-01-01

    This paper proposes using a collection of parameterized waveforms, known as a dictionary, for the purpose of medical image compression. These waveforms, denoted as phi(sub gamma), are discrete time signals, where gamma represents the dictionary index. A dictionary with a collection of these waveforms is typically complete or overcomplete. Given such a dictionary, the goal is to obtain a representation image based on the dictionary. We examine the effectiveness of applying Basis Pursuit (BP), Best Orthogonal Basis (BOB), Matching Pursuits (MP), and the Method of Frames (MOF) methods for the compression of digitized radiological images with a wavelet-packet dictionary. The performance of these algorithms is studied for medical images with and without additive noise.

  9. System and method for three-dimensional image reconstruction using an absolute orientation sensor

    KAUST Repository

    Giancola, Silvio; Ghanem, Bernard; Schneider, Jens; Wonka, Peter

    2018-01-01

    A three-dimensional image reconstruction system includes an image capture device, an inertial measurement unit (IMU), and an image processor. The image capture device captures image data. The inertial measurement unit (IMU) is affixed to the image

  10. Joint model of motion and anatomy for PET image reconstruction

    International Nuclear Information System (INIS)

    Qiao Feng; Pan Tinsu; Clark, John W. Jr.; Mawlawi, Osama

    2007-01-01

    Anatomy-based positron emission tomography (PET) image enhancement techniques have been shown to have the potential for improving PET image quality. However, these techniques assume an accurate alignment between the anatomical and the functional images, which is not always valid when imaging the chest due to respiratory motion. In this article, we present a joint model of both motion and anatomical information by integrating a motion-incorporated PET imaging system model with an anatomy-based maximum a posteriori image reconstruction algorithm. The mismatched anatomical information due to motion can thus be effectively utilized through this joint model. A computer simulation and a phantom study were conducted to assess the efficacy of the joint model, whereby motion and anatomical information were either modeled separately or combined. The reconstructed images in each case were compared to corresponding reference images obtained using a quadratic image prior based maximum a posteriori reconstruction algorithm for quantitative accuracy. Results of these studies indicated that while modeling anatomical information or motion alone improved the PET image quantitation accuracy, a larger improvement in accuracy was achieved when using the joint model. In the computer simulation study and using similar image noise levels, the improvement in quantitation accuracy compared to the reference images was 5.3% and 19.8% when using anatomical or motion information alone, respectively, and 35.5% when using the joint model. In the phantom study, these results were 5.6%, 5.8%, and 19.8%, respectively. These results suggest that motion compensation is important in order to effectively utilize anatomical information in chest imaging using PET. The joint motion-anatomy model presented in this paper provides a promising solution to this problem

  11. 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.

  12. CT image reconstruction system based on hardware implementation

    International Nuclear Information System (INIS)

    Silva, Hamilton P. da; Evseev, Ivan; Schelin, Hugo R.; Paschuk, Sergei A.; Milhoretto, Edney; Setti, Joao A.P.; Zibetti, Marcelo; Hormaza, Joel M.; Lopes, Ricardo T.

    2009-01-01

    Full text: The timing factor is very important for medical imaging systems, which can nowadays be synchronized by vital human signals, like heartbeats or breath. The use of hardware implemented devices in such a system has advantages considering the high speed of information treatment combined with arbitrary low cost on the market. This article refers to a hardware system which is based on electronic programmable logic called FPGA, model Cyclone II from ALTERA Corporation. The hardware was implemented on the UP3 ALTERA Kit. A partially connected neural network with unitary weights was programmed. The system was tested with 60 topographic projections, 100 points in each, of the Shepp and Logan phantom created by MATLAB. The main restriction was found to be the memory size available on the device: the dynamic range of reconstructed image was limited to 0 65535. Also, the normalization factor must be observed in order to do not saturate the image during the reconstruction and filtering process. The test shows a principal possibility to build CT image reconstruction systems for any reasonable amount of input data by arranging the parallel work of the hardware units like we have tested. However, further studies are necessary for better understanding of the error propagation from topographic projections to reconstructed image within the implemented method. (author)

  13. PET image reconstruction: mean, variance, and optimal minimax criterion

    International Nuclear Information System (INIS)

    Liu, Huafeng; Guo, Min; Gao, Fei; Shi, Pengcheng; Xue, Liying; Nie, Jing

    2015-01-01

    Given the noise nature of positron emission tomography (PET) measurements, it is critical to know the image quality and reliability as well as expected radioactivity map (mean image) for both qualitative interpretation and quantitative analysis. While existing efforts have often been devoted to providing only the reconstructed mean image, we present a unified framework for joint estimation of the mean and corresponding variance of the radioactivity map based on an efficient optimal min–max criterion. The proposed framework formulates the PET image reconstruction problem to be a transformation from system uncertainties to estimation errors, where the minimax criterion is adopted to minimize the estimation errors with possibly maximized system uncertainties. The estimation errors, in the form of a covariance matrix, express the measurement uncertainties in a complete way. The framework is then optimized by ∞-norm optimization and solved with the corresponding H ∞ filter. Unlike conventional statistical reconstruction algorithms, that rely on the statistical modeling methods of the measurement data or noise, the proposed joint estimation stands from the point of view of signal energies and can handle from imperfect statistical assumptions to even no a priori statistical assumptions. The performance and accuracy of reconstructed mean and variance images are validated using Monte Carlo simulations. Experiments on phantom scans with a small animal PET scanner and real patient scans are also conducted for assessment of clinical potential. (paper)

  14. Software for 3D diagnostic image reconstruction and analysis

    International Nuclear Information System (INIS)

    Taton, G.; Rokita, E.; Sierzega, M.; Klek, S.; Kulig, J.; Urbanik, A.

