Bias in iterative reconstruction of low-statistics PET data: benefits of a resolution model

Energy Technology Data Exchange (ETDEWEB)

Walker, M D; Asselin, M-C; Julyan, P J; Feldmann, M; Matthews, J C [School of Cancer and Enabling Sciences, Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Talbot, P S [Mental Health and Neurodegeneration Research Group, Wolfson Molecular Imaging Centre, MAHSC, University of Manchester, Manchester M20 3LJ (United Kingdom); Jones, T, E-mail: matthew.walker@manchester.ac.uk [Academic Department of Radiation Oncology, Christie Hospital, University of Manchester, Manchester M20 4BX (United Kingdom)

2011-02-21

Iterative image reconstruction methods such as ordered-subset expectation maximization (OSEM) are widely used in PET. Reconstructions via OSEM are however reported to be biased for low-count data. We investigated this and considered the impact for dynamic PET. Patient listmode data were acquired in [{sup 11}C]DASB and [{sup 15}O]H{sub 2}O scans on the HRRT brain PET scanner. These data were subsampled to create many independent, low-count replicates. The data were reconstructed and the images from low-count data were compared to the high-count originals (from the same reconstruction method). This comparison enabled low-statistics bias to be calculated for the given reconstruction, as a function of the noise-equivalent counts (NEC). Two iterative reconstruction methods were tested, one with and one without an image-based resolution model (RM). Significant bias was observed when reconstructing data of low statistical quality, for both subsampled human and simulated data. For human data, this bias was substantially reduced by including a RM. For [{sup 11}C]DASB the low-statistics bias in the caudate head at 1.7 M NEC (approx. 30 s) was -5.5% and -13% with and without RM, respectively. We predicted biases in the binding potential of -4% and -10%. For quantification of cerebral blood flow for the whole-brain grey- or white-matter, using [{sup 15}O]H{sub 2}O and the PET autoradiographic method, a low-statistics bias of <2.5% and <4% was predicted for reconstruction with and without the RM. The use of a resolution model reduces low-statistics bias and can hence be beneficial for quantitative dynamic PET.

Gamma regularization based reconstruction for low dose CT

International Nuclear Information System (INIS)

Zhang, Junfeng; Chen, Yang; Hu, Yining; Luo, Limin; Shu, Huazhong; Li, Bicao; Liu, Jin; Coatrieux, Jean-Louis

2015-01-01

Reducing the radiation in computerized tomography is today a major concern in radiology. Low dose computerized tomography (LDCT) offers a sound way to deal with this problem. However, more severe noise in the reconstructed CT images is observed under low dose scan protocols (e.g. lowered tube current or voltage values). In this paper we propose a Gamma regularization based algorithm for LDCT image reconstruction. This solution is flexible and provides a good balance between the regularizations based on l 0 -norm and l 1 -norm. We evaluate the proposed approach using the projection data from simulated phantoms and scanned Catphan phantoms. Qualitative and quantitative results show that the Gamma regularization based reconstruction can perform better in both edge-preserving and noise suppression when compared with other norms. (paper)

Kalman-Takens filtering in the presence of dynamical noise

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Hamilton, Franz; Berry, Tyrus; Sauer, Timothy

2017-12-01

The use of data assimilation for the merging of observed data with dynamical models is becoming standard in modern physics. If a parametric model is known, methods such as Kalman filtering have been developed for this purpose. If no model is known, a hybrid Kalman-Takens method has been recently introduced, in order to exploit the advantages of optimal filtering in a nonparametric setting. This procedure replaces the parametric model with dynamics reconstructed from delay coordinates, while using the Kalman update formulation to assimilate new observations. In this article, we study the efficacy of this method for identifying underlying dynamics in the presence of dynamical noise. Furthermore, by combining the Kalman-Takens method with an adaptive filtering procedure we are able to estimate the statistics of the observational and dynamical noise. This solves a long-standing problem of separating dynamical and observational noise in time series data, which is especially challenging when no dynamical model is specified.

Noise in off-axis type holograms including reconstruction and CCD camera parameters

Energy Technology Data Exchange (ETDEWEB)

Voelkl, Edgar, E-mail: edgar.voelkl@fei.com [FEI Company, 5350 NE Dawson Creek Drive, Hillsboro, OR 97124-5793 (United States)

2010-02-15

Phase and amplitude images as contained in digital holograms are commonly extracted via a process called 'reconstruction'. Expressions for the expected noise in these images have been given in the past by several authors; however, the effect of the actual reconstruction process has not been fully appreciated. By starting with the Quantum Mechanical intensity distribution of the off-axis type interference pattern, then building the digital hologram on an electron-by-electron base while simultaneously reconstructing the phase/amplitude images and evaluating their noise levels, an expression is derived that consistently describes the noise in simulated and experimental phase/amplitude images and contains the reconstruction parameters. Because of the necessity to discretize the intensity distribution function, the digitization effects of an ideal CCD camera had to be included. Subsequently, this allowed a comparison between real and simulated holograms which then led to a comparison between the performance of an 'ideal' CCD camera versus a real device. It was concluded that significant improvement of the phase and amplitude noise may be obtained if CCD cameras were optimized for digitizing intensity distributions at low sampling rates.

Maximum a posteriori reconstruction of the Patlak parametric image from sinograms in dynamic PET

International Nuclear Information System (INIS)

Wang Guobao; Fu Lin; Qi Jinyi

2008-01-01

Parametric imaging using the Patlak graphical method has been widely used to analyze dynamic PET data. Conventionally a Patlak parametric image is generated by reconstructing a sequence of dynamic images first and then performing Patlak graphical analysis on the time-activity curves pixel-by-pixel. However, because it is rather difficult to model the noise distribution in reconstructed images, the spatially variant noise correlation is simply ignored in the Patlak analysis, which leads to sub-optimal results. In this paper we present a Bayesian method for reconstructing Patlak parametric images directly from raw sinogram data by incorporating the Patlak plot model into the image reconstruction procedure. A preconditioned conjugate gradient algorithm is used to find the maximum a posteriori solution. The proposed direct method is statistically more efficient than the conventional indirect approach because the Poisson noise distribution in PET data can be accurately modeled in the direct reconstruction. The computation cost of the direct method is similar to reconstruction time of two dynamic frames. Therefore, when more than two dynamic frames are used in the Patlak analysis, the direct method is faster than the conventional indirect approach. We conduct computer simulations to validate the proposed direct method. Comparisons with the conventional indirect approach show that the proposed method results in a more accurate estimate of the parametric image. The proposed method has been applied to dynamic fully 3D PET data from a microPET scanner

Accuracy of dynamical-decoupling-based spectroscopy of Gaussian noise

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Szańkowski, Piotr; Cywiński, Łukasz

2018-03-01

The fundamental assumption of dynamical-decoupling-based noise spectroscopy is that the coherence decay rate of qubit (or qubits) driven with a sequence of many pulses, is well approximated by the environmental noise spectrum spanned on frequency comb defined by the sequence. Here we investigate the precise conditions under which this commonly used spectroscopic approach is quantitatively correct. To this end we focus on two representative examples of spectral densities: the long-tailed Lorentzian, and finite-ranged Gaussian—both expected to be encountered when using the qubit for nanoscale nuclear resonance imaging. We have found that, in contrast to Lorentz spectrum, for which the corrections to the standard spectroscopic formulas can easily be made negligible, the spectra with finite range are more challenging to reconstruct accurately. For Gaussian line shape of environmental spectral density, direct application of the standard dynamical-decoupling-based spectroscopy leads to erroneous attribution of long-tail behavior to the reconstructed spectrum. Fortunately, artifacts such as this, can be completely avoided with the simple extension to standard reconstruction method.

Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

International Nuclear Information System (INIS)

Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang- Hee

2014-01-01

State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time. - Highlights: • The PDS-OSEM reconstructs PET images with iteratively compensating random and scatter corrections from prompt sinogram. • The PDS-OSEM can reconstruct PET images with low count data and data contaminations. • The PDS-OSEM provides less noise and higher quality of reconstructed images than those of OP-OSEM algorithm in statistical sense

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in vivo studies

Science.gov (United States)

Petibon, Yoann; Rakvongthai, Yothin; El Fakhri, Georges; Ouyang, Jinsong

2017-05-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves-TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans—each containing 1/8th of the total number of events—were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard ordered subset expectation maximization (OSEM) reconstruction algorithm on one side, and the one-step late maximum a posteriori (OSL-MAP) algorithm on the other

Direct parametric reconstruction in dynamic PET myocardial perfusion imaging: in-vivo studies

Science.gov (United States)

Petibon, Yoann; Rakvongthai, Yothin; Fakhri, Georges El; Ouyang, Jinsong

2017-01-01

Dynamic PET myocardial perfusion imaging (MPI) used in conjunction with tracer kinetic modeling enables the quantification of absolute myocardial blood flow (MBF). However, MBF maps computed using the traditional indirect method (i.e. post-reconstruction voxel-wise fitting of kinetic model to PET time-activity-curves -TACs) suffer from poor signal-to-noise ratio (SNR). Direct reconstruction of kinetic parameters from raw PET projection data has been shown to offer parametric images with higher SNR compared to the indirect method. The aim of this study was to extend and evaluate the performance of a direct parametric reconstruction method using in-vivo dynamic PET MPI data for the purpose of quantifying MBF. Dynamic PET MPI studies were performed on two healthy pigs using a Siemens Biograph mMR scanner. List-mode PET data for each animal were acquired following a bolus injection of ~7-8 mCi of 18F-flurpiridaz, a myocardial perfusion agent. Fully-3D dynamic PET sinograms were obtained by sorting the coincidence events into 16 temporal frames covering ~5 min after radiotracer administration. Additionally, eight independent noise realizations of both scans - each containing 1/8th of the total number of events - were generated from the original list-mode data. Dynamic sinograms were then used to compute parametric maps using the conventional indirect method and the proposed direct method. For both methods, a one-tissue compartment model accounting for spillover from the left and right ventricle blood-pools was used to describe the kinetics of 18F-flurpiridaz. An image-derived arterial input function obtained from a TAC taken in the left ventricle cavity was used for tracer kinetic analysis. For the indirect method, frame-by-frame images were estimated using two fully-3D reconstruction techniques: the standard Ordered Subset Expectation Maximization (OSEM) reconstruction algorithm on one side, and the One-Step Late Maximum a Posteriori (OSL-MAP) algorithm on the other

Trend extraction of rail corrugation measured dynamically based on the relevant low-frequency principal components reconstruction

International Nuclear Information System (INIS)

Li, Yanfu; Liu, Hongli; Ma, Ziji

2016-01-01

Rail corrugation dynamic measurement techniques are critical to guarantee transport security and guide rail maintenance. During the inspection process, low-frequency trends caused by rail fluctuation are usually superimposed on rail corrugation and seriously affect the assessment of rail maintenance quality. In order to extract and remove the nonlinear and non-stationary trends from original mixed signals, a hybrid model based ensemble empirical mode decomposition (EEMD) and modified principal component analysis (MPCA) is proposed in this paper. Compared with the existing de-trending methods based on EMD, this method first considers low-frequency intrinsic mode functions (IMFs) thought to be underlying trend components that maybe contain some unrelated components, such as white noise and low-frequency signal itself, and proposes to use PCA to accurately extract the pure trends from the IMFs containing multiple components. On the other hand, due to the energy contribution ratio between trends and mixed signals is prior unknown, and the principal components (PCs) decomposed by PCA are arranged in order of energy reduction without considering frequency distribution, the proposed method modifies traditional PCA and just selects relevant low-frequency PCs to reconstruct the trends based on the zero-crossing numbers (ZCN) of each PC. Extensive tests are presented to illustrate the effectiveness of the proposed method. The results show the proposed EEMD-PCA-ZCN is an effective tool for trend extraction of rail corrugation measured dynamically. (paper)

A noise power spectrum study of a new model-based iterative reconstruction system: Veo 3.0.

Science.gov (United States)

Li, Guang; Liu, Xinming; Dodge, Cristina T; Jensen, Corey T; Rong, X John

2016-09-08

The purpose of this study was to evaluate performance of the third generation of model-based iterative reconstruction (MBIR) system, Veo 3.0, based on noise power spectrum (NPS) analysis with various clinical presets over a wide range of clinically applicable dose levels. A CatPhan 600 surrounded by an oval, fat-equivalent ring to mimic patient size/shape was scanned 10 times at each of six dose levels on a GE HD 750 scanner. NPS analysis was performed on images reconstructed with various Veo 3.0 preset combinations for comparisons of those images reconstructed using Veo 2.0, filtered back projection (FBP) and adaptive statistical iterative reconstruc-tion (ASiR). The new Target Thickness setting resulted in higher noise in thicker axial images. The new Texture Enhancement function achieved a more isotropic noise behavior with less image artifacts. Veo 3.0 provides additional reconstruction options designed to allow the user choice of balance between spatial resolution and image noise, relative to Veo 2.0. Veo 3.0 provides more user selectable options and in general improved isotropic noise behavior in comparison to Veo 2.0. The overall noise reduction performance of both versions of MBIR was improved in comparison to FBP and ASiR, especially at low-dose levels. © 2016 The Authors.

3.5D dynamic PET image reconstruction incorporating kinetics-based clusters

International Nuclear Information System (INIS)

Lu Lijun; Chen Wufan; Karakatsanis, Nicolas A; Rahmim, Arman; Tang Jing

2012-01-01

Standard 3D dynamic positron emission tomographic (PET) imaging consists of independent image reconstructions of individual frames followed by application of appropriate kinetic model to the time activity curves at the voxel or region-of-interest (ROI). The emerging field of 4D PET reconstruction, by contrast, seeks to move beyond this scheme and incorporate information from multiple frames within the image reconstruction task. Here we propose a novel reconstruction framework aiming to enhance quantitative accuracy of parametric images via introduction of priors based on voxel kinetics, as generated via clustering of preliminary reconstructed dynamic images to define clustered neighborhoods of voxels with similar kinetics. This is then followed by straightforward maximum a posteriori (MAP) 3D PET reconstruction as applied to individual frames; and as such the method is labeled ‘3.5D’ image reconstruction. The use of cluster-based priors has the advantage of further enhancing quantitative performance in dynamic PET imaging, because: (a) there are typically more voxels in clusters than in conventional local neighborhoods, and (b) neighboring voxels with distinct kinetics are less likely to be clustered together. Using realistic simulated 11 C-raclopride dynamic PET data, the quantitative performance of the proposed method was investigated. Parametric distribution-volume (DV) and DV ratio (DVR) images were estimated from dynamic image reconstructions using (a) maximum-likelihood expectation maximization (MLEM), and MAP reconstructions using (b) the quadratic prior (QP-MAP), (c) the Green prior (GP-MAP) and (d, e) two proposed cluster-based priors (CP-U-MAP and CP-W-MAP), followed by graphical modeling, and were qualitatively and quantitatively compared for 11 ROIs. Overall, the proposed dynamic PET reconstruction methodology resulted in substantial visual as well as quantitative accuracy improvements (in terms of noise versus bias performance) for parametric DV

Simultaneous reconstruction and segmentation for dynamic SPECT imaging

International Nuclear Information System (INIS)

Burger, Martin; Rossmanith, Carolin; Zhang, Xiaoqun

2016-01-01

This work deals with the reconstruction of dynamic images that incorporate characteristic dynamics in certain subregions, as arising for the kinetics of many tracers in emission tomography (SPECT, PET). We make use of a basis function approach for the unknown tracer concentration by assuming that the region of interest can be divided into subregions with spatially constant concentration curves. Applying a regularised variational framework reminiscent of the Chan-Vese model for image segmentation we simultaneously reconstruct both the labelling functions of the subregions as well as the subconcentrations within each region. Our particular focus is on applications in SPECT with the Poisson noise model, resulting in a Kullback–Leibler data fidelity in the variational approach. We present a detailed analysis of the proposed variational model and prove existence of minimisers as well as error estimates. The latter apply to a more general class of problems and generalise existing results in literature since we deal with a nonlinear forward operator and a nonquadratic data fidelity. A computational algorithm based on alternating minimisation and splitting techniques is developed for the solution of the problem and tested on appropriately designed synthetic data sets. For those we compare the results to those of standard EM reconstructions and investigate the effects of Poisson noise in the data. (paper)

Reconstructing plate-motion changes in the presence of finite-rotations noise.

Science.gov (United States)

Iaffaldano, Giampiero; Bodin, Thomas; Sambridge, Malcolm

2012-01-01

Understanding lithospheric plate motions is of paramount importance to geodynamicists. Much effort is going into kinematic reconstructions featuring progressively finer temporal resolution. However, the challenge of precisely identifying ocean-floor magnetic lineations, and uncertainties in geomagnetic reversal timescales result in substantial finite-rotations noise. Unless some type of temporal smoothing is applied, the scenario arising at the native temporal resolution is puzzling, as plate motions vary erratically and significantly over short periods (<1 Myr). This undermines our ability to make geodynamic inferences, as the rates at which forces need to be built upon plates to explain these kinematics far exceed the most optimistic estimates. Here we show that the largest kinematic changes reconstructed across the Atlantic, Indian and South Pacific ridges arise from data noise. We overcome this limitation using a trans-dimensional hierarchical Bayesian framework. We find that plate-motion changes occur on timescales no shorter than a few million years, yielding simpler kinematic patterns and more plausible dynamics.

Improved magnetic resonance fingerprinting reconstruction with low-rank and subspace modeling.

Science.gov (United States)

Zhao, Bo; Setsompop, Kawin; Adalsteinsson, Elfar; Gagoski, Borjan; Ye, Huihui; Ma, Dan; Jiang, Yun; Ellen Grant, P; Griswold, Mark A; Wald, Lawrence L

2018-02-01

This article introduces a constrained imaging method based on low-rank and subspace modeling to improve the accuracy and speed of MR fingerprinting (MRF). A new model-based imaging method is developed for MRF to reconstruct high-quality time-series images and accurate tissue parameter maps (e.g., T 1 , T 2 , and spin density maps). Specifically, the proposed method exploits low-rank approximations of MRF time-series images, and further enforces temporal subspace constraints to capture magnetization dynamics. This allows the time-series image reconstruction problem to be formulated as a simple linear least-squares problem, which enables efficient computation. After image reconstruction, tissue parameter maps are estimated via dictionary-based pattern matching, as in the conventional approach. The effectiveness of the proposed method was evaluated with in vivo experiments. Compared with the conventional MRF reconstruction, the proposed method reconstructs time-series images with significantly reduced aliasing artifacts and noise contamination. Although the conventional approach exhibits some robustness to these corruptions, the improved time-series image reconstruction in turn provides more accurate tissue parameter maps. The improvement is pronounced especially when the acquisition time becomes short. The proposed method significantly improves the accuracy of MRF, and also reduces data acquisition time. Magn Reson Med 79:933-942, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Reconstructing Interlaced High-Dynamic-Range Video Using Joint Learning.

Science.gov (United States)

Inchang Choi; Seung-Hwan Baek; Kim, Min H

2017-11-01

For extending the dynamic range of video, it is a common practice to capture multiple frames sequentially with different exposures and combine them to extend the dynamic range of each video frame. However, this approach results in typical ghosting artifacts due to fast and complex motion in nature. As an alternative, video imaging with interlaced exposures has been introduced to extend the dynamic range. However, the interlaced approach has been hindered by jaggy artifacts and sensor noise, leading to concerns over image quality. In this paper, we propose a data-driven approach for jointly solving two specific problems of deinterlacing and denoising that arise in interlaced video imaging with different exposures. First, we solve the deinterlacing problem using joint dictionary learning via sparse coding. Since partial information of detail in differently exposed rows is often available via interlacing, we make use of the information to reconstruct details of the extended dynamic range from the interlaced video input. Second, we jointly solve the denoising problem by tailoring sparse coding to better handle additive noise in low-/high-exposure rows, and also adopt multiscale homography flow to temporal sequences for denoising. We anticipate that the proposed method will allow for concurrent capture of higher dynamic range video frames without suffering from ghosting artifacts. We demonstrate the advantages of our interlaced video imaging compared with the state-of-the-art high-dynamic-range video methods.

Effect of ultra-low doses, ASIR and MBIR on density and noise levels of MDCT images of dental implant sites.

Science.gov (United States)

Widmann, Gerlig; Al-Shawaf, Reema; Schullian, Peter; Al-Sadhan, Ra'ed; Hörmann, Romed; Al-Ekrish, Asma'a A

2017-05-01

Differences in noise and density values in MDCT images obtained using ultra-low doses with FBP, ASIR, and MBIR may possibly affect implant site density analysis. The aim of this study was to compare density and noise measurements recorded from dental implant sites using ultra-low doses combined with FBP, ASIR, and MBIR. Cadavers were scanned using a standard protocol and four low-dose protocols. Scans were reconstructed using FBP, ASIR-50, ASIR-100, and MBIR, and either a bone or standard reconstruction kernel. Density (mean Hounsfield units [HUs]) of alveolar bone and noise levels (mean standard deviation of HUs) was recorded from all datasets and measurements were compared by paired t tests and two-way ANOVA with repeated measures. Significant differences in density and noise were found between the reference dose/FBP protocol and almost all test combinations. Maximum mean differences in HU were 178.35 (bone kernel) and 273.74 (standard kernel), and in noise, were 243.73 (bone kernel) and 153.88 (standard kernel). Decreasing radiation dose increased density and noise regardless of reconstruction technique and kernel. The effect of reconstruction technique on density and noise depends on the reconstruction kernel used. • Ultra-low-dose MDCT protocols allowed more than 90 % reductions in dose. • Decreasing the dose generally increased density and noise. • Effect of IRT on density and noise varies with reconstruction kernel. • Accuracy of low-dose protocols for interpretation of bony anatomy not known. • Effect of low doses on accuracy of computer-aided design models unknown.

Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

Energy Technology Data Exchange (ETDEWEB)

Solomon, Justin, E-mail: justin.solomon@duke.edu [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 (United States); Samei, Ehsan [Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University Medical Center, Durham, North Carolina 27705 and Departments of Biomedical Engineering and Electrical and Computer Engineering, Pratt School of Engineering, Duke University, Durham, North Carolina 27705 (United States)

2014-09-15

Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

Quantum noise properties of CT images with anatomical textured backgrounds across reconstruction algorithms: FBP and SAFIRE

International Nuclear Information System (INIS)

Solomon, Justin; Samei, Ehsan

2014-01-01

Purpose: Quantum noise properties of CT images are generally assessed using simple geometric phantoms with uniform backgrounds. Such phantoms may be inadequate when assessing nonlinear reconstruction or postprocessing algorithms. The purpose of this study was to design anatomically informed textured phantoms and use the phantoms to assess quantum noise properties across two clinically available reconstruction algorithms, filtered back projection (FBP) and sinogram affirmed iterative reconstruction (SAFIRE). Methods: Two phantoms were designed to represent lung and soft-tissue textures. The lung phantom included intricate vessel-like structures along with embedded nodules (spherical, lobulated, and spiculated). The soft tissue phantom was designed based on a three-dimensional clustered lumpy background with included low-contrast lesions (spherical and anthropomorphic). The phantoms were built using rapid prototyping (3D printing) technology and, along with a uniform phantom of similar size, were imaged on a Siemens SOMATOM Definition Flash CT scanner and reconstructed with FBP and SAFIRE. Fifty repeated acquisitions were acquired for each background type and noise was assessed by estimating pixel-value statistics, such as standard deviation (i.e., noise magnitude), autocorrelation, and noise power spectrum. Noise stationarity was also assessed by examining the spatial distribution of noise magnitude. The noise properties were compared across background types and between the two reconstruction algorithms. Results: In FBP and SAFIRE images, noise was globally nonstationary for all phantoms. In FBP images of all phantoms, and in SAFIRE images of the uniform phantom, noise appeared to be locally stationary (within a reasonably small region of interest). Noise was locally nonstationary in SAFIRE images of the textured phantoms with edge pixels showing higher noise magnitude compared to pixels in more homogenous regions. For pixels in uniform regions, noise magnitude was

Effect of noise on the bifurcation behavior of nonlinear dynamical systems

Energy Technology Data Exchange (ETDEWEB)

Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alta., T2N 1N4 (Canada)]. E-mail: Serletis@ucalgary.ca; Shahmoradi, Asghar [Faculty of Economics, University of Tehran, Tehran (Iran, Islamic Republic of); Serletis, Demitre [Division of Neurosurgery, University of Toronto, Toronto, Ont., M5G 1L5 (Canada)

2007-08-15

We argue that dynamical noise can dramatically change the dynamics of low dimensional chaotic systems. Moreover, we show that chaos tests are highly sensitive to dynamical noise and this becomes worse when the intensity of the noise increases.

Favorable noise uniformity properties of Fourier-based interpolation and reconstruction approaches in single-slice helical computed tomography

International Nuclear Information System (INIS)

La Riviere, Patrick J.; Pan Xiaochuan

2002-01-01

Volumes reconstructed by standard methods from single-slice helical computed tomography (CT) data have been shown to have noise levels that are highly nonuniform relative to those in conventional CT. These noise nonuniformities can affect low-contrast object detectability and have also been identified as the cause of the zebra artifacts that plague maximum intensity projection (MIP) images of such volumes. While these spatially variant noise levels have their root in the peculiarities of the helical scan geometry, there is also a strong dependence on the interpolation and reconstruction algorithms employed. In this paper, we seek to develop image reconstruction strategies that eliminate or reduce, at its source, the nonuniformity of noise levels in helical CT relative to that in conventional CT. We pursue two approaches, independently and in concert. We argue, and verify, that Fourier-based longitudinal interpolation approaches lead to more uniform noise ratios than do the standard 360LI and 180LI approaches. We also demonstrate that a Fourier-based fan-to-parallel rebinning algorithm, used as an alternative to fanbeam filtered backprojection for slice reconstruction, also leads to more uniform noise ratios, even when making use of the 180LI and 360LI interpolation approaches

Effect of ultra-low doses, ASIR and MBIR on density and noise levels of MDCT images of dental implant sites

Energy Technology Data Exchange (ETDEWEB)

Widmann, Gerlig; Schullian, Peter [Medical University of Innsbruck, Department of Radiology, Innsbruck (Austria); Al-Shawaf, Reema; Al-Sadhan, Ra' ed; Al-Ekrish, Asma' a A. [King Saud University, Department of Oral Medicine and Diagnostic Sciences, College of Dentistry, Riyadh (Saudi Arabia); Hoermann, Romed [Medical University of Innsbruck, Division of Clinical and Functional Anatomy, Innsbruck (Austria)

2017-05-15

Differences in noise and density values in MDCT images obtained using ultra-low doses with FBP, ASIR, and MBIR may possibly affect implant site density analysis. The aim of this study was to compare density and noise measurements recorded from dental implant sites using ultra-low doses combined with FBP, ASIR, and MBIR. Cadavers were scanned using a standard protocol and four low-dose protocols. Scans were reconstructed using FBP, ASIR-50, ASIR-100, and MBIR, and either a bone or standard reconstruction kernel. Density (mean Hounsfield units [HUs]) of alveolar bone and noise levels (mean standard deviation of HUs) was recorded from all datasets and measurements were compared by paired t tests and two-way ANOVA with repeated measures. Significant differences in density and noise were found between the reference dose/FBP protocol and almost all test combinations. Maximum mean differences in HU were 178.35 (bone kernel) and 273.74 (standard kernel), and in noise, were 243.73 (bone kernel) and 153.88 (standard kernel). Decreasing radiation dose increased density and noise regardless of reconstruction technique and kernel. The effect of reconstruction technique on density and noise depends on the reconstruction kernel used. (orig.)

Effect of ultra-low doses, ASIR and MBIR on density and noise levels of MDCT images of dental implant sites

International Nuclear Information System (INIS)

Widmann, Gerlig; Schullian, Peter; Al-Shawaf, Reema; Al-Sadhan, Ra'ed; Al-Ekrish, Asma'a A.; Hoermann, Romed

2017-01-01

Differences in noise and density values in MDCT images obtained using ultra-low doses with FBP, ASIR, and MBIR may possibly affect implant site density analysis. The aim of this study was to compare density and noise measurements recorded from dental implant sites using ultra-low doses combined with FBP, ASIR, and MBIR. Cadavers were scanned using a standard protocol and four low-dose protocols. Scans were reconstructed using FBP, ASIR-50, ASIR-100, and MBIR, and either a bone or standard reconstruction kernel. Density (mean Hounsfield units [HUs]) of alveolar bone and noise levels (mean standard deviation of HUs) was recorded from all datasets and measurements were compared by paired t tests and two-way ANOVA with repeated measures. Significant differences in density and noise were found between the reference dose/FBP protocol and almost all test combinations. Maximum mean differences in HU were 178.35 (bone kernel) and 273.74 (standard kernel), and in noise, were 243.73 (bone kernel) and 153.88 (standard kernel). Decreasing radiation dose increased density and noise regardless of reconstruction technique and kernel. The effect of reconstruction technique on density and noise depends on the reconstruction kernel used. (orig.)

Coronary CT angiography: Comparison of a novel iterative reconstruction with filtered back projection for reconstruction of low-dose CT—Initial experience

International Nuclear Information System (INIS)

Takx, Richard A.P.; Schoepf, U. Joseph; Moscariello, Antonio; Das, Marco; Rowe, Garrett; Schoenberg, Stefan O.; Fink, Christian; Henzler, Thomas

2013-01-01

Objective: To prospectively compare subjective and objective image quality in 20% tube current coronary CT angiography (cCTA) datasets between an iterative reconstruction algorithm (SAFIRE) and traditional filtered back projection (FBP). Materials and methods: Twenty patients underwent a prospectively ECG-triggered dual-step cCTA protocol using 2nd generation dual-source CT (DSCT). CT raw data was reconstructed using standard FBP at full-dose (Group 1 a) and 80% tube current reduced low-dose (Group 1 b). The low-dose raw data was additionally reconstructed using iterative raw data reconstruction (Group 2 ). Attenuation and image noise were measured in three regions of interest and signal-to-noise-ratio (SNR) as well as contrast-to-noise-ratio (CNR) was calculated. Subjective diagnostic image quality was evaluated using a 4-point Likert scale. Results: Mean image noise of group 2 was lowered by 22% on average when compared to group 1 b (p 2 compared to group 1 b (p 2 (1.88 ± 0.63) was also rated significantly higher when compared to group 1 b (1.58 ± 0.63, p = 0.004). Conclusions: Image quality of 80% tube current reduced iteratively reconstructed cCTA raw data is significantly improved when compared to standard FBP and consequently may improve the diagnostic accuracy of cCTA

Integrated ensemble noise-reconstructed empirical mode decomposition for mechanical fault detection

Science.gov (United States)

Yuan, Jing; Ji, Feng; Gao, Yuan; Zhu, Jun; Wei, Chenjun; Zhou, Yu

2018-05-01

A new branch of fault detection is utilizing the noise such as enhancing, adding or estimating the noise so as to improve the signal-to-noise ratio (SNR) and extract the fault signatures. Hereinto, ensemble noise-reconstructed empirical mode decomposition (ENEMD) is a novel noise utilization method to ameliorate the mode mixing and denoised the intrinsic mode functions (IMFs). Despite the possibility of superior performance in detecting weak and multiple faults, the method still suffers from the major problems of the user-defined parameter and the powerless capability for a high SNR case. Hence, integrated ensemble noise-reconstructed empirical mode decomposition is proposed to overcome the drawbacks, improved by two noise estimation techniques for different SNRs as well as the noise estimation strategy. Independent from the artificial setup, the noise estimation by the minimax thresholding is improved for a low SNR case, which especially shows an outstanding interpretation for signature enhancement. For approximating the weak noise precisely, the noise estimation by the local reconfiguration using singular value decomposition (SVD) is proposed for a high SNR case, which is particularly powerful for reducing the mode mixing. Thereinto, the sliding window for projecting the phase space is optimally designed by the correlation minimization. Meanwhile, the reasonable singular order for the local reconfiguration to estimate the noise is determined by the inflection point of the increment trend of normalized singular entropy. Furthermore, the noise estimation strategy, i.e. the selection approaches of the two estimation techniques along with the critical case, is developed and discussed for different SNRs by means of the possible noise-only IMF family. The method is validated by the repeatable simulations to demonstrate the synthetical performance and especially confirm the capability of noise estimation. Finally, the method is applied to detect the local wear fault

Low-dose X-ray computed tomography image reconstruction with a combined low-mAs and sparse-view protocol.

Science.gov (United States)

Gao, Yang; Bian, Zhaoying; Huang, Jing; Zhang, Yunwan; Niu, Shanzhou; Feng, Qianjin; Chen, Wufan; Liang, Zhengrong; Ma, Jianhua

2014-06-16

To realize low-dose imaging in X-ray computed tomography (CT) examination, lowering milliampere-seconds (low-mAs) or reducing the required number of projection views (sparse-view) per rotation around the body has been widely studied as an easy and effective approach. In this study, we are focusing on low-dose CT image reconstruction from the sinograms acquired with a combined low-mAs and sparse-view protocol and propose a two-step image reconstruction strategy. Specifically, to suppress significant statistical noise in the noisy and insufficient sinograms, an adaptive sinogram restoration (ASR) method is first proposed with consideration of the statistical property of sinogram data, and then to further acquire a high-quality image, a total variation based projection onto convex sets (TV-POCS) method is adopted with a slight modification. For simplicity, the present reconstruction strategy was termed as "ASR-TV-POCS." To evaluate the present ASR-TV-POCS method, both qualitative and quantitative studies were performed on a physical phantom. Experimental results have demonstrated that the present ASR-TV-POCS method can achieve promising gains over other existing methods in terms of the noise reduction, contrast-to-noise ratio, and edge detail preservation.

Qualitative and quantitative analysis of reconstructed images using projections with noises

International Nuclear Information System (INIS)

Lopes, R.T.; Assis, J.T. de

1988-01-01

The reconstruction of a two-dimencional image from one-dimensional projections in an analytic algorithm ''convolution method'' is simulated on a microcomputer. In this work it was analysed the effects caused in the reconstructed image in function of the number of projections and noise level added to the projection data. Qualitative and quantitative (distortion and image noise) comparison were done with the original image and the reconstructed images. (author) [pt

Incorporating HYPR de-noising within iterative PET reconstruction (HYPR-OSEM)

Science.gov (United States)

(Kevin Cheng, Ju-Chieh; Matthews, Julian; Sossi, Vesna; Anton-Rodriguez, Jose; Salomon, André; Boellaard, Ronald

2017-08-01

HighlY constrained back-PRojection (HYPR) is a post-processing de-noising technique originally developed for time-resolved magnetic resonance imaging. It has been recently applied to dynamic imaging for positron emission tomography and shown promising results. In this work, we have developed an iterative reconstruction algorithm (HYPR-OSEM) which improves the signal-to-noise ratio (SNR) in static imaging (i.e. single frame reconstruction) by incorporating HYPR de-noising directly within the ordered subsets expectation maximization (OSEM) algorithm. The proposed HYPR operator in this work operates on the target image(s) from each subset of OSEM and uses the sum of the preceding subset images as the composite which is updated every iteration. Three strategies were used to apply the HYPR operator in OSEM: (i) within the image space modeling component of the system matrix in forward-projection only, (ii) within the image space modeling component in both forward-projection and back-projection, and (iii) on the image estimate after the OSEM update for each subset thus generating three forms: (i) HYPR-F-OSEM, (ii) HYPR-FB-OSEM, and (iii) HYPR-AU-OSEM. Resolution and contrast phantom simulations with various sizes of hot and cold regions as well as experimental phantom and patient data were used to evaluate the performance of the three forms of HYPR-OSEM, and the results were compared to OSEM with and without a post reconstruction filter. It was observed that the convergence in contrast recovery coefficients (CRC) obtained from all forms of HYPR-OSEM was slower than that obtained from OSEM. Nevertheless, HYPR-OSEM improved SNR without degrading accuracy in terms of resolution and contrast. It achieved better accuracy in CRC at equivalent noise level and better precision than OSEM and better accuracy than filtered OSEM in general. In addition, HYPR-AU-OSEM has been determined to be the more effective form of HYPR-OSEM in terms of accuracy and precision based on the studies

Cardiac-gated parametric images from 82 Rb PET from dynamic frames and direct 4D reconstruction.

