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[IEEE 2019 5th International Conference on Signal Processing, Computing and Control (ISPCC) - Solan, India (2019.10.10-2019.10.12)] 2019 5th International Conference on Signal Processing, Computing and Control (ISPCC) - Technical Survey and review on MPPT techniques to attain Maximum Power of Photovoltaic system
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： Compressive sensing,lp regularization,least square solution,image reconstruction,alternating iteration,computed tomography
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Marked improvement of the photoresponsivity of BaSi <sub/>2</sub> light absorbers by increasing growth temperature and three-step growth method
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： Compressive sensing,lp regularization,least square solution,image reconstruction,alternating iteration,computed tomography
更新于2025-09-19 17:13:59
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[IEEE 2019 16th International Conference on the European Energy Market (EEM) - Ljubljana, Slovenia (2019.9.18-2019.9.20)] 2019 16th International Conference on the European Energy Market (EEM) - Shapley-Value-Based Distribution of the Costs of Solar Photovoltaic Plant Grid Connection
摘要： Positron emission tomography (PET) images are typically reconstructed with an in-plane pixel size of approximately 4 mm for cancer imaging. The objective of this work was to evaluate the effect of using smaller pixels on general oncologic lesion-detection. A series of observer studies was performed using experimental phantom data from the Utah PET Lesion Detection Database, which modeled whole-body FDG PET cancer imaging of a 92 kg patient. The data comprised 24 scans over 4 days on a Biograph mCT time-of-flight (TOF) PET/CT scanner, with up to 23 lesions (diam. 6–16 mm) distributed throughout the phantom each day. Images were reconstructed with 2.036 mm and 4.073 mm pixels using ordered-subsets expectation-maximization (OSEM) both with and without point spread function (PSF) modeling and TOF. Detection performance was assessed using the channelized non-prewhitened numerical observer with localization receiver operating characteristic (LROC) analysis. Tumor localization performance and the area under the LROC curve were then analyzed as functions of the pixel size. In all cases, the images with ～2 mm pixels provided higher detection performance than those with ～4 mm pixels. The degree of improvement from the smaller pixels was larger than that offered by PSF modeling for these data, and provided roughly half the benefit of using TOF. Key results were confirmed by two human observers, who read subsets of the test data. This study suggests that a significant improvement in tumor detection performance for PET can be attained by using smaller voxel sizes than commonly used at many centers. The primary drawback is a 4-fold increase in reconstruction time and data storage requirements.
关键词： PET/CT reconstruction,PET/CT,image reconstruction,Image quality assessment
更新于2025-09-16 10:30:52
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[IEEE 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC) - Sydney, Australia (2018.11.10-2018.11.17)] 2018 IEEE Nuclear Science Symposium and Medical Imaging Conference Proceedings (NSS/MIC) - PET-enabled Dual-energy CT: A Proof-of-Concept Simulation Study
摘要： Standard dual-energy CT uses two different x-ray energies to obtain energy-dependent tissue attenuation information to allow quantitative material decomposition. Combined use of dual-energy CT and PET may provide a more comprehensive characterization of disease states in cancer and many other integration of dual-energy CT with PET diseases. However, is not trivial, either requiring costly hardware upgrade or increasing radiation dose. This paper proposes a novel dual-energy CT imaging method that is enabled by the already-available PET data on PET/CT. Instead of using a second x-ray CT scan with a different energy, this method exploits time-of-flight PET image reconstruction to obtain a 511 keV gamma-ray attenuation image from PET emission data and combines the high-energy gamma-ray CT image with the low-energy x-ray CT of PET/CT to provide a pair of dual-energy CT images. We conducted a computer simulation to test the concept for material decomposition using air, soft tissue, fat and calcium. The simulations results indicate that this PET-enabled dual-energy CT method is promising for quantitative material decomposition, though future work is needed for noise supression. The proposed method can be readily implemented on time-of-flight PET/CT scanners to enable simultaneous PET and dual-energy CT for multiparametric imaging.