    2005-01-01

    Recent advances in computer technologies have opened new frontiers in medical diagnostics. Interesting possibilities are the use of three-dimensional (3D) imaging and the combination of images from different modalities. Software prepared in our laboratories devoted to 3D image reconstruction and analysis from computed tomography and ultrasonography is presented. In developing our software it was assumed that it should be applicable in standard medical practice, i.e. it should work effectively with a PC. An additional feature is the possibility of combining 3D images from different modalities. The reconstruction and data processing can be conducted using a standard PC, so low investment costs result in the introduction of advanced and useful diagnostic possibilities. The program was tested on a PC using DICOM data from computed tomography and TIFF files obtained from a 3D ultrasound system. The results of the anthropomorphic phantom and patient data were taken into consideration. A new approach was used to achieve spatial correlation of two independently obtained 3D images. The method relies on the use of four pairs of markers within the regions under consideration. The user selects the markers manually and the computer calculates the transformations necessary for coupling the images. The main software feature is the possibility of 3D image reconstruction from a series of two-dimensional (2D) images. The reconstructed 3D image can be: (1) viewed with the most popular methods of 3D image viewing, (2) filtered and processed to improve image quality, (3) analyzed quantitatively (geometrical measurements), and (4) coupled with another, independently acquired 3D image. The reconstructed and processed 3D image can be stored at every stage of image processing. The overall software performance was good considering the relatively low costs of the hardware used and the huge data sets processed. The program can be freely used and tested (source code and program available at

  15. Parametric image reconstruction using spectral analysis of PET projection data

    International Nuclear Information System (INIS)

    Meikle, Steven R.; Matthews, Julian C.; Cunningham, Vincent J.; Bailey, Dale L.; Livieratos, Lefteris; Jones, Terry; Price, Pat

    1998-01-01

    Spectral analysis is a general modelling approach that enables calculation of parametric images from reconstructed tracer kinetic data independent of an assumed compartmental structure. We investigated the validity of applying spectral analysis directly to projection data motivated by the advantages that: (i) the number of reconstructions is reduced by an order of magnitude and (ii) iterative reconstruction becomes practical which may improve signal-to-noise ratio (SNR). A dynamic software phantom with typical 2-[ 11 C]thymidine kinetics was used to compare projection-based and image-based methods and to assess bias-variance trade-offs using iterative expectation maximization (EM) reconstruction. We found that the two approaches are not exactly equivalent due to properties of the non-negative least-squares algorithm. However, the differences are small ( 1 and, to a lesser extent, VD). The optimal number of EM iterations was 15-30 with up to a two-fold improvement in SNR over filtered back projection. We conclude that projection-based spectral analysis with EM reconstruction yields accurate parametric images with high SNR and has potential application to a wide range of positron emission tomography ligands. (author)

  16. Generalized Fourier slice theorem for cone-beam image reconstruction.

    Science.gov (United States)

    Zhao, Shuang-Ren; Jiang, Dazong; Yang, Kevin; Yang, Kang

    2015-01-01

    The cone-beam reconstruction theory has been proposed by Kirillov in 1961, Tuy in 1983, Feldkamp in 1984, Smith in 1985, Pierre Grangeat in 1990. The Fourier slice theorem is proposed by Bracewell 1956, which leads to the Fourier image reconstruction method for parallel-beam geometry. The Fourier slice theorem is extended to fan-beam geometry by Zhao in 1993 and 1995. By combining the above mentioned cone-beam image reconstruction theory and the above mentioned Fourier slice theory of fan-beam geometry, the Fourier slice theorem in cone-beam geometry is proposed by Zhao 1995 in short conference publication. This article offers the details of the derivation and implementation of this Fourier slice theorem for cone-beam geometry. Especially the problem of the reconstruction from Fourier domain has been overcome, which is that the value of in the origin of Fourier space is 0/0. The 0/0 type of limit is proper handled. As examples, the implementation results for the single circle and two perpendicular circle source orbits are shown. In the cone-beam reconstruction if a interpolation process is considered, the number of the calculations for the generalized Fourier slice theorem algorithm is O(N^4), which is close to the filtered back-projection method, here N is the image size of 1-dimension. However the interpolation process can be avoid, in that case the number of the calculations is O(N5).

  17. Dynamic PET Image reconstruction for parametric imaging using the HYPR kernel method

    Science.gov (United States)

    Spencer, Benjamin; Qi, Jinyi; Badawi, Ramsey D.; Wang, Guobao

    2017-03-01

    Dynamic PET image reconstruction is a challenging problem because of the ill-conditioned nature of PET and the lowcounting statistics resulted from short time-frames in dynamic imaging. The kernel method for image reconstruction has been developed to improve image reconstruction of low-count PET data by incorporating prior information derived from high-count composite data. In contrast to most of the existing regularization-based methods, the kernel method embeds image prior information in the forward projection model and does not require an explicit regularization term in the reconstruction formula. Inspired by the existing highly constrained back-projection (HYPR) algorithm for dynamic PET image denoising, we propose in this work a new type of kernel that is simpler to implement and further improves the kernel-based dynamic PET image reconstruction. Our evaluation study using a physical phantom scan with synthetic FDG tracer kinetics has demonstrated that the new HYPR kernel-based reconstruction can achieve a better region-of-interest (ROI) bias versus standard deviation trade-off for dynamic PET parametric imaging than the post-reconstruction HYPR denoising method and the previously used nonlocal-means kernel.

  18. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation

    International Nuclear Information System (INIS)

    Zhao, Zhanqi; Möller, Knut; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich

    2014-01-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton–Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR C ) and (4) GREIT with individual thorax geometry (GR T ). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal–Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms. (paper)

  19. The influence of image reconstruction algorithms on linear thorax EIT image analysis of ventilation.

    Science.gov (United States)

    Zhao, Zhanqi; Frerichs, Inéz; Pulletz, Sven; Müller-Lisse, Ullrich; Möller, Knut

    2014-06-01

    Analysis methods of electrical impedance tomography (EIT) images based on different reconstruction algorithms were examined. EIT measurements were performed on eight mechanically ventilated patients with acute respiratory distress syndrome. A maneuver with step increase of airway pressure was performed. EIT raw data were reconstructed offline with (1) filtered back-projection (BP); (2) the Dräger algorithm based on linearized Newton-Raphson (DR); (3) the GREIT (Graz consensus reconstruction algorithm for EIT) reconstruction algorithm with a circular forward model (GR(C)) and (4) GREIT with individual thorax geometry (GR(T)). Individual thorax contours were automatically determined from the routine computed tomography images. Five indices were calculated on the resulting EIT images respectively: (a) the ratio between tidal and deep inflation impedance changes; (b) tidal impedance changes in the right and left lungs; (c) center of gravity; (d) the global inhomogeneity index and (e) ventilation delay at mid-dorsal regions. No significant differences were found in all examined indices among the four reconstruction algorithms (p > 0.2, Kruskal-Wallis test). The examined algorithms used for EIT image reconstruction do not influence the selected indices derived from the EIT image analysis. Indices that validated for images with one reconstruction algorithm are also valid for other reconstruction algorithms.