Science.gov (United States)

Germino, Mary; Carson, Richard E

2018-02-01

Cardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for 82 Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T). PMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated 82 Rb dataset, including a perfusion defect, as well as a human 82 Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a

Accurate 3D reconstruction by a new PDS-OSEM algorithm for HRRT

Science.gov (United States)

Chen, Tai-Been; Horng-Shing Lu, Henry; Kim, Hang-Keun; Son, Young-Don; Cho, Zang-Hee

2014-03-01

State-of-the-art high resolution research tomography (HRRT) provides high resolution PET images with full 3D human brain scanning. But, a short time frame in dynamic study causes many problems related to the low counts in the acquired data. The PDS-OSEM algorithm was proposed to reconstruct the HRRT image with a high signal-to-noise ratio that provides accurate information for dynamic data. The new algorithm was evaluated by simulated image, empirical phantoms, and real human brain data. Meanwhile, the time activity curve was adopted to validate a reconstructed performance of dynamic data between PDS-OSEM and OP-OSEM algorithms. According to simulated and empirical studies, the PDS-OSEM algorithm reconstructs images with higher quality, higher accuracy, less noise, and less average sum of square error than those of OP-OSEM. The presented algorithm is useful to provide quality images under the condition of low count rates in dynamic studies with a short scan time.

An investigation of temporal regularization techniques for dynamic PET reconstructions using temporal splines

International Nuclear Information System (INIS)

Verhaeghe, Jeroen; D'Asseler, Yves; Vandenberghe, Stefaan; Staelens, Steven; Lemahieu, Ignace

2007-01-01

The use of a temporal B-spline basis for the reconstruction of dynamic positron emission tomography data was investigated. Maximum likelihood (ML) reconstructions using an expectation maximization framework and maximum A-posteriori (MAP) reconstructions using the generalized expectation maximization framework were evaluated. Different parameters of the B-spline basis of such as order, number of basis functions and knot placing were investigated in a reconstruction task using simulated dynamic list-mode data. We found that a higher order basis reduced both the bias and variance. Using a higher number of basis functions in the modeling of the time activity curves (TACs) allowed the algorithm to model faster changes of the TACs, however, the TACs became noisier. We have compared ML, Gaussian postsmoothed ML and MAP reconstructions. The noise level in the ML reconstructions was controlled by varying the number of basis functions. The MAP algorithm penalized the integrated squared curvature of the reconstructed TAC. The postsmoothed ML was always outperformed in terms of bias and variance properties by the MAP and ML reconstructions. A simple adaptive knot placing strategy was also developed and evaluated. It is based on an arc length redistribution scheme during the reconstruction. The free knot reconstruction allowed a more accurate reconstruction while reducing the noise level especially for fast changing TACs such as blood input functions. Limiting the number of temporal basis functions combined with the adaptive knot placing strategy is in this case advantageous for regularization purposes when compared to the other regularization techniques

Performance of 3DOSEM and MAP algorithms for reconstructing low count SPECT acquisitions

Energy Technology Data Exchange (ETDEWEB)

Grootjans, Willem [Radboud Univ. Medical Center, Nijmegen (Netherlands). Dept. of Radiology and Nuclear Medicine; Leiden Univ. Medical Center (Netherlands). Dept. of Radiology; Meeuwis, Antoi P.W.; Gotthardt, Martin; Visser, Eric P. [Radboud Univ. Medical Center, Nijmegen (Netherlands). Dept. of Radiology and Nuclear Medicine; Slump, Cornelis H. [Univ. Twente, Enschede (Netherlands). MIRA Inst. for Biomedical Technology and Technical Medicine; Geus-Oei, Lioe-Fee de [Radboud Univ. Medical Center, Nijmegen (Netherlands). Dept. of Radiology and Nuclear Medicine; Univ. Twente, Enschede (Netherlands). MIRA Inst. for Biomedical Technology and Technical Medicine; Leiden Univ. Medical Center (Netherlands). Dept. of Radiology

2016-07-01

Low count single photon emission computed tomography (SPECT) is becoming more important in view of whole body SPECT and reduction of radiation dose. In this study, we investigated the performance of several 3D ordered subset expectation maximization (3DOSEM) and maximum a posteriori (MAP) algorithms for reconstructing low count SPECT images. Phantom experiments were conducted using the National Electrical Manufacturers Association (NEMA) NU2 image quality (IQ) phantom. The background compartment of the phantom was filled with varying concentrations of pertechnetate and indiumchloride, simulating various clinical imaging conditions. Images were acquired using a hybrid SPECT/CT scanner and reconstructed with 3DOSEM and MAP reconstruction algorithms implemented in Siemens Syngo MI.SPECT (Flash3D) and Hermes Hybrid Recon Oncology (Hyrid Recon 3DOSEM and MAP). Image analysis was performed by calculating the contrast recovery coefficient (CRC),percentage background variability (N%), and contrast-to-noise ratio (CNR), defined as the ratio between CRC and N%. Furthermore, image distortion is characterized by calculating the aspect ratio (AR) of ellipses fitted to the hot spheres. Additionally, the performance of these algorithms to reconstruct clinical images was investigated. Images reconstructed with 3DOSEM algorithms demonstrated superior image quality in terms of contrast and resolution recovery when compared to images reconstructed with filtered-back-projection (FBP), OSEM and 2DOSEM. However, occurrence of correlated noise patterns and image distortions significantly deteriorated the quality of 3DOSEM reconstructed images. The mean AR for the 37, 28, 22, and 17 mm spheres was 1.3, 1.3, 1.6, and 1.7 respectively. The mean N% increase in high and low count Flash3D and Hybrid Recon 3DOSEM from 5.9% and 4.0% to 11.1% and 9.0%, respectively. Similarly, the mean CNR decreased in high and low count Flash3D and Hybrid Recon 3DOSEM from 8.7 and 8.8 to 3.6 and 4

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-03-15

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

Quantum interferences reconstruction with low homodyne detection efficiency

Energy Technology Data Exchange (ETDEWEB)

Esposito, Martina; Randi, Francesco [Universita degli studi di Trieste, Dipartimento di Fisica, Trieste (Italy); Titimbo, Kelvin; Zimmermann, Klaus; Benatti, Fabio [Universita degli studi di Trieste, Dipartimento di Fisica, Trieste (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, Trieste (Italy); Kourousias, Georgios; Curri, Alessio [Sincrotrone Trieste S.C.p.A., Trieste (Italy); Floreanini, Roberto [Istituto Nazionale di Fisica Nucleare, Sezione di Trieste, Trieste (Italy); Parmigiani, Fulvio [Universita degli studi di Trieste, Dipartimento di Fisica, Trieste (Italy); Sincrotrone Trieste S.C.p.A., Trieste (Italy); University of Cologne, Institute of Physics II, Cologne (Germany); Fausti, Daniele [Universita degli studi di Trieste, Dipartimento di Fisica, Trieste (Italy); Sincrotrone Trieste S.C.p.A., Trieste (Italy)

2016-12-15

Optical homodyne tomography consists in reconstructing the quantum state of an optical field from repeated measurements of its amplitude at different field phases (homodyne data). The experimental noise, which unavoidably affects the homodyne data, leads to a detection efficiency η<1. The problem of reconstructing quantum states from noisy homodyne data sets prompted an intense scientific debate about the presence or absence of a lower homodyne efficiency bound (η>0.5) below which quantum features, like quantum interferences, cannot be retrieved. Here, by numerical experiments, we demonstrate that quantum interferences can be effectively reconstructed also for low homodyne detection efficiency. In particular, we address the challenging case of a Schroedinger cat state and test the minimax and adaptive Wigner function reconstruction technique by processing homodyne data distributed according to the chosen state but with an efficiency η>0.5. By numerically reproducing the Schroedinger's cat interference pattern, we give evidence that quantum state reconstruction is actually possible in these conditions, and provide a guideline for handling optical tomography based on homodyne data collected by low efficiency detectors. (orig.)

Impact of the adaptive statistical iterative reconstruction technique on image quality in ultra-low-dose CT

International Nuclear Information System (INIS)

Xu, Yan; He, Wen; Chen, Hui; Hu, Zhihai; Li, Juan; Zhang, Tingting

2013-01-01

Aim: To evaluate the relationship between different noise indices (NIs) and radiation dose and to compare the effect of different reconstruction algorithm applications for ultra-low-dose chest computed tomography (CT) on image quality improvement and the accuracy of volumetric measurement of ground-glass opacity (GGO) nodules using a phantom study. Materials and methods: A 11 cm thick transverse phantom section with a chest wall, mediastinum, and 14 artificial GGO nodules with known volumes (919.93 ± 64.05 mm 3 ) was constructed. The phantom was scanned on a Discovery CT 750HD scanner with five different NIs (NIs = 20, 30, 40, 50, and 60). All data were reconstructed with a 0.625 mm section thickness using the filtered back-projection (FBP), 50% adaptive statistical iterative reconstruction (ASiR), and Veo model-base iterative reconstruction algorithms. Image noise was measured in six regions of interest (ROIs). Nodule volumes were measured using a commercial volumetric software package. The image quality and the volume measurement errors were analysed. Results: Image noise increased dramatically from 30.7 HU at NI 20 to 122.4 HU at NI 60, with FBP reconstruction. Conversely, Veo reconstruction effectively controlled the noise increase, with an increase from 9.97 HU at NI 20 to only 15.1 HU at NI 60. Image noise at NI 60 with Veo was even lower (50.8%) than that at NI 20 with FBP. The contrast-to-noise ratio (CNR) of Veo at NI 40 was similar to that of FBP at NI 20. All artificial GGO nodules were successfully identified and measured with an average relative volume measurement error with Veo at NI 60 of 4.24%, comparable to a value of 10.41% with FBP at NI 20. At NI 60, the radiation dose was only one-tenth that at NI 20. Conclusion: The Veo reconstruction algorithms very effectively reduced image noise compared with the conventional FBP reconstructions. Using ultra-low-dose CT scanning and Veo reconstruction, GGOs can be detected and quantified with an acceptable

Comparison of computational to human observer detection for evaluation of CT low dose iterative reconstruction

Science.gov (United States)

Eck, Brendan; Fahmi, Rachid; Brown, Kevin M.; Raihani, Nilgoun; Wilson, David L.

2014-03-01

Model observers were created and compared to human observers for the detection of low contrast targets in computed tomography (CT) images reconstructed with an advanced, knowledge-based, iterative image reconstruction method for low x-ray dose imaging. A 5-channel Laguerre-Gauss Hotelling Observer (CHO) was used with internal noise added to the decision variable (DV) and/or channel outputs (CO). Models were defined by parameters: (k1) DV-noise with standard deviation (std) proportional to DV std; (k2) DV-noise with constant std; (k3) CO-noise with constant std across channels; and (k4) CO-noise in each channel with std proportional to CO variance. Four-alternative forced choice (4AFC) human observer studies were performed on sub-images extracted from phantom images with and without a "pin" target. Model parameters were estimated using maximum likelihood comparison to human probability correct (PC) data. PC in human and all model observers increased with dose, contrast, and size, and was much higher for advanced iterative reconstruction (IMR) as compared to filtered back projection (FBP). Detection in IMR was better than FPB at 1/3 dose, suggesting significant dose savings. Model(k1,k2,k3,k4) gave the best overall fit to humans across independent variables (dose, size, contrast, and reconstruction) at fixed display window. However Model(k1) performed better when considering model complexity using the Akaike information criterion. Model(k1) fit the extraordinary detectability difference between IMR and FBP, despite the different noise quality. It is anticipated that the model observer will predict results from iterative reconstruction methods having similar noise characteristics, enabling rapid comparison of methods.

MO-DE-207A-05: Dictionary Learning Based Reconstruction with Low-Rank Constraint for Low-Dose Spectral CT

International Nuclear Information System (INIS)

Xu, Q; Liu, H; Xing, L; Yu, H; Wang, G

2016-01-01

Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channel and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low-dose spectral

MO-DE-207A-05: Dictionary Learning Based Reconstruction with Low-Rank Constraint for Low-Dose Spectral CT

Energy Technology Data Exchange (ETDEWEB)

Xu, Q [Xi’an Jiaotong University, Xi’an (China); Stanford University School of Medicine, Stanford, CA (United States); Liu, H; Xing, L [Stanford University School of Medicine, Stanford, CA (United States); Yu, H [University of Massachusetts Lowell, Lowell, MA (United States); Wang, G [Rensselaer Polytechnic Instute., Troy, NY (United States)

2016-06-15

Purpose: Spectral CT enabled by an energy-resolved photon-counting detector outperforms conventional CT in terms of material discrimination, contrast resolution, etc. One reconstruction method for spectral CT is to generate a color image from a reconstructed component in each energy channel. However, given the radiation dose, the number of photons in each channel is limited, which will result in strong noise in each channel and affect the final color reconstruction. Here we propose a novel dictionary learning method for spectral CT that combines dictionary-based sparse representation method and the patch based low-rank constraint to simultaneously improve the reconstruction in each channel and to address the inter-channel correlations to further improve the reconstruction. Methods: The proposed method has two important features: (1) guarantee of the patch based sparsity in each energy channel, which is the result of the dictionary based sparse representation constraint; (2) the explicit consideration of the correlations among different energy channels, which is realized by patch-by-patch nuclear norm-based low-rank constraint. For each channel, the dictionary consists of two sub-dictionaries. One is learned from the average of the images in all energy channels, and the other is learned from the average of the images in all energy channels except the current channel. With average operation to reduce noise, these two dictionaries can effectively preserve the structural details and get rid of artifacts caused by noise. Combining them together can express all structural information in current channel. Results: Dictionary learning based methods can obtain better results than FBP and the TV-based method. With low-rank constraint, the image quality can be further improved in the channel with more noise. The final color result by the proposed method has the best visual quality. Conclusion: The proposed method can effectively improve the image quality of low-dose spectral

Noise propagation in iterative reconstruction algorithms with line searches

International Nuclear Information System (INIS)

Qi, Jinyi

2003-01-01

In this paper we analyze the propagation of noise in iterative image reconstruction algorithms. We derive theoretical expressions for the general form of preconditioned gradient algorithms with line searches. The results are applicable to a wide range of iterative reconstruction problems, such as emission tomography, transmission tomography, and image restoration. A unique contribution of this paper comparing to our previous work [1] is that the line search is explicitly modeled and we do not use the approximation that the gradient of the objective function is zero. As a result, the error in the estimate of noise at early iterations is significantly reduced

Reconstruction of Undersampled Big Dynamic MRI Data Using Non-Convex Low-Rank and Sparsity Constraints

Directory of Open Access Journals (Sweden)

Ryan Wen Liu

2017-03-01

Full Text Available Dynamic magnetic resonance imaging (MRI has been extensively utilized for enhancing medical living environment visualization, however, in clinical practice it often suffers from long data acquisition times. Dynamic imaging essentially reconstructs the visual image from raw (k,t-space measurements, commonly referred to as big data. The purpose of this work is to accelerate big medical data acquisition in dynamic MRI by developing a non-convex minimization framework. In particular, to overcome the inherent speed limitation, both non-convex low-rank and sparsity constraints were combined to accelerate the dynamic imaging. However, the non-convex constraints make the dynamic reconstruction problem difficult to directly solve through the commonly-used numerical methods. To guarantee solution efficiency and stability, a numerical algorithm based on Alternating Direction Method of Multipliers (ADMM is proposed to solve the resulting non-convex optimization problem. ADMM decomposes the original complex optimization problem into several simple sub-problems. Each sub-problem has a closed-form solution or could be efficiently solved using existing numerical methods. It has been proven that the quality of images reconstructed from fewer measurements can be significantly improved using non-convex minimization. Numerous experiments have been conducted on two in vivo cardiac datasets to compare the proposed method with several state-of-the-art imaging methods. Experimental results illustrated that the proposed method could guarantee the superior imaging performance in terms of quantitative and visual image quality assessments.

Low-dose CT image reconstruction using gain intervention-based dictionary learning

Science.gov (United States)

Pathak, Yadunath; Arya, K. V.; Tiwari, Shailendra

2018-05-01

Computed tomography (CT) approach is extensively utilized in clinical diagnoses. However, X-ray residue in human body may introduce somatic damage such as cancer. Owing to radiation risk, research has focused on the radiation exposure distributed to patients through CT investigations. Therefore, low-dose CT has become a significant research area. Many researchers have proposed different low-dose CT reconstruction techniques. But, these techniques suffer from various issues such as over smoothing, artifacts, noise, etc. Therefore, in this paper, we have proposed a novel integrated low-dose CT reconstruction technique. The proposed technique utilizes global dictionary-based statistical iterative reconstruction (GDSIR) and adaptive dictionary-based statistical iterative reconstruction (ADSIR)-based reconstruction techniques. In case the dictionary (D) is predetermined, then GDSIR can be used and if D is adaptively defined then ADSIR is appropriate choice. The gain intervention-based filter is also used as a post-processing technique for removing the artifacts from low-dose CT reconstructed images. Experiments have been done by considering the proposed and other low-dose CT reconstruction techniques on well-known benchmark CT images. Extensive experiments have shown that the proposed technique outperforms the available approaches.

Dynamic SPECT reconstruction from few projections: a sparsity enforced matrix factorization approach

Science.gov (United States)

Ding, Qiaoqiao; Zan, Yunlong; Huang, Qiu; Zhang, Xiaoqun

2015-02-01

The reconstruction of dynamic images from few projection data is a challenging problem, especially when noise is present and when the dynamic images are vary fast. In this paper, we propose a variational model, sparsity enforced matrix factorization (SEMF), based on low rank matrix factorization of unknown images and enforced sparsity constraints for representing both coefficients and bases. The proposed model is solved via an alternating iterative scheme for which each subproblem is convex and involves the efficient alternating direction method of multipliers (ADMM). The convergence of the overall alternating scheme for the nonconvex problem relies upon the Kurdyka-Łojasiewicz property, recently studied by Attouch et al (2010 Math. Oper. Res. 35 438) and Attouch et al (2013 Math. Program. 137 91). Finally our proof-of-concept simulation on 2D dynamic images shows the advantage of the proposed method compared to conventional methods.

High dynamic range low-noise focal plane readout for VLWIR applications implemented with current mode background subtraction

Science.gov (United States)

Yang, Guang; Sun, Chao; Shaw, Timothy; Wrigley, Chris; Peddada, Pavani; Blazejewski, Edward R.; Pain, Bedabrata

1998-09-01

Design and operation of a low noise CMOS focal pa;ne readout circuit with ultra-high charge handling capacity is presented. Designed for high-background, VLWIR detector readout, each readout unit cell use an accurate dynamic current memory for automatic subtraction of the dark pedestal in current domain enabling measurement of small signals 85 dB below the dark level. The redout circuit operates with low-power dissipation, high linearity, and is capable of handling pedestal currents up to 300 nA. Measurements indicate an effective charge handling capacity of over 5 X 10(superscript 9) charges/pixel with less than 10(superscript 5) electrons of input referred noise.

Error Propagation dynamics: from PIV-based pressure reconstruction to vorticity field calculation

Science.gov (United States)

Pan, Zhao; Whitehead, Jared; Richards, Geordie; Truscott, Tadd; USU Team; BYU Team

2017-11-01

Noninvasive data from velocimetry experiments (e.g., PIV) have been used to calculate vorticity and pressure fields. However, the noise, error, or uncertainties in the PIV measurements would eventually propagate to the calculated pressure or vorticity field through reconstruction schemes. Despite the vast applications of pressure and/or vorticity field calculated from PIV measurements, studies on the error propagation from the velocity field to the reconstructed fields (PIV-pressure and PIV-vorticity are few. In the current study, we break down the inherent connections between PIV-based pressure reconstruction and PIV-based vorticity calculation. The similar error propagation dynamics, which involve competition between physical properties of the flow and numerical errors from reconstruction schemes, are found in both PIV-pressure and PIV-vorticity reconstructions.

Do our reconstructions of ENSO have too much low-frequency variability?

Science.gov (United States)

Loope, G. R.; Overpeck, J. T.

2017-12-01

Reconstructing the spectrum of Pacific SST variability has proven to be difficult both because of complications with proxy systems such as tree rings and the relatively small number of records from the tropical Pacific. We show that the small number of long coral δ18O and Sr/Ca records has caused a bias towards having too much low-frequency variability in PCR, CPS, and RegEM reconstructions of Pacific variability. This occurs because the individual coral records used in the reconstructions have redder spectra than the shared signal (e.g. ENSO). This causes some of the unshared, low-frequency signal from local climate, salinity and possibly coral biology to bleed into the reconstruction. With enough chronologies in a reconstruction, this unshared noise cancels out but the problem is exacerbated in our longest reconstructions where fewer records are available. Coral proxies tend to have more low-frequency variability than SST observations so this problem is smaller but can still be seen in pseudoproxy experiments using observations and reanalysis data. The identification of this low-frequency bias in coral reconstructions helps bring the spectra of ENSO reconstructions back into line with both models and observations. Although our analysis is mostly constrained to the 20th century due to lack of sufficient data, we expect that as more long chronologies are developed, the low-frequency signal in ENSO reconstructions will be greatly reduced.

Reference Information Based Remote Sensing Image Reconstruction with Generalized Nonconvex Low-Rank Approximation

Directory of Open Access Journals (Sweden)

Hongyang Lu

2016-06-01

Full Text Available Because of the contradiction between the spatial and temporal resolution of remote sensing images (RSI and quality loss in the process of acquisition, it is of great significance to reconstruct RSI in remote sensing applications. Recent studies have demonstrated that reference image-based reconstruction methods have great potential for higher reconstruction performance, while lacking accuracy and quality of reconstruction. For this application, a new compressed sensing objective function incorporating a reference image as prior information is developed. We resort to the reference prior information inherent in interior and exterior data simultaneously to build a new generalized nonconvex low-rank approximation framework for RSI reconstruction. Specifically, the innovation of this paper consists of the following three respects: (1 we propose a nonconvex low-rank approximation for reconstructing RSI; (2 we inject reference prior information to overcome over smoothed edges and texture detail losses; (3 on this basis, we combine conjugate gradient algorithms and a single-value threshold (SVT simultaneously to solve the proposed algorithm. The performance of the algorithm is evaluated both qualitatively and quantitatively. Experimental results demonstrate that the proposed algorithm improves several dBs in terms of peak signal to noise ratio (PSNR and preserves image details significantly compared to most of the current approaches without reference images as priors. In addition, the generalized nonconvex low-rank approximation of our approach is naturally robust to noise, and therefore, the proposed algorithm can handle low resolution with noisy inputs in a more unified framework.

Realistic camera noise modeling with application to improved HDR synthesis

Science.gov (United States)

Goossens, Bart; Luong, Hiêp; Aelterman, Jan; Pižurica, Aleksandra; Philips, Wilfried

2012-12-01

Due to the ongoing miniaturization of digital camera sensors and the steady increase of the "number of megapixels", individual sensor elements of the camera become more sensitive to noise, even deteriorating the final image quality. To go around this problem, sophisticated processing algorithms in the devices, can help to maximally exploit the knowledge on the sensor characteristics (e.g., in terms of noise), and offer a better image reconstruction. Although a lot of research focuses on rather simplistic noise models, such as stationary additive white Gaussian noise, only limited attention has gone to more realistic digital camera noise models. In this article, we first present a digital camera noise model that takes several processing steps in the camera into account, such as sensor signal amplification, clipping, post-processing,.. We then apply this noise model to the reconstruction problem of high dynamic range (HDR) images from a small set of low dynamic range (LDR) exposures of a static scene. In literature, HDR reconstruction is mostly performed by computing a weighted average, in which the weights are directly related to the observer pixel intensities of the LDR image. In this work, we derive a Bayesian probabilistic formulation of a weighting function that is near-optimal in the MSE sense (or SNR sense) of the reconstructed HDR image, by assuming exponentially distributed irradiance values. We define the weighting function as the probability that the observed pixel intensity is approximately unbiased. The weighting function can be directly computed based on the noise model parameters, which gives rise to different symmetric and asymmetric shapes when electronic noise or photon noise is dominant. We also explain how to deal with the case that some of the noise model parameters are unknown and explain how the camera response function can be estimated using the presented noise model. Finally, experimental results are provided to support our findings.

Reversal time of jump-noise magnetization dynamics in nanomagnets via Monte Carlo simulations

Science.gov (United States)

Parthasarathy, Arun; Rakheja, Shaloo

2018-06-01

The jump-noise is a nonhomogeneous Poisson process which models thermal effects in magnetization dynamics, with special applications in low temperature escape rate phenomena. In this work, we develop improved numerical methods for Monte Carlo simulation of the jump-noise dynamics and validate the method by comparing the stationary distribution obtained empirically against the Boltzmann distribution. In accordance with the Néel-Brown theory, the jump-noise dynamics display an exponential relaxation toward equilibrium with a characteristic reversal time, which we extract for nanomagnets with uniaxial and cubic anisotropy. We relate the jump-noise dynamics to the equivalent Landau-Lifshitz dynamics up to second order correction for a general energy landscape and obtain the analogous Néel-Brown theory's solution of the reversal time. We find that the reversal time of jump-noise dynamics is characterized by Néel-Brown theory's solution at the energy saddle point for small noise. For large noise, the magnetization reversal due to jump-noise dynamics phenomenologically represents macroscopic tunneling of magnetization.

Noise and signal properties in PSF-based fully 3D PET image reconstruction: an experimental evaluation

International Nuclear Information System (INIS)

Tong, S; Alessio, A M; Kinahan, P E

2010-01-01

The addition of accurate system modeling in PET image reconstruction results in images with distinct noise texture and characteristics. In particular, the incorporation of point spread functions (PSF) into the system model has been shown to visually reduce image noise, but the noise properties have not been thoroughly studied. This work offers a systematic evaluation of noise and signal properties in different combinations of reconstruction methods and parameters. We evaluate two fully 3D PET reconstruction algorithms: (1) OSEM with exact scanner line of response modeled (OSEM+LOR), (2) OSEM with line of response and a measured point spread function incorporated (OSEM+LOR+PSF), in combination with the effects of four post-reconstruction filtering parameters and 1-10 iterations, representing a range of clinically acceptable settings. We used a modified NEMA image quality (IQ) phantom, which was filled with 68 Ge and consisted of six hot spheres of different sizes with a target/background ratio of 4:1. The phantom was scanned 50 times in 3D mode on a clinical system to provide independent noise realizations. Data were reconstructed with OSEM+LOR and OSEM+LOR+PSF using different reconstruction parameters, and our implementations of the algorithms match the vendor's product algorithms. With access to multiple realizations, background noise characteristics were quantified with four metrics. Image roughness and the standard deviation image measured the pixel-to-pixel variation; background variability and ensemble noise quantified the region-to-region variation. Image roughness is the image noise perceived when viewing an individual image. At matched iterations, the addition of PSF leads to images with less noise defined as image roughness (reduced by 35% for unfiltered data) and as the standard deviation image, while it has no effect on background variability or ensemble noise. In terms of signal to noise performance, PSF-based reconstruction has a 7% improvement in

Muon Signals at a Low Signal-to-Noise Ratio Environment

CERN Document Server

Zakareishvili, Tamar; The ATLAS collaboration

2017-01-01

Calorimeters provide high-resolution energy measurements for particle detection. Muon signals are important for evaluating electronics performance, since they produce a signal that is close to electronic noise values. This work provides a noise RMS analysis for the Demonstrator drawer of the 2016 Tile Calorimeter (TileCal) Test Beam in order to help reconstruct events in a low signal-to-noise environment. Muon signals were then found for a beam penetrating through all three layers of the drawer. The Demonstrator drawer is an electronic candidate for TileCal, part of the ATLAS experiment for the Large Hadron Collider that operates at the European Organization for Nuclear Research (CERN).

Reconstruction of dynamic structures of experimental setups based on measurable experimental data only

Science.gov (United States)

Chen, Tian-Yu; Chen, Yang; Yang, Hu-Jiang; Xiao, Jing-Hua; Hu, Gang

2018-03-01

Nowadays, massive amounts of data have been accumulated in various and wide fields, it has become today one of the central issues in interdisciplinary fields to analyze existing data and extract as much useful information as possible from data. It is often that the output data of systems are measurable while dynamic structures producing these data are hidden, and thus studies to reveal system structures by analyzing available data, i.e., reconstructions of systems become one of the most important tasks of information extractions. In the past, most of the works in this respect were based on theoretical analyses and numerical verifications. Direct analyses of experimental data are very rare. In physical science, most of the analyses of experimental setups were based on the first principles of physics laws, i.e., so-called top-down analyses. In this paper, we conducted an experiment of “Boer resonant instrument for forced vibration” (BRIFV) and inferred the dynamic structure of the experimental set purely from the analysis of the measurable experimental data, i.e., by applying the bottom-up strategy. Dynamics of the experimental set is strongly nonlinear and chaotic, and itʼs subjects to inevitable noises. We proposed to use high-order correlation computations to treat nonlinear dynamics; use two-time correlations to treat noise effects. By applying these approaches, we have successfully reconstructed the structure of the experimental setup, and the dynamic system reconstructed with the measured data reproduces good experimental results in a wide range of parameters.

Noise suppressed partial volume correction for cardiac SPECT/CT

Energy Technology Data Exchange (ETDEWEB)

Chan, Chung; Liu, Chi, E-mail: chi.liu@yale.edu [Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut 06520 (United States); Liu, Hui [Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut 06520 and Key Laboratory of Particle and Radiation Imaging (Tsinghua University), Ministry of Education, Beijing 100084 (China); Grobshtein, Yariv [GE Healthcare, Haifa 3910101 (Israel); Stacy, Mitchel R. [Department of Internal Medicine, Yale University, New Haven, Connecticut 06520 (United States); Sinusas, Albert J. [Department of Radiology and Biomedical Imaging, Yale University, New Haven, Connecticut 06520 and Department of Internal Medicine, Yale University, New Haven, Connecticut 06520 (United States)

2016-09-15

Purpose: Partial volume correction (PVC) methods typically improve quantification at the expense of increased image noise and reduced reproducibility. In this study, the authors developed a novel voxel-based PVC method that incorporates anatomical knowledge to improve quantification while suppressing noise for cardiac SPECT/CT imaging. Methods: In the proposed method, the SPECT images were first reconstructed using anatomical-based maximum a posteriori (AMAP) with Bowsher’s prior to penalize noise while preserving boundaries. A sequential voxel-by-voxel PVC approach (Yang’s method) was then applied on the AMAP reconstruction using a template response. This template response was obtained by forward projecting a template derived from a contrast-enhanced CT image, and then reconstructed using AMAP to model the partial volume effects (PVEs) introduced by both the system resolution and the smoothing applied during reconstruction. To evaluate the proposed noise suppressed PVC (NS-PVC), the authors first simulated two types of cardiac SPECT studies: a {sup 99m}Tc-tetrofosmin myocardial perfusion scan and a {sup 99m}Tc-labeled red blood cell (RBC) scan on a dedicated cardiac multiple pinhole SPECT/CT at both high and low count levels. The authors then applied the proposed method on a canine equilibrium blood pool study following injection with {sup 99m}Tc-RBCs at different count levels by rebinning the list-mode data into shorter acquisitions. The proposed method was compared to MLEM reconstruction without PVC, two conventional PVC methods, including Yang’s method and multitarget correction (MTC) applied on the MLEM reconstruction, and AMAP reconstruction without PVC. Results: The results showed that the Yang’s method improved quantification, however, yielded increased noise and reduced reproducibility in the regions with higher activity. MTC corrected for PVE on high count data with amplified noise, although yielded the worst performance among all the methods

Motion estimation and compensation in dynamic spiral CT reconstruction

International Nuclear Information System (INIS)

Kimdon, J.; Grangeat, P.; Koenig, A.; Bonnet, St.

2004-01-01

Respiratory and cardiac motion causes blurring in dynamic X-ray Computed Tomography (CT). Fast scans reduce this problem, but they require a higher radiation dose per time period to maintain the signal to noise ratio of the resulting images, thereby magnifying the health risk to the patient. As an alternative to increased radiation, our team has already developed a cone-beam reconstruction algorithm based on a dynamic particle model that estimates, predicts, and compensates for respiratory motion in circular X-ray CT. The current paper presents an extension of this method to spiral CT, applicable to modern multi-slice scanners that take advantage of the speed and dose benefits of helical trajectories. We adapted all three main areas of the algorithm: backprojection, prediction, and compensation/accumulation. In backprojection, we changed the longitudinal re-binning technique, filter direction, and the method of enforcing the data sufficiency requirements. For prediction, we had to be careful of objects appearing and disappearing as the scanner bed advanced. For compensation/accumulation, we controlled the reconstruction time and combined images to cover a greater longitudinal extent for each phase in the respiratory or cardiac cycle. Tests with moving numerical phantoms demonstrate that the algorithm successfully improves the temporal resolution of the images without increasing the dose or reducing the signal-to-noise ratio. (authors)

A Kullback-Leibler approach for 3D reconstruction of spectral CT data corrupted by Poisson noise

Science.gov (United States)

Hohweiller, Tom; Ducros, Nicolas; Peyrin, Françoise; Sixou, Bruno

2017-09-01

While standard computed tomography (CT) data do not depend on energy, spectral computed tomography (SPCT) acquire energy-resolved data, which allows material decomposition of the object of interest. Decompo- sitions in the projection domain allow creating projection mass density (PMD) per materials. From decomposed projections, a tomographic reconstruction creates 3D material density volume. The decomposition is made pos- sible by minimizing a cost function. The variational approach is preferred since this is an ill-posed non-linear inverse problem. Moreover, noise plays a critical role when decomposing data. That is why in this paper, a new data fidelity term is used to take into account of the photonic noise. In this work two data fidelity terms were investigated: a weighted least squares (WLS) term, adapted to Gaussian noise, and the Kullback-Leibler distance (KL), adapted to Poisson noise. A regularized Gauss-Newton algorithm minimizes the cost function iteratively. Both methods decompose materials from a numerical phantom of a mouse. Soft tissues and bones are decomposed in the projection domain; then a tomographic reconstruction creates a 3D material density volume for each material. Comparing relative errors, KL is shown to outperform WLS for low photon counts, in 2D and 3D. This new method could be of particular interest when low-dose acquisitions are performed.

Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: application to high-quality head imaging

International Nuclear Information System (INIS)

Dang, H; Stayman, J W; Sisniega, A; Xu, J; Zbijewski, W; Siewerdsen, J H; Wang, X; Foos, D H; Aygun, N; Koliatsos, V E

2015-01-01

Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ∼40–80 HU, size  >  1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution, CNR = 11.9 compared to CNR = 5.6 and CNR = 9.9, respectively) and substantially reduced image noise especially in challenging regions such as skull base. The results support the hypothesis that with high-fidelity artifact correction and statistical reconstruction using an accurate post-artifact-correction noise model, FPD-CBCT can achieve image quality allowing reliable detection of

MR-guided dynamic PET reconstruction with the kernel method and spectral temporal basis functions

Science.gov (United States)

Novosad, Philip; Reader, Andrew J.