关键词： Time-of-flight PET,multi-material decomposition,image reconstruction,dual-energy CT
更新于2025-09-16 10:30:52
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Development of a 3-D scintillator detector for Compton imaging based on laser engraving
摘要： Y2SiO5: Ce (YSO) scintillation with characteristics of high light yield, fast decay time and high Compton scattering fraction shows good application potential for Compton imaging. In this study, we propose a three-dimensional (3-D) scintillator detector, which is segmented by the YSO monolithic rods and pixelated by sub-surface laser engraving (SSLE) in the depth direction. Two arrays of silicon photomultipliers are optically coupled to the YSO array at each end, in which the pixels are designed for a one-to-one match. By identifying the location number of array pixels and measuring depth-of-interaction (DOI) of pixelated scintillator rods, the interaction coordinates of gamma photon can be obtained accurately. After energy consistent calibration, the energy resolutions of the pixels in 3-D detector were evaluated. The imaging test results indicate that the detector has a capability to locate a 0.1 μSv/h Cs-137 gamma-ray source within 90 seconds in 4π field-of-view (FOV). The efficiency of the imaging events is 2.2 %. By using the maximum likelihood expectation maximization (MLEM) algorithm with 10 iterations, the full width at half maximum (FWHM) of the reconstructed hotspot decreases to less than 9.0 °. This configuration mainly simplifies the calculation of interaction coordinates compared to the center of gravity method. Moreover, the higher segment precision for DOI estimation are realized thanks to the SSLE technique. The 3-D scintillator detector achieves 4π Compton imaging with high detection efficiency and high localization accuracy.
关键词： Sub-surface laser engraving,Scintillation detectors,Compton imaging,Image reconstruction
更新于2025-09-12 10:27:22
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The effect of different image reconstruction techniques on pre-clinical quantitative imaging and dual-energy CT
摘要： To analyse the effect of different image reconstruction techniques on image quality and dual energy CT (DECT) imaging metrics. A software platform for pre-clinical cone beam CT X-ray image reconstruction was built using the open-source reconstruction toolkit. Pre-processed projections were reconstructed with filtered back-projection and iterative algorithms, namely Feldkamp, Davis, and Kress (FDK), Iterative FDK, simultaneous algebraic reconstruction technique (SART), simultaneous iterative reconstruction technique and conjugate gradient. Imaging metrics were quantitatively assessed, using a quality assurance phantom, and DECT analysis was performed to determine the influence of each reconstruction technique on the relative electron density (ρe) and effective atomic number (Zeff) values. Iterative reconstruction had favourable results for the DECT analysis: a significantly smaller spread for each material in the ρe-Zeff space and lower Zeff and ρe residuals (on average 24 and 25% lower, respectively). In terms of image quality assurance, the techniques FDK, Iterative FDK and SART provided acceptable results. The three reconstruction methods showed similar geometric accuracy, uniformity and CT number results. The technique SART had a contrast-to-noise ratio up to 76% higher for solid water and twice as high for Teflon, but resolution was up to 28% lower when compared to the other two techniques. Advanced image reconstruction can be beneficial, but the benefit is small, and calculation times may be unacceptable with current technology. The use of targeted and downscaled reconstruction grids, larger, yet practicable, pixel sizes and GPU are recommended. An iterative CBCT reconstruction platform was build using RTK.
关键词： image reconstruction,iterative reconstruction,quantitative imaging,dual-energy CT,pre-clinical imaging
更新于2025-09-11 14:15:04
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3D Reconstruction of Slug Flow in Mini-Channels with a Simple and Low-Cost Optical Sensor
摘要： The present work provides a new approach for 3D image reconstruction of gas-liquid two-phase flow (GLF) in mini-channels based on a new optical sensor. The sensor consists of a vertical and a horizontal photodiode array. Firstly, with the optical signals obtained by the vertical array, a measurement model developed by Support Vector Regression (SVR) was used to determine the cross-sectional information. The determined information was further used to reconstruct cross-sectional 2D images. Then, the gas velocity was calculated according to the signals obtained by the horizontal array, and the spatial interval of the 2D images was determined. Finally, 3D images were reconstructed by piling up the 2D images. In this work, the cross-sectional gas-liquid interface was considered as circular, and high-speed visualization was utilized to provide the reference values. The image deformation caused by channel wall was also considered. Experiments of slug flow in a channel with an inner diameter of 4.0 mm were carried out. The results verify the feasibility of the proposed 3D reconstruction method. The proposed method has the advantages of simple construct, low cost, and easily multipliable. The reconstructed 3D images can provide detailed and undistorted information of flow structure, which could further improve the measurement accuracy of other important parameters of gas-liquid two-phase flow, such as void fraction, pressure drop, and flow pattern.