  20. Image Reconstruction of Metal Pipe in Electrical Resistance Tomography

    Directory of Open Access Journals (Sweden)

    Suzanna RIDZUAN AW

    2017-02-01

    Full Text Available This paper demonstrates a Linear Back Projection (LBP algorithm based on the reconstruction of conductivity distributions to identify different sizes and locations of bubble phantoms in a metal pipe. Both forward and inverse problems are discussed. Reconstructed images of the phantoms under test conditions are presented. From the results, it was justified that the sensitivity maps of the conducting boundary strategy can be applied successfully in identifying the location for the phantom of interest using LBP algorithm. Additionally, the number and spatial distribution of the bubble phantoms can be clearly distinguished at any location in the pipeline. It was also shown that the reconstructed images agree well with the bubble phantoms.

  1. The feasibility of images reconstructed with the method of sieves

    International Nuclear Information System (INIS)

    Veklerov, E.; Llacer, J.

    1990-01-01

    The concept of sieves has been applied with the maximum likelihood estimator (MLE) to image reconstruction. While it makes it possible to recover smooth images consistent with the data, the degree of smoothness provided by it is arbitrary. It is shown that the concept of feasibility is able to resolve this arbitrariness. By varying the values of parameters determining the degree of smoothness, one can generate images on both sides of the feasibility region, as well as within the region. Feasible images recovered by using different sieve parameters are compared with feasible results of other procedures. One- and two-dimensional examples using both simulated and real data sets are considered

  2. Electron image reconstruction of helical protein assemblies

    International Nuclear Information System (INIS)

    Cremers, A.F.M.

    1980-01-01

    The analysis of projections of large ordered biological systems obtained by electron microscopy of negatively stained specimens is described. The biological structures amenable to this approach are constructed from a large number of identical protein molecules, which are arranged according to helical symmetry. Electron images of these structures generally contain sufficient information in order to calculate a three-dimensional density map. (Auth.)

  3. Realise : reconstruction of reality from image sequences

    NARCIS (Netherlands)

    Leymarie, F.; de la Fortelle, A.; Koenderink, Jan J.; Kappers, A. M L; Stavridi, M.; van Ginneken, B.; Muller, S.; Krake, S.; Faugeras, O.; Robert, L.; Gauclin, C.; Laveau, S.; Zeller, C.; Anon,

    1996-01-01

    REALISE has for principal goals to extract from sequences of images, acquired with a moving camera, information necessary for determining the 3D (CAD-like) structure of a real-life scene together with information about the radiometric signatures of surfaces bounding the extracted 3D objects (e.g.

  4. Fluorescence Image Segmentation by using Digitally Reconstructed Fluorescence Images

    OpenAIRE

    Blumer, Clemens; Vivien, Cyprien; Oertner, Thomas G; Vetter, Thomas

    2011-01-01

    In biological experiments fluorescence imaging is used to image living and stimulated neurons. But the analysis of fluorescence images is a difficult task. It is not possible to conclude the shape of an object from fluorescence images alone. Therefore, it is not feasible to get good manual segmented nor ground truth data from fluorescence images. Supervised learning approaches are not possible without training data. To overcome this issues we propose to synthesize fluorescence images and call...

  5. RECONSTRUCTION OF HUMAN LUNG MORPHOLOGY MODELS FROM MAGNETIC RESONANCE IMAGES

    Science.gov (United States)

    Reconstruction of Human Lung Morphology Models from Magnetic Resonance ImagesT. B. Martonen (Experimental Toxicology Division, U.S. EPA, Research Triangle Park, NC 27709) and K. K. Isaacs (School of Public Health, University of North Carolina, Chapel Hill, NC 27514)

  6. Use of a model for 3D image reconstruction

    International Nuclear Information System (INIS)

    Delageniere, S.; Grangeat, P.

    1991-01-01

    We propose a software for 3D image reconstruction in transmission tomography. This software is based on the use of a model and of the RADON algorithm developed at LETI. The introduction of a markovian model helps us to enhance contrast and straitened the natural transitions existing in the objects studied, whereas standard transform methods smoothe them

  7. Image quality of multiplanar reconstruction of pulmonary CT scans using adaptive statistical iterative reconstruction.

    Science.gov (United States)

    Honda, O; Yanagawa, M; Inoue, A; Kikuyama, A; Yoshida, S; Sumikawa, H; Tobino, K; Koyama, M; Tomiyama, N

    2011-04-01

    We investigated the image quality of multiplanar reconstruction (MPR) using adaptive statistical iterative reconstruction (ASIR). Inflated and fixed lungs were scanned with a garnet detector CT in high-resolution mode (HR mode) or non-high-resolution (HR) mode, and MPR images were then reconstructed. Observers compared 15 MPR images of ASIR (40%) and ASIR (80%) with those of ASIR (0%), and assessed image quality using a visual five-point scale (1, definitely inferior; 5, definitely superior), with particular emphasis on normal pulmonary structures, artefacts, noise and overall image quality. The mean overall image quality scores in HR mode were 3.67 with ASIR (40%) and 4.97 with ASIR (80%). Those in non-HR mode were 3.27 with ASIR (40%) and 3.90 with ASIR (80%). The mean artefact scores in HR mode were 3.13 with ASIR (40%) and 3.63 with ASIR (80%), but those in non-HR mode were 2.87 with ASIR (40%) and 2.53 with ASIR (80%). The mean scores of the other parameters were greater than 3, whereas those in HR mode were higher than those in non-HR mode. There were significant differences between ASIR (40%) and ASIR (80%) in overall image quality (pASIR did not suppress the severe artefacts of contrast medium. In general, MPR image quality with ASIR (80%) was superior to that with ASIR (40%). However, there was an increased incidence of artefacts by ASIR when CT images were obtained in non-HR mode.

  8. Bayesian PET image reconstruction incorporating anato-functional joint entropy

    International Nuclear Information System (INIS)

    Tang Jing; Rahmim, Arman

    2009-01-01

    We developed a maximum a posterior (MAP) reconstruction method for positron emission tomography (PET) image reconstruction incorporating magnetic resonance (MR) image information, with the joint entropy between the PET and MR image features serving as the regularization constraint. A non-parametric method was used to estimate the joint probability density of the PET and MR images. Using realistically simulated PET and MR human brain phantoms, the quantitative performance of the proposed algorithm was investigated. Incorporation of the anatomic information via this technique, after parameter optimization, was seen to dramatically improve the noise versus bias tradeoff in every region of interest, compared to the result from using conventional MAP reconstruction. In particular, hot lesions in the FDG PET image, which had no anatomical correspondence in the MR image, also had improved contrast versus noise tradeoff. Corrections were made to figures 3, 4 and 6, and to the second paragraph of section 3.1 on 13 November 2009. The corrected electronic version is identical to the print version.