2016-06-01

Recent advances in dynamic positron emission tomography (PET) reconstruction have demonstrated that it is possible to achieve markedly improved end-point kinetic parameter maps by incorporating a temporal model of the radiotracer directly into the reconstruction algorithm. In this work we have developed a highly constrained, fully dynamic PET reconstruction algorithm incorporating both spectral analysis temporal basis functions and spatial basis functions derived from the kernel method applied to a co-registered T1-weighted magnetic resonance (MR) image. The dynamic PET image is modelled as a linear combination of spatial and temporal basis functions, and a maximum likelihood estimate for the coefficients can be found using the expectation-maximization (EM) algorithm. Following reconstruction, kinetic fitting using any temporal model of interest can be applied. Based on a BrainWeb T1-weighted MR phantom, we performed a realistic dynamic [18F]FDG simulation study with two noise levels, and investigated the quantitative performance of the proposed reconstruction algorithm, comparing it with reconstructions incorporating either spectral analysis temporal basis functions alone or kernel spatial basis functions alone, as well as with conventional frame-independent reconstruction. Compared to the other reconstruction algorithms, the proposed algorithm achieved superior performance, offering a decrease in spatially averaged pixel-level root-mean-square-error on post-reconstruction kinetic parametric maps in the grey/white matter, as well as in the tumours when they were present on the co-registered MR image. When the tumours were not visible in the MR image, reconstruction with the proposed algorithm performed similarly to reconstruction with spectral temporal basis functions and was superior to both conventional frame-independent reconstruction and frame-independent reconstruction with kernel spatial basis functions. Furthermore, we demonstrate that a joint spectral

Emergence of nonwhite noise in Langevin dynamics with magnetic Lorentz force

Science.gov (United States)

Chun, Hyun-Myung; Durang, Xavier; Noh, Jae Dong

2018-03-01

We investigate the low mass limit of Langevin dynamics for a charged Brownian particle driven by a magnetic Lorentz force. In the low mass limit, velocity variables relaxing quickly are coarse-grained out to yield effective dynamics for position variables. Without the Lorentz force, the low mass limit is equivalent to the high friction limit. Both cases share the same Langevin equation that is obtained by setting the mass to zero. The equivalence breaks down in the presence of the Lorentz force. The low mass limit cannot be achieved by setting the mass to zero. The limit is also distinct from the large friction limit. We derive the effective equations of motion in the low mass limit. The resulting stochastic differential equation involves a nonwhite noise whose correlation matrix has antisymmetric components. We demonstrate the importance of the nonwhite noise by investigating the heat dissipation by a driven Brownian particle, where the emergent nonwhite noise has a physically measurable effect.

Characteristics of computed tomographic reconstruction noise and their effect on detectability

International Nuclear Information System (INIS)

Hanson, K.M.; Boyd, D.P.

1977-01-01

The EMI 5005 scanner produces images with noise characteristics similar to those in simulated CT reconstructions. A detectability phantom is described which will provide a means of investigation of the effect on human detection capability of the peculiar correlations present in the noise present in CT scanner images

Annoyance of low frequency noise and traffic noise

DEFF Research Database (Denmark)

Mortensen, F.R.; Poulsen, Torben

2001-01-01

The annoyance of different low frequency noise sources was determined and compared to the annoyance from traffic noise. Twenty-two subjects participated in laboratory listening tests. The sounds were presented by loudspeakers in a listening room and the spectra of the low frequency noises were...

A deep convolutional neural network using directional wavelets for low-dose X-ray CT reconstruction.

Science.gov (United States)

Kang, Eunhee; Min, Junhong; Ye, Jong Chul

2017-10-01

Due to the potential risk of inducing cancer, radiation exposure by X-ray CT devices should be reduced for routine patient scanning. However, in low-dose X-ray CT, severe artifacts typically occur due to photon starvation, beam hardening, and other causes, all of which decrease the reliability of the diagnosis. Thus, a high-quality reconstruction method from low-dose X-ray CT data has become a major research topic in the CT community. Conventional model-based de-noising approaches are, however, computationally very expensive, and image-domain de-noising approaches cannot readily remove CT-specific noise patterns. To tackle these problems, we want to develop a new low-dose X-ray CT algorithm based on a deep-learning approach. We propose an algorithm which uses a deep convolutional neural network (CNN) which is applied to the wavelet transform coefficients of low-dose CT images. More specifically, using a directional wavelet transform to extract the directional component of artifacts and exploit the intra- and inter- band correlations, our deep network can effectively suppress CT-specific noise. In addition, our CNN is designed with a residual learning architecture for faster network training and better performance. Experimental results confirm that the proposed algorithm effectively removes complex noise patterns from CT images derived from a reduced X-ray dose. In addition, we show that the wavelet-domain CNN is efficient when used to remove noise from low-dose CT compared to existing approaches. Our results were rigorously evaluated by several radiologists at the Mayo Clinic and won second place at the 2016 "Low-Dose CT Grand Challenge." To the best of our knowledge, this work is the first deep-learning architecture for low-dose CT reconstruction which has been rigorously evaluated and proven to be effective. In addition, the proposed algorithm, in contrast to existing model-based iterative reconstruction (MBIR) methods, has considerable potential to benefit from

Low rank alternating direction method of multipliers reconstruction for MR fingerprinting.

Science.gov (United States)

Assländer, Jakob; Cloos, Martijn A; Knoll, Florian; Sodickson, Daniel K; Hennig, Jürgen; Lattanzi, Riccardo

2018-01-01

The proposed reconstruction framework addresses the reconstruction accuracy, noise propagation and computation time for magnetic resonance fingerprinting. Based on a singular value decomposition of the signal evolution, magnetic resonance fingerprinting is formulated as a low rank (LR) inverse problem in which one image is reconstructed for each singular value under consideration. This LR approximation of the signal evolution reduces the computational burden by reducing the number of Fourier transformations. Also, the LR approximation improves the conditioning of the problem, which is further improved by extending the LR inverse problem to an augmented Lagrangian that is solved by the alternating direction method of multipliers. The root mean square error and the noise propagation are analyzed in simulations. For verification, in vivo examples are provided. The proposed LR alternating direction method of multipliers approach shows a reduced root mean square error compared to the original fingerprinting reconstruction, to a LR approximation alone and to an alternating direction method of multipliers approach without a LR approximation. Incorporating sensitivity encoding allows for further artifact reduction. The proposed reconstruction provides robust convergence, reduced computational burden and improved image quality compared to other magnetic resonance fingerprinting reconstruction approaches evaluated in this study. Magn Reson Med 79:83-96, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Carotid dual-energy CT angiography: Evaluation of low keV calculated monoenergetic datasets by means of a frequency-split approach for noise reduction at low keV levels.

Science.gov (United States)

Riffel, Philipp; Haubenreisser, Holger; Meyer, Mathias; Sudarski, Sonja; Morelli, John N; Schmidt, Bernhard; Schoenberg, Stefan O; Henzler, Thomas

2016-04-01

Calculated monoenergetic ultra-low keV datasets did not lead to improved contrast-to-noise ratio (CNR) due to the dramatic increase in image noise. The aim of the present study was to evaluate the objective image quality of ultra-low keV monoenergetic images (MEIs) calculated from carotid DECT angiography data with a new monoenergetic imaging algorithm using a frequency-split technique. 20 patients (12 male; mean age 53±17 years) were retrospectively analyzed. MEIs from 40 to 120 keV were reconstructed using the monoenergetic split frequency approach (MFSA). Additionally MEIs were reconstructed for 40 and 50 keV using a conventional monoenergetic (CM) software application. Signal intensity, noise, signal-to-noise ratio (SNR) and CNR were assessed in the basilar, common, internal carotid arteries. Ultra-low keV MEIs at 40 keV and 50 keV demonstrated highest vessel attenuation, significantly greater than those of the polyenergetic images (PEI) (all p-values 0.05). Thus MEIs with MFSA showed significantly higher SNR and CNR compared to MEIs with CM. Combining the lower spatial frequency stack for contrast at low keV levels with the high spatial frequency stack for noise at high keV levels (frequency-split technique) leads to improved image quality of ultra-low keV monoenergetic DECT datasets when compared to previous monoenergetic reconstruction techniques without the frequency-split technique. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Dynamic PET reconstruction using temporal patch-based low rank penalty for ROI-based brain kinetic analysis

International Nuclear Information System (INIS)

Kim, Kyungsang; Ye, Jong Chul; Son, Young Don; Cho, Zang Hee; Bresler, Yoram; Ra, Jong Beom

2015-01-01

Dynamic positron emission tomography (PET) is widely used to measure changes in the bio-distribution of radiopharmaceuticals within particular organs of interest over time. However, to retain sufficient temporal resolution, the number of photon counts in each time frame must be limited. Therefore, conventional reconstruction algorithms such as the ordered subset expectation maximization (OSEM) produce noisy reconstruction images, thus degrading the quality of the extracted time activity curves (TACs). To address this issue, many advanced reconstruction algorithms have been developed using various spatio-temporal regularizations. In this paper, we extend earlier results and develop a novel temporal regularization, which exploits the self-similarity of patches that are collected in dynamic images. The main contribution of this paper is to demonstrate that the correlation of patches can be exploited using a low-rank constraint that is insensitive to global intensity variations. The resulting optimization framework is, however, non-Lipschitz and non-convex due to the Poisson log-likelihood and low-rank penalty terms. Direct application of the conventional Poisson image deconvolution by an augmented Lagrangian (PIDAL) algorithm is, however, problematic due to its large memory requirements, which prevents its parallelization. Thus, we propose a novel optimization framework using the concave-convex procedure (CCCP) by exploiting the Legendre–Fenchel transform, which is computationally efficient and parallelizable. In computer simulation and a real in vivo experiment using a high-resolution research tomograph (HRRT) scanner, we confirm that the proposed algorithm can improve image quality while also extracting more accurate region of interests (ROI) based kinetic parameters. Furthermore, we show that the total reconstruction time for HRRT PET is significantly accelerated using our GPU implementation, which makes the algorithm very practical in clinical environments

Experimental study of stochastic noise propagation in SPECT images reconstructed using the conjugate gradient algorithm.

Science.gov (United States)

Mariano-Goulart, D; Fourcade, M; Bernon, J L; Rossi, M; Zanca, M

2003-01-01

Thanks to an experimental study based on simulated and physical phantoms, the propagation of the stochastic noise in slices reconstructed using the conjugate gradient algorithm has been analysed versus iterations. After a first increase corresponding to the reconstruction of the signal, the noise stabilises before increasing linearly with iterations. The level of the plateau as well as the slope of the subsequent linear increase depends on the noise in the projection data.

A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems

Science.gov (United States)

Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J.

2017-06-01

We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

A Bayesian nonparametric approach to reconstruction and prediction of random dynamical systems.

Science.gov (United States)

Merkatas, Christos; Kaloudis, Konstantinos; Hatjispyros, Spyridon J

2017-06-01

We propose a Bayesian nonparametric mixture model for the reconstruction and prediction from observed time series data, of discretized stochastic dynamical systems, based on Markov Chain Monte Carlo methods. Our results can be used by researchers in physical modeling interested in a fast and accurate estimation of low dimensional stochastic models when the size of the observed time series is small and the noise process (perhaps) is non-Gaussian. The inference procedure is demonstrated specifically in the case of polynomial maps of an arbitrary degree and when a Geometric Stick Breaking mixture process prior over the space of densities, is applied to the additive errors. Our method is parsimonious compared to Bayesian nonparametric techniques based on Dirichlet process mixtures, flexible and general. Simulations based on synthetic time series are presented.

Value of a noise-optimized virtual monoenergetic reconstruction technique in dual-energy CT for planning of transcatheter aortic valve replacement

International Nuclear Information System (INIS)

Martin, Simon S.; Albrecht, Moritz H.; Wichmann, Julian L.; Huesers, Kristina; Scholtz, Jan-Erik; Booz, Christian; Bodelle, Boris; Bauer, Ralf W.; Metzger, Sarah C.; Vogl, Thomas J.; Lehnert, Thomas

2017-01-01

To evaluate objective and subjective image quality of a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique in dual-energy computed tomography (DECT) angiography prior to transcatheter aortic valve replacement (TAVR). Datasets of 47 patients (35 men; 64.1 ± 10.9 years) who underwent DECT angiography of heart and vascular access prior to TAVR were reconstructed with standard linear blending (F_0.5), VMI+, and traditional monoenergetic (VMI) algorithms in 10-keV intervals from 40-100 keV. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of 564 arterial segments were evaluated. Subjective analysis was rated by three blinded observers using a Likert scale. Mean SNR and CNR were highest in 40 keV VMI+ series (SNR, 27.8 ± 13.0; CNR, 26.3 ± 12.7), significantly (all p 0.05), significantly superior to all VMI and standard linearly-blended images (all p < 0.01). Low-keV VMI+ reconstructions significantly increase CNR and SNR compared to VMI and standard linear-blending image reconstruction and improve subjective image quality in preprocedural DECT angiography in the context of TAVR planning. (orig.)

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

International Nuclear Information System (INIS)

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

2005-01-01

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

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.

Low noise constant current source for bias dependent noise measurements

International Nuclear Information System (INIS)

Talukdar, D.; Bose, Suvendu; Bardhan, K. K.; Chakraborty, R. K.

2011-01-01

A low noise constant current source used for measuring the 1/f noise in disordered systems in ohmic as well as nonohmic regime is described. The source can supply low noise constant current starting from as low as 1 μA to a few tens of milliampere with a high voltage compliance limit of around 20 V. The constant current source has several stages, which can work in a standalone manner or together to supply the desired value of load current. The noise contributed by the current source is very low in the entire current range. The fabrication of a low noise voltage preamplifier modified for bias dependent noise measurements and based on the existing design available in the MAT04 data sheet is also described.

A quantitative comparison of noise reduction across five commercial (hybrid and model-based) iterative reconstruction techniques: an anthropomorphic phantom study.

Science.gov (United States)

Patino, Manuel; Fuentes, Jorge M; Hayano, Koichi; Kambadakone, Avinash R; Uyeda, Jennifer W; Sahani, Dushyant V

2015-02-01

OBJECTIVE. The objective of our study was to compare the performance of three hybrid iterative reconstruction techniques (IRTs) (ASiR, iDose4, SAFIRE) and their respective strengths for image noise reduction on low-dose CT examinations using filtered back projection (FBP) as the standard reference. Also, we compared the performance of these three hybrid IRTs with two model-based IRTs (Veo and IMR) for image noise reduction on low-dose examinations. MATERIALS AND METHODS. An anthropomorphic abdomen phantom was scanned at 100 and 120 kVp and different tube current-exposure time products (25-100 mAs) on three CT systems (for ASiR and Veo, Discovery CT750 HD; for iDose4 and IMR, Brilliance iCT; and for SAFIRE, Somatom Definition Flash). Images were reconstructed using FBP and using IRTs at various strengths. Nine noise measurements (mean ROI size, 423 mm(2)) on extracolonic fat for the different strengths of IRTs were recorded and compared with FBP using ANOVA. Radiation dose, which was measured as the volume CT dose index and dose-length product, was also compared. RESULTS. There were no significant differences in radiation dose and image noise among the scanners when FBP was used (p > 0.05). Gradual image noise reduction was observed with each increasing increment of hybrid IRT strength, with a maximum noise suppression of approximately 50% (48.2-53.9%). Similar noise reduction was achieved on the scanners by applying specific hybrid IRT strengths. Maximum noise reduction was higher on model-based IRTs (68.3-81.1%) than hybrid IRTs (48.2-53.9%) (p < 0.05). CONCLUSION. When constant scanning parameters are used, radiation dose and image noise on FBP are similar for CT scanners made by different manufacturers. Significant image noise reduction is achieved on low-dose CT examinations rendered with IRTs. The image noise on various scanners can be matched by applying specific hybrid IRT strengths. Model-based IRTs attain substantially higher noise reduction than hybrid

Priori mask guided image reconstruction (p-MGIR) for ultra-low dose cone-beam computed tomography

Science.gov (United States)

Park, Justin C.; Zhang, Hao; Chen, Yunmei; Fan, Qiyong; Kahler, Darren L.; Liu, Chihray; Lu, Bo

2015-11-01

Recently, the compressed sensing (CS) based iterative reconstruction method has received attention because of its ability to reconstruct cone beam computed tomography (CBCT) images with good quality using sparsely sampled or noisy projections, thus enabling dose reduction. However, some challenges remain. In particular, there is always a tradeoff between image resolution and noise/streak artifact reduction based on the amount of regularization weighting that is applied uniformly across the CBCT volume. The purpose of this study is to develop a novel low-dose CBCT reconstruction algorithm framework called priori mask guided image reconstruction (p-MGIR) that allows reconstruction of high-quality low-dose CBCT images while preserving the image resolution. In p-MGIR, the unknown CBCT volume was mathematically modeled as a combination of two regions: (1) where anatomical structures are complex, and (2) where intensities are relatively uniform. The priori mask, which is the key concept of the p-MGIR algorithm, was defined as the matrix that distinguishes between the two separate CBCT regions where the resolution needs to be preserved and where streak or noise needs to be suppressed. We then alternately updated each part of image by solving two sub-minimization problems iteratively, where one minimization was focused on preserving the edge information of the first part while the other concentrated on the removal of noise/artifacts from the latter part. To evaluate the performance of the p-MGIR algorithm, a numerical head-and-neck phantom, a Catphan 600 physical phantom, and a clinical head-and-neck cancer case were used for analysis. The results were compared with the standard Feldkamp-Davis-Kress as well as conventional CS-based algorithms. Examination of the p-MGIR algorithm showed that high-quality low-dose CBCT images can be reconstructed without compromising the image resolution. For both phantom and the patient cases, the p-MGIR is able to achieve a clinically

A Third-Generation Adaptive Statistical Iterative Reconstruction Technique: Phantom Study of Image Noise, Spatial Resolution, Lesion Detectability, and Dose Reduction Potential.

Science.gov (United States)

Euler, André; Solomon, Justin; Marin, Daniele; Nelson, Rendon C; Samei, Ehsan

2018-06-01

The purpose of this study was to assess image noise, spatial resolution, lesion detectability, and the dose reduction potential of a proprietary third-generation adaptive statistical iterative reconstruction (ASIR-V) technique. A phantom representing five different body sizes (12-37 cm) and a contrast-detail phantom containing lesions of five low-contrast levels (5-20 HU) and three sizes (2-6 mm) were deployed. Both phantoms were scanned on a 256-MDCT scanner at six different radiation doses (1.25-10 mGy). Images were reconstructed with filtered back projection (FBP), ASIR-V with 50% blending with FBP (ASIR-V 50%), and ASIR-V without blending (ASIR-V 100%). In the first phantom, noise properties were assessed by noise power spectrum analysis. Spatial resolution properties were measured by use of task transfer functions for objects of different contrasts. Noise magnitude, noise texture, and resolution were compared between the three groups. In the second phantom, low-contrast detectability was assessed by nine human readers independently for each condition. The dose reduction potential of ASIR-V was estimated on the basis of a generalized linear statistical regression model. On average, image noise was reduced 37.3% with ASIR-V 50% and 71.5% with ASIR-V 100% compared with FBP. ASIR-V shifted the noise power spectrum toward lower frequencies compared with FBP. The spatial resolution of ASIR-V was equivalent or slightly superior to that of FBP, except for the low-contrast object, which had lower resolution. Lesion detection significantly increased with both ASIR-V levels (p = 0.001), with an estimated radiation dose reduction potential of 15% ± 5% (SD) for ASIR-V 50% and 31% ± 9% for ASIR-V 100%. ASIR-V reduced image noise and improved lesion detection compared with FBP and had potential for radiation dose reduction while preserving low-contrast detectability.

A Total Variation-Based Reconstruction Method for Dynamic MRI

Directory of Open Access Journals (Sweden)

Germana Landi

2008-01-01

Full Text Available In recent years, total variation (TV regularization has become a popular and powerful tool for image restoration and enhancement. In this work, we apply TV minimization to improve the quality of dynamic magnetic resonance images. Dynamic magnetic resonance imaging is an increasingly popular clinical technique used to monitor spatio-temporal changes in tissue structure. Fast data acquisition is necessary in order to capture the dynamic process. Most commonly, the requirement of high temporal resolution is fulfilled by sacrificing spatial resolution. Therefore, the numerical methods have to address the issue of images reconstruction from limited Fourier data. One of the most successful techniques for dynamic imaging applications is the reduced-encoded imaging by generalized-series reconstruction method of Liang and Lauterbur. However, even if this method utilizes a priori data for optimal image reconstruction, the produced dynamic images are degraded by truncation artifacts, most notably Gibbs ringing, due to the spatial low resolution of the data. We use a TV regularization strategy in order to reduce these truncation artifacts in the dynamic images. The resulting TV minimization problem is solved by the fixed point iteration method of Vogel and Oman. The results of test problems with simulated and real data are presented to illustrate the effectiveness of the proposed approach in reducing the truncation artifacts of the reconstructed images.

LBP-based penalized weighted least-squares approach to low-dose cone-beam computed tomography reconstruction

Science.gov (United States)

Ma, Ming; Wang, Huafeng; Liu, Yan; Zhang, Hao; Gu, Xianfeng; Liang, Zhengrong

2014-03-01

Cone-beam computed tomography (CBCT) has attracted growing interest of researchers in image reconstruction. The mAs level of the X-ray tube current, in practical application of CBCT, is mitigated in order to reduce the CBCT dose. The lowering of the X-ray tube current, however, results in the degradation of image quality. Thus, low-dose CBCT image reconstruction is in effect a noise problem. To acquire clinically acceptable quality of image, and keep the X-ray tube current as low as achievable in the meanwhile, some penalized weighted least-squares (PWLS)-based image reconstruction algorithms have been developed. One representative strategy in previous work is to model the prior information for solution regularization using an anisotropic penalty term. To enhance the edge preserving and noise suppressing in a finer scale, a novel algorithm combining the local binary pattern (LBP) with penalized weighted leastsquares (PWLS), called LBP-PWLS-based image reconstruction algorithm, is proposed in this work. The proposed LBP-PWLS-based algorithm adaptively encourages strong diffusion on the local spot/flat region around a voxel and less diffusion on edge/corner ones by adjusting the penalty for cost function, after the LBP is utilized to detect the region around the voxel as spot, flat and edge ones. The LBP-PWLS-based reconstruction algorithm was evaluated using the sinogram data acquired by a clinical CT scanner from the CatPhan® 600 phantom. Experimental results on the noiseresolution tradeoff measurement and other quantitative measurements demonstrated its feasibility and effectiveness in edge preserving and noise suppressing in comparison with a previous PWLS reconstruction algorithm.

Evaluation of bias and variance in low-count OSEM list mode reconstruction

International Nuclear Information System (INIS)

Jian, Y; Carson, R E; Planeta, B

2015-01-01

Statistical algorithms have been widely used in PET image reconstruction. The maximum likelihood expectation maximization reconstruction has been shown to produce bias in applications where images are reconstructed from a relatively small number of counts. In this study, image bias and variability in low-count OSEM reconstruction are investigated on images reconstructed with MOLAR (motion-compensation OSEM list-mode algorithm for resolution-recovery reconstruction) platform. A human brain ([ 11 C]AFM) and a NEMA phantom are used in the simulation and real experiments respectively, for the HRRT and Biograph mCT. Image reconstructions were repeated with different combinations of subsets and iterations. Regions of interest were defined on low-activity and high-activity regions to evaluate the bias and noise at matched effective iteration numbers (iterations × subsets). Minimal negative biases and no positive biases were found at moderate count levels and less than 5% negative bias was found using extremely low levels of counts (0.2 M NEC). At any given count level, other factors, such as subset numbers and frame-based scatter correction may introduce small biases (1–5%) in the reconstructed images. The observed bias was substantially lower than that reported in the literature, perhaps due to the use of point spread function and/or other implementation methods in MOLAR. (paper)

A noise power spectrum study of a new model‐based iterative reconstruction system: Veo 3.0

Science.gov (United States)

Li, Guang; Liu, Xinming; Dodge, Cristina T.; Jensen, Corey T.

2016-01-01

The purpose of this study was to evaluate performance of the third generation of model‐based iterative reconstruction (MBIR) system, Veo 3.0, based on noise power spectrum (NPS) analysis with various clinical presets over a wide range of clinically applicable dose levels. A CatPhan 600 surrounded by an oval, fat‐equivalent ring to mimic patient size/shape was scanned 10 times at each of six dose levels on a GE HD 750 scanner. NPS analysis was performed on images reconstructed with various Veo 3.0 preset combinations for comparisons of those images reconstructed using Veo 2.0, filtered back projection (FBP) and adaptive statistical iterative reconstruction (ASiR). The new Target Thickness setting resulted in higher noise in thicker axial images. The new Texture Enhancement function achieved a more isotropic noise behavior with less image artifacts. Veo 3.0 provides additional reconstruction options designed to allow the user choice of balance between spatial resolution and image noise, relative to Veo 2.0. Veo 3.0 provides more user selectable options and in general improved isotropic noise behavior in comparison to Veo 2.0. The overall noise reduction performance of both versions of MBIR was improved in comparison to FBP and ASiR, especially at low‐dose levels. PACS number(s): 87.57.‐s, 87.57.Q‐, 87.57.C‐, 87.57.nf, 87.57.C‐, 87.57.cm PMID:27685118

Low-dose X-ray CT reconstruction via dictionary learning.

Science.gov (United States)

Xu, Qiong; Yu, Hengyong; Mou, Xuanqin; Zhang, Lei; Hsieh, Jiang; Wang, Ge

2012-09-01

Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures.

Low frequency noise study.

Science.gov (United States)

2007-04-01

This report documents a study to investigate human response to the low-frequency : content of aviation noise, or low-frequency noise (LFN). The study comprised field : measurements and laboratory studies. The major findings were: : 1. Start-of-takeof...

A Shearlet-based algorithm for quantum noise removal in low-dose CT images

Science.gov (United States)

Zhang, Aguan; Jiang, Huiqin; Ma, Ling; Liu, Yumin; Yang, Xiaopeng

2016-03-01

Low-dose CT (LDCT) scanning is a potential way to reduce the radiation exposure of X-ray in the population. It is necessary to improve the quality of low-dose CT images. In this paper, we propose an effective algorithm for quantum noise removal in LDCT images using shearlet transform. Because the quantum noise can be simulated by Poisson process, we first transform the quantum noise by using anscombe variance stabilizing transform (VST), producing an approximately Gaussian noise with unitary variance. Second, the non-noise shearlet coefficients are obtained by adaptive hard-threshold processing in shearlet domain. Third, we reconstruct the de-noised image using the inverse shearlet transform. Finally, an anscombe inverse transform is applied to the de-noised image, which can produce the improved image. The main contribution is to combine the anscombe VST with the shearlet transform. By this way, edge coefficients and noise coefficients can be separated from high frequency sub-bands effectively. A number of experiments are performed over some LDCT images by using the proposed method. Both quantitative and visual results show that the proposed method can effectively reduce the quantum noise while enhancing the subtle details. It has certain value in clinical application.

Low-dose CT imaging of a total hip arthroplasty phantom using model-based iterative reconstruction and orthopedic metal artifact reduction

Energy Technology Data Exchange (ETDEWEB)

Wellenberg, R.H.H.; Streekstra, G.J.; Maas, M. [Academic Medical Center, Department of Radiology, Amsterdam (Netherlands); Boomsma, M.F.; Osch, J.A.C. van [Department of Radiology, Zwolle (Netherlands); Vlassenbroek, A. [Philips Medical Systems, Brussels (Belgium); Milles, J. [Philips Medical Systems, Eindhoven (Netherlands); Edens, M.A. [Department of Innovation and Science, Zwolle (Netherlands); Slump, C.H. [University of Twente, MIRA Institute for Biomedical Technology and Technical Medicine, Enschede (Netherlands)

2017-05-15

To compare quantitative measures of image quality, in terms of CT number accuracy, noise, signal-to-noise-ratios (SNRs), and contrast-to-noise ratios (CNRs), at different dose levels with filtered-back-projection (FBP), iterative reconstruction (IR), and model-based iterative reconstruction (MBIR) alone and in combination with orthopedic metal artifact reduction (O-MAR) in a total hip arthroplasty (THA) phantom. Scans were acquired from high- to low-dose (CTDI{sub vol}: 40.0, 32.0, 24.0, 16.0, 8.0, and 4.0 mGy) at 120- and 140- kVp. Images were reconstructed using FBP, IR (iDose{sup 4} level 2, 4, and 6) and MBIR (IMR, level 1, 2, and 3) with and without O-MAR. CT number accuracy in Hounsfield Units (HU), noise or standard deviation, SNRs, and CNRs were analyzed. The IMR technique showed lower noise levels (p < 0.01), higher SNRs (p < 0.001) and CNRs (p < 0.001) compared with FBP and iDose{sup 4} in all acquisitions from high- to low-dose with constant CT numbers. O-MAR reduced noise (p < 0.01) and improved SNRs (p < 0.01) and CNRs (p < 0.001) while improving CT number accuracy only at a low dose. At the low dose of 4.0 mGy, IMR level 1, 2, and 3 showed 83%, 89%, and 95% lower noise values, a factor 6.0, 9.2, and 17.9 higher SNRs, and 5.7, 8.8, and 18.2 higher CNRs compared with FBP respectively. Based on quantitative analysis of CT number accuracy, noise values, SNRs, and CNRs, we conclude that the combined use of IMR and O-MAR enables a reduction in radiation dose of 83% compared with FBP and iDose{sup 4} in the CT imaging of a THA phantom. (orig.)

Wideband Low Noise Amplifiers Exploiting Thermal Noise Cancellation

NARCIS (Netherlands)

Bruccoleri, F.; Klumperink, Eric A.M.; Nauta, Bram

2005-01-01

Low Noise Amplifiers (LNAs) are commonly used to amplify signals that are too weak for direct processing for example in radio or cable receivers. Traditionally, low noise amplifiers are implemented via tuned amplifiers, exploiting inductors and capacitors in resonating LC-circuits. This can render

Comprehensive quantification of signal-to-noise ratio and g-factor for image-based and k-space-based parallel imaging reconstructions.

Science.gov (United States)

Robson, Philip M; Grant, Aaron K; Madhuranthakam, Ananth J; Lattanzi, Riccardo; Sodickson, Daniel K; McKenzie, Charles A

2008-10-01

Parallel imaging reconstructions result in spatially varying noise amplification characterized by the g-factor, precluding conventional measurements of noise from the final image. A simple Monte Carlo based method is proposed for all linear image reconstruction algorithms, which allows measurement of signal-to-noise ratio and g-factor and is demonstrated for SENSE and GRAPPA reconstructions for accelerated acquisitions that have not previously been amenable to such assessment. Only a simple "prescan" measurement of noise amplitude and correlation in the phased-array receiver, and a single accelerated image acquisition are required, allowing robust assessment of signal-to-noise ratio and g-factor. The "pseudo multiple replica" method has been rigorously validated in phantoms and in vivo, showing excellent agreement with true multiple replica and analytical methods. This method is universally applicable to the parallel imaging reconstruction techniques used in clinical applications and will allow pixel-by-pixel image noise measurements for all parallel imaging strategies, allowing quantitative comparison between arbitrary k-space trajectories, image reconstruction, or noise conditioning techniques. (c) 2008 Wiley-Liss, Inc.

Investigation and optimization of low-frequency noise performance in readout electronics of dc superconducting quantum interference device

International Nuclear Information System (INIS)

Zhao, Jing; Zhang, Yi; Krause, Hans-Joachim; Lee, Yong-Ho

2014-01-01

We investigated and optimized the low-frequency noise characteristics of a preamplifier used for readout of direct current superconducting quantum interference devices (SQUIDs). When the SQUID output was detected directly using a room-temperature low-voltage-noise preamplifier, the low-frequency noise of a SQUID system was found to be dominated by the input current noise of the preamplifiers in case of a large dynamic resistance of the SQUID. To reduce the current noise of the preamplifier in the low-frequency range, we investigated the dependence of total preamplifier noise on the collector current and source resistance. When the collector current was decreased from 8.4 mA to 3 mA in the preamplifier made of 3 parallel SSM2220 transistor pairs, the low-frequency total voltage noise of the preamplifier (at 0.1 Hz) decreased by about 3 times for a source resistance of 30 Ω whereas the white noise level remained nearly unchanged. Since the relative contribution of preamplifier's input voltage and current noise is different depending on the dynamic resistance or flux-to-voltage transfer of the SQUID, the results showed that the total noise of a SQUID system at low-frequency range can be improved significantly by optimizing the preamplifier circuit parameters, mainly the collector current in case of low-noise bipolar transistor pairs

Investigation and optimization of low-frequency noise performance in readout electronics of dc superconducting quantum interference device

Science.gov (United States)

Zhao, Jing; Zhang, Yi; Lee, Yong-Ho; Krause, Hans-Joachim

2014-05-01

We investigated and optimized the low-frequency noise characteristics of a preamplifier used for readout of direct current superconducting quantum interference devices (SQUIDs). When the SQUID output was detected directly using a room-temperature low-voltage-noise preamplifier, the low-frequency noise of a SQUID system was found to be dominated by the input current noise of the preamplifiers in case of a large dynamic resistance of the SQUID. To reduce the current noise of the preamplifier in the low-frequency range, we investigated the dependence of total preamplifier noise on the collector current and source resistance. When the collector current was decreased from 8.4 mA to 3 mA in the preamplifier made of 3 parallel SSM2220 transistor pairs, the low-frequency total voltage noise of the preamplifier (at 0.1 Hz) decreased by about 3 times for a source resistance of 30 Ω whereas the white noise level remained nearly unchanged. Since the relative contribution of preamplifier's input voltage and current noise is different depending on the dynamic resistance or flux-to-voltage transfer of the SQUID, the results showed that the total noise of a SQUID system at low-frequency range can be improved significantly by optimizing the preamplifier circuit parameters, mainly the collector current in case of low-noise bipolar transistor pairs.

Low-Dose X-ray CT Reconstruction via Dictionary Learning

Science.gov (United States)

Xu, Qiong; Zhang, Lei; Hsieh, Jiang; Wang, Ge

2013-01-01

Although diagnostic medical imaging provides enormous benefits in the early detection and accuracy diagnosis of various diseases, there are growing concerns on the potential side effect of radiation induced genetic, cancerous and other diseases. How to reduce radiation dose while maintaining the diagnostic performance is a major challenge in the computed tomography (CT) field. Inspired by the compressive sensing theory, the sparse constraint in terms of total variation (TV) minimization has already led to promising results for low-dose CT reconstruction. Compared to the discrete gradient transform used in the TV method, dictionary learning is proven to be an effective way for sparse representation. On the other hand, it is important to consider the statistical property of projection data in the low-dose CT case. Recently, we have developed a dictionary learning based approach for low-dose X-ray CT. In this paper, we present this method in detail and evaluate it in experiments. In our method, the sparse constraint in terms of a redundant dictionary is incorporated into an objective function in a statistical iterative reconstruction framework. The dictionary can be either predetermined before an image reconstruction task or adaptively defined during the reconstruction process. An alternating minimization scheme is developed to minimize the objective function. Our approach is evaluated with low-dose X-ray projections collected in animal and human CT studies, and the improvement associated with dictionary learning is quantified relative to filtered backprojection and TV-based reconstructions. The results show that the proposed approach might produce better images with lower noise and more detailed structural features in our selected cases. However, there is no proof that this is true for all kinds of structures. PMID:22542666

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

Science.gov (United States)

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

2018-06-01

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

Motion estimation and compensation in dynamic spiral CT reconstruction; Estimation et compensation de mouvement en reconstruction dynamique de tomodensitometrie helicoidale

Energy Technology Data Exchange (ETDEWEB)

Kimdon, J.; Grangeat, P.; Koenig, A.; Bonnet, St

2004-07-01

Respiratory and cardiac motion causes blurring in dynamic X-ray Computed Tomography (CT). Fast scans reduce this problem, but they require a higher radiation dose per time period to maintain the signal to noise ratio of the resulting images, thereby magnifying the health risk to the patient. As an alternative to increased radiation, our team has already developed a cone-beam reconstruction algorithm based on a dynamic particle model that estimates, predicts, and compensates for respiratory motion in circular X-ray CT. The current paper presents an extension of this method to spiral CT, applicable to modern multi-slice scanners that take advantage of the speed and dose benefits of helical trajectories. We adapted all three main areas of the algorithm: backprojection, prediction, and compensation/accumulation. In backprojection, we changed the longitudinal re-binning technique, filter direction, and the method of enforcing the data sufficiency requirements. For prediction, we had to be careful of objects appearing and disappearing as the scanner bed advanced. For compensation/accumulation, we controlled the reconstruction time and combined images to cover a greater longitudinal extent for each phase in the respiratory or cardiac cycle. Tests with moving numerical phantoms demonstrate that the algorithm successfully improves the temporal resolution of the images without increasing the dose or reducing the signal-to-noise ratio. (authors)

RF dynamic and noise performance of Metallic Source/Drain SOI n-MOSFETs

Science.gov (United States)

Martin, Maria J.; Pascual, Elena; Rengel, Raúl

2012-07-01

This paper presents a detailed study of the RF and noise performance of n-type Schottky barrier (SB) MOSFETs with a particular focus on the influence of the Schottky barrier height (SBH) on the main dynamic and noise figures of merit. With this aim, a 2D Monte Carlo simulator including tunnelling transport across Schottky interfaces has been developed, with special care to consider quantum transmission coefficients and the influence of image charge effects at the Schottky junctions. Particular attention is paid to the microscopic transport features, including carrier mean free paths or number of scattering events along the channel for investigating the optimization of the device topology and the strategic concepts related to the noise performance of this new architecture. A more effective control of the gate electrode over drain current for low SBH (discussed in terms of internal physical quantities) is translated into an enhanced transconductance gm, cut-off frequency fT, and non-quasistatic dynamic parameters. The drain and gate intrinsic noise sources show a noteworthy degradation with the SBH reduction due to the increased current, influence of hot carriers and reduced number of phonon scatterings. However, the results evidence that this effect is counterbalanced by the extremely improved dynamic performance in terms of gm and fT. Therefore, the deterioration of the intrinsic noise performance of the SB-MOSFET has no significant impact on high-frequency noise FoMs as NFmin, Rn and Gass for low SBH and large gate overdrive conditions. The role of the SBH on Γopt, optimum noise reactance and susceptance has been also analyzed.