关键词： Support Vector Machine,3D image reconstruction,gas-liquid two-phase flow,mini-channels,optical sensor,slug flow
更新于2025-09-11 14:15:04
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A Hexagonal Pseudo-polar FFT for Formation-Flying Interferometric Radiometry
摘要： A novel mission concept applying satellite formation flight to passive microwave interferometry was recently proposed to significantly improve the interferometer’s spatial resolution. This concept was shown to sample the visibility in a hexagonal tile of polar grids, and to recover the brightness map, this visibility must be inverted via a discrete polar inverse Fourier transform. For a fast and accurate solution, this letter develops a modified hexagonal variant of the pseudo-polar fast Fourier transform (PPFFT) and its inverse and explores its performance when applied to the proposed formation-flight radiometer. Compared to the conventional rectangular PPFFT, we find approximately a fivefold improvement in the recovered radiometric accuracy, where the rms radiometric error is in the order of 10?2 K. The impact of visibility interpolation method is also explored, showing that an FFT-based interpolation technique leads to the most accurate final image recovery.
关键词： mission concept,synthetic aperture imaging,microwave radiometry,Image reconstruction,satellite formation flight
更新于2025-09-11 14:15:04
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Comparison of four iterative methods for improving the contrast of the radiography images
摘要： Recently, radiography image elaboration using different image processing methods has been introduced as an alternative to enhance the radiographs. The ability of improving the quality of an image depends on the scattered X-ray and the acquisition data by electronic system in digital radiography (RT). Iterative methods, well known in general sparse signal reconstruction, can be suited for the radiography images. In this research, the digital radiography image is improved by minimizing an objective function using the Fast Iterative Shrinkage-Thresholding Algorithm (FISTA), Monotone FISTA (MFISTA), Over relaxation MFISTA (OMFISTA) and Converged FISTA (CFISTA), where the solution sparsity may be adjusted as desired. The paper surveys four well-known methods for sparse process, and assesses their optimization parameters with the goal of obtaining the best algorithm for industrial radiography images. First, the radiographs from the welded objects were provided and four iterative methods were implemented to the radiographs for enhancing the contrast. Then reconstructed images were assessed on the basis of their quality. The results show that the reconstructed images have better contrast than the original radiography and the OMFISTA method has a lower runtime compared to others. Also, the results demonstrate the viability and efficiency of the four proposed algorithms on radiography image deblurring problems without any information about the noise of radiography system.
关键词： Image Reconstruction,Welded Objects,Radiography Image,Iterative Methods
更新于2025-09-10 09:29:36
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Solving Inverse Computational Imaging Problems using Deep Pixel-level Prior
摘要： Signal reconstruction is a challenging aspect of computational imaging as it often involves solving ill-posed inverse problems. Recently, deep feed-forward neural networks have led to state-of-the-art results in solving various inverse imaging problems. However, being task specific, these networks have to be learned for each inverse problem. On the other hand, a more flexible approach would be to learn a deep generative model once and then use it as a signal prior for solving various inverse problems. We show that among the various state of the art deep generative models, autoregressive models are especially suitable for our purpose for the following reasons. First, they explicitly model the pixel level dependencies and hence are capable of reconstructing low-level details such as texture patterns and edges better. Second, they provide an explicit expression for the image prior which can then be used for MAP based inference along with the forward model. Third, they can model long range dependencies in images which make them ideal for handling global multiplexing as encountered in various compressive imaging systems. We demonstrate the efficacy of our proposed approach in solving three computational imaging problems: Single Pixel Camera (SPC), LiSens and FlatCam. For both real and simulated cases, we obtain better reconstructions than the state-of-the-art methods in terms of perceptual and quantitative metrics.
关键词： lensless image reconstruction,MAP inference,Inverse problems,compressive image recovery,autoregressive models,deep generative models
更新于2025-09-10 09:29:36