  9. An automated 3D reconstruction method of UAV images

    Science.gov (United States)

    Liu, Jun; Wang, He; Liu, Xiaoyang; Li, Feng; Sun, Guangtong; Song, Ping

    2015-10-01

    In this paper a novel fully automated 3D reconstruction approach based on low-altitude unmanned aerial vehicle system (UAVs) images will be presented, which does not require previous camera calibration or any other external prior knowledge. Dense 3D point clouds are generated by integrating orderly feature extraction, image matching, structure from motion (SfM) and multi-view stereo (MVS) algorithms, overcoming many of the cost, time limitations of rigorous photogrammetry techniques. An image topology analysis strategy is introduced to speed up large scene reconstruction by taking advantage of the flight-control data acquired by UAV. Image topology map can significantly reduce the running time of feature matching by limiting the combination of images. A high-resolution digital surface model of the study area is produced base on UAV point clouds by constructing the triangular irregular network. Experimental results show that the proposed approach is robust and feasible for automatic 3D reconstruction of low-altitude UAV images, and has great potential for the acquisition of spatial information at large scales mapping, especially suitable for rapid response and precise modelling in disaster emergency.

  10. Improvement of Quality of Reconstructed Images in Multi-Frame Fresnel Digital Holography

    International Nuclear Information System (INIS)

    Xiao-Wei, Lu; Jing-Zhen, Li; Hong-Yi, Chen

    2010-01-01

    A modified reconstruction algorithm to improve the quality of reconstructed images of multi-frame Fresnel digital holography is presented. When the reference beams are plane or spherical waves with azimuth encoding, by introducing two spherical wave factors, images can be reconstructed with only one time Fourier transform. In numerical simulation, this algorithm could simplify the reconstruction process and improve the signal-to-noise ratio of the reconstructed images. In single-frame reconstruction experiments, the accurate reconstructed image is obtained with this simplified algorithm

  11. Terahertz Imaging for Biomedical Applications Pattern Recognition and Tomographic Reconstruction

    CERN Document Server

    Yin, Xiaoxia; Abbott, Derek

    2012-01-01

    Terahertz Imaging for Biomedical Applications: Pattern Recognition and Tomographic Reconstruction presents the necessary algorithms needed to assist screening, diagnosis, and treatment, and these algorithms will play a critical role in the accurate detection of abnormalities present in biomedical imaging. Terahertz biomedical imaging has become an area of interest due to its ability to simultaneously acquire both image and spectral information. Terahertz imaging systems are being commercialized with an increasing number of trials performed in a biomedical setting. Terahertz tomographic imaging and detection technology contributes to the ability to identify opaque objects with clear boundaries,and would be useful to both in vivo and ex vivo environments. This book also: Introduces terahertz radiation techniques and provides a number of topical examples of signal and image processing, as well as machine learning Presents the most recent developments in an emerging field, terahertz radiation Utilizes new methods...

  12. Three-dimensional reconstruction of functional brain images

    International Nuclear Information System (INIS)

    Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao

    1999-01-01

    We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: routine images by SPM, three-dimensional static images, and three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface

  13. Three-dimensional reconstruction of functional brain images

    Energy Technology Data Exchange (ETDEWEB)

    Inoue, Masato; Shoji, Kazuhiko; Kojima, Hisayoshi; Hirano, Shigeru; Naito, Yasushi; Honjo, Iwao [Kyoto Univ. (Japan)

    1999-08-01

    We consider PET (positron emission tomography) measurement with SPM (Statistical Parametric Mapping) analysis to be one of the most useful methods to identify activated areas of the brain involved in language processing. SPM is an effective analytical method that detects markedly activated areas over the whole brain. However, with the conventional presentations of these functional brain images, such as horizontal slices, three directional projection, or brain surface coloring, makes understanding and interpreting the positional relationships among various brain areas difficult. Therefore, we developed three-dimensionally reconstructed images from these functional brain images to improve the interpretation. The subjects were 12 normal volunteers. The following three types of images were constructed: routine images by SPM, three-dimensional static images, and three-dimensional dynamic images, after PET images were analyzed by SPM during daily dialog listening. The creation of images of both the three-dimensional static and dynamic types employed the volume rendering method by VTK (The Visualization Toolkit). Since the functional brain images did not include original brain images, we synthesized SPM and MRI brain images by self-made C++ programs. The three-dimensional dynamic images were made by sequencing static images with available software. Images of both the three-dimensional static and dynamic types were processed by a personal computer system. Our newly created images showed clearer positional relationships among activated brain areas compared to the conventional method. To date, functional brain images have been employed in fields such as neurology or neurosurgery, however, these images may be useful even in the field of otorhinolaryngology, to assess hearing and speech. Exact three-dimensional images based on functional brain images are important for exact and intuitive interpretation, and may lead to new developments in brain science. Currently, the surface

  14. Sparse representation based image interpolation with nonlocal autoregressive modeling.

    Science.gov (United States)

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

    2013-04-01

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

  15. Sparse Reconstruction Schemes for Nonlinear Electromagnetic Imaging

    KAUST Repository

    Desmal, Abdulla

    2016-03-01

    Electromagnetic imaging is the problem of determining material properties from scattered fields measured away from the domain under investigation. Solving this inverse problem is a challenging task because (i) it is ill-posed due to the presence of (smoothing) integral operators used in the representation of scattered fields in terms of material properties, and scattered fields are obtained at a finite set of points through noisy measurements; and (ii) it is nonlinear simply due the fact that scattered fields are nonlinear functions of the material properties. The work described in this thesis tackles the ill-posedness of the electromagnetic imaging problem using sparsity-based regularization techniques, which assume that the scatterer(s) occupy only a small fraction of the investigation domain. More specifically, four novel imaging methods are formulated and implemented. (i) Sparsity-regularized Born iterative method iteratively linearizes the nonlinear inverse scattering problem and each linear problem is regularized using an improved iterative shrinkage algorithm enforcing the sparsity constraint. (ii) Sparsity-regularized nonlinear inexact Newton method calls for the solution of a linear system involving the Frechet derivative matrix of the forward scattering operator at every iteration step. For faster convergence, the solution of this matrix system is regularized under the sparsity constraint and preconditioned by leveling the matrix singular values. (iii) Sparsity-regularized nonlinear Tikhonov method directly solves the nonlinear minimization problem using Landweber iterations, where a thresholding function is applied at every iteration step to enforce the sparsity constraint. (iv) This last scheme is accelerated using a projected steepest descent method when it is applied to three-dimensional investigation domains. Projection replaces the thresholding operation and enforces the sparsity constraint. Numerical experiments, which are carried out using

  16. A novel data processing technique for image reconstruction of penumbral imaging

    Science.gov (United States)

    Xie, Hongwei; Li, Hongyun; Xu, Zeping; Song, Guzhou; Zhang, Faqiang; Zhou, Lin

    2011-06-01

    CT image reconstruction technique was applied to the data processing of the penumbral imaging. Compared with other traditional processing techniques for penumbral coded pinhole image such as Wiener, Lucy-Richardson and blind technique, this approach is brand new. In this method, the coded aperture processing method was used for the first time independent to the point spread function of the image diagnostic system. In this way, the technical obstacles was overcome in the traditional coded pinhole image processing caused by the uncertainty of point spread function of the image diagnostic system. Then based on the theoretical study, the simulation of penumbral imaging and image reconstruction was carried out to provide fairly good results. While in the visible light experiment, the point source of light was used to irradiate a 5mm×5mm object after diffuse scattering and volume scattering. The penumbral imaging was made with aperture size of ~20mm. Finally, the CT image reconstruction technique was used for image reconstruction to provide a fairly good reconstruction result.