Characterization of adaptive statistical iterative reconstruction (ASIR) in low contrast helical abdominal imaging via a transfer function based method

Science.gov (United States)

Zhang, Da; Li, Xinhua; Liu, Bob

2012-03-01

Since the introduction of ASiR, its potential in noise reduction has been reported in various clinical applications. However, the influence of different scan and reconstruction parameters on the trade off between ASiR's blurring effect and noise reduction in low contrast imaging has not been fully studied. Simple measurements on low contrast images, such as CNR or phantom scores could not explore the nuance nature of this problem. We tackled this topic using a method which compares the performance of ASiR in low contrast helical imaging based on an assumed filter layer on top of the FBP reconstruction. Transfer functions of this filter layer were obtained from the noise power spectra (NPS) of corresponding FBP and ASiR images that share the same scan and reconstruction parameters. 2D transfer functions were calculated as sqrt[NPSASiR(u, v)/NPSFBP(u, v)]. Synthesized ACR phantom images were generated by filtering the FBP images with the transfer functions of specific (FBP, ASiR) pairs, and were compared with the ASiR images. It is shown that the transfer functions could predict the deterministic blurring effect of ASiR on low contrast objects, as well as the degree of noise reductions. Using this method, the influence of dose, scan field of view (SFOV), display field of view (DFOV), ASiR level, and Recon Mode on the behavior of ASiR in low contrast imaging was studied. It was found that ASiR level, dose level, and DFOV play more important roles in determining the behavior of ASiR than the other two parameters.

Looking for the Signal: A guide to iterative noise and artefact removal in X-ray tomographic reconstructions of porous geomaterials

Science.gov (United States)

Bruns, S.; Stipp, S. L. S.; Sørensen, H. O.

2017-07-01

X-ray micro- and nanotomography has evolved into a quantitative analysis tool rather than a mere qualitative visualization technique for the study of porous natural materials. Tomographic reconstructions are subject to noise that has to be handled by image filters prior to quantitative analysis. Typically, denoising filters are designed to handle random noise, such as Gaussian or Poisson noise. In tomographic reconstructions, noise has been projected from Radon space to Euclidean space, i.e. post reconstruction noise cannot be expected to be random but to be correlated. Reconstruction artefacts, such as streak or ring artefacts, aggravate the filtering process so algorithms performing well with random noise are not guaranteed to provide satisfactory results for X-ray tomography reconstructions. With sufficient image resolution, the crystalline origin of most geomaterials results in tomography images of objects that are untextured. We developed a denoising framework for these kinds of samples that combines a noise level estimate with iterative nonlocal means denoising. This allows splitting the denoising task into several weak denoising subtasks where the later filtering steps provide a controlled level of texture removal. We describe a hands-on explanation for the use of this iterative denoising approach and the validity and quality of the image enhancement filter was evaluated in a benchmarking experiment with noise footprints of a varying level of correlation and residual artefacts. They were extracted from real tomography reconstructions. We found that our denoising solutions were superior to other denoising algorithms, over a broad range of contrast-to-noise ratios on artificial piecewise constant signals.

Low dose CBCT reconstruction via prior contour based total variation (PCTV) regularization: a feasibility study

Science.gov (United States)

Chen, Yingxuan; Yin, Fang-Fang; Zhang, Yawei; Zhang, You; Ren, Lei

2018-04-01

Purpose: compressed sensing reconstruction using total variation (TV) tends to over-smooth the edge information by uniformly penalizing the image gradient. The goal of this study is to develop a novel prior contour based TV (PCTV) method to enhance the edge information in compressed sensing reconstruction for CBCT. Methods: the edge information is extracted from prior planning-CT via edge detection. Prior CT is first registered with on-board CBCT reconstructed with TV method through rigid or deformable registration. The edge contours in prior-CT is then mapped to CBCT and used as the weight map for TV regularization to enhance edge information in CBCT reconstruction. The PCTV method was evaluated using extended-cardiac-torso (XCAT) phantom, physical CatPhan phantom and brain patient data. Results were compared with both TV and edge preserving TV (EPTV) methods which are commonly used for limited projection CBCT reconstruction. Relative error was used to calculate pixel value difference and edge cross correlation was defined as the similarity of edge information between reconstructed images and ground truth in the quantitative evaluation. Results: compared to TV and EPTV, PCTV enhanced the edge information of bone, lung vessels and tumor in XCAT reconstruction and complex bony structures in brain patient CBCT. In XCAT study using 45 half-fan CBCT projections, compared with ground truth, relative errors were 1.5%, 0.7% and 0.3% and edge cross correlations were 0.66, 0.72 and 0.78 for TV, EPTV and PCTV, respectively. PCTV is more robust to the projection number reduction. Edge enhancement was reduced slightly with noisy projections but PCTV was still superior to other methods. PCTV can maintain resolution while reducing the noise in the low mAs CatPhan reconstruction. Low contrast edges were preserved better with PCTV compared with TV and EPTV. Conclusion: PCTV preserved edge information as well as reduced streak artifacts and noise in low dose CBCT reconstruction

Dynamics of double-well Bose–Einstein condensates subject to external Gaussian white noise

International Nuclear Information System (INIS)

Zheng Hanlei; Hao Yajiang; Gu Qiang

2013-01-01

Dynamical properties of the Bose–Einstein condensate in a double-well potential subject to Gaussian white noise are investigated by numerically solving the time-dependent Gross–Pitaevskii equation. The Gaussian white noise is used to describe influence of the random environmental disturbance on the double-well condensate. Dynamical evolutions from three different initial states, the Josephson oscillation state, the running phase and π-mode macroscopic quantum self-trapping states, are considered. It is shown that the system is rather robust with respect to the weak noise whose strength is small and change rate is high. If the evolution time is sufficiently long, the weak noise will finally drive the system to evolve from high-energy states to low-energy states, but in a manner rather different from the energy-dissipation effect. In the presence of strong noise with either large strength or slow change rate, the double-well condensate may exhibit very irregular dynamical behaviours. (paper)

Optimal noise reduction in 3D reconstructions of single particles using a volume-normalized filter

Science.gov (United States)

Sindelar, Charles V.; Grigorieff, Nikolaus

2012-01-01

The high noise level found in single-particle electron cryo-microscopy (cryo-EM) image data presents a special challenge for three-dimensional (3D) reconstruction of the imaged molecules. The spectral signal-to-noise ratio (SSNR) and related Fourier shell correlation (FSC) functions are commonly used to assess and mitigate the noise-generated error in the reconstruction. Calculation of the SSNR and FSC usually includes the noise in the solvent region surrounding the particle and therefore does not accurately reflect the signal in the particle density itself. Here we show that the SSNR in a reconstructed 3D particle map is linearly proportional to the fractional volume occupied by the particle. Using this relationship, we devise a novel filter (the “single-particle Wiener filter”) to minimize the error in a reconstructed particle map, if the particle volume is known. Moreover, we show how to approximate this filter even when the volume of the particle is not known, by optimizing the signal within a representative interior region of the particle. We show that the new filter improves on previously proposed error-reduction schemes, including the conventional Wiener filter as well as figure-of-merit weighting, and quantify the relationship between all of these methods by theoretical analysis as well as numeric evaluation of both simulated and experimentally collected data. The single-particle Wiener filter is applicable across a broad range of existing 3D reconstruction techniques, but is particularly well suited to the Fourier inversion method, leading to an efficient and accurate implementation. PMID:22613568

High Dynamic Range RF Front End with Noise Cancellation and Linearization for WiMAX Receivers

Directory of Open Access Journals (Sweden)

J.-M. Wu

2012-06-01

Full Text Available This research deals with verification of the high dynamic range for a heterodyne radio frequency (RF front end. A 2.6 GHz RF front end is designed and implemented in a hybrid microwave integrated circuit (HMIC for worldwide interoperability for microwave access (WiMAX receivers. The heterodyne RF front end consists of a low-noise amplifier (LNA with noise cancellation, an RF bandpass filter (BPF, a downconverter with linearization, and an intermediate frequency (IF BPF. A noise canceling technique used in the low-noise amplifier eliminates a thermal noise and then reduces the noise figure (NF of the RF front end by 0.9 dB. Use of a downconverter with diode linearizer also compensates for gain compression, which increases the input-referred third-order intercept point (IIP3 of the RF front end by 4.3 dB. The proposed method substantially increases the spurious-free dynamic range (DRf of the RF front end by 3.5 dB.

A Minimum Fuel Based Estimator for Maneuver and Natrual Dynamics Reconstruction

Science.gov (United States)

Lubey, D.; Scheeres, D.

2013-09-01

The vast and growing population of objects in Earth orbit (active and defunct spacecraft, orbital debris, etc.) offers many unique challenges when it comes to tracking these objects and associating the resulting observations. Complicating these challenges are the inaccurate natural dynamical models of these objects, the active maneuvers of spacecraft that deviate them from their ballistic trajectories, and the fact that spacecraft are tracked and operated by separate agencies. Maneuver detection and reconstruction algorithms can help with each of these issues by estimating mismodeled and unmodeled dynamics through indirect observation of spacecraft. It also helps to verify the associations made by an object correlation algorithm or aid in making those associations, which is essential when tracking objects in orbit. The algorithm developed in this study applies an Optimal Control Problem (OCP) Distance Metric approach to the problems of Maneuver Reconstruction and Dynamics Estimation. This was first developed by Holzinger, Scheeres, and Alfriend (2011), with a subsequent study by Singh, Horwood, and Poore (2012). This method estimates the minimum fuel control policy rather than the state as a typical Kalman Filter would. This difference ensures that the states are connected through a given dynamical model and allows for automatic covariance manipulation, which can help to prevent filter saturation. Using a string of measurements (either verified or hypothesized to correlate with one another), the algorithm outputs a corresponding string of adjoint and state estimates with associated noise. Post-processing techniques are implemented, which when applied to the adjoint estimates can remove noise and expose unmodeled maneuvers and mismodeled natural dynamics. Specifically, the estimated controls are used to determine spacecraft dependent accelerations (atmospheric drag and solar radiation pressure) using an adapted form of the Optimal Control based natural dynamics

Shot-noise at a Fermi-edge singularity: Non-Markovian dynamics

Energy Technology Data Exchange (ETDEWEB)

Ubbelohde, N.; Maire, N.; Haug, R. J. [Institut für Festkörperphysik, Leibniz Universität Hannover, Appelstraße 2, D-30167 Hannover (Germany); Roszak, K. [Institute of Physics, Wrocław University of Technology, PL-50370 Wrocław (Poland); Hohls, F. [Physikalisch-Technische Bundesanstalt, D-38116 Braunschweig (Germany); Novotný, T. [Department of Condensed Matter Physics, Faculty of Mathematics and Physics, Charles University, CZ-12116 Prague (Czech Republic)

2013-12-04

For an InAs quantum dot we study the current shot noise at a Fermi-edge singularity in low temperature cross-correlation measurements. In the regime of the interaction effect the strong suppression of noise observed at zero magnetic field and the sequence of enhancement and suppression in magnetic field go beyond a Markovian master equation model. Qualitative and quantitative agreement can however be achieved by a generalized master equation model taking non-Markovian dynamics into account.

Superlinearly scalable noise robustness of redundant coupled dynamical systems.

Science.gov (United States)

Kohar, Vivek; Kia, Behnam; Lindner, John F; Ditto, William L

2016-03-01

We illustrate through theory and numerical simulations that redundant coupled dynamical systems can be extremely robust against local noise in comparison to uncoupled dynamical systems evolving in the same noisy environment. Previous studies have shown that the noise robustness of redundant coupled dynamical systems is linearly scalable and deviations due to noise can be minimized by increasing the number of coupled units. Here, we demonstrate that the noise robustness can actually be scaled superlinearly if some conditions are met and very high noise robustness can be realized with very few coupled units. We discuss these conditions and show that this superlinear scalability depends on the nonlinearity of the individual dynamical units. The phenomenon is demonstrated in discrete as well as continuous dynamical systems. This superlinear scalability not only provides us an opportunity to exploit the nonlinearity of physical systems without being bogged down by noise but may also help us in understanding the functional role of coupled redundancy found in many biological systems. Moreover, engineers can exploit superlinear noise suppression by starting a coupled system near (not necessarily at) the appropriate initial condition.

Noise-based tube current reduction method with iterative reconstruction for reduction of radiation exposure in coronary CT angiography

International Nuclear Information System (INIS)

Shen, Junlin; Du, Xiangying; Guo, Daode; Cao, Lizhen; Gao, Yan; Bai, Mei; Li, Pengyu; Liu, Jiabin; Li, Kuncheng

2013-01-01

Purpose: To investigate the potential of noise-based tube current reduction method with iterative reconstruction to reduce radiation exposure while achieving consistent image quality in coronary CT angiography (CCTA). Materials and methods: 294 patients underwent CCTA on a 64-detector row CT equipped with iterative reconstruction. 102 patients with fixed tube current were assigned to Group 1, which was used to establish noise-based tube current modulation formulas, where tube current was modulated by the noise of test bolus image. 192 patients with noise-based tube current were randomly assigned to Group 2 and Group 3. Filtered back projection was applied for Group 2 and iterative reconstruction for Group 3. Qualitative image quality was assessed with a 5 point score. Image noise, signal intensity, volume CT dose index, and dose-length product were measured. Results: The noise-based tube current modulation formulas were established through regression analysis using image noise measurements in Group 1. Image noise was precisely maintained at the target value of 35.00 HU with small interquartile ranges for Group 2 (34.17–35.08 HU) and Group 3 (34.34–35.03 HU), while it was from 28.41 to 36.49 HU for Group 1. All images in the three groups were acceptable for diagnosis. A relative 14% and 41% reduction in effective dose for Group 2 and Group 3 were observed compared with Group 1. Conclusion: Adequate image quality could be maintained at a desired and consistent noise level with overall 14% dose reduction using noise-based tube current reduction method. The use of iterative reconstruction further achieved approximately 40% reduction in effective dose

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

Value of a noise-optimized virtual monoenergetic reconstruction technique in dual-energy CT for planning of transcatheter aortic valve replacement

Energy Technology Data Exchange (ETDEWEB)

Martin, Simon S.; Albrecht, Moritz H.; Wichmann, Julian L.; Huesers, Kristina; Scholtz, Jan-Erik; Booz, Christian; Bodelle, Boris; Bauer, Ralf W.; Metzger, Sarah C.; Vogl, Thomas J.; Lehnert, Thomas [University Hospital Frankfurt, Department of Diagnostic and Interventional Radiology, Frankfurt (Germany)

2017-02-15

To evaluate objective and subjective image quality of a noise-optimized virtual monoenergetic imaging (VMI+) reconstruction technique in dual-energy computed tomography (DECT) angiography prior to transcatheter aortic valve replacement (TAVR). Datasets of 47 patients (35 men; 64.1 ± 10.9 years) who underwent DECT angiography of heart and vascular access prior to TAVR were reconstructed with standard linear blending (F{sub 0}.5), VMI+, and traditional monoenergetic (VMI) algorithms in 10-keV intervals from 40-100 keV. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of 564 arterial segments were evaluated. Subjective analysis was rated by three blinded observers using a Likert scale. Mean SNR and CNR were highest in 40 keV VMI+ series (SNR, 27.8 ± 13.0; CNR, 26.3 ± 12.7), significantly (all p < 0.001) superior to all VMI series, which showed highest values at 70 keV (SNR, 18.5 ± 7.6; CNR, 16.0 ± 7.4), as well as linearly-blended F{sub 0}.5 series (SNR, 16.8 ± 7.3; CNR, 13.6 ± 6.9). Highest subjective image quality scores were observed for 40, 50, and 60 keV VMI+ reconstructions (all p > 0.05), significantly superior to all VMI and standard linearly-blended images (all p < 0.01). Low-keV VMI+ reconstructions significantly increase CNR and SNR compared to VMI and standard linear-blending image reconstruction and improve subjective image quality in preprocedural DECT angiography in the context of TAVR planning. (orig.)

SU-E-I-86: Ultra-Low Dose Computed Tomography Attenuation Correction for Pediatric PET CT Using Adaptive Statistical Iterative Reconstruction (ASiR™)

Energy Technology Data Exchange (ETDEWEB)

Brady, S; Shulkin, B [St. Jude Children’s Research Hospital, Memphis, TN (United States)

2015-06-15

Purpose: To develop ultra-low dose computed tomography (CT) attenuation correction (CTAC) acquisition protocols for pediatric positron emission tomography CT (PET CT). Methods: A GE Discovery 690 PET CT hybrid scanner was used to investigate the change to quantitative PET and CT measurements when operated at ultra-low doses (10–35 mAs). CT quantitation: noise, low-contrast resolution, and CT numbers for eleven tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% CTDIvol (0.39/3.64; mGy) radiation dose from baseline. To minimize noise infiltration, 100% adaptive statistical iterative reconstruction (ASiR) was used for CT reconstruction. PET images were reconstructed with the lower-dose CTAC iterations and analyzed for: maximum body weight standardized uptake value (SUVbw) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation organ dose, as derived from patient exam size specific dose estimate (SSDE), was converted to effective dose using the standard ICRP report 103 method. Effective dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative patient population dose reduction and noise control. Results: CT numbers were constant to within 10% from the non-dose reduced CTAC image down to 90% dose reduction. No change in SUVbw, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols reconstructed with ASiR and down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62%–86% (3.2/8.3−0.9/6.2; mSv). Noise magnitude in dose-reduced patient images increased but was not statistically different from pre dose-reduced patient images. Conclusion: Using ASiR allowed for aggressive reduction in CTAC dose with no change in PET reconstructed images while maintaining sufficient image quality for co

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

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Li, Si; Xu, Yuesheng, E-mail: yxu06@syr.edu [Guangdong Provincial Key Laboratory of Computational Science, School of Mathematics and Computational Sciences, Sun Yat-sen University, Guangzhou 510275 (China); Zhang, Jiahan; Lipson, Edward [Department of Physics, Syracuse University, Syracuse, New York 13244 (United States); Krol, Andrzej; Feiglin, David [Department of Radiology, SUNY Upstate Medical University, Syracuse, New York 13210 (United States); Schmidtlein, C. Ross [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York 10065 (United States); Vogelsang, Levon [Carestream Health, Rochester, New York 14608 (United States); Shen, Lixin [Guangdong Provincial Key Laboratory of Computational Science, School of Mathematics and Computational Sciences, Sun Yat-sen University, Guangzhou 510275, China and Department of Mathematics, Syracuse University, Syracuse, New York 13244 (United States)

2015-08-15

square errors (MSEs), and report the convergence speed and computation time. Results: HOTV-PAPA yields the best signal-to-noise ratio, followed by TV-PAPA and TV-OSL/GPF-EM. The local spatial resolution of HOTV-PAPA is somewhat worse than that of TV-PAPA and TV-OSL. Images reconstructed using HOTV-PAPA have the lowest local noise power spectrum (LNPS) amplitudes, followed by TV-PAPA, TV-OSL, and GPF-EM. The LNPS peak of GPF-EM is shifted toward higher spatial frequencies than those for the three other methods. The PAPA-type methods exhibit much lower ensemble noise, ensemble voxel variance, and image roughness. HOTV-PAPA performs best in these categories. Whereas images reconstructed using both TV-PAPA and TV-OSL are degraded by severe staircase artifacts; HOTV-PAPA substantially reduces such artifacts. It also converges faster than the other three methods and exhibits the lowest overall reconstruction error level, as measured by MSE. Conclusions: For high-noise simulated SPECT data, HOTV-PAPA outperforms TV-PAPA, GPF-EM, and TV-OSL in terms of hot lesion detectability, noise suppression, MSE, and computational efficiency. Unlike TV-PAPA and TV-OSL, HOTV-PAPA does not create sizable staircase artifacts. Moreover, HOTV-PAPA effectively suppresses noise, with only limited loss of local spatial resolution. Of the four methods, HOTV-PAPA shows the best lesion detectability, thanks to its superior noise suppression. HOTV-PAPA shows promise for clinically useful reconstructions of low-dose SPECT data.

Effective noise-suppressed and artifact-reduced reconstruction of SPECT data using a preconditioned alternating projection algorithm

International Nuclear Information System (INIS)

Li, Si; Xu, Yuesheng; Zhang, Jiahan; Lipson, Edward; Krol, Andrzej; Feiglin, David; Schmidtlein, C. Ross; Vogelsang, Levon; Shen, Lixin

2015-01-01

square errors (MSEs), and report the convergence speed and computation time. Results: HOTV-PAPA yields the best signal-to-noise ratio, followed by TV-PAPA and TV-OSL/GPF-EM. The local spatial resolution of HOTV-PAPA is somewhat worse than that of TV-PAPA and TV-OSL. Images reconstructed using HOTV-PAPA have the lowest local noise power spectrum (LNPS) amplitudes, followed by TV-PAPA, TV-OSL, and GPF-EM. The LNPS peak of GPF-EM is shifted toward higher spatial frequencies than those for the three other methods. The PAPA-type methods exhibit much lower ensemble noise, ensemble voxel variance, and image roughness. HOTV-PAPA performs best in these categories. Whereas images reconstructed using both TV-PAPA and TV-OSL are degraded by severe staircase artifacts; HOTV-PAPA substantially reduces such artifacts. It also converges faster than the other three methods and exhibits the lowest overall reconstruction error level, as measured by MSE. Conclusions: For high-noise simulated SPECT data, HOTV-PAPA outperforms TV-PAPA, GPF-EM, and TV-OSL in terms of hot lesion detectability, noise suppression, MSE, and computational efficiency. Unlike TV-PAPA and TV-OSL, HOTV-PAPA does not create sizable staircase artifacts. Moreover, HOTV-PAPA effectively suppresses noise, with only limited loss of local spatial resolution. Of the four methods, HOTV-PAPA shows the best lesion detectability, thanks to its superior noise suppression. HOTV-PAPA shows promise for clinically useful reconstructions of low-dose SPECT data

Effect of Low-Dose MDCT and Iterative Reconstruction on Trabecular Bone Microstructure Assessment.

Science.gov (United States)

Kopp, Felix K; Holzapfel, Konstantin; Baum, Thomas; Nasirudin, Radin A; Mei, Kai; Garcia, Eduardo G; Burgkart, Rainer; Rummeny, Ernst J; Kirschke, Jan S; Noël, Peter B

2016-01-01

We investigated the effects of low-dose multi detector computed tomography (MDCT) in combination with statistical iterative reconstruction algorithms on trabecular bone microstructure parameters. Twelve donated vertebrae were scanned with the routine radiation exposure used in our department (standard-dose) and a low-dose protocol. Reconstructions were performed with filtered backprojection (FBP) and maximum-likelihood based statistical iterative reconstruction (SIR). Trabecular bone microstructure parameters were assessed and statistically compared for each reconstruction. Moreover, fracture loads of the vertebrae were biomechanically determined and correlated to the assessed microstructure parameters. Trabecular bone microstructure parameters based on low-dose MDCT and SIR significantly correlated with vertebral bone strength. There was no significant difference between microstructure parameters calculated on low-dose SIR and standard-dose FBP images. However, the results revealed a strong dependency on the regularization strength applied during SIR. It was observed that stronger regularization might corrupt the microstructure analysis, because the trabecular structure is a very small detail that might get lost during the regularization process. As a consequence, the introduction of SIR for trabecular bone microstructure analysis requires a specific optimization of the regularization parameters. Moreover, in comparison to other approaches, superior noise-resolution trade-offs can be found with the proposed methods.

Statistical model based iterative reconstruction (MBIR) in clinical CT systems: Experimental assessment of noise performance

Energy Technology Data Exchange (ETDEWEB)

Li, Ke; Tang, Jie [Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, Wisconsin 53705 (United States); Chen, Guang-Hong, E-mail: gchen7@wisc.edu [Department of Medical Physics, University of Wisconsin-Madison, 1111 Highland Avenue, Madison, Wisconsin 53705 and Department of Radiology, University of Wisconsin-Madison, 600 Highland Avenue, Madison, Wisconsin 53792 (United States)

2014-04-15

Purpose: To reduce radiation dose in CT imaging, the statistical model based iterative reconstruction (MBIR) method has been introduced for clinical use. Based on the principle of MBIR and its nonlinear nature, the noise performance of MBIR is expected to be different from that of the well-understood filtered backprojection (FBP) reconstruction method. The purpose of this work is to experimentally assess the unique noise characteristics of MBIR using a state-of-the-art clinical CT system. Methods: Three physical phantoms, including a water cylinder and two pediatric head phantoms, were scanned in axial scanning mode using a 64-slice CT scanner (Discovery CT750 HD, GE Healthcare, Waukesha, WI) at seven different mAs levels (5, 12.5, 25, 50, 100, 200, 300). At each mAs level, each phantom was repeatedly scanned 50 times to generate an image ensemble for noise analysis. Both the FBP method with a standard kernel and the MBIR method (Veo{sup ®}, GE Healthcare, Waukesha, WI) were used for CT image reconstruction. Three-dimensional (3D) noise power spectrum (NPS), two-dimensional (2D) NPS, and zero-dimensional NPS (noise variance) were assessed both globally and locally. Noise magnitude, noise spatial correlation, noise spatial uniformity and their dose dependence were examined for the two reconstruction methods. Results: (1) At each dose level and at each frequency, the magnitude of the NPS of MBIR was smaller than that of FBP. (2) While the shape of the NPS of FBP was dose-independent, the shape of the NPS of MBIR was strongly dose-dependent; lower dose lead to a “redder” NPS with a lower mean frequency value. (3) The noise standard deviation (σ) of MBIR and dose were found to be related through a power law of σ ∝ (dose){sup −β} with the component β ≈ 0.25, which violated the classical σ ∝ (dose){sup −0.5} power law in FBP. (4) With MBIR, noise reduction was most prominent for thin image slices. (5) MBIR lead to better noise spatial

Technical Note: Measuring contrast- and noise-dependent spatial resolution of an iterative reconstruction method in CT using ensemble averaging

Energy Technology Data Exchange (ETDEWEB)

Yu, Lifeng, E-mail: yu.lifeng@mayo.edu; Vrieze, Thomas J.; Leng, Shuai; Fletcher, Joel G.; McCollough, Cynthia H. [Department of Radiology, Mayo Clinic, Rochester, Minnesota 55905 (United States)

2015-05-15

Purpose: The spatial resolution of iterative reconstruction (IR) in computed tomography (CT) is contrast- and noise-dependent because of the nonlinear regularization. Due to the severe noise contamination, it is challenging to perform precise spatial-resolution measurements at very low-contrast levels. The purpose of this study was to measure the spatial resolution of a commercially available IR method using ensemble-averaged images acquired from repeated scans. Methods: A low-contrast phantom containing three rods (7, 14, and 21 HU below background) was scanned on a 128-slice CT scanner at three dose levels (CTDI{sub vol} = 16, 8, and 4 mGy). Images were reconstructed using two filtered-backprojection (FBP) kernels (B40 and B20) and a commercial IR method (sinogram affirmed iterative reconstruction, SAFIRE, Siemens Healthcare) with two strength settings (I40-3 and I40-5). The same scan was repeated 100 times at each dose level. The modulation transfer function (MTF) was calculated based on the edge profile measured on the ensemble-averaged images. Results: The spatial resolution of the two FBP kernels, B40 and B20, remained relatively constant across contrast and dose levels. However, the spatial resolution of the two IR kernels degraded relative to FBP as contrast or dose level decreased. For a given dose level at 16 mGy, the MTF{sub 50%} value normalized to the B40 kernel decreased from 98.4% at 21 HU to 88.5% at 7 HU for I40-3 and from 97.6% to 82.1% for I40-5. At 21 HU, the relative MTF{sub 50%} value decreased from 98.4% at 16 mGy to 90.7% at 4 mGy for I40-3 and from 97.6% to 85.6% for I40-5. Conclusions: A simple technique using ensemble averaging from repeated CT scans can be used to measure the spatial resolution of IR techniques in CT at very low contrast levels. The evaluated IR method degraded the spatial resolution at low contrast and high noise levels.

Programmable, very low noise current source

Science.gov (United States)

Scandurra, G.; Cannatà, G.; Giusi, G.; Ciofi, C.

2014-12-01

We propose a new approach for the realization of very low noise programmable current sources mainly intended for application in the field of low frequency noise measurements. The design is based on a low noise Junction Field Effect Transistor (JFET) acting as a high impedance current source and programmability is obtained by resorting to a low noise, programmable floating voltage source that allows to set the sourced current at the desired value. The floating voltage source is obtained by exploiting the properties of a standard photovoltaic MOSFET driver. Proper filtering and a control network employing super-capacitors allow to reduce the low frequency output noise to that due to the low noise JFET down to frequencies as low as 100 mHz while allowing, at the same time, to set the desired current by means of a standard DA converter with an accuracy better than 1%. A prototype of the system capable of supplying currents from a few hundreds of μA up to a few mA demonstrates the effectiveness of the approach we propose. When delivering a DC current of about 2 mA, the power spectral density of the current fluctuations at the output is found to be less than 25 pA/√Hz at 100 mHz and less than 6 pA/√Hz for f > 1 Hz, resulting in an RMS noise in the bandwidth from 0.1 to 10 Hz of less than 14 pA.

Improving temporal resolution in fMRI using a 3D spiral acquisition and low rank plus sparse (L+S) reconstruction.

Science.gov (United States)

Petrov, Andrii Y; Herbst, Michael; Andrew Stenger, V

2017-08-15

Rapid whole-brain dynamic Magnetic Resonance Imaging (MRI) is of particular interest in Blood Oxygen Level Dependent (BOLD) functional MRI (fMRI). Faster acquisitions with higher temporal sampling of the BOLD time-course provide several advantages including increased sensitivity in detecting functional activation, the possibility of filtering out physiological noise for improving temporal SNR, and freezing out head motion. Generally, faster acquisitions require undersampling of the data which results in aliasing artifacts in the object domain. A recently developed low-rank (L) plus sparse (S) matrix decomposition model (L+S) is one of the methods that has been introduced to reconstruct images from undersampled dynamic MRI data. The L+S approach assumes that the dynamic MRI data, represented as a space-time matrix M, is a linear superposition of L and S components, where L represents highly spatially and temporally correlated elements, such as the image background, while S captures dynamic information that is sparse in an appropriate transform domain. This suggests that L+S might be suited for undersampled task or slow event-related fMRI acquisitions because the periodic nature of the BOLD signal is sparse in the temporal Fourier transform domain and slowly varying low-rank brain background signals, such as physiological noise and drift, will be predominantly low-rank. In this work, as a proof of concept, we exploit the L+S method for accelerating block-design fMRI using a 3D stack of spirals (SoS) acquisition where undersampling is performed in the k z -t domain. We examined the feasibility of the L+S method to accurately separate temporally correlated brain background information in the L component while capturing periodic BOLD signals in the S component. We present results acquired in control human volunteers at 3T for both retrospective and prospectively acquired fMRI data for a visual activation block-design task. We show that a SoS fMRI acquisition with an

Evaluation and comparison of contrast to noise ratio and signal to noise ratio according to change of reconstruction on breast PET/CT

Energy Technology Data Exchange (ETDEWEB)

Lee, Young Jae [Dept. of Nuclear Medicine, Seoul National University Hospital, Seoul (Korea, Republic of); Lee, Eul Kyu [Dept. of Radiology, Inje Paik University Hospital Jeo-dong, Seoul (Korea, Republic of); Kim, Ki Won [Dept. of Radiology, Kyung Hee University Hospital at Gang-dong, Seoul (Korea, Republic of); Jeong, Hoi Woun [Dept. of Radiological Technology, The Baekseok Culture University, Cheonan (Korea, Republic of); Lyu, Kwang Yeul; Park, Hoon Hee; Son, Jin Hyun; Min, Jung Whan [Dept. of Radiological Technology, The Shingu University, Sungnam (Korea, Republic of)

2017-03-15

The purpose of this study was to measure contrast to noise ratio (CNR) and signal to noise ratio (SNR) according to change of reconstruction from region of interest (ROI) in breast positron emission tomography- computed tomography (PET-CT), and to analyze the CNR and SNR statically. We examined images of breast PET-CT of 100 patients in a University-affiliated hospital, Seoul, Korea. Each patient's image of breast PET-CT were calculated by using Image J. Differences of CNR and SNR among four reconstruction algorithms were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p<0.05). We have analysis socio-demographical variables, CNR and SNR according to reconstruction images, 95% confidence according to CNR and SNR of reconstruction and difference in a mean of CNR and SNR. SNR results, with the quality of distributions in the order of PSF{sub T}OF, Iterative and Iterative-TOF, FBP-TOF. CNR, with the quality of distributions in the order of PSF{sub T}OF, Iterative and Iterative-TOF, FBP-TOF. CNR and SNR of PET-CT reconstruction methods of the breast would be useful to evaluate breast diseases.

