- 标题
- 摘要
- 关键词
- 实验方案
- 产品
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Locality estimates for Fresnel-wave-propagation and stability of x-ray phase contrast imaging with finite detectors
摘要： Coherent wave-propagation in the near-field Fresnel-regime is the underlying contrast-mechanism to (propagation-based) x-ray phase contrast imaging (XPCI), an emerging lensless technique that enables 2D- and 3D-imaging of biological soft tissues and other light-element samples down to nanometer-resolutions. Mathematically, propagation is described by the Fresnel-propagator, a convolution with an arbitrarily non-local kernel. As real-world detectors may only capture a finite field-of-view, this non-locality implies that the recorded diffraction-patterns are necessarily incomplete. This raises the question of stability of image-reconstruction from the truncated data—even if the complex-valued wave-field, and not just its modulus, could be measured. Contrary to the latter restriction of the acquisition, known as the phase-problem, the finite-detector-problem has not received much attention in literature. The present work therefore analyzes locality of Fresnel-propagation in order to establish stability of XPCI with finite detectors. Image-reconstruction is shown to be severely ill-posed in this setting—even without a phase-problem. However, quantitative estimates of the leaked wave-field reveal that Lipschitz-stability holds down to a sharp resolution limit that depends on the detector-size and varies within the field-of-view. The smallest resolvable lengthscale is found to be ≈1/–f times the detector’s aspect length, where –f is the Fresnel number associated with the latter scale. The stability results are extended to phaseless imaging in the linear contrast-transfer-function regime.
关键词： resolution,phase contrast,image reconstruction,stability,x-ray imaging,Fresnel propagation
更新于2025-09-23 15:21:21
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Lower Power, Better Uniformity, and Stability CBRAM Enabled by Graphene Nanohole Interface Engineering
摘要： With the steadily increasing spatial resolution of synthetic aperture radar images, the need for a consistent but locally adaptive image enhancement rises considerably. Numerous studies already showed that adaptive multilooking, able to adjust the degree of smoothing locally to the size of the targets, is superior to uniform multilooking. This study introduces a novel approach of multiscale and multidirectional multilooking based on intensity images exclusively but applicable to an arbitrary number of image layers. A set of 2-D circular and elliptical filter kernels in different scales and orientations (named Schmittlets) is derived from hyperbolic functions. The original intensity image is transformed into the Schmittlet coefficient domain where each coefficient measures the existence of Schmittlet-like structures in the image. By estimating their significance via the perturbation-based noise model, the best-fitting Schmittlets are selected for image reconstruction. On the one hand, the index image indicating the locally best-fitting Schmittlets is utilized to consistently enhance further image layers, e.g., multipolarized, multitemporal, or multifrequency layers, and on the other hand, it provides an optimal description of spatial patterns valuable for further image analysis. The final validation proves the advantages of the Schmittlets over six contemporary speckle reduction techniques in six different categories (preservation of the mean intensity, equivalent number of looks, and preservation of edges and local curvature both in strength and in direction) by the help of four test sites on three resolution levels. The additional value of the Schmittlet index layer for automated image interpretation, although obvious, still is subject to further studies.
关键词： image reconstruction,image representations,Adaptive filters,image edge analysis,image enhancement,synthetic aperture radar (SAR),image analysis,digital filters
更新于2025-09-23 15:21:01
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Geometric distortion correction of long-range imaging containing moving objects
摘要： Video sequences of long-range imaging are inevitably affected by optical turbulence, which leads to non-uniform geometric distortion and object position shifts. Restoration of this turbulence-degraded data containing moving objects is a challenging task, which essentially involves in video stabilization and moving objects detection. In this work, a novel method for simultaneously realizing turbulence mitigation and moving objects detection is proposed in such scenarios. We firstly model the turbulent foreground with a specific mixture of Gaussian (MoG) distribution, which is regularized online by the low-rank subspace of background. Furthermore, to well preserve the low-rank property of dynamic background, we embed a transformation operator into the proposed model which makes it much more robust in practical camera jitters or rotation. Finally, a simple mask strategy is used to reconstruct stable frame containing moving objects. Extensive experiments using synthetic and real-life turbulence-degraded data show that the proposed method outperforms other compared approaches in terms of both geometric distortion correction and moving objects preservation.