  17. Scattering calculation and image reconstruction using elevation-focused beams.

    Science.gov (United States)

    Duncan, David P; Astheimer, Jeffrey P; Waag, Robert C

    2009-05-01

    Pressure scattered by cylindrical and spherical objects with elevation-focused illumination and reception has been analytically calculated, and corresponding cross sections have been reconstructed with a two-dimensional algorithm. Elevation focusing was used to elucidate constraints on quantitative imaging of three-dimensional objects with two-dimensional algorithms. Focused illumination and reception are represented by angular spectra of plane waves that were efficiently computed using a Fourier interpolation method to maintain the same angles for all temporal frequencies. Reconstructions were formed using an eigenfunction method with multiple frequencies, phase compensation, and iteration. The results show that the scattered pressure reduces to a two-dimensional expression, and two-dimensional algorithms are applicable when the region of a three-dimensional object within an elevation-focused beam is approximately constant in elevation. The results also show that energy scattered out of the reception aperture by objects contained within the focused beam can result in the reconstructed values of attenuation slope being greater than true values at the boundary of the object. Reconstructed sound speed images, however, appear to be relatively unaffected by the loss in scattered energy. The broad conclusion that can be drawn from these results is that two-dimensional reconstructions require compensation to account for uncaptured three-dimensional scattering.

  18. Three-dimensional image reconstruction from stereo DSA

    International Nuclear Information System (INIS)

    Sakamoto, Kiyoshi; Kotoura, Noriko; Umehara, Takayoshi; Yamada, Eiji; Inaba, Tomohiro; Itou, Hiroshi

    1999-01-01

    The technique of interventional radiology has spread rapidly in recent years, and three-dimensional information from blood vessel images is being sought to enhance examinations. Stereo digital subtraction angiography (DSA) and rotational DSA were developed for that purpose. However, it is difficult with stereo DSA to observe the image pair during examination and to obtain positional information on blood vessels. Further, the exposure dose is increased in rotational DSA when many mask images need to be collected, and the patient is required to hold his or her breath for a long duration. We therefore devised a technique to construct three-dimensional blood vessel images by employing geometrical information extracted from stereo DSA images using the right and left images. We used a judgment method based on the correlation coefficient, although we had to extract an equal blood vessel from the right and left images to determine the three-dimensional coordinates of the blood vessel. The reconstructed three-dimensional blood vessels were projected from various angles, again by using a virtual focus, and new images were created. These image groups were displayed as rotational images by the animation display function incorporated in the DSA device. This system can observe blood vessel images of the same phase at a free angle, although the image quality is inferior to that of rotational DSA. In addition, because collection of the mask images is reduced, exposure dose can be decreased. Further, the system offers enhanced safety because no mechanical movement of the imaging system is involved. (author)

  19. Image quality of iterative reconstruction in cranial CT imaging: comparison of model-based iterative reconstruction (MBIR) and adaptive statistical iterative reconstruction (ASiR).

    Science.gov (United States)

    Notohamiprodjo, S; Deak, Z; Meurer, F; Maertz, F; Mueck, F G; Geyer, L L; Wirth, S

    2015-01-01

    The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p ASiR was 2 (p ASiR (p ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. • Model-Based iterative reconstruction (MBIR) effectively decreased artefacts in cranial CT. • MBIR reconstructed images were rated with significantly higher scores for image quality. • Model-Based iterative reconstruction may allow reduced-dose diagnostic examination protocols.

  20. Optimized 3D Street Scene Reconstruction from Driving Recorder Images

    Directory of Open Access Journals (Sweden)

    Yongjun Zhang

    2015-07-01

    Full Text Available The paper presents an automatic region detection based method to reconstruct street scenes from driving recorder images. The driving recorder in this paper is a dashboard camera that collects images while the motor vehicle is moving. An enormous number of moving vehicles are included in the collected data because the typical recorders are often mounted in the front of moving vehicles and face the forward direction, which can make matching points on vehicles and guardrails unreliable. Believing that utilizing these image data can reduce street scene reconstruction and updating costs because of their low price, wide use, and extensive shooting coverage, we therefore proposed a new method, which is called the Mask automatic detecting method, to improve the structure results from the motion reconstruction. Note that we define vehicle and guardrail regions as “mask” in this paper since the features on them should be masked out to avoid poor matches. After removing the feature points in our new method, the camera poses and sparse 3D points that are reconstructed with the remaining matches. Our contrast experiments with the typical pipeline of structure from motion (SfM reconstruction methods, such as Photosynth and VisualSFM, demonstrated that the Mask decreased the root-mean-square error (RMSE of the pairwise matching results, which led to more accurate recovering results from the camera-relative poses. Removing features from the Mask also increased the accuracy of point clouds by nearly 30%–40% and corrected the problems of the typical methods on repeatedly reconstructing several buildings when there was only one target building.