Dynamic PET image reconstruction integrating temporal regularization associated with respiratory motion correction for applications in oncology

Science.gov (United States)

Merlin, Thibaut; Visvikis, Dimitris; Fernandez, Philippe; Lamare, Frédéric

2018-02-01

Respiratory motion reduces both the qualitative and quantitative accuracy of PET images in oncology. This impact is more significant for quantitative applications based on kinetic modeling, where dynamic acquisitions are associated with limited statistics due to the necessity of enhanced temporal resolution. The aim of this study is to address these drawbacks, by combining a respiratory motion correction approach with temporal regularization in a unique reconstruction algorithm for dynamic PET imaging. Elastic transformation parameters for the motion correction are estimated from the non-attenuation-corrected PET images. The derived displacement matrices are subsequently used in a list-mode based OSEM reconstruction algorithm integrating a temporal regularization between the 3D dynamic PET frames, based on temporal basis functions. These functions are simultaneously estimated at each iteration, along with their relative coefficients for each image voxel. Quantitative evaluation has been performed using dynamic FDG PET/CT acquisitions of lung cancer patients acquired on a GE DRX system. The performance of the proposed method is compared with that of a standard multi-frame OSEM reconstruction algorithm. The proposed method achieved substantial improvements in terms of noise reduction while accounting for loss of contrast due to respiratory motion. Results on simulated data showed that the proposed 4D algorithms led to bias reduction values up to 40% in both tumor and blood regions for similar standard deviation levels, in comparison with a standard 3D reconstruction. Patlak parameter estimations on reconstructed images with the proposed reconstruction methods resulted in 30% and 40% bias reduction in the tumor and lung region respectively for the Patlak slope, and a 30% bias reduction for the intercept in the tumor region (a similar Patlak intercept was achieved in the lung area). Incorporation of the respiratory motion correction using an elastic model along with a

Low frequency noise peak near magnon emission energy in magnetic tunnel junctions

Energy Technology Data Exchange (ETDEWEB)

Liu, Liang; Xiang, Li; Guo, Huiqiang; Wei, Jian, E-mail: weijian6791@pku.edu.cn [International Center for Quantum Materials, School of Physics, Peking University, Beijing 100871, China and Collaborative Innovation Center of Quantum Matter, Beijing (China); Li, D. L.; Yuan, Z. H.; Feng, J. F., E-mail: jiafengfeng@iphy.ac.cn; Han, X. F. [Beijing National Laboratory of Condensed Matter Physics, Institute of Physics, Chinese Academy of Sciences, Beijing 100190 (China); Coey, J. M. D. [CRANN and School of Physics, Trinity College, Dublin 2 (Ireland)

2014-12-15

We report on the low frequency (LF) noise measurements in magnetic tunnel junctions (MTJs) below 4 K and at low bias, where the transport is strongly affected by scattering with magnons emitted by hot tunnelling electrons, as thermal activation of magnons from the environment is suppressed. For both CoFeB/MgO/CoFeB and CoFeB/AlO{sub x}/CoFeB MTJs, enhanced LF noise is observed at bias voltage around magnon emission energy, forming a peak in the bias dependence of noise power spectra density, independent of magnetic configurations. The noise peak is much higher and broader for unannealed AlO{sub x}-based MTJ, and besides Lorentzian shape noise spectra in the frequency domain, random telegraph noise (RTN) is visible in the time traces. During repeated measurements the noise peak reduces and the RTN becomes difficult to resolve, suggesting defects being annealed. The Lorentzian shape noise spectra can be fitted with bias-dependent activation of RTN, with the attempt frequency in the MHz range, consistent with magnon dynamics. These findings suggest magnon-assisted activation of defects as the origin of the enhanced LF noise.

Low frequency noise peak near magnon emission energy in magnetic tunnel junctions

Directory of Open Access Journals (Sweden)

Liang Liu

2014-12-01

Full Text Available We report on the low frequency (LF noise measurements in magnetic tunnel junctions (MTJs below 4 K and at low bias, where the transport is strongly affected by scattering with magnons emitted by hot tunnelling electrons, as thermal activation of magnons from the environment is suppressed. For both CoFeB/MgO/CoFeB and CoFeB/AlOx/CoFeB MTJs, enhanced LF noise is observed at bias voltage around magnon emission energy, forming a peak in the bias dependence of noise power spectra density, independent of magnetic configurations. The noise peak is much higher and broader for unannealed AlOx-based MTJ, and besides Lorentzian shape noise spectra in the frequency domain, random telegraph noise (RTN is visible in the time traces. During repeated measurements the noise peak reduces and the RTN becomes difficult to resolve, suggesting defects being annealed. The Lorentzian shape noise spectra can be fitted with bias-dependent activation of RTN, with the attempt frequency in the MHz range, consistent with magnon dynamics. These findings suggest magnon-assisted activation of defects as the origin of the enhanced LF noise.

Model-based iterative reconstruction for reduction of radiation dose in abdominopelvic CT: comparison to adaptive statistical iterative reconstruction.

Science.gov (United States)

Yasaka, Koichiro; Katsura, Masaki; Akahane, Masaaki; Sato, Jiro; Matsuda, Izuru; Ohtomo, Kuni

2013-12-01

To evaluate dose reduction and image quality of abdominopelvic computed tomography (CT) reconstructed with model-based iterative reconstruction (MBIR) compared to adaptive statistical iterative reconstruction (ASIR). In this prospective study, 85 patients underwent referential-, low-, and ultralow-dose unenhanced abdominopelvic CT. Images were reconstructed with ASIR for low-dose (L-ASIR) and ultralow-dose CT (UL-ASIR), and with MBIR for ultralow-dose CT (UL-MBIR). Image noise was measured in the abdominal aorta and iliopsoas muscle. Subjective image analyses and a lesion detection study (adrenal nodules) were conducted by two blinded radiologists. A reference standard was established by a consensus panel of two different radiologists using referential-dose CT reconstructed with filtered back projection. Compared to low-dose CT, there was a 63% decrease in dose-length product with ultralow-dose CT. UL-MBIR had significantly lower image noise than L-ASIR and UL-ASIR (all pASIR and UL-ASIR (all pASIR in diagnostic acceptability (p>0.65), or diagnostic performance for adrenal nodules (p>0.87). MBIR significantly improves image noise and streak artifacts compared to ASIR, and can achieve radiation dose reduction without severely compromising image quality.

Low voltage excess noise and shot noise in YBCO bicrystal junctions

DEFF Research Database (Denmark)

Constantinian, K.Y.; Ovsyannikov, G.A.; Borisenko, I.V.

2002-01-01

The spectral density of background noise emitted by symmetric bicrystal YBaCuO Josephson junctions on sapphire substrates have been measured by a low noise cooled HEMT amplifier for bias voltages up to V approximate to 50 mV. At relatively low voltages V noise rise has been...... registered. At large bias voltages V > 30 mV a clear dependence of noise power. exactly coinciding to the asymptote of the Schottky shot noise function, has been observed for the first time. Experimental results are discussed in terms of multiple Andreev reflections which may take place in d...

Influence of Ultra-Low-Dose and Iterative Reconstructions on the Visualization of Orbital Soft Tissues on Maxillofacial CT.

Science.gov (United States)

Widmann, G; Juranek, D; Waldenberger, F; Schullian, P; Dennhardt, A; Hoermann, R; Steurer, M; Gassner, E-M; Puelacher, W

2017-08-01

Dose reduction on CT scans for surgical planning and postoperative evaluation of midface and orbital fractures is an important concern. The purpose of this study was to evaluate the variability of various low-dose and iterative reconstruction techniques on the visualization of orbital soft tissues. Contrast-to-noise ratios of the optic nerve and inferior rectus muscle and subjective scores of a human cadaver were calculated from CT with a reference dose protocol (CT dose index volume = 36.69 mGy) and a subsequent series of low-dose protocols (LDPs I-4: CT dose index volume = 4.18, 2.64, 0.99, and 0.53 mGy) with filtered back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR)-50, ASIR-100, and model-based iterative reconstruction. The Dunn Multiple Comparison Test was used to compare each combination of protocols (α = .05). Compared with the reference dose protocol with FBP, the following statistically significant differences in contrast-to-noise ratios were shown (all, P ≤ .012) for the following: 1) optic nerve: LDP-I with FBP; LDP-II with FBP and ASIR-50; LDP-III with FBP, ASIR-50, and ASIR-100; and LDP-IV with FBP, ASIR-50, and ASIR-100; and 2) inferior rectus muscle: LDP-II with FBP, LDP-III with FBP and ASIR-50, and LDP-IV with FBP, ASIR-50, and ASIR-100. Model-based iterative reconstruction showed the best contrast-to-noise ratio in all images and provided similar subjective scores for LDP-II. ASIR-50 had no remarkable effect, and ASIR-100, a small effect on subjective scores. Compared with a reference dose protocol with FBP, model-based iterative reconstruction may show similar diagnostic visibility of orbital soft tissues at a CT dose index volume of 2.64 mGy. Low-dose technology and iterative reconstruction technology may redefine current reference dose levels in maxillofacial CT. © 2017 by American Journal of Neuroradiology.

Temperature characterization of deep and shallow defect centers of low noise silicon JFETs

International Nuclear Information System (INIS)

Arnaboldi, Claudio; Fascilla, Andrea; Lund, M.W.; Pessina, Gianluigi

2004-01-01

We have selected different low noise JFET processes that have shown outstanding dynamic and noise performance at both room temperature and low temperatures. We have studied JFETs made with a process optimized for cryogenic operation, testing several devices of varying capacitance. For most of them, we have been able to detect the presence of shallow individual traps at low temperature which create low frequency (LF) Generation-Recombination (G-R) noise. For one device type no evidence of traps has been observed at the optimum temperature of operation (around 100 K). It had a very small residual LF noise. This device has been cooled down to 14 K. From below 100 K down to 14 K the noise was observed to increase due to G-R noise originating from donor atoms (dopants) inside the channel. A very simple theoretical interpretation confirms the nature of G-R noise from these very shallow trapping centers. We also studied devices from a process optimized for room temperature operation and found noise corresponding to the presence of a single deep level trap. Even for this circumstance the theory was experimentally confirmed. The measurement approach we used allowed us to achieve a very high accuracy in the modeling of the measured G-R noise. The ratio of the density of the atoms responsible for G-R noise above the doping concentration, N T /N d , has been verified with a sensitivity around 10 -7

Median prior constrained TV algorithm for sparse view low-dose CT reconstruction.

Science.gov (United States)

Liu, Yi; Shangguan, Hong; Zhang, Quan; Zhu, Hongqing; Shu, Huazhong; Gui, Zhiguo

2015-05-01

It is known that lowering the X-ray tube current (mAs) or tube voltage (kVp) and simultaneously reducing the total number of X-ray views (sparse view) is an effective means to achieve low-dose in computed tomography (CT) scan. However, the associated image quality by the conventional filtered back-projection (FBP) usually degrades due to the excessive quantum noise. Although sparse-view CT reconstruction algorithm via total variation (TV), in the scanning protocol of reducing X-ray tube current, has been demonstrated to be able to result in significant radiation dose reduction while maintain image quality, noticeable patchy artifacts still exist in reconstructed images. In this study, to address the problem of patchy artifacts, we proposed a median prior constrained TV regularization to retain the image quality by introducing an auxiliary vector m in register with the object. Specifically, the approximate action of m is to draw, in each iteration, an object voxel toward its own local median, aiming to improve low-dose image quality with sparse-view projection measurements. Subsequently, an alternating optimization algorithm is adopted to optimize the associative objective function. We refer to the median prior constrained TV regularization as "TV_MP" for simplicity. Experimental results on digital phantoms and clinical phantom demonstrated that the proposed TV_MP with appropriate control parameters can not only ensure a higher signal to noise ratio (SNR) of the reconstructed image, but also its resolution compared with the original TV method. Copyright © 2015 Elsevier Ltd. All rights reserved.

Low-Arousal Speech Noise Improves Performance in N-Back Task: An ERP Study

Science.gov (United States)

Zhang, Dandan; Jin, Yi; Luo, Yuejia

2013-01-01

The relationship between noise and human performance is a crucial topic in ergonomic research. However, the brain dynamics of the emotional arousal effects of background noises are still unclear. The current study employed meaningless speech noises in the n-back working memory task to explore the changes of event-related potentials (ERPs) elicited by the noises with low arousal level vs. high arousal level. We found that the memory performance in low arousal condition were improved compared with the silent and the high arousal conditions; participants responded more quickly and had larger P2 and P3 amplitudes in low arousal condition while the performance and ERP components showed no significant difference between high arousal and silent conditions. These findings suggested that the emotional arousal dimension of background noises had a significant influence on human working memory performance, and that this effect was independent of the acoustic characteristics of noises (e.g., intensity) and the meaning of speech materials. The current findings improve our understanding of background noise effects on human performance and lay the ground for the investigation of patients with attention deficits. PMID:24204607

Low-arousal speech noise improves performance in N-back task: an ERP study.

Science.gov (United States)

Han, Longzhu; Liu, Yunzhe; Zhang, Dandan; Jin, Yi; Luo, Yuejia

2013-01-01

The relationship between noise and human performance is a crucial topic in ergonomic research. However, the brain dynamics of the emotional arousal effects of background noises are still unclear. The current study employed meaningless speech noises in the n-back working memory task to explore the changes of event-related potentials (ERPs) elicited by the noises with low arousal level vs. high arousal level. We found that the memory performance in low arousal condition were improved compared with the silent and the high arousal conditions; participants responded more quickly and had larger P2 and P3 amplitudes in low arousal condition while the performance and ERP components showed no significant difference between high arousal and silent conditions. These findings suggested that the emotional arousal dimension of background noises had a significant influence on human working memory performance, and that this effect was independent of the acoustic characteristics of noises (e.g., intensity) and the meaning of speech materials. The current findings improve our understanding of background noise effects on human performance and lay the ground for the investigation of patients with attention deficits.

Low-arousal speech noise improves performance in N-back task: an ERP study.

Directory of Open Access Journals (Sweden)

Longzhu Han

Full Text Available The relationship between noise and human performance is a crucial topic in ergonomic research. However, the brain dynamics of the emotional arousal effects of background noises are still unclear. The current study employed meaningless speech noises in the n-back working memory task to explore the changes of event-related potentials (ERPs elicited by the noises with low arousal level vs. high arousal level. We found that the memory performance in low arousal condition were improved compared with the silent and the high arousal conditions; participants responded more quickly and had larger P2 and P3 amplitudes in low arousal condition while the performance and ERP components showed no significant difference between high arousal and silent conditions. These findings suggested that the emotional arousal dimension of background noises had a significant influence on human working memory performance, and that this effect was independent of the acoustic characteristics of noises (e.g., intensity and the meaning of speech materials. The current findings improve our understanding of background noise effects on human performance and lay the ground for the investigation of patients with attention deficits.

Real-time dynamic MR image reconstruction using compressed sensing and principal component analysis (CS-PCA): Demonstration in lung tumor tracking.

Science.gov (United States)

Dietz, Bryson; Yip, Eugene; Yun, Jihyun; Fallone, B Gino; Wachowicz, Keith

2017-08-01

This work presents a real-time dynamic image reconstruction technique, which combines compressed sensing and principal component analysis (CS-PCA), to achieve real-time adaptive radiotherapy with the use of a linac-magnetic resonance imaging system. Six retrospective fully sampled dynamic data sets of patients diagnosed with non-small-cell lung cancer were used to investigate the CS-PCA algorithm. Using a database of fully sampled k-space, principal components (PC's) were calculated to aid in the reconstruction of undersampled images. Missing k-space data were calculated by projecting the current undersampled k-space data onto the PC's to generate the corresponding PC weights. The weighted PC's were summed together, and the missing k-space was iteratively updated. To gain insight into how the reconstruction might proceed at lower fields, 6× noise was added to the 3T data to investigate how the algorithm handles noisy data. Acceleration factors ranging from 2 to 10× were investigated using CS-PCA and Split Bregman CS for comparison. Metrics to determine the reconstruction quality included the normalized mean square error (NMSE), as well as the dice coefficients (DC) and centroid displacement of the tumor segmentations. Our results demonstrate that CS-PCA performed superior than CS alone. The CS-PCA patient averaged DC for 3T and 6× noise added data remained above 0.9 for acceleration factors up to 10×. The patient averaged NMSE gradually increased with increasing acceleration; however, it remained below 0.06 up to an acceleration factor of 10× for both 3T and 6× noise added data. The CS-PCA reconstruction speed ranged from 5 to 20 ms (Intel i7-4710HQ CPU @ 2.5 GHz), depending on the chosen parameters. A real-time reconstruction technique was developed for adaptive radiotherapy using a Linac-MRI system. Our CS-PCA algorithm can achieve tumor contours with DC greater than 0.9 and NMSE less than 0.06 at acceleration factors of up to, and including, 10×. The

Objective task-based assessment of low-contrast detectability in iterative reconstruction

International Nuclear Information System (INIS)

Racine, Damien; Ott, Julien G.; Ba, Alexandre; Ryckx, Nick; Bochud, Francois O.; Verdun, Francis R.

2016-01-01

Evaluating image quality by using receiver operating characteristic studies is time consuming and difficult to implement. This work assesses a new iterative algorithm using a channelised Hotelling observer (CHO). For this purpose, an anthropomorphic abdomen phantom with spheres of various sizes and contrasts was scanned at 3 volume computed tomography dose index (CTDI vol ) levels on a GE Revolution CT. Images were reconstructed using the iterative reconstruction method adaptive statistical iterative reconstruction-V (ASIR-V) at ASIR-V 0, 50 and 70 % and assessed by applying a CHO with dense difference of Gaussian and internal noise. Both CHO and human observers (HO) were compared based on a four-alternative forced-choice experiment, using the percentage correct as a figure of merit. The results showed accordance between CHO and HO. Moreover, an improvement in the low-contrast detection was observed when switching from ASIR-V 0 to 50 %. The results underpin the finding that ASIR-V allows dose reduction. (authors)

RADIANCE DOMAIN COMPOSITING FOR HIGH DYNAMIC RANGE IMAGING

Directory of Open Access Journals (Sweden)

M.R. Renu

2013-02-01

Full Text Available High dynamic range imaging aims at creating an image with a range of intensity variations larger than the range supported by a camera sensor. Most commonly used methods combine multiple exposure low dynamic range (LDR images, to obtain the high dynamic range (HDR image. Available methods typically neglect the noise term while finding appropriate weighting functions to estimate the camera response function as well as the radiance map. We look at the HDR imaging problem in a denoising frame work and aim at reconstructing a low noise radiance map from noisy low dynamic range images, which is tone mapped to get the LDR equivalent of the HDR image. We propose a maximum aposteriori probability (MAP based reconstruction of the HDR image using Gibb’s prior to model the radiance map, with total variation (TV as the prior to avoid unnecessary smoothing of the radiance field. To make the computation with TV prior efficient, we extend the majorize-minimize method of upper bounding the total variation by a quadratic function to our case which has a nonlinear term arising from the camera response function. A theoretical justification for doing radiance domain denoising as opposed to image domain denoising is also provided.

Nonlinearly stacked low noise turbofan stator

Science.gov (United States)

Schuster, William B. (Inventor); Nolcheff, Nick A. (Inventor); Gunaraj, John A. (Inventor); Kontos, Karen B. (Inventor); Weir, Donald S. (Inventor)

2009-01-01

A nonlinearly stacked low noise turbofan stator vane having a characteristic curve that is characterized by a nonlinear sweep and a nonlinear lean is provided. The stator is in an axial fan or compressor turbomachinery stage that is comprised of a collection of vanes whose highly three-dimensional shape is selected to reduce rotor-stator and rotor-strut interaction noise while maintaining the aerodynamic and mechanical performance of the vane. The nonlinearly stacked low noise turbofan stator vane reduces noise associated with the fan stage of turbomachinery to improve environmental compatibility.

Superconducting low-noise oscillator

International Nuclear Information System (INIS)

Riebman, L.

1992-01-01

This patent describes a cryogenic oscillator having low phase noise and low noise. It comprises resonant circuit means formed of superconducting material for generating a signal at a desired frequency; linear amplifier means electrically connected to the resonant circuit means at first and second locations thereon; limiter means electrically connected to the resonant circuit means at a third location thereon; and buffer amplifier means for applying the signal generated by the resonant circuit means to a load and electrically connected to the resonant circuit means at a fourth location thereon. This patent also describes a method of minimizing phase noise and 1/f noise in an oscillator circuit of the type having a resonant circuit driving a load and at least a linear amplifier connected to the resonant circuit defining a closed loop having a loop gain greater than unity, and having a limiter for stabilizing the oscillator. It comprises connecting between the resonant circuit and the load a buffer amplifier and connecting the linear amplifier and the buffer amplifier to the resonant circuit

Compressed Sensing with Linear Correlation Between Signal and Measurement Noise

DEFF Research Database (Denmark)

Arildsen, Thomas; Larsen, Torben

2014-01-01

reconstruction algorithms, but is not known in existing literature. The proposed technique reduces reconstruction error considerably in the case of linearly correlated measurements and noise. Numerical experiments confirm the efficacy of the technique. The technique is demonstrated with application to low......Existing convex relaxation-based approaches to reconstruction in compressed sensing assume that noise in the measurements is independent of the signal of interest. We consider the case of noise being linearly correlated with the signal and introduce a simple technique for improving compressed...... sensing reconstruction from such measurements. The technique is based on a linear model of the correlation of additive noise with the signal. The modification of the reconstruction algorithm based on this model is very simple and has negligible additional computational cost compared to standard...

Optimization of SPECT-CT Hybrid Imaging Using Iterative Image Reconstruction for Low-Dose CT: A Phantom Study.

Directory of Open Access Journals (Sweden)

Oliver S Grosser

Full Text Available Hybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT or positron emission tomography (PET with computed tomography (CT. Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR on the image quality of the low-dose CT images.Examinations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88 and the contrast-to-noise ratio (CNR was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04. In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001.In general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.

A low-power high dynamic range front-end ASIC for imaging calorimeters

CERN Document Server

Bagliesi, M G; Marrocchesi, P S; Meucci, M; Millucci, V; Morsani, F; Paoletti, R; Pilo, F; Scribano, A; Turini, N; Valle, G D

2002-01-01

High granularity calorimeters with shower imaging capabilities require dedicated front-end electronics. The ICON 4CH and VA4 PMT chip-set is suitable for very high dynamic range systems with strict noise requirements. The ICON 4CH is a 4 channel input, 12 channel output ASIC designed for use in a multi-anode photomultiplier system with very large dynamic range and low-noise requirements. Each of the four input signals to the ASIC is split equally into three branches by a current conveyor. Each of the three branches is scaled differently: 1:1, 1:8 and 1:80. The signal is read out by a 12 channel low noise/low power high dynamic range charge sensitive preamplifier-shaper circuit (VA4-PMT chip), with simultaneous sample- and-hold, multiplexed analog read-out, calibration facilities. Tests performed in our lab with a PMT are reported in terms of linearity, dynamic range and cross-talk of the system. (5 refs).

Low-frequency-noise complaints

DEFF Research Database (Denmark)

Pedersen, Christian Sejer; Møller, Henrik; Persson-Waye, Kerstin

2008-01-01

From 203 cases of low-frequency complaints a random selection of twenty-one cases were investigated. The main aim of the investigation was to answer the question whether the annoyance is caused by an external physical sound or by a physically non-existing sound, i.e. low-frequency tinnitus. Noise...... of the complainants are annoyed by a physical sound (20-180 Hz), while others suffer from low-frequency tinnitus (perceived frequency 40-100 Hz). Physical sound at frequencies below 20 Hz (infrasound) is not responsible for the annoyance - or at all audible - in any of the investigated cases, and none...... of the complainants has extraordinary hearing sensitivity at low frequencies. For comparable cases of low-frequency noise complaints in general, it is anticipated that physical sound is responsible in a substantial part of the cases, while low-frequency tinnitus is responsible in another substantial part of the cases....

Dynamic X-ray computed tomography

International Nuclear Information System (INIS)

Grangeat, P.

2003-01-01

Paper Dynamic computed tomography (CT) imaging aims at reconstructing image sequences where the dynamic nature of the living human body is of primary interest. Main concerned applications are image-guided interventional procedures, functional studies and cardiac imaging. The introduction of ultra-fast rotating gantries along with multi-row detectors and in near future area detectors allows a huge progress toward the imaging of moving organs with low-contrast resolution. This paper gives an overview of the different concepts used in dynamic CT. A new reconstruction algorithm based on a voxel-specific dynamic evolution compensation is also presented. It provides four-dimensional image sequences with accurate spatio-temporal information, where each frame is reconstructed using a long-scan acquisition mode on several half-turns. In the same time, this technique permits to reduce the dose delivered per rotation while keeping the same signal to noise ratio for every frame using an adaptive motion-compensated temporal averaging. Results are illustrated on simulated data. (authors)

Subjective annoyance caused by indoor low-level and low frequency noise and control method

Institute of Scientific and Technical Information of China (English)

DI Guo-qing; ZHANG Bang-jun; SHANG Qi

2005-01-01

The influence of low-level noise has not been widely noticed. This paper discovered that low-level and low frequency noise(Aweighted equivalent level Leq ＜ 45 dB) causes higher probability of subjective annoyance. The fuzzy mathematic principle was applied to deal with the threshold level of subjective annoyance from noise in this study; there is preferable relationship between the indoor noise and noise annoyance at low frequency noise level. Study indicated at the same centered noise level, the change of annoyance probability is mainly caused by the change of the frequency spectrum characteristic of the indoor noise. Under low noise level environment, without change of the medium-low frequency noise, the slight increase of medium-high frequency noise level with the help of noise sheltering effect can significantly reduce the noise annoyance. This discovery brings a new resolution on how to improve the environmental quality of working or living places. A noise control model is given in this study according to the acoustic analysis.

MO-DE-207A-01: Impact of Statistical Weights On Detection of Low-Contrast Details in Model-Based Iterative CT Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Noo, F; Guo, Z [University of Utah, Salt Lake City, UT (United States)

2016-06-15

Purpose: Penalized-weighted least-square reconstruction has become an important research topic in CT, to reduce dose without affecting image quality. Two components impact image quality in this reconstruction: the statistical weights and the use of an edge-preserving penalty term. We are interested in assessing the influence of statistical weights on their own, without the edge-preserving feature. Methods: The influence of statistical weights on image quality was assessed in terms of low-contrast detail detection using LROC analysis. The task amounted to detect and localize a 6-mm lesion with random contrast inside the FORBILD head phantom. A two-alternative forced-choice experiment was used with two human observers performing the task. Reconstructions without and with statistical weights were compared, both using the same quadratic penalty term. The beam energy was set to 30keV to amplify spatial differences in attenuation and thereby the role of statistical weights. A fan-beam data acquisition geometry was used. Results: Visual inspection of images clearly showed a difference in noise between the two reconstructions methods. As expected, the reconstruction without statistical weights exhibited noise streaks. The other reconstruction appeared better in this aspect, but presented other disturbing noise patterns and artifacts induced by the weights. The LROC analysis yield the following 95-percent confidence interval for the difference in reader-averaged AUC (reconstruction without weights minus reconstruction with weights): [0.0026,0.0599]. The mean AUC value was 0.9094. Conclusion: We have investigated the impact of statistical weights without the use of edge-preserving penalty in penalized weighted least-square reconstruction. A decrease rather than increase in image quality was observed when using statistical weights. Thus, the observers were better able to cope with the noise streaks than the noise patterns and artifacts induced by the statistical weights. It

MO-DE-207A-01: Impact of Statistical Weights On Detection of Low-Contrast Details in Model-Based Iterative CT Reconstruction

International Nuclear Information System (INIS)

Noo, F; Guo, Z

2016-01-01

Purpose: Penalized-weighted least-square reconstruction has become an important research topic in CT, to reduce dose without affecting image quality. Two components impact image quality in this reconstruction: the statistical weights and the use of an edge-preserving penalty term. We are interested in assessing the influence of statistical weights on their own, without the edge-preserving feature. Methods: The influence of statistical weights on image quality was assessed in terms of low-contrast detail detection using LROC analysis. The task amounted to detect and localize a 6-mm lesion with random contrast inside the FORBILD head phantom. A two-alternative forced-choice experiment was used with two human observers performing the task. Reconstructions without and with statistical weights were compared, both using the same quadratic penalty term. The beam energy was set to 30keV to amplify spatial differences in attenuation and thereby the role of statistical weights. A fan-beam data acquisition geometry was used. Results: Visual inspection of images clearly showed a difference in noise between the two reconstructions methods. As expected, the reconstruction without statistical weights exhibited noise streaks. The other reconstruction appeared better in this aspect, but presented other disturbing noise patterns and artifacts induced by the weights. The LROC analysis yield the following 95-percent confidence interval for the difference in reader-averaged AUC (reconstruction without weights minus reconstruction with weights): [0.0026,0.0599]. The mean AUC value was 0.9094. Conclusion: We have investigated the impact of statistical weights without the use of edge-preserving penalty in penalized weighted least-square reconstruction. A decrease rather than increase in image quality was observed when using statistical weights. Thus, the observers were better able to cope with the noise streaks than the noise patterns and artifacts induced by the statistical weights. It

Practical implementation of tetrahedral mesh reconstruction in emission tomography

Science.gov (United States)

Boutchko, R.; Sitek, A.; Gullberg, G. T.

2013-05-01

This paper presents a practical implementation of image reconstruction on tetrahedral meshes optimized for emission computed tomography with parallel beam geometry. Tetrahedral mesh built on a point cloud is a convenient image representation method, intrinsically three-dimensional and with a multi-level resolution property. Image intensities are defined at the mesh nodes and linearly interpolated inside each tetrahedron. For the given mesh geometry, the intensities can be computed directly from tomographic projections using iterative reconstruction algorithms with a system matrix calculated using an exact analytical formula. The mesh geometry is optimized for a specific patient using a two stage process. First, a noisy image is reconstructed on a finely-spaced uniform cloud. Then, the geometry of the representation is adaptively transformed through boundary-preserving node motion and elimination. Nodes are removed in constant intensity regions, merged along the boundaries, and moved in the direction of the mean local intensity gradient in order to provide higher node density in the boundary regions. Attenuation correction and detector geometric response are included in the system matrix. Once the mesh geometry is optimized, it is used to generate the final system matrix for ML-EM reconstruction of node intensities and for visualization of the reconstructed images. In dynamic PET or SPECT imaging, the system matrix generation procedure is performed using a quasi-static sinogram, generated by summing projection data from multiple time frames. This system matrix is then used to reconstruct the individual time frame projections. Performance of the new method is evaluated by reconstructing simulated projections of the NCAT phantom and the method is then applied to dynamic SPECT phantom and patient studies and to a dynamic microPET rat study. Tetrahedral mesh-based images are compared to the standard voxel-based reconstruction for both high and low signal-to-noise ratio

Practical implementation of tetrahedral mesh reconstruction in emission tomography

International Nuclear Information System (INIS)

Boutchko, R; Gullberg, G T; Sitek, A

2013-01-01

This paper presents a practical implementation of image reconstruction on tetrahedral meshes optimized for emission computed tomography with parallel beam geometry. Tetrahedral mesh built on a point cloud is a convenient image representation method, intrinsically three-dimensional and with a multi-level resolution property. Image intensities are defined at the mesh nodes and linearly interpolated inside each tetrahedron. For the given mesh geometry, the intensities can be computed directly from tomographic projections using iterative reconstruction algorithms with a system matrix calculated using an exact analytical formula. The mesh geometry is optimized for a specific patient using a two stage process. First, a noisy image is reconstructed on a finely-spaced uniform cloud. Then, the geometry of the representation is adaptively transformed through boundary-preserving node motion and elimination. Nodes are removed in constant intensity regions, merged along the boundaries, and moved in the direction of the mean local intensity gradient in order to provide higher node density in the boundary regions. Attenuation correction and detector geometric response are included in the system matrix. Once the mesh geometry is optimized, it is used to generate the final system matrix for ML-EM reconstruction of node intensities and for visualization of the reconstructed images. In dynamic PET or SPECT imaging, the system matrix generation procedure is performed using a quasi-static sinogram, generated by summing projection data from multiple time frames. This system matrix is then used to reconstruct the individual time frame projections. Performance of the new method is evaluated by reconstructing simulated projections of the NCAT phantom and the method is then applied to dynamic SPECT phantom and patient studies and to a dynamic microPET rat study. Tetrahedral mesh-based images are compared to the standard voxel-based reconstruction for both high and low signal-to-noise ratio

Combining automatic tube current modulation with adaptive statistical iterative reconstruction for low-dose chest CT screening.

Science.gov (United States)

Chen, Jiang-Hong; Jin, Er-Hu; He, Wen; Zhao, Li-Qin

2014-01-01

To reduce radiation dose while maintaining image quality in low-dose chest computed tomography (CT) by combining adaptive statistical iterative reconstruction (ASIR) and automatic tube current modulation (ATCM). Patients undergoing cancer screening (n = 200) were subjected to 64-slice multidetector chest CT scanning with ASIR and ATCM. Patients were divided into groups 1, 2, 3, and 4 (n = 50 each), with a noise index (NI) of 15, 20, 30, and 40, respectively. Each image set was reconstructed with 4 ASIR levels (0% ASIR, 30% ASIR, 50% ASIR, and 80% ASIR) in each group. Two radiologists assessed subjective image noise, image artifacts, and visibility of the anatomical structures. Objective image noise and signal-to-noise ratio (SNR) were measured, and effective dose (ED) was recorded. Increased NI was associated with increased subjective and objective image noise results (PASIR levels (PASIR had average subjective image noise scores and nearly average anatomical structure visibility scores, with a mean objective image noise of 23.42 HU. The EDs for groups 1, 2, 3 and 4 were 2.79 ± 1.17, 1.69 ± 0.59, 0.74 ± 0.29, and 0.37 ± 0.22 mSv, respectively. Compared to group 1 (NI = 15), the ED reductions were 39.43%, 73.48%, and 86.74% for groups 2, 3, and 4, respectively. Using NI = 30 with 50% ASIR in the chest CT protocol, we obtained average or above-average image quality but a reduced ED.

Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique

Energy Technology Data Exchange (ETDEWEB)

Katsura, Masaki; Matsuda, Izuru; Akahane, Masaaki; Sato, Jiro; Akai, Hiroyuki; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni [University of Tokyo, Department of Radiology, Graduate School of Medicine, Bunkyo-ku, Tokyo (Japan)

2012-08-15

To prospectively evaluate dose reduction and image quality characteristics of chest CT reconstructed with model-based iterative reconstruction (MBIR) compared with adaptive statistical iterative reconstruction (ASIR). One hundred patients underwent reference-dose and low-dose unenhanced chest CT with 64-row multidetector CT. Images were reconstructed with 50 % ASIR-filtered back projection blending (ASIR50) for reference-dose CT, and with ASIR50 and MBIR for low-dose CT. Two radiologists assessed the images in a blinded manner for subjective image noise, artefacts and diagnostic acceptability. Objective image noise was measured in the lung parenchyma. Data were analysed using the sign test and pair-wise Student's t-test. Compared with reference-dose CT, there was a 79.0 % decrease in dose-length product with low-dose CT. Low-dose MBIR images had significantly lower objective image noise (16.93 {+-} 3.00) than low-dose ASIR (49.24 {+-} 9.11, P < 0.01) and reference-dose ASIR images (24.93 {+-} 4.65, P < 0.01). Low-dose MBIR images were all diagnostically acceptable. Unique features of low-dose MBIR images included motion artefacts and pixellated blotchy appearances, which did not adversely affect diagnostic acceptability. Diagnostically acceptable chest CT images acquired with nearly 80 % less radiation can be obtained using MBIR. MBIR shows greater potential than ASIR for providing diagnostically acceptable low-dose CT images without severely compromising image quality. (orig.)