关键词： Image detection systems.,Image reconstruction-restoration,Imaging through turbulent media,Atmospheric turbulence
更新于2025-09-23 15:21:01
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Handbook of Neuro-Oncology Neuroimaging || Positron Emission Tomography (PET) and Single-Photon Emission Computed Tomography (SPECT) Physics
摘要： The purpose of emission tomography is to estimate the distribution of a radiotracer from external measurements of the pattern of photons emerging from the brain. Some of these photons are detected, and certain information about them recorded, by the scanner. These external measurements are termed “projections,” and each measurement in a projection represents, ideally, the sum of radioactivity concentration along a line through the brain. From these measured projection data sets and knowledge of certain aspects of the single-photon emission computed tomography (SPECT) or positron emission tomography (PET) instrument, estimated images of the distribution of radioactivity are mathematically reconstructed. All modern SPECT and PET scanners image the three-dimensional (3D) distribution of radioactivity, either as a stack of two-dimensional (2D) transaxial images or directly as a 3D volume.
关键词： Single-Photon Emission Computed Tomography,Positron Emission Tomography,Image Reconstruction,Radiotracer,SPECT,PET,Radioactivity Distribution,Physics
更新于2025-09-23 15:21:01
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[IEEE 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - Macao, Macao (2019.12.1-2019.12.4)] 2019 IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC) - A Single-Stage Flyback LED Driver Based On Energy Distribution Without Electrolytic Capacitor
摘要： The lp (0 < p < 1) regularization has attracted a great attention in the compressive sensing field, because it can obtain sparser solutions than the well-known l1 regularization. Recently, we developed an approximate general analytic thresholding representation for any lp regularization with 0 < p < 1. The derived thresholding representations are exact for the well-known soft-threshold filtering for l1 regularization and the hard-threshold filtering for l0 regularization. Because the lp regularization is a nonconvex problem, an iterative algorithm can only converge to local optima instead of the global optimum. In this paper, we propose an alternating iteration algorithm for computed tomography reconstruction in a thresholding form based on our general analytic thresholding representation for better convergent properties. The alternating iteration algorithm alternatively minimizes one l1 and one lp (0 < p < 1) regularized objective functions. While the lp regularization can help to find a sparser solution, the l1 regularization can help to monitor the solution not away from the global optimum. Both numerical simulations and phantom experiments are performed to evaluate the proposed alternating iteration algorithm. Compared with the lp (0 < p < 1) regularization using a single p, the proposed alternating iteration algorithm reduces more data measurements for accurate reconstruction and is more robust for projection noise.
关键词： image reconstruction,Compressive sensing,least square solution,computed tomography,alternating iteration,lp regularization
更新于2025-09-23 15:19:57
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[IEEE TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON) - Kochi, India (2019.10.17-2019.10.20)] TENCON 2019 - 2019 IEEE Region 10 Conference (TENCON) - Use of Novel Hybrid Plasmonic Nanoparticle Complexes to Increase the Efficiency of Thin-film Solar Cells
摘要： To utilize the synergy between computed tomography (CT) and magnetic resonance imaging (MRI) data sets from an object at the same time, an edge-guided dual-modality image reconstruction approach is proposed. The key is to establish a knowledge-based connection between these two data sets for the tight fusion of different imaging modalities. Our scheme consists of four inter-related elements: 1) segmentation; 2) initial guess generation; 3) CT image reconstruction; and 4) MRI image reconstruction. Our experiments show that, aided by the image obtained from one imaging modality, even with highly under-sampled data, we can better reconstruct the image of the other modality. This approach can be potentially useful for a simultaneous CT-MRI system.