  1. Analyser-based phase contrast image reconstruction using geometrical optics

    International Nuclear Information System (INIS)

    Kitchen, M J; Pavlov, K M; Siu, K K W; Menk, R H; Tromba, G; Lewis, R A

    2007-01-01

    Analyser-based phase contrast imaging can provide radiographs of exceptional contrast at high resolution (<100 μm), whilst quantitative phase and attenuation information can be extracted using just two images when the approximations of geometrical optics are satisfied. Analytical phase retrieval can be performed by fitting the analyser rocking curve with a symmetric Pearson type VII function. The Pearson VII function provided at least a 10% better fit to experimentally measured rocking curves than linear or Gaussian functions. A test phantom, a hollow nylon cylinder, was imaged at 20 keV using a Si(1 1 1) analyser at the ELETTRA synchrotron radiation facility. Our phase retrieval method yielded a more accurate object reconstruction than methods based on a linear fit to the rocking curve. Where reconstructions failed to map expected values, calculations of the Takagi number permitted distinction between the violation of the geometrical optics conditions and the failure of curve fitting procedures. The need for synchronized object/detector translation stages was removed by using a large, divergent beam and imaging the object in segments. Our image acquisition and reconstruction procedure enables quantitative phase retrieval for systems with a divergent source and accounts for imperfections in the analyser

  2. Robust linearized image reconstruction for multifrequency EIT of the breast.

    Science.gov (United States)

    Boverman, Gregory; Kao, Tzu-Jen; Kulkarni, Rujuta; Kim, Bong Seok; Isaacson, David; Saulnier, Gary J; Newell, Jonathan C

    2008-10-01

    Electrical impedance tomography (EIT) is a developing imaging modality that is beginning to show promise for detecting and characterizing tumors in the breast. At Rensselaer Polytechnic Institute, we have developed a combined EIT-tomosynthesis system that allows for the coregistered and simultaneous analysis of the breast using EIT and X-ray imaging. A significant challenge in EIT is the design of computationally efficient image reconstruction algorithms which are robust to various forms of model mismatch. Specifically, we have implemented a scaling procedure that is robust to the presence of a thin highly-resistive layer of skin at the boundary of the breast and we have developed an algorithm to detect and exclude from the image reconstruction electrodes that are in poor contact with the breast. In our initial clinical studies, it has been difficult to ensure that all electrodes make adequate contact with the breast, and thus procedures for the use of data sets containing poorly contacting electrodes are particularly important. We also present a novel, efficient method to compute the Jacobian matrix for our linearized image reconstruction algorithm by reducing the computation of the sensitivity for each voxel to a quadratic form. Initial clinical results are presented, showing the potential of our algorithms to detect and localize breast tumors.

  3. Development of Image Reconstruction Algorithms in electrical Capacitance Tomography

    International Nuclear Information System (INIS)

    Fernandez Marron, J. L.; Alberdi Primicia, J.; Barcala Riveira, J. M.

    2007-01-01

    The Electrical Capacitance Tomography (ECT) has not obtained a good development in order to be used at industrial level. That is due first to difficulties in the measurement of very little capacitances (in the range of femto farads) and second to the problem of reconstruction on- line of the images. This problem is due also to the small numbers of electrodes (maximum 16), that made the usual algorithms of reconstruction has many errors. In this work it is described a new purely geometrical method that could be used for this purpose. (Author) 4 refs

  4. 3D Tomographic Image Reconstruction using CUDA C

    International Nuclear Information System (INIS)

    Dominguez, J. S.; Assis, J. T.; Oliveira, L. F. de

    2011-01-01

    This paper presents the study and implementation of a software for three dimensional reconstruction of images obtained with a tomographic system using the capabilities of Graphic Processing Units(GPU). The reconstruction by filtered back-projection method was developed using the CUDA C, for maximum utilization of the processing capabilities of GPUs to solve computational problems with large computational cost and highly parallelizable. It was discussed the potential of GPUs and shown its advantages to solving this kind of problems. The results in terms of runtime will be compared with non-parallelized implementations and must show a great reduction of processing time. (Author)

  5. Scattering Correction For Image Reconstruction In Flash Radiography

    International Nuclear Information System (INIS)

    Cao, Liangzhi; Wang, Mengqi; Wu, Hongchun; Liu, Zhouyu; Cheng, Yuxiong; Zhang, Hongbo

    2013-01-01

    Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency

  6. Scattering Correction For Image Reconstruction In Flash Radiography

    Energy Technology Data Exchange (ETDEWEB)

    Cao, Liangzhi; Wang, Mengqi; Wu, Hongchun; Liu, Zhouyu; Cheng, Yuxiong; Zhang, Hongbo [Xi' an Jiaotong Univ., Xi' an (China)

    2013-08-15

    Scattered photons cause blurring and distortions in flash radiography, reducing the accuracy of image reconstruction significantly. The effect of the scattered photons is taken into account and an iterative deduction of the scattered photons is proposed to amend the scattering effect for image restoration. In order to deduct the scattering contribution, the flux of scattered photons is estimated as the sum of two components. The single scattered component is calculated accurately together with the uncollided flux along the characteristic ray, while the multiple scattered component is evaluated using correction coefficients pre-obtained from Monte Carlo simulations.The arbitrary geometry pretreatment and ray tracing are carried out based on the customization of AutoCAD. With the above model, an Iterative Procedure for image restORation code, IPOR, is developed. Numerical results demonstrate that the IPOR code is much more accurate than the direct reconstruction solution without scattering correction and it has a very high computational efficiency.

  7. 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...

  8. Monte-Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography

    International Nuclear Information System (INIS)

    Gillam, John E.; Rafecas, Magdalena

    2016-01-01

    Emission imaging incorporates both the development of dedicated devices for data acquisition as well as algorithms for recovering images from that data. Emission tomography is an indirect approach to imaging. The effect of device modification on the final image can be understood through both the way in which data are gathered, using simulation, and the way in which the image is formed from that data, or image reconstruction. When developing novel devices, systems and imaging tasks, accurate simulation and image reconstruction allow performance to be estimated, and in some cases optimized, using computational methods before or during the process of physical construction. However, there are a vast range of approaches, algorithms and pre-existing computational tools that can be exploited and the choices made will affect the accuracy of the in silico results and quality of the reconstructed images. On the one hand, should important physical effects be neglected in either the simulation or reconstruction steps, specific enhancements provided by novel devices may not be represented in the results. On the other hand, over-modeling of device characteristics in either step leads to large computational overheads that can confound timely results. Here, a range of simulation methodologies and toolkits are discussed, as well as reconstruction algorithms that may be employed in emission imaging. The relative advantages and disadvantages of a range of options are highlighted using specific examples from current research scenarios.