Feasibility Study of Radiation Dose Reduction in Adult Female Pelvic CT Scan with Low Tube-Voltage and Adaptive Statistical Iterative Reconstruction

Science.gov (United States)

Wang, Xinlian; Chen, Jianghong; Hu, Zhihai; Zhao, Liqin

2015-01-01

Objective To evaluate image quality of female pelvic computed tomography (CT) scans reconstructed with the adaptive statistical iterative reconstruction (ASIR) technique combined with low tube-voltage and to explore the feasibility of its clinical application. Materials and Methods Ninety-four patients were divided into two groups. The study group used 100 kVp, and images were reconstructed with 30%, 50%, 70%, and 90% ASIR. The control group used 120 kVp, and images were reconstructed with 30% ASIR. The noise index was 15 for the study group and 11 for the control group. The CT values and noise levels of different tissues were measured. The contrast to noise ratio (CNR) was calculated. A subjective evaluation was carried out by two experienced radiologists. The CT dose index volume (CTDIvol) was recorded. Results A 44.7% reduction in CTDIvol was observed in the study group (8.18 ± 3.58 mGy) compared with that in the control group (14.78 ± 6.15 mGy). No significant differences were observed in the tissue noise levels and CNR values between the 70% ASIR group and the control group (p = 0.068-1.000). The subjective scores indicated that visibility of small structures, diagnostic confidence, and the overall image quality score in the 70% ASIR group was the best, and were similar to those in the control group (1.87 vs. 1.79, 1.26 vs. 1.28, and 4.53 vs. 4.57; p = 0.122-0.585). No significant difference in diagnostic accuracy was detected between the study group and the control group (42/47 vs. 43/47, p = 1.000). Conclusion Low tube-voltage combined with automatic tube current modulation and 70% ASIR allowed the low CT radiation dose to be reduced by 44.7% without losing image quality on female pelvic scan. PMID:26357499

Penalized weighted least-squares approach for low-dose x-ray computed tomography

Science.gov (United States)

Wang, Jing; Li, Tianfang; Lu, Hongbing; Liang, Zhengrong

2006-03-01

The noise of low-dose computed tomography (CT) sinogram follows approximately a Gaussian distribution with nonlinear dependence between the sample mean and variance. The noise is statistically uncorrelated among detector bins at any view angle. However the correlation coefficient matrix of data signal indicates a strong signal correlation among neighboring views. Based on above observations, Karhunen-Loeve (KL) transform can be used to de-correlate the signal among the neighboring views. In each KL component, a penalized weighted least-squares (PWLS) objective function can be constructed and optimal sinogram can be estimated by minimizing the objective function, followed by filtered backprojection (FBP) for CT image reconstruction. In this work, we compared the KL-PWLS method with an iterative image reconstruction algorithm, which uses the Gauss-Seidel iterative calculation to minimize the PWLS objective function in image domain. We also compared the KL-PWLS with an iterative sinogram smoothing algorithm, which uses the iterated conditional mode calculation to minimize the PWLS objective function in sinogram space, followed by FBP for image reconstruction. Phantom experiments show a comparable performance of these three PWLS methods in suppressing the noise-induced artifacts and preserving resolution in reconstructed images. Computer simulation concurs with the phantom experiments in terms of noise-resolution tradeoff and detectability in low contrast environment. The KL-PWLS noise reduction may have the advantage in computation for low-dose CT imaging, especially for dynamic high-resolution studies.

The noise power spectrum in CT with direct fan beam reconstruction

International Nuclear Information System (INIS)

Baek, Jongduk; Pelc, Norbert J.

2010-01-01

The noise power spectrum (NPS) is a useful metric for understanding the noise content in images. To examine some unique properties of the NPS of fan beam CT, the authors derived an analytical expression for the NPS of fan beam CT and validated it with computer simulations. The nonstationary noise behavior of fan beam CT was examined by analyzing local regions and the entire field-of-view (FOV). This was performed for cases with uniform as well as nonuniform noise across the detector cells and across views. The simulated NPS from the entire FOV and local regions showed good agreement with the analytically derived NPS. The analysis shows that whereas the NPS of a large FOV in parallel beam CT (using a ramp filter) is proportional to frequency, the NPS with direct fan beam FBP reconstruction shows a high frequency roll off. Even in small regions, the fan beam NPS can show a sharp transition (discontinuity) at high frequencies. These effects are due to the variable magnification and therefore are more pronounced as the fan angle increases. For cases with nonuniform noise, the NPS can show the directional dependence and additional effects.

Correlated Levy Noise in Linear Dynamical Systems

International Nuclear Information System (INIS)

Srokowski, T.

2011-01-01

Linear dynamical systems, driven by a non-white noise which has the Levy distribution, are analysed. Noise is modelled by a specific stochastic process which is defined by the Langevin equation with a linear force and the Levy distributed symmetric white noise. Correlation properties of the process are discussed. The Fokker-Planck equation driven by that noise is solved. Distributions have the Levy shape and their width, for a given time, is smaller than for processes in the white noise limit. Applicability of the adiabatic approximation in the case of the linear force is discussed. (author)

Relaxed Simultaneous Tomographic Reconstruction and Segmentation with Class Priors for Poisson Noise

DEFF Research Database (Denmark)

Romanov, Mikhail; Dahl, Anders Bjorholm; Dong, Yiqiu

: our new algorithm can handle Poisson noise in the data, and it can solve much larger problems since it does not store the matrix. We formulate this algorithm and test it on artificial test problems. Our results show that the algorithm performs well, and that we are able to produce reconstructions...

Nonlocal low-rank and sparse matrix decomposition for spectral CT reconstruction

Science.gov (United States)

Niu, Shanzhou; Yu, Gaohang; Ma, Jianhua; Wang, Jing

2018-02-01

Spectral computed tomography (CT) has been a promising technique in research and clinics because of its ability to produce improved energy resolution images with narrow energy bins. However, the narrow energy bin image is often affected by serious quantum noise because of the limited number of photons used in the corresponding energy bin. To address this problem, we present an iterative reconstruction method for spectral CT using nonlocal low-rank and sparse matrix decomposition (NLSMD), which exploits the self-similarity of patches that are collected in multi-energy images. Specifically, each set of patches can be decomposed into a low-rank component and a sparse component, and the low-rank component represents the stationary background over different energy bins, while the sparse component represents the rest of the different spectral features in individual energy bins. Subsequently, an effective alternating optimization algorithm was developed to minimize the associated objective function. To validate and evaluate the NLSMD method, qualitative and quantitative studies were conducted by using simulated and real spectral CT data. Experimental results show that the NLSMD method improves spectral CT images in terms of noise reduction, artifact suppression and resolution preservation.

New adaptive statistical iterative reconstruction ASiR-V: Assessment of noise performance in comparison to ASiR.

Science.gov (United States)

De Marco, Paolo; Origgi, Daniela

2018-03-01

To assess the noise characteristics of the new adaptive statistical iterative reconstruction (ASiR-V) in comparison to ASiR. A water phantom was acquired with common clinical scanning parameters, at five different levels of CTDI vol . Images were reconstructed with different kernels (STD, SOFT, and BONE), different IR levels (40%, 60%, and 100%) and different slice thickness (ST) (0.625 and 2.5 mm), both for ASiR-V and ASiR. Noise properties were investigated and noise power spectrum (NPS) was evaluated. ASiR-V significantly reduced noise relative to FBP: noise reduction was in the range 23%-60% for a 0.625 mm ST and 12%-64% for the 2.5 mm ST. Above 2 mGy, noise reduction for ASiR-V had no dependence on dose. Noise reduction for ASIR-V has dependence on ST, being greater for STD and SOFT kernels at 2.5 mm. For the STD kernel ASiR-V has greater noise reduction for both ST, if compared to ASiR. For the SOFT kernel, results varies according to dose and ST, while for BONE kernel ASIR-V shows less noise reduction. NPS for CT Revolution has dose dependent behavior at lower doses. NPS for ASIR-V and ASiR is similar, showing a shift toward lower frequencies as the IR level increases for STD and SOFT kernels. The NPS is different between ASiR-V and ASIR with BONE kernel. NPS for ASiR-V appears to be ST dependent, having a shift toward lower frequencies for 2.5 mm ST. ASiR-V showed greater noise reduction than ASiR for STD and SOFT kernels, while keeping the same NPS. For the BONE kernel, ASiR-V presents a completely different behavior, with less noise reduction and modified NPS. Noise properties of the ASiR-V are dependent on reconstruction slice thickness. The noise properties of ASiR-V suggest the need for further measurements and efforts to establish new CT protocols to optimize clinical imaging. © 2018 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine.

Tensor-based dictionary learning for dynamic tomographic reconstruction

International Nuclear Information System (INIS)

Tan, Shengqi; Wu, Zhifang; Zhang, Yanbo; Mou, Xuanqin; Wang, Ge; Cao, Guohua; Yu, Hengyong

2015-01-01

In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. (paper)

Tensor-based Dictionary Learning for Dynamic Tomographic Reconstruction

Science.gov (United States)

Tan, Shengqi; Zhang, Yanbo; Wang, Ge; Mou, Xuanqin; Cao, Guohua; Wu, Zhifang; Yu, Hengyong

2015-01-01

In dynamic computed tomography (CT) reconstruction, the data acquisition speed limits the spatio-temporal resolution. Recently, compressed sensing theory has been instrumental in improving CT reconstruction from far few-view projections. In this paper, we present an adaptive method to train a tensor-based spatio-temporal dictionary for sparse representation of an image sequence during the reconstruction process. The correlations among atoms and across phases are considered to capture the characteristics of an object. The reconstruction problem is solved by the alternating direction method of multipliers. To recover fine or sharp structures such as edges, the nonlocal total variation is incorporated into the algorithmic framework. Preclinical examples including a sheep lung perfusion study and a dynamic mouse cardiac imaging demonstrate that the proposed approach outperforms the vectorized dictionary-based CT reconstruction in the case of few-view reconstruction. PMID:25779991

Adrenal and nephrogenic hypertension: an image quality study of low tube voltage, low-concentration contrast media combined with adaptive statistical iterative reconstruction.

Science.gov (United States)

Li, Zhen; Li, Qiong; Shen, Yaqi; Li, Anqin; Li, Haojie; Liang, Lili; Hu, Yao; Hu, Xuemei; Hu, Daoyu

2016-09-01

The aim of this study was to investigate the effect of using low tube voltage, low-concentration contrast media and adaptive statistical iterative reconstruction (ASIR) for reducing the radiation and iodine contrast doses in adrenal and nephrogenic hypertension patients. A total of 148 hypertension patients who were suspected for adrenal lesions or renal artery stenoses were assigned to two groups and. Group A (n=74) underwent a low tube voltage, low molecular weight dextran enhanced multi-detector row spiral CT (MDCT) (80 kVp, 270 mg I/mL contrast agent), and the raw data were reconstructed with standard filtered back projection (FBP) and ASIR at four different levels of blending (20%, 40%, 60% and 80%, respectively). The control group (Group B, n=74) underwent conventional MDCT (120 kVp, 370 mg I/mL contrast agent), and the data were reconstructed with FBP. The CT values, standard deviation (SD), signal-noise-ratio (SNR) and contrast-noise-ratio (CNR) were measured in the renal vessels, normal adrenal tissue, adrenal neoplasms and subcutaneous fat. The volume CT dose index (CTDIvol ) and dose length product (DLP) were recorded, and an effective dose (ED) was obtained. Two-tailed independent t-tests, paired Chi-square tests and Kappa consistency tests were used for statistical analysis of the data. The CTDIvol , DLP and total iodine dose in group A were decreased by 47.8%, 49.0% and 26.07%, respectively, compared to group B (Pcontrast media and 60% ASIR provides similar enhancement and image quality with a reduced radiation dose and contrast iodine dose. © 2016 John Wiley & Sons Ltd.

Coupled dynamic systems and Le Chatelier's principle in noise control

Science.gov (United States)

Maidanik, G.; Becker, K. J.

2004-05-01

Investigation of coupling an externally driven dynamic system-a master dynamic system-to a passive one-an adjunct dynamic system-reveals that the response of the adjunct dynamic system affects the precoupled response of the master dynamic system. The responses, in the two dynamic systems when coupled, are estimated by the stored energies (Es) and (E0), respectively. Since the adjunct dynamic system, prior to coupling, was with zero (0) stored energy, E0s=0, the precoupled stored energy (E00) in the master dynamic system is expected to be reduced to (E0) when coupling is instituted; i.e., one expects E0noise control of the master dynamic system would result from the coupling. It is argued that the change in the disposition of the stored energies as just described may not be the only change. The coupling may influence the external input power into the master dynamic system which may interfere with the expected noise control. Indeed, the coupling may influence the external input power such that the expected beneficial noise control may not materialize. Examples of these kinds of noise control reversals are cited.

Patellofemoral Pressure Changes After Static and Dynamic Medial Patellofemoral Ligament Reconstructions.

Science.gov (United States)

Rood, Akkie; Hannink, Gerjon; Lenting, Anke; Groenen, Karlijn; Koëter, Sander; Verdonschot, Nico; van Kampen, Albert

2015-10-01

Reconstructing the medial patellofemoral ligament (MPFL) has become a key procedure for stabilizing the patella. Different techniques to reconstruct the MPFL have been described: static techniques in which the graft is fixed rigidly to the bone or dynamic techniques with soft tissue fixation. Static MPFL reconstruction is most commonly used. However, dynamic reconstruction deforms more easily and presumably functions more like the native MPFL. The aim of the study was to evaluate the effect of the different MPFL fixation techniques on patellofemoral pressures compared with the native situation. The hypothesis was that dynamic reconstruction would result in patellofemoral pressures closer to those generated in an intact knee. Controlled laboratory study. Seven fresh-frozen knee specimens were tested in an in vitro knee joint loading apparatus. Tekscan pressure-sensitive films fixed to the retropatellar cartilage measured mean patellofemoral and peak pressures, contact area, and location of the center of force (COF) at fixed flexion angles from 0° to 110°. Four different conditions were tested: intact, dynamic, partial dynamic, and static MPFL reconstruction. Data were analyzed using linear mixed models. Static MPFL reconstruction resulted in higher peak and mean pressures from 60° to 110° of flexion (P .05). The COF in the static reconstruction group moved more medially on the patella from 50° to 110° of flexion compared with the other conditions. The contact area showed no significant differences between the test conditions. After static MPFL reconstruction, the patellofemoral pressures in flexion angles from 60° to 110° were 3 to 5 times higher than those in the intact situation. The pressures after dynamic MPFL reconstruction were similar as compared with those in the intact situation, and therefore, dynamic MPFL reconstruction could be a safer option than static reconstruction for stabilizing the patella. This study showed that static MPFL reconstruction

Low-frequency noise from large wind turbines

DEFF Research Database (Denmark)

Møller, Henrik; Pedersen, Christian Sejer

2011-01-01

As wind turbines get larger, worries have emerged that the turbine noise would move down in frequency and that the low-frequency noise would cause annoyance for the neighbors. The noise emission from 48 wind turbines with nominal electric power up to 3.6 MW is analyzed and discussed. The relative...... amount of low-frequency noise is higher for large turbines (2.3–3.6 MW) than for small turbines (≤ 2 MW), and the difference is statistically significant. The difference can also be expressed as a downward shift of the spectrum of approximately one-third of an octave. A further shift of similar size...... is suggested for future turbines in the 10-MW range. Due to the air absorption, the higher low-frequency content becomes even more pronounced, when sound pressure levels in relevant neighbor distances are considered. Even when A-weighted levels are considered, a substantial part of the noise is at low...

Model-based iterative reconstruction technique for radiation dose reduction in chest CT: comparison with the adaptive statistical iterative reconstruction technique

International Nuclear Information System (INIS)

Katsura, Masaki; Matsuda, Izuru; Akahane, Masaaki; Sato, Jiro; Akai, Hiroyuki; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni

2012-01-01

To prospectively evaluate dose reduction and image quality characteristics of chest CT reconstructed with model-based iterative reconstruction (MBIR) compared with adaptive statistical iterative reconstruction (ASIR). One hundred patients underwent reference-dose and low-dose unenhanced chest CT with 64-row multidetector CT. Images were reconstructed with 50 % ASIR-filtered back projection blending (ASIR50) for reference-dose CT, and with ASIR50 and MBIR for low-dose CT. Two radiologists assessed the images in a blinded manner for subjective image noise, artefacts and diagnostic acceptability. Objective image noise was measured in the lung parenchyma. Data were analysed using the sign test and pair-wise Student's t-test. Compared with reference-dose CT, there was a 79.0 % decrease in dose-length product with low-dose CT. Low-dose MBIR images had significantly lower objective image noise (16.93 ± 3.00) than low-dose ASIR (49.24 ± 9.11, P < 0.01) and reference-dose ASIR images (24.93 ± 4.65, P < 0.01). Low-dose MBIR images were all diagnostically acceptable. Unique features of low-dose MBIR images included motion artefacts and pixellated blotchy appearances, which did not adversely affect diagnostic acceptability. Diagnostically acceptable chest CT images acquired with nearly 80 % less radiation can be obtained using MBIR. MBIR shows greater potential than ASIR for providing diagnostically acceptable low-dose CT images without severely compromising image quality. (orig.)

Low-frequency noise from large wind turbines.

Science.gov (United States)

Møller, Henrik; Pedersen, Christian Sejer

2011-06-01

As wind turbines get larger, worries have emerged that the turbine noise would move down in frequency and that the low-frequency noise would cause annoyance for the neighbors. The noise emission from 48 wind turbines with nominal electric power up to 3.6 MW is analyzed and discussed. The relative amount of low-frequency noise is higher for large turbines (2.3-3.6 MW) than for small turbines (≤ 2 MW), and the difference is statistically significant. The difference can also be expressed as a downward shift of the spectrum of approximately one-third of an octave. A further shift of similar size is suggested for future turbines in the 10-MW range. Due to the air absorption, the higher low-frequency content becomes even more pronounced, when sound pressure levels in relevant neighbor distances are considered. Even when A-weighted levels are considered, a substantial part of the noise is at low frequencies, and for several of the investigated large turbines, the one-third-octave band with the highest level is at or below 250 Hz. It is thus beyond any doubt that the low-frequency part of the spectrum plays an important role in the noise at the neighbors. © 2011 Acoustical Society of America

Quantitative evaluation of ASiR image quality: an adaptive statistical iterative reconstruction technique

Science.gov (United States)

Van de Casteele, Elke; Parizel, Paul; Sijbers, Jan

2012-03-01

Adaptive statistical iterative reconstruction (ASiR) is a new reconstruction algorithm used in the field of medical X-ray imaging. This new reconstruction method combines the idealized system representation, as we know it from the standard Filtered Back Projection (FBP) algorithm, and the strength of iterative reconstruction by including a noise model in the reconstruction scheme. It studies how noise propagates through the reconstruction steps, feeds this model back into the loop and iteratively reduces noise in the reconstructed image without affecting spatial resolution. In this paper the effect of ASiR on the contrast to noise ratio is studied using the low contrast module of the Catphan phantom. The experiments were done on a GE LightSpeed VCT system at different voltages and currents. The results show reduced noise and increased contrast for the ASiR reconstructions compared to the standard FBP method. For the same contrast to noise ratio the images from ASiR can be obtained using 60% less current, leading to a reduction in dose of the same amount.

Image quality and radiation dose of low dose coronary CT angiography in obese patients: Sinogram affirmed iterative reconstruction versus filtered back projection

International Nuclear Information System (INIS)

Wang, Rui; Schoepf, U. Joseph; Wu, Runze; Reddy, Ryan P.; Zhang, Chuanchen; Yu, Wei; Liu, Yi; Zhang, Zhaoqi

2012-01-01

Purpose: To investigate the image quality and radiation dose of low radiation dose CT coronary angiography (CTCA) using sinogram affirmed iterative reconstruction (SAFIRE) compared with standard dose CTCA using filtered back-projection (FBP) in obese patients. Materials and methods: Seventy-eight consecutive obese patients were randomized into two groups and scanned using a prospectively ECG-triggered step-and-shot (SAS) CTCA protocol on a dual-source CT scanner. Thirty-nine patients (protocol A) were examined using a routine radiation dose protocol at 120 kV and images were reconstructed with FBP (protocol A). Thirty-nine patients (protocol B) were examined using a low dose protocol at 100 kV and images were reconstructed with SAFIRE. Two blinded observers independently assessed the image quality of each coronary segment using a 4-point scale (1 = non-diagnostic, 4 = excellent) and measured the objective parameters image noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). Radiation dose was calculated. Results: The coronary artery image quality scores, image noise, SNR and CNR were not significantly different between protocols A and B (all p > 0.05), with image quality scores of 3.51 ± 0.70 versus 3.55 ± 0.47, respectively. The effective radiation dose was significantly lower in protocol B (4.41 ± 0.83 mSv) than that in protocol A (8.83 ± 1.74 mSv, p < 0.01). Conclusion: Compared with standard dose CTCA using FBP, low dose CTCA using SAFIRE can maintain diagnostic image quality with 50% reduction of radiation dose.

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

International Nuclear Information System (INIS)

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

2014-01-01

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

Noise-induced effects in population dynamics

Science.gov (United States)

Spagnolo, Bernardo; Cirone, Markus; La Barbera, Antonino; de Pasquale, Ferdinando

2002-03-01

We investigate the role of noise in the nonlinear relaxation of two ecosystems described by generalized Lotka-Volterra equations in the presence of multiplicative noise. Specifically we study two cases: (i) an ecosystem with two interacting species in the presence of periodic driving; (ii) an ecosystem with a great number of interacting species with random interaction matrix. We analyse the interplay between noise and periodic modulation for case (i) and the role of the noise in the transient dynamics of the ecosystem in the presence of an absorbing barrier in case (ii). We find that the presence of noise is responsible for the generation of temporal oscillations and for the appearance of spatial patterns in the first case. In the other case we obtain the asymptotic behaviour of the time average of the ith population and discuss the effect of the noise on the probability distributions of the population and of the local field.

Comparison of analysis and experiment for dynamics of low-contact-ratio spur gears

Science.gov (United States)

Oswald, Fred B.; Rebbechi, Brian; Zakrajsek, James J.; Townsend, Dennis P.; Lin, Hsiang Hsi

1991-01-01

Low-contact-ratio spur gears were tested in NASA gear-noise-rig to study gear dynamics including dynamic load, tooth bending stress, vibration, and noise. The experimental results were compared with a NASA gear dynamics code to validate the code as a design tool for predicting transmission vibration and noise. Analytical predictions and experimental data for gear-tooth dynamic loads and tooth-root bending stress were compared at 28 operating conditions. Strain gage data were used to compute the normal load between meshing teeth and the bending stress at the tooth root for direct comparison with the analysis. The computed and measured waveforms for dynamic load and stress were compared for several test conditions. These are very similar in shape, which means the analysis successfully simulates the physical behavior of the test gears. The predicted peak value of the dynamic load agrees with the measurement results within an average error of 4.9 percent except at low-torque, high-speed conditions. Predictions of peak dynamic root stress are generally within 10 to 15 percent of the measured values.

CT urography in the urinary bladder: To compare excretory phase images using a low noise index and a high noise index with adaptive noise reduction filter

International Nuclear Information System (INIS)

Takeyama, Nobuyuki; Hayashi, Takaki; Ohgiya, Yoshimitsu

2011-01-01

Background: Although CT urography (CTU) is widely used for the evaluation of the entire urinary tract, the most important drawback is the radiation exposure. Purpose: To evaluate the effect of a noise reduction filter (NRF) using a phantom and to quantitatively and qualitatively compare excretory phase (EP) images using a low noise index (NI) with those using a high NI and postprocessing NRF (pNRF). Material and Methods: Each NI value was defined for a slice thickness of 5 mm, and reconstructed images with a slice thickness of 1.25 mm were assessed. Sixty patients who were at high risk of developing bladder tumors (BT) were divided into two groups according to whether their EP images were obtained using an NI of 9.88 (29 patients; group A) or an NI of 20 and pNRF (31 patients; group B). The CT dose index volume (CTDI vol ) and the contrast-to-noise ratio (CNR) of the bladder with respect to the anterior pelvic fat were compared in both groups. Qualitative assessment of the urinary bladder for image noise, sharpness, streak artifacts, homogeneity, and the conspicuity of polypoid or sessile-shaped BTs with a short-axis diameter greater than 10 mm was performed using a 3-point scale. Results: The phantom study showed noise reduction of approximately 40% and 76% dose reduction between group A and group B. CTDI vol demonstrated a 73% reduction in group B (4.6 ± 1.1 mGy) compared with group A (16.9 ± 3.4 mGy). The CNR value was not significantly different (P = 0.60) between group A (16.1 ± 5.1) and group B (16.6 ± 7.6). Although group A was superior (P < 0.01) to group B with regard to image noise, other qualitative analyses did not show significant differences. Conclusion: EP images using a high NI and pNRF were quantitatively and qualitatively comparable to those using a low NI, except with regard to image noise

SU-F-I-12: Region-Specific Dictionary Learning for Low-Dose X-Ray CT Reconstruction

International Nuclear Information System (INIS)

Xu, Q; Han, H; Xing, L

2016-01-01

Purpose: Dictionary learning based method has attracted more and more attentions in low-dose CT due to the superior performance on suppressing noise and preserving structural details. Considering the structures and noise vary from region to region in one imaging object, we propose a region-specific dictionary learning method to improve the low-dose CT reconstruction. Methods: A set of normal-dose images was used for dictionary learning. Segmentations were performed on these images, so that the training patch sets corresponding to different regions can be extracted out. After that, region-specific dictionaries were learned from these training sets. For the low-dose CT reconstruction, a conventional reconstruction, such as filtered back-projection (FBP), was performed firstly, and then segmentation was followed to segment the image into different regions. Sparsity constraints of each region based on its dictionary were used as regularization terms. The regularization parameters were selected adaptively according to different regions. A low-dose human thorax dataset was used to evaluate the proposed method. The single dictionary based method was performed for comparison. Results: Since the lung region is very different from the other part of thorax, two dictionaries corresponding to lung region and the rest part of thorax respectively were learned to better express the structural details and avoid artifacts. With only one dictionary some artifact appeared in the body region caused by the spot atoms corresponding to the structures in the lung region. And also some structure in the lung regions cannot be recovered well by only one dictionary. The quantitative indices of the result by the proposed method were also improved a little compared to the single dictionary based method. Conclusion: Region-specific dictionary can make the dictionary more adaptive to different region characteristics, which is much desirable for enhancing the performance of dictionary learning

SU-F-I-12: Region-Specific Dictionary Learning for Low-Dose X-Ray CT Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Xu, Q; Han, H; Xing, L [Stanford University School of Medicine, Stanford, CA (United States)

2016-06-15

Purpose: Dictionary learning based method has attracted more and more attentions in low-dose CT due to the superior performance on suppressing noise and preserving structural details. Considering the structures and noise vary from region to region in one imaging object, we propose a region-specific dictionary learning method to improve the low-dose CT reconstruction. Methods: A set of normal-dose images was used for dictionary learning. Segmentations were performed on these images, so that the training patch sets corresponding to different regions can be extracted out. After that, region-specific dictionaries were learned from these training sets. For the low-dose CT reconstruction, a conventional reconstruction, such as filtered back-projection (FBP), was performed firstly, and then segmentation was followed to segment the image into different regions. Sparsity constraints of each region based on its dictionary were used as regularization terms. The regularization parameters were selected adaptively according to different regions. A low-dose human thorax dataset was used to evaluate the proposed method. The single dictionary based method was performed for comparison. Results: Since the lung region is very different from the other part of thorax, two dictionaries corresponding to lung region and the rest part of thorax respectively were learned to better express the structural details and avoid artifacts. With only one dictionary some artifact appeared in the body region caused by the spot atoms corresponding to the structures in the lung region. And also some structure in the lung regions cannot be recovered well by only one dictionary. The quantitative indices of the result by the proposed method were also improved a little compared to the single dictionary based method. Conclusion: Region-specific dictionary can make the dictionary more adaptive to different region characteristics, which is much desirable for enhancing the performance of dictionary learning

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

International Nuclear Information System (INIS)

Pan Xiaochuan; Yu Lifeng

2003-01-01

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

Decoherence of coupled Josephson charge qubits due to partially correlated low-frequency noise

International Nuclear Information System (INIS)

Hu, Yong; Zhou, Zheng-Wei; Cai, Jian-Ming; Guo, Guang-Can

2007-01-01

Josephson charge qubits are promising candidates for scalable quantum computing. However, their performances are strongly degraded by decoherence due to low-frequency background noise, typically with a 1/f spectrum. In this paper, we investigate the decoherence process of two Cooper pair boxes (CPBs) coupled via a capacitor. Going beyond the common and uncorrelated noise models and the Bloch-Redfield formalism of previous works, we study the coupled system's quadratic dephasing under the condition of partially correlated noise sources. Based on reported experiments and generally accepted noise mechanisms, we introduce a reasonable assumption for the noise correlation, with which the calculation of multiqubit decoherence can be simplified to a problem on the single-qubit level. For the conventional Gaussian 1/f noise case, our results demonstrate that the quadratic dephasing rates are not very sensitive to the spatial correlation of the noises. Furthermore, we discuss the feasibility and efficiency of dynamical decoupling in the coupled CPBs

Signal Amplification Technique (SAT): an approach for improving resolution and reducing image noise in computed tomography

International Nuclear Information System (INIS)

Phelps, M.E.; Huang, S.C.; Hoffman, E.J.; Plummer, D.; Carson, R.

1981-01-01

Spatial resolution improvements in computed tomography (CT) have been limited by the large and unique error propagation properties of this technique. The desire to provide maximum image resolution has resulted in the use of reconstruction filter functions designed to produce tomographic images with resolution as close as possible to the intrinsic detector resolution. Thus, many CT systems produce images with excessive noise with the system resolution determined by the detector resolution rather than the reconstruction algorithm. CT is a rigorous mathematical technique which applies an increasing amplification to increasing spatial frequencies in the measured data. This mathematical approach to spatial frequency amplification cannot distinguish between signal and noise and therefore both are amplified equally. We report here a method in which tomographic resolution is improved by using very small detectors to selectively amplify the signal and not noise. Thus, this approach is referred to as the signal amplification technique (SAT). SAT can provide dramatic improvements in image resolution without increases in statistical noise or dose because increases in the cutoff frequency of the reconstruction algorithm are not required to improve image resolution. Alternatively, in cases where image counts are low, such as in rapid dynamic or receptor studies, statistical noise can be reduced by lowering the cutoff frequency while still maintaining the best possible image resolution. A possible system design for a positron CT system with SAT is described

Computational and human observer image quality evaluation of low dose, knowledge-based CT iterative reconstruction

Energy Technology Data Exchange (ETDEWEB)

Eck, Brendan L.; Fahmi, Rachid; Miao, Jun [Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 (United States); Brown, Kevin M.; Zabic, Stanislav; Raihani, Nilgoun [Philips Healthcare, Cleveland, Ohio 44143 (United States); Wilson, David L., E-mail: dlw@case.edu [Department of Biomedical Engineering, Case Western Reserve University, Cleveland, Ohio 44106 and Department of Radiology, Case Western Reserve University, Cleveland, Ohio 44106 (United States)

2015-10-15

Purpose: Aims in this study are to (1) develop a computational model observer which reliably tracks the detectability of human observers in low dose computed tomography (CT) images reconstructed with knowledge-based iterative reconstruction (IMR™, Philips Healthcare) and filtered back projection (FBP) across a range of independent variables, (2) use the model to evaluate detectability trends across reconstructions and make predictions of human observer detectability, and (3) perform human observer studies based on model predictions to demonstrate applications of the model in CT imaging. Methods: Detectability (d′) was evaluated in phantom studies across a range of conditions. Images were generated using a numerical CT simulator. Trained observers performed 4-alternative forced choice (4-AFC) experiments across dose (1.3, 2.7, 4.0 mGy), pin size (4, 6, 8 mm), contrast (0.3%, 0.5%, 1.0%), and reconstruction (FBP, IMR), at fixed display window. A five-channel Laguerre–Gauss channelized Hotelling observer (CHO) was developed with internal noise added to the decision variable and/or to channel outputs, creating six different internal noise models. Semianalytic internal noise computation was tested against Monte Carlo and used to accelerate internal noise parameter optimization. Model parameters were estimated from all experiments at once using maximum likelihood on the probability correct, P{sub C}. Akaike information criterion (AIC) was used to compare models of different orders. The best model was selected according to AIC and used to predict detectability in blended FBP-IMR images, analyze trends in IMR detectability improvements, and predict dose savings with IMR. Predicted dose savings were compared against 4-AFC study results using physical CT phantom images. Results: Detection in IMR was greater than FBP in all tested conditions. The CHO with internal noise proportional to channel output standard deviations, Model-k4, showed the best trade-off between fit

A low noise ASIC for two dimensional neutron gas detector with performance of high spatial resolution (Contract research)

International Nuclear Information System (INIS)

Yamagishi, Hideshi; Toh, Kentaro; Nakamura, Tatsuya; Sakasai, Kaoru; Soyama, Kazuhiko

2012-02-01

An ASD-ASIC (Amplifier-Shaper-Discriminator ASIC) with fast response and low noise performances has been designed for two-dimensional position sensitive neutron gas detectors (InSPaD). The InSPaD is a 2D neutron detector system with 3 He gas and provides a high spatial resolution by making distinction between proton and triton particles generated in the gas chamber. The new ASD-ASIC is required to have very low noise, a wide dynamic range, good output linearity and high counting rate. The new ASD-ASIC has been designed by using CMOS and consisted of 64-channel ASDs, a 16-channel multiplexer with LVTTL drivers and sum amplifier system for summing all analog signals. The performances were evaluated by the Spice simulation. It was confirmed that the new ASD-ASIC had very low noise performance, wide dynamic range and fast signal processing functions. (author)

Dynamic Error Analysis Method for Vibration Shape Reconstruction of Smart FBG Plate Structure

Directory of Open Access Journals (Sweden)

Hesheng Zhang

2016-01-01

Full Text Available Shape reconstruction of aerospace plate structure is an important issue for safe operation of aerospace vehicles. One way to achieve such reconstruction is by constructing smart fiber Bragg grating (FBG plate structure with discrete distributed FBG sensor arrays using reconstruction algorithms in which error analysis of reconstruction algorithm is a key link. Considering that traditional error analysis methods can only deal with static data, a new dynamic data error analysis method are proposed based on LMS algorithm for shape reconstruction of smart FBG plate structure. Firstly, smart FBG structure and orthogonal curved network based reconstruction method is introduced. Then, a dynamic error analysis model is proposed for dynamic reconstruction error analysis. Thirdly, the parameter identification is done for the proposed dynamic error analysis model based on least mean square (LMS algorithm. Finally, an experimental verification platform is constructed and experimental dynamic reconstruction analysis is done. Experimental results show that the dynamic characteristics of the reconstruction performance for plate structure can be obtained accurately based on the proposed dynamic error analysis method. The proposed method can also be used for other data acquisition systems and data processing systems as a general error analysis method.

High-Tc Superconducting Bolometer Noise Measurement Using Low Noise Transformers - Theory and Optimization

Science.gov (United States)

Aslam, Shahid; Jones, Hollis H.

2011-01-01

Care must always be taken when performing noise measurements on high-Tc superconducting materials to ensure that the results are not from the measurement system itself. One situation likely to occur is with low noise transformers. One of the least understood devices, it provides voltage gain for low impedance inputs (< 100 ), e.g., YBaCuO and GdBaCuO thin films, with comparatively lower noise levels than other devices for instance field effect and bipolar junction transistors. An essential point made in this paper is that because of the complex relationships between the transformer ports, input impedance variance alters the transformer s transfer function in particular, the low frequency cutoff shift. The transfer of external and intrinsic transformer noise to the output along with optimization and precautions are treated; all the while, we will cohesively connect the transfer function shift, the load impedance, and the actual noise at the transformer output.

Optimization of number and signal to noise ratio radiographs for defects 3D reconstruction in industrial control

International Nuclear Information System (INIS)

Bruandet, J.-P.