关键词： l1-norm minimization,image reconstruction,CT-MRI system,multi-modality imaging
更新于2025-09-23 15:19:57
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Accurate modeling of event-by-event backprojection for a germanium semiconductor Compton camera for system response evaluation in the LM-ML-EM image reconstruction method
摘要： We develop an image reconstruction method, considering the physical phenomenon in the measurement process of a Compton camera. The image quality is improved by applying an accurate error model of the Compton scattering angle. The angular error has two properties: an error distribution function specific to the detector material and the variation of its function parameters, depending on each measurement event. We incorporate these factors into the backprojection of the list-mode maximum-likelihood expectation-maximization method as the system response function. We apply our image reconstruction method to simulated data assumed to be measured by a Ge-semiconductor Compton camera GREI, and the imaging data of a tumor-bearing live mouse obtained using GREI. This method is evaluated by comparing an image with variable angular error with that having fixed angular error. The consideration of the variable angle estimation error improves the spatial resolution and reduces image roughness.
关键词： Ge-semiconductor,image reconstruction,Compton camera,LM-ML-EM method,Doppler broadening
更新于2025-09-23 15:19:57
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A low-rank estimation method for CTIS image reconstruction
摘要： The computed tomography image spectrometer (CTIS) is a snapshot hyperspectral imaging technique, which enables hyperspectral image acquisition in a dynamic scene. However, traditional image reconstruction methods with no explicit constraints will introduce high-frequency noise. The low-rank property has been used in hyperspectral image denoising and achieved great effects. We develop an effective method of low-rank estimation (LRE) for CTIS image reconstruction, which shows significant improvements in both the image quality and the spectral quality of the reconstructed image. Compared with the traditional methods, the peak signal-to-noise ratio of the LRE hyperspectral image can be increased by 8 dB, and the spectral-angular mapping can be decreased by 4 times.
关键词： computed tomography image spectrometers,image reconstruction,low-rank estimation,hyperspectral image
更新于2025-09-19 17:15:36
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Full model-based iterative reconstruction (MBIR) in abdominal CT increases objective image quality, but decreases subjective acceptance
摘要： Objective Evaluate and compare the image quality and acceptance of a full MBIR algorithm to that of an earlier full IR hybrid algorithm and filtered back projection (FBP). Methods Acquisitions were performed with a 320 detector-row CT scanner with seven different dose levels. Images were reconstructed with three algorithms: FBP, full hybrid iterative reconstruction (HIR), and a full model-based iterative reconstruction algorithm (full MBIR). The sensitometry, spatial resolution, image texture, and low-contrast detectability of these algorithms were compared. Subjective analysis of low-contrast detectability was performed. Ten radiologists answered a questionnaire on image quality and confidence in full MBIR images in clinical practice. Results The contrast-to-noise ratio of full MBIR was significantly higher than in the other algorithms (p < 0.0015). The spatial resolution was also higher with full MBIR at high frequencies (> 0.3 lp/mm). Full MBIR at low dose levels led to better low-contrast detectability and more inserts being identified with a higher confidence (p < 0.0001). Full MBIR was associated with a change in image texture compared to HIR and FBP. Eighty percent of radiologists judged general appearance and texture of full MBIR images worse than HIR. Moreover, compared with HIR, for 50% of radiologists, the diagnostic confidence on full MBIR images was worse. Questionnaire reliability was considered acceptable (Cronbach alpha 0.7). Conclusion Compared to conventional iterative reconstruction algorithms, full MBMIR presented a higher image quality and low-contrast detectability and a worse acceptance among radiologists.
关键词： Computed tomography,Phantom imaging,Image quality,Abdomen,Image reconstruction
更新于2025-09-19 17:15:36
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[IEEE 2018 IEEE International Ultrasonics Symposium (IUS) - Kobe, Japan (2018.10.22-2018.10.25)] 2018 IEEE International Ultrasonics Symposium (IUS) - A Compressed Sensing Based Miniaturized Photoacoustic Imaging System
摘要： Compressed Sensing Based Photoelectric Imaging System
关键词： Photoelectric Imaging,Image Reconstruction,Signal Processing,Compressed Sensing
更新于2025-09-19 17:15:36