  9. Monte-Carlo simulations and image reconstruction for novel imaging scenarios in emission tomography

    Energy Technology Data Exchange (ETDEWEB)

    Gillam, John E. [The University of Sydney, Faculty of Health Sciences and The Brain and Mind Centre, Camperdown (Australia); Rafecas, Magdalena, E-mail: rafecas@imt.uni-luebeck.de [University of Lubeck, Institute of Medical Engineering, Ratzeburger Allee 160, 23538 Lübeck (Germany)

    2016-02-11

    Emission imaging incorporates both the development of dedicated devices for data acquisition as well as algorithms for recovering images from that data. Emission tomography is an indirect approach to imaging. The effect of device modification on the final image can be understood through both the way in which data are gathered, using simulation, and the way in which the image is formed from that data, or image reconstruction. When developing novel devices, systems and imaging tasks, accurate simulation and image reconstruction allow performance to be estimated, and in some cases optimized, using computational methods before or during the process of physical construction. However, there are a vast range of approaches, algorithms and pre-existing computational tools that can be exploited and the choices made will affect the accuracy of the in silico results and quality of the reconstructed images. On the one hand, should important physical effects be neglected in either the simulation or reconstruction steps, specific enhancements provided by novel devices may not be represented in the results. On the other hand, over-modeling of device characteristics in either step leads to large computational overheads that can confound timely results. Here, a range of simulation methodologies and toolkits are discussed, as well as reconstruction algorithms that may be employed in emission imaging. The relative advantages and disadvantages of a range of options are highlighted using specific examples from current research scenarios.

  10. SIRFING: Sparse Image Reconstruction For INterferometry using GPUs

    Science.gov (United States)

    Cranmer, Miles; Garsden, Hugh; Mitchell, Daniel A.; Greenhill, Lincoln

    2018-01-01

    We present a deconvolution code for radio interferometric imaging based on the compressed sensing algorithms in Garsden et al. (2015). Being computationally intensive, compressed sensing is ripe for parallelization over GPUs. Our compressed sensing implementation generates images using wavelets, and we have ported the underlying wavelet library to CUDA, targeting the spline filter reconstruction part of the algorithm. The speedup achieved is almost an order of magnitude. The code is modular but is also being integrated into the calibration and imaging pipeline in use by the LEDA project at the Long Wavelength Array (LWA) as well as by the Murchinson Widefield Array (MWA).

  11. The SRT reconstruction algorithm for semiquantification in PET imaging

    Energy Technology Data Exchange (ETDEWEB)

    Kastis, George A., E-mail: gkastis@academyofathens.gr [Research Center of Mathematics, Academy of Athens, Athens 11527 (Greece); Gaitanis, Anastasios [Biomedical Research Foundation of the Academy of Athens (BRFAA), Athens 11527 (Greece); Samartzis, Alexandros P. [Nuclear Medicine Department, Evangelismos General Hospital, Athens 10676 (Greece); Fokas, Athanasios S. [Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB30WA, United Kingdom and Research Center of Mathematics, Academy of Athens, Athens 11527 (Greece)

    2015-10-15

    Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of {sup 18}F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT

  12. The SRT reconstruction algorithm for semiquantification in PET imaging

    International Nuclear Information System (INIS)

    Kastis, George A.; Gaitanis, Anastasios; Samartzis, Alexandros P.; Fokas, Athanasios S.

    2015-01-01

    Purpose: The spline reconstruction technique (SRT) is a new, fast algorithm based on a novel numerical implementation of an analytic representation of the inverse Radon transform. The mathematical details of this algorithm and comparisons with filtered backprojection were presented earlier in the literature. In this study, the authors present a comparison between SRT and the ordered-subsets expectation–maximization (OSEM) algorithm for determining contrast and semiquantitative indices of 18 F-FDG uptake. Methods: The authors implemented SRT in the software for tomographic image reconstruction (STIR) open-source platform and evaluated this technique using simulated and real sinograms obtained from the GE Discovery ST positron emission tomography/computer tomography scanner. All simulations and reconstructions were performed in STIR. For OSEM, the authors used the clinical protocol of their scanner, namely, 21 subsets and two iterations. The authors also examined images at one, four, six, and ten iterations. For the simulation studies, the authors analyzed an image-quality phantom with cold and hot lesions. Two different versions of the phantom were employed at two different hot-sphere lesion-to-background ratios (LBRs), namely, 2:1 and 4:1. For each noiseless sinogram, 20 Poisson realizations were created at five different noise levels. In addition to making visual comparisons of the reconstructed images, the authors determined contrast and bias as a function of the background image roughness (IR). For the real-data studies, sinograms of an image-quality phantom simulating the human torso were employed. The authors determined contrast and LBR as a function of the background IR. Finally, the authors present plots of contrast as a function of IR after smoothing each reconstructed image with Gaussian filters of six different sizes. Statistical significance was determined by employing the Wilcoxon rank-sum test. Results: In both simulated and real studies, SRT

  13. Observation of Eye Pattern on Super-Resolution Near-Field Structure Disk with Write-Strategy Technique

    Science.gov (United States)

    Fuji, Hiroshi; Kikukawa, Takashi; Tominaga, Junji

    2004-07-01

    Pit-edge recording at a density of 150 nm pits and spaces is carried out on a super-resolution near-field structure (super-RENS) disk with a platinum oxide layer. Pits are recorded and read using a 635-nm-wavelength laser and an objective lens with a 0.6 numerical aperture. We arrange laser pulses to correctly record the pits on the disk by a write-strategy technique. The laser-pulse figure includes a unit time of 0.25 T and intensities of Pw1, Pw2 and Pw3. After recording pits of various lengths, the observation of an eye pattern is achieved despite a pit smaller than the resolution limit. Furthermore, the eye pattern maintains its shape even though other pits fill the adjacent tracks at a track density of 600 nm. The disk can be used as a pit-edge recording system through a write-strategy technique.

  14. Super-resolution nanofabrication with metal-ion doped hybrid material through an optical dual-beam approach

    International Nuclear Information System (INIS)

    Cao, Yaoyu; Li, Xiangping; Gu, Min

    2014-01-01

    We apply an optical dual-beam approach to a metal-ion doped hybrid material to achieve nanofeatures beyond the optical diffraction limit. By spatially inhibiting the photoreduction and the photopolymerization, we realize a nano-line, consisting of polymer matrix and in-situ generated gold nanoparticles, with a lateral size of sub 100 nm, corresponding to a factor of 7 improvement compared to the diffraction limit. With the existence of gold nanoparticles, a plasmon enhanced super-resolution fabrication mechanism in the hybrid material is observed, which benefits in a further reduction in size of the fabricated feature. The demonstrated nanofeature in hybrid materials paves the way for realizing functional nanostructures

  15. A numerical study of super-resolution through fast 3D wideband algorithm for scattering in highly-heterogeneous media

    KAUST Repository

    Létourneau, Pierre-David

    2016-09-19

    We present a wideband fast algorithm capable of accurately computing the full numerical solution of the problem of acoustic scattering of waves by multiple finite-sized bodies such as spherical scatterers in three dimensions. By full solution, we mean that no assumption (e.g. Rayleigh scattering, geometrical optics, weak scattering, Born single scattering, etc.) is necessary regarding the properties of the scatterers, their distribution or the background medium. The algorithm is also fast in the sense that it scales linearly with the number of unknowns. We use this algorithm to study the phenomenon of super-resolution in time-reversal refocusing in highly-scattering media recently observed experimentally (Lemoult et al., 2011), and provide numerical arguments towards the fact that such a phenomenon can be explained through a homogenization theory.