2001-01-01

Among numerous techniques for non-destructive evaluation (NOE), X-rays systems are well suited to inspect inner objects. Acquiring several radiographs of inspected objects under different points of view enables to recover a three dimensional structural information. In this NOE application, a tomographic testing is considered. This work deals with two tomographic testing optimizations in order to improve the characterization of defects that may occur into metallic welds. The first one consists in the optimization of the acquisition strategy. Because tomographic testing is made on-line, the total duration for image acquisition is fixed, limiting the number of available views. Hence, for a given acquisition duration, it is possible either to acquire a very limited number of radiographs with a good signal to noise ratio in each single acquisition or a larger number of radiographs with a limited signal to noise ratio. The second one consists in optimizing the 3D reconstruction algorithms from a limited number of cone-beam projections. To manage the lack of data, we first used algebraic reconstruction algorithms such as ART or regularized ICM. In terms of acquisition strategy optimization, an increase of the number of projections was proved to be valuable. Taking into account specific prior knowledge such as support constraint or physical noise model in attenuation images also improved reconstruction quality. Then, a new regularized region based reconstruction approach was developed. Defects to reconstruct are binary (lack of material in a homogeneous object). As a consequence, they are entirely described by their shapes. Because the number of defects to recover is unknown and is totally arbitrary, a level set formulation allowing handling topological changes was used. Results obtained with a regularized level-set reconstruction algorithm are optimistic in the proposed context. (author) [fr

Dynamic beam filtering for miscentered patients.

Science.gov (United States)

Mao, Andrew; Shyr, William; Gang, Grace J; Stayman, J Webster

2018-02-01

Accurate centering of the patient within the bore of a CT scanner takes time and is often difficult to achieve precisely. Patient miscentering can result in significant dose and image noise penalties with the use of traditional bowtie filters. This work describes a system to dynamically position an x-ray beam filter during image acquisition to enable more consistent image performance and potentially lower dose needed for CT imaging. We propose a new approach in which two orthogonal low-dose scout images are used to estimate a parametric model of the object describing its shape, size, and location within the field of view (FOV). This model is then used to compute an optimal filter motion profile by minimizing the variance of the expected detector fluence for each projection. Dynamic filtration was implemented on a cone-beam CT (CBCT) test bench using two different physical filters: 1) an aluminum bowtie and 2) a structured binary filter called a multiple aperture device (MAD). Dynamic filtration performance was compared to a static filter in studies of dose and reconstruction noise as a function of the degree of miscentering of a homogeneous water phantom. Estimated filter trajectories were found to be largely sinusoidal with an amplitude proportional to the amount of miscentering. Dynamic filtration demonstrated an improved ability to keep the spatial distribution of dose and reconstruction noise at baseline levels across varying levels of miscentering, reducing the maximum noise and dose deviation from 53% to 15% and 42% to 14% respectively for the bowtie filter, and 25% to 8% and 24% to 15% respectively for the MAD filter. Dynamic positioning of beam filters during acquisition improves dose utilization and image quality over static filters for miscentered patients. Such dynamic filters relax positioning requirements and have the potential to reduce set-up time and lower dose requirements.

Low-Noise CMOS Circuits for On-Chip Signal Processing in Focal-Plane Arrays

Science.gov (United States)

Pain, Bedabrata

The performance of focal-plane arrays can be significantly enhanced through the use of on-chip signal processing. Novel, in-pixel, on-focal-plane, analog signal-processing circuits for high-performance imaging are presented in this thesis. The presence of a high background-radiation is a major impediment for infrared focal-plane array design. An in-pixel, background-suppression scheme, using dynamic analog current memory circuit, is described. The scheme also suppresses spatial noise that results from response non-uniformities of photo-detectors, leading to background limited infrared detector readout performance. Two new, low-power, compact, current memory circuits, optimized for operation at ultra-low current levels required in infrared-detection, are presented. The first one is a self-cascading current memory that increases the output impedance, and the second one is a novel, switch feed-through reducing current memory, implemented using error-current feedback. This circuit can operate with a residual absolute -error of less than 0.1%. The storage-time of the memory is long enough to also find applications in neural network circuits. In addition, a voltage-mode, accurate, low-offset, low-power, high-uniformity, random-access sample-and-hold cell, implemented using a CCD with feedback, is also presented for use in background-suppression and neural network applications. A new, low noise, ultra-low level signal readout technique, implemented by individually counting photo-electrons within the detection pixel, is presented. The output of each unit-cell is a digital word corresponding to the intensity of the photon flux, and the readout is noise free. This technique requires the use of unit-cell amplifiers that feature ultra-high-gain, low-power, self-biasing capability and noise in sub-electron levels. Both single-input and differential-input implementations of such amplifiers are investigated. A noise analysis technique is presented for analyzing sampled

Unveiling the development of intracranial injury using dynamic brain EIT: an evaluation of current reconstruction algorithms.

Science.gov (United States)

Li, Haoting; Chen, Rongqing; Xu, Canhua; Liu, Benyuan; Tang, Mengxing; Yang, Lin; Dong, Xiuzhen; Fu, Feng

2017-08-21

Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.

Dynamical noise filter and conditional entropy analysis in chaos synchronization.

Science.gov (United States)

Wang, Jiao; Lai, C-H

2006-06-01

It is shown that, in a chaotic synchronization system whose driving signal is exposed to channel noise, the estimation of the drive system states can be greatly improved by applying the dynamical noise filtering to the response system states. If the noise is bounded in a certain range, the estimation errors, i.e., the difference between the filtered responding states and the driving states, can be made arbitrarily small. This property can be used in designing an alternative digital communication scheme. An analysis based on the conditional entropy justifies the application of dynamical noise filtering in generating quality synchronization.

Improving Filtered Backprojection Reconstruction by Data-Dependent Filtering

NARCIS (Netherlands)

D.M. Pelt (Daniël); K.J. Batenburg (Joost)

2014-01-01

htmlabstractFiltered backprojection, one of the most widely used reconstruction methods in tomography, requires a large number of low-noise projections to yield accurate reconstructions. In many applications of tomography, complete projection data of high quality cannot be obtained, because of

Estimating the level of dynamical noise in time series by using fractal dimensions

Energy Technology Data Exchange (ETDEWEB)

Sase, Takumi, E-mail: sase@sat.t.u-tokyo.ac.jp [Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 153-8505 (Japan); Ramírez, Jonatán Peña [CONACYT Research Fellow, Center for Scientific Research and Higher Education at Ensenada (CICESE), Carretera Ensenada-Tijuana No. 3918, Zona Playitas, C.P. 22860, Ensenada, Baja California (Mexico); Kitajo, Keiichi [BSI-Toyota Collaboration Center, RIKEN Brain Science Institute, Wako, Saitama 351-0198 (Japan); Aihara, Kazuyuki; Hirata, Yoshito [Graduate School of Information Science and Technology, The University of Tokyo, Tokyo 153-8505 (Japan); Institute of Industrial Science, The University of Tokyo, Tokyo 153-8505 (Japan)

2016-03-11

We present a method for estimating the dynamical noise level of a ‘short’ time series even if the dynamical system is unknown. The proposed method estimates the level of dynamical noise by calculating the fractal dimensions of the time series. Additionally, the method is applied to EEG data to demonstrate its possible effectiveness as an indicator of temporal changes in the level of dynamical noise. - Highlights: • A dynamical noise level estimator for time series is proposed. • The estimator does not need any information about the dynamics generating the time series. • The estimator is based on a novel definition of time series dimension (TSD). • It is demonstrated that there exists a monotonic relationship between the • TSD and the level of dynamical noise. • We apply the proposed method to human electroencephalographic data.

Estimating the level of dynamical noise in time series by using fractal dimensions

International Nuclear Information System (INIS)

Sase, Takumi; Ramírez, Jonatán Peña; Kitajo, Keiichi; Aihara, Kazuyuki; Hirata, Yoshito

2016-01-01

We present a method for estimating the dynamical noise level of a ‘short’ time series even if the dynamical system is unknown. The proposed method estimates the level of dynamical noise by calculating the fractal dimensions of the time series. Additionally, the method is applied to EEG data to demonstrate its possible effectiveness as an indicator of temporal changes in the level of dynamical noise. - Highlights: • A dynamical noise level estimator for time series is proposed. • The estimator does not need any information about the dynamics generating the time series. • The estimator is based on a novel definition of time series dimension (TSD). • It is demonstrated that there exists a monotonic relationship between the • TSD and the level of dynamical noise. • We apply the proposed method to human electroencephalographic data.

Effects of noise on convergent game-learning dynamics

International Nuclear Information System (INIS)

Sanders, James B T; Galla, Tobias; Shapiro, Jonathan L

2012-01-01

We study stochastic effects on the lagging anchor dynamics, a reinforcement learning algorithm used to learn successful strategies in iterated games, which is known to converge to Nash points in the absence of noise. The dynamics is stochastic when players only have limited information about their opponents’ strategic propensities. The effects of this noise are studied analytically in the case where it is small but finite, and we show that the statistics and correlation properties of fluctuations can be computed to a high accuracy. We find that the system can exhibit quasicycles, driven by intrinsic noise. If players are asymmetric and use different parameters for their learning, a net payoff advantage can be achieved due to these stochastic oscillations around the deterministic equilibrium. (paper)

Image quality at low tube voltage (70 kV) and sinogram-affirmed iterative reconstruction for computed tomography in infants with congenital heart disease

International Nuclear Information System (INIS)

Nakagawa, Motoo; Ozawa, Yoshiyuki; Sakurai, Keita; Shimohira, Masashi; Shibamoto, Yuta; Ohashi, Kazuya; Asano, Miki; Yamaguchi, Sachiko

2015-01-01

Lower tube voltage has advantages for CT angiography, such as improved contrast To evaluate the image quality of low-voltage (70 kV) CT for congenital heart disease and the ability of sinogram-affirmed iterative reconstruction to improve image quality. Forty-six children with congenital heart disease (median age: 109 days) were examined using dual-source CT. Scans were performed at 80 kV and 70 kV in 21 and 25 children, respectively. A nonionic iodinated contrast medium (300 mg I/ml) was used for the 80-kV protocol. The contrast medium was diluted to 75% (225 mgI/mL) with saline for the 70-kV protocol. Image noise was measured in the two protocols for each group by extracting the standard deviations of a region of interest placed on the descending aorta. We then determined whether sinogram-affirmed iterative reconstruction reduced the image noise at 70 kV. There was more noise at 70 kV than at 80 kV (29 ± 12 vs 20 ± 4.8; P < 0.01). Sinogram-affirmed iterative reconstruction with grade 4 strength settings improved the noise (20 ± 5.9; P < 0.01) for the 70-kV group. Sinogram-affirmed iterative reconstruction improved the image quality of CT in congenital heart disease. (orig.)

Image quality at low tube voltage (70 kV) and sinogram-affirmed iterative reconstruction for computed tomography in infants with congenital heart disease

Energy Technology Data Exchange (ETDEWEB)

Nakagawa, Motoo; Ozawa, Yoshiyuki; Sakurai, Keita; Shimohira, Masashi; Shibamoto, Yuta [Nagoya City University Graduate School of Medical Sciences, Department of Radiology, Nagoya (Japan); Ohashi, Kazuya [Nagoya City University Hospital, Division of Central Radiology, Nagoya (Japan); Asano, Miki [Nagoya City University Graduate School of Medical Sciences, Department of Cardiovascular Surgery, Nagoya (Japan); Yamaguchi, Sachiko [Nagoya City University Graduate School of Medical Sciences, Department of Pediatrics and Neonatology, Nagoya (Japan)

2015-09-15

Lower tube voltage has advantages for CT angiography, such as improved contrast To evaluate the image quality of low-voltage (70 kV) CT for congenital heart disease and the ability of sinogram-affirmed iterative reconstruction to improve image quality. Forty-six children with congenital heart disease (median age: 109 days) were examined using dual-source CT. Scans were performed at 80 kV and 70 kV in 21 and 25 children, respectively. A nonionic iodinated contrast medium (300 mg I/ml) was used for the 80-kV protocol. The contrast medium was diluted to 75% (225 mgI/mL) with saline for the 70-kV protocol. Image noise was measured in the two protocols for each group by extracting the standard deviations of a region of interest placed on the descending aorta. We then determined whether sinogram-affirmed iterative reconstruction reduced the image noise at 70 kV. There was more noise at 70 kV than at 80 kV (29 ± 12 vs 20 ± 4.8; P < 0.01). Sinogram-affirmed iterative reconstruction with grade 4 strength settings improved the noise (20 ± 5.9; P < 0.01) for the 70-kV group. Sinogram-affirmed iterative reconstruction improved the image quality of CT in congenital heart disease. (orig.)

Computed Tomography Image Quality Evaluation of a New Iterative Reconstruction Algorithm in the Abdomen (Adaptive Statistical Iterative Reconstruction-V) a Comparison With Model-Based Iterative Reconstruction, Adaptive Statistical Iterative Reconstruction, and Filtered Back Projection Reconstructions.

Science.gov (United States)

Goodenberger, Martin H; Wagner-Bartak, Nicolaus A; Gupta, Shiva; Liu, Xinming; Yap, Ramon Q; Sun, Jia; Tamm, Eric P; Jensen, Corey T

The purpose of this study was to compare abdominopelvic computed tomography images reconstructed with adaptive statistical iterative reconstruction-V (ASIR-V) with model-based iterative reconstruction (Veo 3.0), ASIR, and filtered back projection (FBP). Abdominopelvic computed tomography scans for 36 patients (26 males and 10 females) were reconstructed using FBP, ASIR (80%), Veo 3.0, and ASIR-V (30%, 60%, 90%). Mean ± SD patient age was 32 ± 10 years with mean ± SD body mass index of 26.9 ± 4.4 kg/m. Images were reviewed by 2 independent readers in a blinded, randomized fashion. Hounsfield unit, noise, and contrast-to-noise ratio (CNR) values were calculated for each reconstruction algorithm for further comparison. Phantom evaluation of low-contrast detectability (LCD) and high-contrast resolution was performed. Adaptive statistical iterative reconstruction-V 30%, ASIR-V 60%, and ASIR 80% were generally superior qualitatively compared with ASIR-V 90%, Veo 3.0, and FBP (P ASIR-V 60% with respective CNR values of 5.54 ± 2.39, 8.78 ± 3.15, and 3.49 ± 1.77 (P ASIR 80% had the best and worst spatial resolution, respectively. Adaptive statistical iterative reconstruction-V 30% and ASIR-V 60% provided the best combination of qualitative and quantitative performance. Adaptive statistical iterative reconstruction 80% was equivalent qualitatively, but demonstrated inferior spatial resolution and LCD.

Denoising multicriterion iterative reconstruction in emission spectral tomography

Science.gov (United States)

Wan, Xiong; Yin, Aihan

2007-03-01

In the study of optical testing, the computed tomogaphy technique has been widely adopted to reconstruct three-dimensional distributions of physical parameters of various kinds of fluid fields, such as flame, plasma, etc. In most cases, projection data are often stained by noise due to environmental disturbance, instrumental inaccuracy, and other random interruptions. To improve the reconstruction performance in noisy cases, an algorithm that combines a self-adaptive prefiltering denoising approach (SPDA) with a multicriterion iterative reconstruction (MCIR) is proposed and studied. First, the level of noise is approximately estimated with a frequency domain statistical method. Then the cutoff frequency of a Butterworth low-pass filter was established based on the evaluated noise energy. After the SPDA processing, the MCIR algorithm was adopted for limited-view optical computed tomography reconstruction. Simulated reconstruction of two test phantoms and a flame emission spectral tomography experiment were employed to evaluate the performance of SPDA-MCIR in noisy cases. Comparison with some traditional methods and experiment results showed that the SPDA-MCIR combination had obvious improvement in the case of noisy data reconstructions.

Challenges and limitations in retrofitting facilities for low frequency noise

Energy Technology Data Exchange (ETDEWEB)

Wierzba, P. [ATCO Noise Management, Calgary, AB (Canada)

2007-07-01

The trend to revise and increase environmental regulations regarding low frequency noise emissions from oil and gas facilities was discussed. Noise related complaints can often be traced to low frequency noise, which is the unwanted sound with a frequency range falling within 31.5-Hz, 63-Hz, and 125-Hz octave bands. This paper also discussed the challenges and limitations of field retrofits of the facilities aimed at reducing low frequency noise. The main sources of low frequency noise associated with a compression facility are the radiator cooler, engine exhaust and the building envelope. Regulators are paying close attention not only to the overall noise exposure as measured by the A-weighted levels, but also to the quality of noise emitted by the particular frequency spectrum. The Alberta Energy and Utilities Board recently issued Noise Control Directive 38 and made it a requirement to perform low frequency noise impact assessment for permitting of all new energy facilities. Under Directive 38, the low frequency noise assessment is to be performed using the C-weighted scale as a measure in addition to the previously used A-weighted scale. Directive 38 recommends that in order to avoid low frequency noise problems the difference between the C-weighted and A-weighted levels at the residential locations should be lower than 20 dB. This implies that noise should be limited to 60 dBC for Category 1 residences of low dwelling density. Small upgrades and changes can be made to lower low frequency noise emissions. These may include upgrading building wall insulation, providing wall-to-skid isolation system, upgrading the fan blades, or reducing the rpm of the fans. It was concluded that these upgrades should be considered for facilities in close proximity to residential areas. 3 refs., 2 tabs., 7 figs.

Low-frequency excess flux noise in superconducting devices

Energy Technology Data Exchange (ETDEWEB)

Kempf, Sebastian; Ferring, Anna; Fleischmann, Andreas; Enss, Christian [Kirchhoff-Institute for Physics, Heidelberg University (Germany)

2016-07-01

Low-frequency noise is a rather universal phenomenon and appears in physical, chemical, biological or even economical systems. However, there is often very little known about the underlying processes leading to its occurrence. In particular, the origin of low-frequency excess flux noise in superconducting devices has been an unresolved puzzle for many decades. Its existence limits, for example, the coherence time of superconducting quantum bits or makes high-precision measurements of low-frequency signals using SQUIDs rather challenging. Recent experiments suggest that low-frequency excess flux noise in Josephson junction based devices might be caused by the random reversal of interacting spins in surface layer oxides and in the superconductor-substrate interface. Even if it turns out to be generally correct, the underlying physical processes, i.e. the origin of these spins, their physical nature as well as the interaction mechanisms, have not been resolved so far. In this contribution we discuss recent measurements of low-frequency SQUID noise which we performed to investigate the origin of low-frequency excess flux noise in superconducting devices. Within this context we give an overview of our measurement techniques and link our data with present theoretical models and literature data.

CT of the chest with model-based, fully iterative reconstruction: comparison with adaptive statistical iterative reconstruction.

Science.gov (United States)

Ichikawa, Yasutaka; Kitagawa, Kakuya; Nagasawa, Naoki; Murashima, Shuichi; Sakuma, Hajime

2013-08-09

The recently developed model-based iterative reconstruction (MBIR) enables significant reduction of image noise and artifacts, compared with adaptive statistical iterative reconstruction (ASIR) and filtered back projection (FBP). The purpose of this study was to evaluate lesion detectability of low-dose chest computed tomography (CT) with MBIR in comparison with ASIR and FBP. Chest CT was acquired with 64-slice CT (Discovery CT750HD) with standard-dose (5.7 ± 2.3 mSv) and low-dose (1.6 ± 0.8 mSv) conditions in 55 patients (aged 72 ± 7 years) who were suspected of lung disease on chest radiograms. Low-dose CT images were reconstructed with MBIR, ASIR 50% and FBP, and standard-dose CT images were reconstructed with FBP, using a reconstructed slice thickness of 0.625 mm. Two observers evaluated the image quality of abnormal lung and mediastinal structures on a 5-point scale (Score 5 = excellent and score 1 = non-diagnostic). The objective image noise was also measured as the standard deviation of CT intensity in the descending aorta. The image quality score of enlarged mediastinal lymph nodes on low-dose MBIR CT (4.7 ± 0.5) was significantly improved in comparison with low-dose FBP and ASIR CT (3.0 ± 0.5, p = 0.004; 4.0 ± 0.5, p = 0.02, respectively), and was nearly identical to the score of standard-dose FBP image (4.8 ± 0.4, p = 0.66). Concerning decreased lung attenuation (bulla, emphysema, or cyst), the image quality score on low-dose MBIR CT (4.9 ± 0.2) was slightly better compared to low-dose FBP and ASIR CT (4.5 ± 0.6, p = 0.01; 4.6 ± 0.5, p = 0.01, respectively). There were no significant differences in image quality scores of visualization of consolidation or mass, ground-glass attenuation, or reticular opacity among low- and standard-dose CT series. Image noise with low-dose MBIR CT (11.6 ± 1.0 Hounsfield units (HU)) were significantly lower than with low-dose ASIR (21.1 ± 2.6 HU, p standard-dose FBP CT (16.6 ± 2.3 HU, p 70%, MBIR can provide

Passive detection and localization of fatigue cracking in aluminum plates using Green's function reconstruction from ambient noise.

Science.gov (United States)

Yang, Yang; Xiao, Li; Qu, Wenzhong; Lu, Ye

2017-11-01

Recent theoretical and experimental studies have demonstrated that a local Green's function can be retrieved from the cross-correlation of ambient noise field. This technique can be used to detect fatigue cracking in metallic structures, owing to the fact that the presence of crack can lead to a change in Green's function. This paper presents a method of structural fatigue cracking characterization method by measuring Green's function reconstruction from noise excitation and verifies the feasibility of crack detection in poor noise source distribution. Fatigue cracks usually generate nonlinear effects, in which different wave amplitudes and frequency compositions can cause different nonlinear responses. This study also undertakes analysis of the capacity of the proposed approach to identify fatigue cracking under different noise amplitudes and frequency ranges. Experimental investigations of an aluminum plate are conducted to assess the cross-correlations of received noise between sensor pairs and finally to detect the introduced fatigue crack. A damage index is proposed according to the variation between cross-correlations obtained from the pristine crack closed state and the crack opening-closure state when sufficient noise amplitude is used to generate nonlinearity. A probability distribution map of damage is calculated based on damage indices. The fatigue crack introduced in the aluminum plate is successfully identified and oriented, verifying that a fatigue crack can be detected by reconstructing Green's functions from an imperfect diffuse field in which ambient noise sources exist locally. Copyright © 2017 Elsevier B.V. All rights reserved.

Dynamic dual-tracer PET reconstruction.

Science.gov (United States)

Gao, Fei; Liu, Huafeng; Jian, Yiqiang; Shi, Pengcheng

2009-01-01

Although of important medical implications, simultaneous dual-tracer positron emission tomography reconstruction remains a challenging problem, primarily because the photon measurements from dual tracers are overlapped. In this paper, we propose a simultaneous dynamic dual-tracer reconstruction of tissue activity maps based on guidance from tracer kinetics. The dual-tracer reconstruction problem is formulated in a state-space representation, where parallel compartment models serve as continuous-time system equation describing the tracer kinetic processes of dual tracers, and the imaging data is expressed as discrete sampling of the system states in measurement equation. The image reconstruction problem has therefore become a state estimation problem in a continuous-discrete hybrid paradigm, and H infinity filtering is adopted as the estimation strategy. As H infinity filtering makes no assumptions on the system and measurement statistics, robust reconstruction results can be obtained for the dual-tracer PET imaging system where the statistical properties of measurement data and system uncertainty are not available a priori, even when there are disturbances in the kinetic parameters. Experimental results on digital phantoms, Monte Carlo simulations and physical phantoms have demonstrated the superior performance.

Combining automatic tube current modulation with adaptive statistical iterative reconstruction for low-dose chest CT screening.

Directory of Open Access Journals (Sweden)

Jiang-Hong Chen

Full Text Available To reduce radiation dose while maintaining image quality in low-dose chest computed tomography (CT by combining adaptive statistical iterative reconstruction (ASIR and automatic tube current modulation (ATCM.Patients undergoing cancer screening (n = 200 were subjected to 64-slice multidetector chest CT scanning with ASIR and ATCM. Patients were divided into groups 1, 2, 3, and 4 (n = 50 each, with a noise index (NI of 15, 20, 30, and 40, respectively. Each image set was reconstructed with 4 ASIR levels (0% ASIR, 30% ASIR, 50% ASIR, and 80% ASIR in each group. Two radiologists assessed subjective image noise, image artifacts, and visibility of the anatomical structures. Objective image noise and signal-to-noise ratio (SNR were measured, and effective dose (ED was recorded.Increased NI was associated with increased subjective and objective image noise results (P<0.001, and SNR decreased with increasing NI (P<0.001. These values improved with increased ASIR levels (P<0.001. Images from all 4 groups were clinically diagnosable. Images with NI = 30 and 50% ASIR had average subjective image noise scores and nearly average anatomical structure visibility scores, with a mean objective image noise of 23.42 HU. The EDs for groups 1, 2, 3 and 4 were 2.79 ± 1.17, 1.69 ± 0.59, 0.74 ± 0.29, and 0.37 ± 0.22 mSv, respectively. Compared to group 1 (NI = 15, the ED reductions were 39.43%, 73.48%, and 86.74% for groups 2, 3, and 4, respectively.Using NI = 30 with 50% ASIR in the chest CT protocol, we obtained average or above-average image quality but a reduced ED.

Qualitative criteria and thresholds for low noise asphalt mixture design

Science.gov (United States)

Vaitkus, A.; Andriejauskas, T.; Gražulytė, J.; Šernas, O.; Vorobjovas, V.; Kleizienė, R.

2018-05-01

Low noise asphalt pavements are cost efficient and cost effective alternative for road traffic noise mitigation comparing with noise barriers, façade insulation and other known noise mitigation measures. However, design of low noise asphalt mixtures strongly depends on climate and traffic peculiarities of different regions. Severe climate regions face problems related with short durability of low noise asphalt mixtures in terms of considerable negative impact of harsh climate conditions (frost-thaw, large temperature fluctuations, hydrological behaviour, etc.) and traffic (traffic loads, traffic volumes, studded tyres, etc.). Thus there is a need to find balance between mechanical and acoustical durability as well as to ensure adequate pavement skid resistance for road safety purposes. Paper presents analysis of the qualitative criteria and design parameters thresholds of low noise asphalt mixtures. Different asphalt mixture composition materials (grading, aggregate, binder, additives, etc.) and relevant asphalt layer properties (air void content, texture, evenness, degree of compaction, etc.) were investigated and assessed according their suitability for durable and effective low noise pavements. Paper concluded with the overview of requirements, qualitative criteria and thresholds for low noise asphalt mixture design for severe climate regions.

A computationally efficient OMP-based compressed sensing reconstruction for dynamic MRI

International Nuclear Information System (INIS)

Usman, M; Prieto, C; Schaeffter, T; Batchelor, P G; Odille, F; Atkinson, D

2011-01-01

Compressed sensing (CS) methods in MRI are computationally intensive. Thus, designing novel CS algorithms that can perform faster reconstructions is crucial for everyday applications. We propose a computationally efficient orthogonal matching pursuit (OMP)-based reconstruction, specifically suited to cardiac MR data. According to the energy distribution of a y-f space obtained from a sliding window reconstruction, we label the y-f space as static or dynamic. For static y-f space images, a computationally efficient masked OMP reconstruction is performed, whereas for dynamic y-f space images, standard OMP reconstruction is used. The proposed method was tested on a dynamic numerical phantom and two cardiac MR datasets. Depending on the field of view composition of the imaging data, compared to the standard OMP method, reconstruction speedup factors ranging from 1.5 to 2.5 are achieved. (note)

Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom

International Nuclear Information System (INIS)

Ryu, Young Jin; Choi, Young Hun; Cheon, Jung-Eun; Kim, Woo Sun; Kim, In-One; Ha, Seongmin

2016-01-01

CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT. To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection. We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose 4 , levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire. With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose 4 levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose 4 level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm. Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose 4 obtained at 1.81 mSv. (orig.)

Knowledge-based iterative model reconstruction: comparative image quality and radiation dose with a pediatric computed tomography phantom.

Science.gov (United States)

Ryu, Young Jin; Choi, Young Hun; Cheon, Jung-Eun; Ha, Seongmin; Kim, Woo Sun; Kim, In-One

2016-03-01

CT of pediatric phantoms can provide useful guidance to the optimization of knowledge-based iterative reconstruction CT. To compare radiation dose and image quality of CT images obtained at different radiation doses reconstructed with knowledge-based iterative reconstruction, hybrid iterative reconstruction and filtered back-projection. We scanned a 5-year anthropomorphic phantom at seven levels of radiation. We then reconstructed CT data with knowledge-based iterative reconstruction (iterative model reconstruction [IMR] levels 1, 2 and 3; Philips Healthcare, Andover, MA), hybrid iterative reconstruction (iDose(4), levels 3 and 7; Philips Healthcare, Andover, MA) and filtered back-projection. The noise, signal-to-noise ratio and contrast-to-noise ratio were calculated. We evaluated low-contrast resolutions and detectability by low-contrast targets and subjective and objective spatial resolutions by the line pairs and wire. With radiation at 100 peak kVp and 100 mAs (3.64 mSv), the relative doses ranged from 5% (0.19 mSv) to 150% (5.46 mSv). Lower noise and higher signal-to-noise, contrast-to-noise and objective spatial resolution were generally achieved in ascending order of filtered back-projection, iDose(4) levels 3 and 7, and IMR levels 1, 2 and 3, at all radiation dose levels. Compared with filtered back-projection at 100% dose, similar noise levels were obtained on IMR level 2 images at 24% dose and iDose(4) level 3 images at 50% dose, respectively. Regarding low-contrast resolution, low-contrast detectability and objective spatial resolution, IMR level 2 images at 24% dose showed comparable image quality with filtered back-projection at 100% dose. Subjective spatial resolution was not greatly affected by reconstruction algorithm. Reduced-dose IMR obtained at 0.92 mSv (24%) showed similar image quality to routine-dose filtered back-projection obtained at 3.64 mSv (100%), and half-dose iDose(4) obtained at 1.81 mSv.

Low-frequency 1/f noise in graphene devices

Science.gov (United States)

Balandin, Alexander A.

2013-08-01

Low-frequency noise with a spectral density that depends inversely on frequency has been observed in a wide variety of systems including current fluctuations in resistors, intensity fluctuations in music and signals in human cognition. In electronics, the phenomenon, which is known as 1/f noise, flicker noise or excess noise, hampers the operation of numerous devices and circuits, and can be a significant impediment to the development of practical applications from new materials. Graphene offers unique opportunities for studying 1/f noise because of its two-dimensional structure and widely tunable two-dimensional carrier concentration. The creation of practical graphene-based devices will also depend on our ability to understand and control the low-frequency noise in this material system. Here, the characteristic features of 1/f noise in graphene and few-layer graphene are reviewed, and the implications of such noise for the development of graphene-based electronics including high-frequency devices and sensors are examined.

Dynamic X-ray computed tomography; Tomographie dynamique a rayons X

Energy Technology Data Exchange (ETDEWEB)

Grangeat, P

2003-07-01

Paper Dynamic computed tomography (CT) imaging aims at reconstructing image sequences where the dynamic nature of the living human body is of primary interest. Main concerned applications are image-guided interventional procedures, functional studies and cardiac imaging. The introduction of ultra-fast rotating gantries along with multi-row detectors and in near future area detectors allows a huge progress toward the imaging of moving organs with low-contrast resolution. This paper gives an overview of the different concepts used in dynamic CT. A new reconstruction algorithm based on a voxel-specific dynamic evolution compensation is also presented. It provides four-dimensional image sequences with accurate spatio-temporal information, where each frame is reconstructed using a long-scan acquisition mode on several half-turns. In the same time, this technique permits to reduce the dose delivered per rotation while keeping the same signal to noise ratio for every frame using an adaptive motion-compensated temporal averaging. Results are illustrated on simulated data. (authors)

Dose and image quality in low-dose CT for urinary stone disease: added value of automatic tube current modulation and iterative reconstruction techniques

International Nuclear Information System (INIS)

Soenen, Olivier; Balliauw, Christophe; Oyen, Raymond; Zanca, Federica

2017-01-01

The aim of this study was to compare dose and image quality (IQ) of a baseline low-dose computed tomography (CT) (fix mAs) vs. an ultra-low-dose CT (automatic tube current modulation, ATCM) in patients with suspected urinary stone disease and to assess the added value of iterative reconstruction. CT examination was performed on 193 patients (103 baseline low-dose, 90 ultra-low-dose). Filtered back projection (FBP) was used for both protocols, and Sinogram Affirmed Iterative Reconstruction (SAFIRE) was used for the ultra-low-dose protocol only. Dose and ureter stones information were collected for both protocols. Subjective IQ was assessed by two radiologists scoring noise, visibility of the ureter and overall IQ. Objective IQ (contrast-to-noise ratio, CNR) was assessed for the ultra-low-dose protocol only (FBP and SAFIRE). The ultra-low-dose protocol (ATCM) showed a 22% decrease in mean effective dose ( p < 0.001) and improved visibility of the pelvic ureter (p = 0.02). CNR was higher for SAFIRE (p < 0.0001). SAFIRE improves the objective IQ, but not the subjective IQ for the chosen clinical task. (authors)

Low noise monolithic CMOS front end electronics

International Nuclear Information System (INIS)

Lutz, G.; Bergmann, H.; Holl, P.; Manfredi, P.F.

1987-01-01

Design considerations for low noise charge measurement and their application in CMOS electronics are described. The amplifier driver combination whose noise performance has been measured in detail as well as the analog multiplexing silicon strip detector readout electronics are designed with low power consumption and can be operated in pulsed mode so as to reduce heat dissipation even further in many applications. (orig.)

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN

Directory of Open Access Journals (Sweden)

Rosa Ma Alsina-Pagès

2018-04-01

Full Text Available One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE unrelated to road traffic (sirens, horns, people, etc. should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED. In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap and low-capacity (Lo-Cap sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 1 6 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%. However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.

Detection of Anomalous Noise Events on Low-Capacity Acoustic Nodes for Dynamic Road Traffic Noise Mapping within an Hybrid WASN.

Science.gov (United States)

Alsina-Pagès, Rosa Ma; Alías, Francesc; Socoró, Joan Claudi; Orga, Ferran

2018-04-20

One of the main aspects affecting the quality of life of people living in urban and suburban areas is the continuous exposure to high road traffic noise (RTN) levels. Nowadays, thanks to Wireless Acoustic Sensor Networks (WASN) noise in Smart Cities has started to be automatically mapped. To obtain a reliable picture of the RTN, those anomalous noise events (ANE) unrelated to road traffic (sirens, horns, people, etc.) should be removed from the noise map computation by means of an Anomalous Noise Event Detector (ANED). In Hybrid WASNs, with master-slave architecture, ANED should be implemented in both high-capacity (Hi-Cap) and low-capacity (Lo-Cap) sensors, following the same principle to obtain consistent results. This work presents an ANED version to run in real-time on μ Controller-based Lo-Cap sensors of a hybrid WASN, discriminating RTN from ANE through their Mel-based spectral energy differences. The experiments, considering 9 h and 8 min of real-life acoustic data from both urban and suburban environments, show the feasibility of the proposal both in terms of computational load and in classification accuracy. Specifically, the ANED Lo-Cap requires around 1 6 of the computational load of the ANED Hi-Cap, while classification accuracies are slightly lower (around 10%). However, preliminary analyses show that these results could be improved in around 4% in the future by means of considering optimal frequency selection.

Computed Tomography Image Origin Identification Based on Original Sensor Pattern Noise and 3-D Image Reconstruction Algorithm Footprints.

Science.gov (United States)

Duan, Yuping; Bouslimi, Dalel; Yang, Guanyu; Shu, Huazhong; Coatrieux, Gouenou

2017-07-01

In this paper, we focus on the "blind" identification of the computed tomography (CT) scanner that has produced a CT image. To do so, we propose a set of noise features derived from the image chain acquisition and which can be used as CT-scanner footprint. Basically, we propose two approaches. The first one aims at identifying a CT scanner based on an original sensor pattern noise (OSPN) that is intrinsic to the X-ray detectors. The second one identifies an acquisition system based on the way this noise is modified by its three-dimensional (3-D) image reconstruction algorithm. As these reconstruction algorithms are manufacturer dependent and kept secret, our features are used as input to train a support vector machine (SVM) based classifier to discriminate acquisition systems. Experiments conducted on images issued from 15 different CT-scanner models of 4 distinct manufacturers demonstrate that our system identifies the origin of one CT image with a detection rate of at least 94% and that it achieves better performance than sensor pattern noise (SPN) based strategy proposed for general public camera devices.