  16. 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

  17. D Reconstruction from Uav-Based Hyperspectral Images

    Science.gov (United States)

    Liu, L.; Xu, L.; Peng, J.

    2018-04-01

    Reconstructing the 3D profile from a set of UAV-based images can obtain hyperspectral information, as well as the 3D coordinate of any point on the profile. Our images are captured from the Cubert UHD185 (UHD) hyperspectral camera, which is a new type of high-speed onboard imaging spectrometer. And it can get both hyperspectral image and panchromatic image simultaneously. The panchromatic image have a higher spatial resolution than hyperspectral image, but each hyperspectral image provides considerable information on the spatial spectral distribution of the object. Thus there is an opportunity to derive a high quality 3D point cloud from panchromatic image and considerable spectral information from hyperspectral image. The purpose of this paper is to introduce our processing chain that derives a database which can provide hyperspectral information and 3D position of each point. First, We adopt a free and open-source software, Visual SFM which is based on structure from motion (SFM) algorithm, to recover 3D point cloud from panchromatic image. And then get spectral information of each point from hyperspectral image by a self-developed program written in MATLAB. The production can be used to support further research and applications.

  18. Antimicrobial agent triclosan disrupts mitochondrial structure, revealed by super-resolution microscopy, and inhibits mast cell signaling via calcium modulation.

    Science.gov (United States)

    Weatherly, Lisa M; Nelson, Andrew J; Shim, Juyoung; Riitano, Abigail M; Gerson, Erik D; Hart, Andrew J; de Juan-Sanz, Jaime; Ryan, Timothy A; Sher, Roger; Hess, Samuel T; Gosse, Julie A

    2018-06-15

    The antimicrobial agent triclosan (TCS) is used in products such as toothpaste and surgical soaps and is readily absorbed into oral mucosa and human skin. These and many other tissues contain mast cells, which are involved in numerous physiologies and diseases. Mast cells release chemical mediators through a process termed degranulation, which is inhibited by TCS. Investigation into the underlying mechanisms led to the finding that TCS is a mitochondrial uncoupler at non-cytotoxic, low-micromolar doses in several cell types and live zebrafish. Our aim was to determine the mechanisms underlying TCS disruption of mitochondrial function and of mast cell signaling. We combined super-resolution (fluorescence photoactivation localization) microscopy and multiple fluorescence-based assays to detail triclosan's effects in living mast cells, fibroblasts, and primary human keratinocytes. TCS disrupts mitochondrial nanostructure, causing mitochondria to undergo fission and to form a toroidal, "donut" shape. TCS increases reactive oxygen species production, decreases mitochondrial membrane potential, and disrupts ER and mitochondrial Ca 2+ levels, processes that cause mitochondrial fission. TCS is 60 × more potent than the banned uncoupler 2,4-dinitrophenol. TCS inhibits mast cell degranulation by decreasing mitochondrial membrane potential, disrupting microtubule polymerization, and inhibiting mitochondrial translocation, which reduces Ca 2+ influx into the cell. Our findings provide mechanisms for both triclosan's inhibition of mast cell signaling and its universal disruption of mitochondria. These mechanisms provide partial explanations for triclosan's adverse effects on human reproduction, immunology, and development. This study is the first to utilize super-resolution microscopy in the field of toxicology. Copyright © 2018 Elsevier Inc. All rights reserved.

  19. Comparison of power spectra for tomosynthesis projections and reconstructed images

    International Nuclear Information System (INIS)

    Engstrom, Emma; Reiser, Ingrid; Nishikawa, Robert

    2009-01-01

    Burgess et al. [Med. Phys. 28, 419-437 (2001)] showed that the power spectrum of mammographic breast background follows a power law and that lesion detectability is affected by the power-law exponent β which measures the amount of structure in the background. Following the study of Burgess et al., the authors measured and compared the power-law exponent of mammographic backgrounds in tomosynthesis projections and reconstructed slices to investigate the effect of tomosynthesis imaging on background structure. Our data set consisted of 55 patient cases. For each case, regions of interest (ROIs) were extracted from both projection images and reconstructed slices. The periodogram of each ROI was computed by taking the squared modulus of the Fourier transform of the ROI. The power-law exponent was determined for each periodogram and averaged across all ROIs extracted from all projections or reconstructed slices for each patient data set. For the projections, the mean β averaged across the 55 cases was 3.06 (standard deviation of 0.21), while it was 2.87 (0.24) for the corresponding reconstructions. The difference in β for a given patient between the projection ROIs and the reconstructed ROIs averaged across the 55 cases was 0.194, which was statistically significant (p<0.001). The 95% CI for the difference between the mean value of β for the projections and reconstructions was [0.170, 0.218]. The results are consistent with the observation that the amount of breast structure in the tomosynthesis slice is reduced compared to projection mammography and that this may lead to improved lesion detectability.

  20. Graph-cut based discrete-valued image reconstruction.

    Science.gov (United States)

    Tuysuzoglu, Ahmet; Karl, W Clem; Stojanovic, Ivana; Castañòn, David; Ünlü, M Selim

    2015-05-01

    Efficient graph-cut methods have been used with great success for labeling and denoising problems occurring in computer vision. Unfortunately, the presence of linear image mappings has prevented the use of these techniques in most discrete-amplitude image reconstruction problems. In this paper, we develop a graph-cut based framework for the direct solution of discrete amplitude linear image reconstruction problems cast as regularized energy function minimizations. We first analyze the structure of discrete linear inverse problem cost functions to show that the obstacle to the application of graph-cut methods to their solution is the variable mixing caused by the presence of the linear sensing operator. We then propose to use a surrogate energy functional that overcomes the challenges imposed by the sensing operator yet can be utilized efficiently in existing graph-cut frameworks. We use this surrogate energy functional to devise a monotonic iterative algorithm for the solution of discrete valued inverse problems. We first provide experiments using local convolutional operators and show the robustness of the proposed technique to noise and stability to changes in regularization parameter. Then we focus on nonlocal, tomographic examples where we consider limited-angle data problems. We compare our technique with state-of-the-art discrete and continuous image reconstruction techniques. Experiments show that the proposed method outperforms state-of-the-art techniques in challenging scenarios involving discrete valued unknowns.