Transistor design considerations for low-noise preamplifiers

International Nuclear Information System (INIS)

Fair, R.B.

1976-01-01

A review is presented of design considerations for GaAs Schottky-barrier FETs and other types of transistors in low-noise amplifiers for capacitive sources which are used in nuclear radiation detectors and high speed fiber-optic communication systems. Ultimate limits on performance are evaluated in terms of the g/sub m//C/sub i/ ratio and the gate leakage current to minimize the noise sources. Si bipolar transistors and the future prospects of GaAs, Si and InAs MISFETs are discussed, and performance is compared to FETs currently being used in low-noise preamplifiers

Low dose CT simulation using experimental noise model

Energy Technology Data Exchange (ETDEWEB)

Nakanishi, Satori; Zamyatin, Alexander A. [Toshiba Medical Systems Corporation, Tochigi, Otawarashi (Japan); Silver, Michael D. [Toshiba Medical Research Institute, Vernon Hills, IL (United States)

2011-07-01

We suggest a method to obtain system noise model experimentally without relying on assumptions on statistical distribution of the noise; also, knowledge of DAS gain and electronic noise level are not required. Evaluation with ultra-low dose CT data (5 mAs) shows good match between simulated and real data noise. (orig.)

Low-frequency noise in single electron tunneling transistor

DEFF Research Database (Denmark)

Tavkhelidze, A.N.; Mygind, Jesper

1998-01-01

The noise in current biased aluminium single electron tunneling (SET) transistors has been investigated in the frequency range of 5 mHz ..., we find the same input charge noise, typically QN = 5 × 10–4 e/Hz1/2 at 10 Hz, with and without the HF shielding. At lower frequencies, the noise is due to charge trapping, and the voltage noise pattern superimposed on the V(Vg) curve (voltage across transistor versus gate voltage) strongly depends...... when ramping the junction voltage. Dynamic trapping may limit the high frequency applications of the SET transistor. Also reported on are the effects of rf irradiation and the dependence of the SET transistor noise on bias voltage. ©1998 American Institute of Physics....

Low frequency noise in resonant Josephson soliton oscillators

DEFF Research Database (Denmark)

Hansen, Jørn Bindslev; Holst, T.; Wellstood, Frederick C.

1991-01-01

The noise in the resonant soliton mode of long and narrow Josephson tunnel junctions (Josephson transmission lines or JTLs) have been measured in the frequency range from 0.1 Hz to 25 kHz by means of a DC SQUID. The measured white noise was found, to within a factor of two, to be equal...... to the Nyquist voltage noise in a resistance equal to the dynamic resistance RD of the current-voltage characteristic of the bias point. In contrast, measurements of the linewidth of the microwave radiation from the same JTL showed that the spectral density of the underlying noise voltage scaled as R D2/RS where...

The Analysis of Low Noise Protection Barriers Influence on Tram Traffic Noise Levels

Directory of Open Access Journals (Sweden)

Ahac Maja

2013-07-01

Full Text Available The paper describes the analysis of tram traffic noise situation in residential areas in the vicinity of Drzic Avenue, one of the major routes between the northern and southern part of the Croatian capital city Zagreb, and the effect of low barriers placed by the tracks on tram noise mitigation. In order to evaluate the effect of planned protection measure, noise models were produced and verified with short-term field measurements. Calculations were conducted by means of noise prediction software, using European interim noise prediction method and 3D model of analyzed area. Finally, the results of noise calculations for existing tram traffic situation and planned measure of protection are presented on noise maps.

The robustness of two tomography reconstructing techniques with heavily noisy dynamical experimental data from a high speed gamma-ray tomograph

International Nuclear Information System (INIS)

Vasconcelos, Geovane Vitor; Melo, Silvio de Barros; Dantas, Carlos Costa; Moreira, Icaro Malta; Johansen, Geira; Maad, Rachid

2013-01-01

The PSIRT (Particle Systems Iterative Reconstructive Technique) is, just like the ART method, an iterative tomographic reconstruction technique with the recommended use in the reconstruction of catalytic density distribution in the refining process of oil in the FCC-type riser. The PSIRT is based upon computer graphics' particle systems, where the reconstructing material is initially represented as composed of particles subject to a force field emanating from the beams, whose intensities are parameterized by the differences between the experimental readings of a given beam trajectory, and the values corresponding to the current amount of particles landed in this trajectory. A dynamical process is set as the beams fields of attracting forces dispute the particles. At the end, with the equilibrium established, the particles are replaced by the corresponding regions of pixels. The High Speed Gamma-ray Tomograph is a 5-source-fan-beam device with a 17-detector deck per source, capable of producing up to a thousand complete sinograms per second. Around 70.000 experimental sinograms from this tomograph were produced simulating the move of gas bubbles in different angular speeds immersed in oil within the vessel, through the use of a two-hole-polypropylene phantom. The sinogram frames were set with several different detector integration times. This article studies and compares the robustness of both ART and PSIRT methods in this heavily noisy scenario, where this noise comes not only from limitations in the dynamical sampling, but also from to the underlying apparatus that produces the counting in the tomograph. These experiments suggest that PSIRT is a more robust method than ART for noisy data. Visual inspection on the resulting images suggests that PSIRT is a more robust method than ART for noisy data, since it almost never presents globally scattered noise. (author)

A fast sparse reconstruction algorithm for electrical tomography

International Nuclear Information System (INIS)

Zhao, Jia; Xu, Yanbin; Tan, Chao; Dong, Feng

2014-01-01

Electrical tomography (ET) has been widely investigated due to its advantages of being non-radiative, low-cost and high-speed. However, the image reconstruction of ET is a nonlinear and ill-posed inverse problem and the imaging results are easily affected by measurement noise. A sparse reconstruction algorithm based on L 1 regularization is robust to noise and consequently provides a high quality of reconstructed images. In this paper, a sparse reconstruction by separable approximation algorithm (SpaRSA) is extended to solve the ET inverse problem. The algorithm is competitive with the fastest state-of-the-art algorithms in solving the standard L 2 −L 1 problem. However, it is computationally expensive when the dimension of the matrix is large. To further improve the calculation speed of solving inverse problems, a projection method based on the Krylov subspace is employed and combined with the SpaRSA algorithm. The proposed algorithm is tested with image reconstruction of electrical resistance tomography (ERT). Both simulation and experimental results demonstrate that the proposed method can reduce the computational time and improve the noise robustness for the image reconstruction. (paper)

Signal-to-noise limitations in white light holography.

Science.gov (United States)

Ribak, E; Roddier, C; Roddier, F; Breckinridge, J B

1988-03-15

A simple derivation is given for the signal-to-noise ratio (SNR) in images reconstructed from incoherent holograms. Dependence is shown to be on the hologram SNR, object complexity, and the number of pixels in the detector. Reconstruction of involved objects becomes possible with high dynamic range detectors such as charge coupled devices. We have produced such white light holograms by means of a rotational shear interferometer combined with a chromatic corrector. A digital inverse transform recreated the object.

EUDP Project: Low Noise Airfoil - Final Report

DEFF Research Database (Denmark)

This document summarizes the scientific results achieved during the EUDP-funded project `Low-Noise Airfoil'. The goals of this project are, on one side to develop a measurement technique that permits the evaluation of trailing edge noise in a classical aerodynamic wind tunnel, and on the other side...... to develop and implement a design procedure to manufacture airfoil profiles with low noise emission. The project involved two experimental campaigns: one in the LM Wind Power wind tunnel, a classical aerodynamic wind tunnel, in Lunderskov (DK), the second one in the Virginia Tech Stability Wind Tunnel....... In particular, the so-called TNO trailing edge noise model could be significantly improved by introducing turbulence anisotropy in its formulation, as well as the influence of the boundary layer mean pressure gradient. This two characteristics are inherent to airfoil flows but were neglected in the original...

Low-noise analog readout channel for SDD in X-ray spectrometry

Science.gov (United States)

Atkin, E.; Gusev, A.; Krivchenko, A.; Levin, V.; Malankin, E.; Normanov, D.; Rotin, A.; Sagdiev, I.; Samsonov, V.

2016-01-01

A low-noise analog readout channel optimized for operation with the Silicon Drift Detectors (SDDs) with built-in JFET is presented. The Charge Sensitive Amplifier (CSA) operates in a pulse reset mode using the reset diode built-in the SDD detector. The shaper is a 6th order semi-Gaussian filter with switchable discrete shaping times. The readout channel provides the Equivalent Noise Charge (ENC) of 12e- (simulation) and input dynamic range of 30 keV . The measured energy resolution at the 5,89 keV line of a 55Fe X-ray source is 336 eV (FWHM). The channel was prototyped via Europractice in the AMS 350 nm process as miniASIC. The simulation and first measurement results are presented in the paper.

Noise Reduction Effect of Multiple-Sampling-Based Signal-Readout Circuits for Ultra-Low Noise CMOS Image Sensors

Directory of Open Access Journals (Sweden)

Shoji Kawahito

2016-11-01

Full Text Available This paper discusses the noise reduction effect of multiple-sampling-based signal readout circuits for implementing ultra-low-noise image sensors. The correlated multiple sampling (CMS technique has recently become an important technology for high-gain column readout circuits in low-noise CMOS image sensors (CISs. This paper reveals how the column CMS circuits, together with a pixel having a high-conversion-gain charge detector and low-noise transistor, realizes deep sub-electron read noise levels based on the analysis of noise components in the signal readout chain from a pixel to the column analog-to-digital converter (ADC. The noise measurement results of experimental CISs are compared with the noise analysis and the effect of noise reduction to the sampling number is discussed at the deep sub-electron level. Images taken with three CMS gains of two, 16, and 128 show distinct advantage of image contrast for the gain of 128 (noise(median: 0.29 e−rms when compared with the CMS gain of two (2.4 e−rms, or 16 (1.1 e−rms.

A programmable ultra-low noise X-band exciter.

Science.gov (United States)

MacMullen, A; Hoover, L R; Justice, R D; Callahan, B S

2001-07-01

A programmable ultra-low noise X-band exciter has been developed using commercial off-the-shelf components. Its phase noise is more than 10 dB below the best available microwave synthesizers. It covers a 7% frequency band with 0.1-Hz resolution. The X-band output at +23 dBm is a combination of signals from an X-band sapphire-loaded cavity oscillator (SLCO), a low noise UHF frequency synthesizer, and special-purpose frequency translation and up-conversion circuitry.

Sub-harmonic broadband humps and tip noise in low-speed ring fans.

Science.gov (United States)

Moreau, Stéphane; Sanjose, Marlène

2016-01-01

A joint experimental and numerical study has been achieved on a low-speed axial ring fan in clean inflow. Experimental evidence shows large periodic broadband humps at lower frequencies than the blade passing frequencies and harmonics even at design conditions. These sub-harmonic humps are also found to be sensitive to the fan process and consequently to its tip geometry. Softer fans yield more intense humps more shifted to lower frequencies with respect to the fan harmonics. Unsteady turbulent flow simulations of this ring fan mounted on a test plenum have been achieved by four different methods that have been validated by comparing with overall performances and detailed hot-wire velocity measurements in the wake. Noise predictions are either obtained directly or are obtained through Ffowcs Williams and Hawkings' analogy, and compared with narrowband and third-octave power spectra. All unsteady simulations correctly capture the low flow rates, the coherent vortex dynamics in the tip clearance and consequently the noise radiation dominated by the tip noise in the low- to mid-frequency range. Yet, only the scale-adaptive simulation and the lattice Boltzmann method simulations which can describe most of the turbulent structures accurately provide the proper spectral shape and levels, and consequently the overall sound power level.

Obtaining and Estimating Low Noise Floors in Vibration Sensors

DEFF Research Database (Denmark)

Brincker, Rune; Larsen, Jesper Abildgaard

2007-01-01

For some applications like seismic applications and measuring ambient vibrations in structures, it is essential that the noise floors of the sensors and other system components are low and known to the user. Some of the most important noise sources are reviewed and it is discussed how the sensor...... can be designed in order to obtain a low noise floor. Techniques to estimate the noise floors for sensors are reviewed and are demonstrated on a commercial commonly used sensor for vibration testing. It is illustrated how the noise floor can be calculated using the coherence between simultaneous...

Twenty-two cases of low-frequency noise complaints

DEFF Research Database (Denmark)

Pedersen, Christian Sejer; Møller, Henrik; Persson-Waye, Kerstin

2006-01-01

In Denmark and in other industrialized countries there are cases where people complain about annoying low-frequency or infrasonic noise in their homes. Besides noise annoyance people often report other adverse effects such as insomnia, headache, lack of concentration etc. In many cases the noise...

Investigation of the noise effect on tomographic reconstructions for a tangentially viewing vacuum ultraviolet imaging diagnostic

International Nuclear Information System (INIS)

Ming, Tingfeng; Ohdachi, Satoshi; Suzuki, Yasuhiro

2011-01-01

Tomographic reconstruction for a tangentially viewing two-dimensional (2D) imaging system is studied. A method to calculate the geometry matrix in 2D tomography is introduced. An algorithm based on a Phillips-Tikhonov (P-T) type regularization method is investigated, and numerical tests using the P-T method are conducted with both tokamak and Heliotron configurations. The numerical tests show that the P-T method is not sensitive to the added noise levels and the emission profiles with higher mode numbers can be reconstructed with adequate resolution. The results indicate that this method is suitable for 2D tomographic reconstruction for a tangentially viewing vacuum ultraviolet telescope system. (author)

Low concentration contrast medium for dual-source computed tomography coronary angiography by a combination of iterative reconstruction and low-tube-voltage technique: Feasibility study

Energy Technology Data Exchange (ETDEWEB)

Zheng, Minwen, E-mail: zhengmw2007@163.com; Liu, Ying, E-mail: yingyinglyly@126.com; Wei, Mengqi, E-mail: weimengqi2008@163.com; Wu, Yongjie, E-mail: wu18291988526@163.com; Zhao, Hongliang, E-mail: zhaohl1980@163.com; Li, Jian, E-mail: xjyylj@yeah.net

2014-02-15

Objectives: To assess the impact of low-concentration contrast medium on vascular enhancement, image quality and radiation dose of coronary CT angiography (cCTA) by using a combination of iterative reconstruction (IR) and low-tube-voltage technique. Materials and methods: One hundred patients were prospectively randomized to two types of contrast medium and underwent prospective electrocardiogram-triggering cCTA (Definition Flash, Siemens Healthcare; collimation: 128 mm × 0.6 mm; tube current: 300 mA s). Fifty patients received Iopromide 370 were scanned using the conventional tube setting (100 kVp or 120 kVp if BMI ≥ 25 kg/m{sup 2}) and reconstructed with filtered back projection (FBP). Fifty patients received Iodixanol 270 were scanned using the low-tube-voltage (80 kVp or 100 kVp if BMI ≥ 25 kg/m{sup 2}) technique and reconstructed with IR. CT attenuation was measured in coronary artery and other anatomical regions. Noise, image quality and radiation dose were compared. Results: Compared with two Iopromide 370 subgroups, Iomeprol 270 subgroups showed no significant difference in CT attenuation (576.63 ± 95.50 vs. 569.51 ± 118.93 for BMI < 25 kg/m{sup 2}, p = 0.647 and 394.19 ± 68.09 vs. 383.72 ± 63.11 for BMI ≥ 25 kg/m{sup 2}, p = 0.212), noise (in various anatomical regions of interest) and image quality (3.5 vs. 4.0, p = 0.13), but significantly (0.41 ± 0.17 vs. 0.94 ± 0.45 for BMI < 25 kg/m{sup 2}, p < 0.001 and 1.14 ± 0.24 vs. 2.37 ± 0.69 for BMI ≥ 25 kg/m{sup 2}, p < 0.001) lower radiation dose, which reflects dose saving of 56.4% and 51.9%, respectively. Conclusions: Combined IR with low-tube-voltage technique, a low-concentration contrast medium of 270 mg I/ml can still maintain the contrast enhancement without impairing image quality, as well as significantly lower the radiation dose.

Adaptive statistical iterative reconstruction versus filtered back projection in the same patient: 64 channel liver CT image quality and patient radiation dose

International Nuclear Information System (INIS)

Mitsumori, Lee M.; Shuman, William P.; Busey, Janet M.; Kolokythas, Orpheus; Koprowicz, Kent M.

2012-01-01

To compare routine dose liver CT reconstructed with filtered back projection (FBP) versus low dose images reconstructed with FBP and adaptive statistical iterative reconstruction (ASIR). In this retrospective study, patients had a routine dose protocol reconstructed with FBP, and again within 17 months (median 6.1 months), had a low dose protocol reconstructed twice, with FBP and ASIR. These reconstructions were compared for noise, image quality, and radiation dose. Nineteen patients were included. (12 male, mean age 58). Noise was significantly lower in low dose images reconstructed with ASIR compared to routine dose images reconstructed with FBP (liver: p <.05, aorta: p < 0.001). Low dose FBP images were scored significantly lower for subjective image quality than low dose ASIR (2.1 ± 0.5, 3.2 ± 0.8, p < 0.001). There was no difference in subjective image quality scores between routine dose FBP images and low dose ASIR images (3.6 ± 0.5, 3.2 ± 0.8, NS).Radiation dose was 41% less for the low dose protocol (4.4 ± 2.4 mSv versus 7.5 ± 5.5 mSv, p < 0.05). Our initial results suggest low dose CT images reconstructed with ASIR may have lower measured noise, similar image quality, yet significantly less radiation dose compared with higher dose images reconstructed with FBP. (orig.)

Adaptive statistical iterative reconstruction versus filtered back projection in the same patient: 64 channel liver CT image quality and patient radiation dose

Energy Technology Data Exchange (ETDEWEB)

Mitsumori, Lee M.; Shuman, William P.; Busey, Janet M.; Kolokythas, Orpheus; Koprowicz, Kent M. [University of Washington School of Medicine, Department of Radiology, Seattle, WA (United States)

2012-01-15

To compare routine dose liver CT reconstructed with filtered back projection (FBP) versus low dose images reconstructed with FBP and adaptive statistical iterative reconstruction (ASIR). In this retrospective study, patients had a routine dose protocol reconstructed with FBP, and again within 17 months (median 6.1 months), had a low dose protocol reconstructed twice, with FBP and ASIR. These reconstructions were compared for noise, image quality, and radiation dose. Nineteen patients were included. (12 male, mean age 58). Noise was significantly lower in low dose images reconstructed with ASIR compared to routine dose images reconstructed with FBP (liver: p <.05, aorta: p < 0.001). Low dose FBP images were scored significantly lower for subjective image quality than low dose ASIR (2.1 {+-} 0.5, 3.2 {+-} 0.8, p < 0.001). There was no difference in subjective image quality scores between routine dose FBP images and low dose ASIR images (3.6 {+-} 0.5, 3.2 {+-} 0.8, NS).Radiation dose was 41% less for the low dose protocol (4.4 {+-} 2.4 mSv versus 7.5 {+-} 5.5 mSv, p < 0.05). Our initial results suggest low dose CT images reconstructed with ASIR may have lower measured noise, similar image quality, yet significantly less radiation dose compared with higher dose images reconstructed with FBP. (orig.)

Low noise amplifier for ZnS(Ag) scintillation chamber

International Nuclear Information System (INIS)

Do Hoang Cuong

1998-01-01

A new pulse amplifier that can be used with standard photomultiplier tubes coupled with Zn(Ag) scintillation chamber is presented. The amplifier based on an IC operational amplifier LF 356N consists of a low-noise charge sensitive preamplifier and pulse shaping circuits for optimization of signal to noise ratio. Temperature instability is ≤ 0.05%/ o C. Dynamic range for linear output signals is equal +7 V. The presented amplifier is used in a measuring head for 0.17 L Lucas chambers developed in Department of Nuclear Instruments and Methods of the INCT in laboratory investigations aimed to develop methods and instruments for measurement of radon concentration in the air. The amplifier can also be employed for measurement of ionizing radiation by means of other scintillators coupled to PM tube. The amplifier is followed by a pulse discriminator with adjustable discrimination level. The amplifier output signal and discriminator output pulses are fed to external devices. (author)

Optimization of CMOS image sensor utilizing variable temporal multisampling partial transfer technique to achieve full-frame high dynamic range with superior low light and stop motion capability

Science.gov (United States)

Kabir, Salman; Smith, Craig; Armstrong, Frank; Barnard, Gerrit; Schneider, Alex; Guidash, Michael; Vogelsang, Thomas; Endsley, Jay

2018-03-01

Differential binary pixel technology is a threshold-based timing, readout, and image reconstruction method that utilizes the subframe partial charge transfer technique in a standard four-transistor (4T) pixel CMOS image sensor to achieve a high dynamic range video with stop motion. This technology improves low light signal-to-noise ratio (SNR) by up to 21 dB. The method is verified in silicon using a Taiwan Semiconductor Manufacturing Company's 65 nm 1.1 μm pixel technology 1 megapixel test chip array and is compared with a traditional 4 × oversampling technique using full charge transfer to show low light SNR superiority of the presented technology.

Iterative model reconstruction: Improved image quality of low-tube-voltage prospective ECG-gated coronary CT angiography images at 256-slice CT

Energy Technology Data Exchange (ETDEWEB)

Oda, Seitaro, E-mail: seisei0430@nifty.com [Department of Cardiology, MedStar Washington Hospital Center, 110 Irving Street, NW, Washington, DC 20010 (United States); Department of Diagnostic Radiology, Faculty of Life Sciences, Kumamoto University, 1-1-1 Honjyo, Chuo-ku, Kumamoto, 860-8556 (Japan); Weissman, Gaby, E-mail: Gaby.Weissman@medstar.net [Department of Cardiology, MedStar Washington Hospital Center, 110 Irving Street, NW, Washington, DC 20010 (United States); Vembar, Mani, E-mail: mani.vembar@philips.com [CT Clinical Science, Philips Healthcare, c595 Miner Road, Cleveland, OH 44143 (United States); Weigold, Wm. Guy, E-mail: Guy.Weigold@MedStar.net [Department of Cardiology, MedStar Washington Hospital Center, 110 Irving Street, NW, Washington, DC 20010 (United States)

2014-08-15

Objectives: To investigate the effects of a new model-based type of iterative reconstruction (M-IR) technique, the iterative model reconstruction, on image quality of prospectively gated coronary CT angiography (CTA) acquired at low-tube-voltage. Methods: Thirty patients (16 men, 14 women; mean age 52.2 ± 13.2 years) underwent coronary CTA at 100-kVp on a 256-slice CT. Paired image sets were created using 3 types of reconstruction, i.e. filtered back projection (FBP), a hybrid type of iterative reconstruction (H-IR), and M-IR. Quantitative parameters including CT-attenuation, image noise, and contrast-to-noise ratio (CNR) were measured. The visual image quality, i.e. graininess, beam-hardening, vessel sharpness, and overall image quality, was scored on a 5-point scale. Lastly, coronary artery segments were evaluated using a 4-point scale to investigate the assessability of each segment. Results: There was no significant difference in coronary arterial CT attenuation among the 3 reconstruction methods. The mean image noise of FBP, H-IR, and M-IR images was 29.3 ± 9.6, 19.3 ± 6.9, and 12.9 ± 3.3 HU, respectively, there were significant differences for all comparison combinations among the 3 methods (p < 0.01). The CNR of M-IR was significantly better than of FBP and H-IR images (13.5 ± 5.0 [FBP], 20.9 ± 8.9 [H-IR] and 39.3 ± 13.9 [M-IR]; p < 0.01). The visual scores were significantly higher for M-IR than the other images (p < 0.01), and 95.3% of the coronary segments imaged with M-IR were of assessable quality compared with 76.7% of FBP- and 86.9% of H-IR images. Conclusions: M-IR can provide significantly improved qualitative and quantitative image quality in prospectively gated coronary CTA using a low-tube-voltage.

Entanglement dynamics of two-qubit systems in different quantum noises

International Nuclear Information System (INIS)

Pan Chang-Ning; Fang Jian-Shu; Li-Fei; Fang Mao-Fa

2011-01-01

The entanglement dynamics of two-qubit systems in different quantum noises are investigated by means of the operator-sum representation method. We find that, except for the amplitude damping and phase damping quantum noise, the sudden death of entanglement is always observed in different two-qubit systems with generalized amplitude damping and depolarizing quantum noise. (general)

Cross correlation measurement of low frequency conductivity noise

Science.gov (United States)

Jain, Aditya Kumar; Nigudkar, Himanshu; Chakraborti, Himadri; Udupa, Aditi; Gupta, Kantimay Das

2018-04-01

In order to study the low frequency noise(1/f noise)an experimental technique based on cross correlation of two channels is presented. In this method the device under test (DUT)is connected to the two independently powered preamplifiers in parallel. The amplified signals from the two preamplifiers are fed to two channels of a digitizer. Subsequent data processing largelyeliminates the uncorrelated noise of the two channels. This method is tested for various commercial carbon/metal film resistors by measuring equilibrium thermal noise (4kBTR). The method is then modified to study the non-equilibrium low frequency noise of heterostructure samples using fiveprobe configuration. Five contact probes allow two parts of the sample to become two arms of a balanced bridge. This configuration helps in suppressing the effect of power supply fluctuations, bath temperature fluctuations and contact resistances.

Noise-induced temporal dynamics in Turing systems

KAUST Repository

Schumacher, Linus J.; Woolley, Thomas E.; Baker, Ruth E.

2013-01-01

We examine the ability of intrinsic noise to produce complex temporal dynamics in Turing pattern formation systems, with particular emphasis on the Schnakenberg kinetics. Using power spectral methods, we characterize the behavior of the system using

'Pipetron' beam dynamics with noise

International Nuclear Information System (INIS)

Shiltsev, V.D.

1996-10-01

Extra-large hadron collider, ''Pipetron'', at 100 TeV energy is currently under consideration. In this article we study the Pipetron transverse and longitudinal beam dynamics under influence of external noises. The major effects are growths of transverse and longitudinal emittances of the beam caused by noisy forces which vary over the revolution period or synchrotron oscillation period, respectively; and closed orbit distortions induced by slow drift of magnet positions. Based on analytical consideration of these phenomena, we estimate tolerable levels of these noises and compare them with available experimental data. Although it is concluded that transverse and, probably, longitudinal feedback systems are necessary for the emittance's preservation, and sophisticated beam-based orbit correction methods should be used at the Pipetron, we observe no unreasonable requirements which present and impenetrable barrier to the project

Quantum and Private Capacities of Low-Noise Channels

Science.gov (United States)

Leditzky, Felix; Leung, Debbie; Smith, Graeme

2018-04-01

We determine both the quantum and the private capacities of low-noise quantum channels to leading orders in the channel's distance to the perfect channel. It has been an open problem for more than 20 yr to determine the capacities of some of these low-noise channels such as the depolarizing channel. We also show that both capacities are equal to the single-letter coherent information of the channel, again to leading orders. We thus find that, in the low-noise regime, superadditivity and degenerate codes have a negligible benefit for the quantum capacity, and shielding does not improve the private capacity beyond the quantum capacity, in stark contrast to the situation when noisier channels are considered.

Implications of CT noise and artifacts for quantitative 99mTc SPECT/CT imaging

International Nuclear Information System (INIS)

Hulme, K. W.; Kappadath, S. C.

2014-01-01

Purpose: This paper evaluates the effects of computed tomography (CT) image noise and artifacts on quantitative single-photon emission computed-tomography (SPECT) imaging, with the aim of establishing an appropriate range of CT acquisition parameters for low-dose protocols with respect to accurate SPECT attenuation correction (AC). Methods: SPECT images of two geometric and one anthropomorphic phantom were reconstructed iteratively using CT scans acquired at a range of dose levels (CTDI vol = 0.4 to 46 mGy). Resultant SPECT image quality was evaluated by comparing mean signal, background noise, and artifacts to SPECT images reconstructed using the highest dose CT for AC. Noise injection was performed on linear-attenuation (μ) maps to determine the CT noise threshold for accurate AC. Results: High levels of CT noise (σ ∼ 200–400 HU) resulted in low μ-maps noise (σ ∼ 1%–3%). Noise levels greater than ∼10% in 140 keV μ-maps were required to produce visibly perceptible increases of ∼15% in 99m Tc SPECT images. These noise levels would be achieved at low CT dose levels (CTDI vol = 4 μGy) that are over 2 orders of magnitude lower than the minimum dose for diagnostic CT scanners. CT noise could also lower (bias) the expected μ values. The relative error in reconstructed SPECT signal trended linearly with the relative shift in μ. SPECT signal was, on average, underestimated in regions corresponding with beam-hardening artifacts in CT images. Any process that has the potential to change the CT number of a region by ∼100 HU (e.g., misregistration between CT images and SPECT images due to motion, the presence of contrast in CT images) could introduce errors in μ 140 keV on the order of 10%, that in turn, could introduce errors on the order of ∼10% into the reconstructed 99m Tc SPECT image. Conclusions: The impact of CT noise on SPECT noise was demonstrated to be negligible for clinically achievable CT parameters. Because CT dose levels that affect

Dynamical reduction models with general gaussian noises

International Nuclear Information System (INIS)

Bassi, Angelo; Ghirardi, GianCarlo

2002-02-01

We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the statevector, white noise stochastic processes with non white ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view the most relevant motivation for the approach we propose here derives from the fact that in relativistic models the occurrence of white noises is the main responsible for the appearance of untractable divergences. Therefore, one can hope that resorting to non white noises one can overcome such a difficulty. We investigate stochastic equations with non white noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above mentioned subject but also for the general study of dissipative systems and decoherence. (author)

Dynamical reduction models with general Gaussian noises

International Nuclear Information System (INIS)

Bassi, Angelo; Ghirardi, GianCarlo

2002-01-01

We consider the effect of replacing in stochastic differential equations leading to the dynamical collapse of the state vector, white-noise stochastic processes with nonwhite ones. We prove that such a modification can be consistently performed without altering the most interesting features of the previous models. One of the reasons to discuss this matter derives from the desire of being allowed to deal with physical stochastic fields, such as the gravitational one, which cannot give rise to white noises. From our point of view, the most relevant motivation for the approach we propose here derives from the fact that in relativistic models intractable divergences appear as a consequence of the white nature of the noises. Therefore, one can hope that resorting to nonwhite noises, one can overcome such a difficulty. We investigate stochastic equations with nonwhite noises, we discuss their reduction properties and their physical implications. Our analysis has a precise interest not only for the above-mentioned subject but also for the general study of dissipative systems and decoherence

Low Cost/Low Noise Variable Pitch Ducted Fan, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — ACI proposes a design for a Propulsor (Low Cost/Low Noise Variable Pitch Ducted Fan) that has wide application in all sectors of Aviation. Propulsor hardware of this...

Quantitation of PET data with the EM reconstruction technique

International Nuclear Information System (INIS)

Rosenqvist, G.; Dahlbom, M.; Erikson, L.; Bohm, C.; Blomqvist, G.

1989-01-01

The expectation maximization (EM) algorithm offers high spatial resolution and excellent noise reduction with low statistics PET data, since it incorporates the Poisson nature of the data. The main difficulties are long computation times, difficulties to find appropriate criteria to terminate the reconstruction and to quantify the resulting image data. In the present work a modified EM algorithm has been implements on a VAX 11/780. Its capability to quantify image data has been tested in phantom studies and in two clinical cases, cerebral blood flow studies and dopamine D2-receptor studies. Data from phantom studies indicate the superiority of images reconstructed with the EM technique compared to images reconstructed with the conventional filtered back-projection (FB) technique in areas with low statistics. At higher statistics the noise characteristics of the two techniques coincide. Clinical data support these findings

A Dynamically Focusing Cochlear Implant Strategy Can Improve Vowel Identification in Noise.

Science.gov (United States)

Arenberg, Julie G; Parkinson, Wendy S; Litvak, Leonid; Chen, Chen; Kreft, Heather A; Oxenham, Andrew J

2018-03-09

The standard, monopolar (MP) electrode configuration used in commercially available cochlear implants (CI) creates a broad electrical field, which can lead to unwanted channel interactions. Use of more focused configurations, such as tripolar and phased array, has led to mixed results for improving speech understanding. The purpose of the present study was to assess the efficacy of a physiologically inspired configuration called dynamic focusing, using focused tripolar stimulation at low levels and less focused stimulation at high levels. Dynamic focusing may better mimic cochlear excitation patterns in normal acoustic hearing, while reducing the current levels necessary to achieve sufficient loudness at high levels. Twenty postlingually deafened adult CI users participated in the study. Speech perception was assessed in quiet and in a four-talker babble background noise. Speech stimuli were closed-set spondees in noise, and medial vowels at 50 and 60 dB SPL in quiet and in noise. The signal to noise ratio was adjusted individually such that performance was between 40 and 60% correct with the MP strategy. Subjects were fitted with three experimental strategies matched for pulse duration, pulse rate, filter settings, and loudness on a channel-by-channel basis. The strategies included 14 channels programmed in MP, fixed partial tripolar (σ = 0.8), and dynamic partial tripolar (σ at 0.8 at threshold and 0.5 at the most comfortable level). Fifteen minutes of listening experience was provided with each strategy before testing. Sound quality ratings were also obtained. Speech perception performance for vowel identification in quiet at 50 and 60 dB SPL and for spondees in noise was similar for the three tested strategies. However, performance on vowel identification in noise was significantly better for listeners using the dynamic focusing strategy. Sound quality ratings were similar for the three strategies. Some subjects obtained more benefit than others, with some

Low-tube-voltage (80 kVp) CT aortography using 320-row volume CT with adaptive iterative reconstruction: lower contrast medium and radiation dose

Energy Technology Data Exchange (ETDEWEB)

Chen, Chien-Ming; Chu, Sung-Yu; Hsu, Ming-Yi [Chang Gung University, Department of Medical Imaging and Intervention, Chang Gung Memorial Hospital Linkou, College of Medicine, Taoyuan (China); Liao, Ying-Lan [National Tsing Hua University, Department of Biomedical Engineering and Environmental Sciences, Hsinchu (China); Tsai, Hui-Yu [Chang Gung University, Department of Medical Imaging and Radiological Sciences, College of Medicine, Taoyuan (China); Chang Gung University, Healthy Aging Research Center, Taoyuan (China); Chang Gung University, Department of Medical Imaging and Radiological Sciences, Taoyuan (China)

2014-02-15

To evaluate CT aortography at reduced tube voltage and contrast medium dose while maintaining image quality through iterative reconstruction (IR). The Institutional Review Board approved a prospective study of 48 patients who underwent follow-up CT aortography. We performed intra-individual comparisons of arterial phase images using 120 kVp (standard tube voltage) and 80 kVp (low tube voltage). Low-tube-voltage imaging was performed on a 320-detector CT with IR following injection of 40 ml of contrast medium. We assessed aortic attenuation, aortic attenuation gradient, image noise, contrast-to-noise ratio (CNR), volume CT dose index (CTDI{sub vol}), and figure of merit (FOM) of image noise and CNR. Two readers assessed images for diagnostic quality, image noise, and artefacts. The low-tube-voltage protocol showed 23-31 % higher mean aortic attenuation and image noise (both P < 0.01) than the standard-tube-voltage protocol, but no significant difference in the CNR and aortic attenuation gradients. The low-tube-voltage protocol showed a 48 % reduction in CTDI{sub vol} and an 80 % increase in FOM of CNR. Subjective diagnostic quality was similar for both protocols, but low-tube-voltage images showed greater image noise (P = 0.01). Application of IR to an 80-kVp CT aortography protocol allows radiation dose and contrast medium reduction without affecting image quality. (orig.)

Variance analysis of x-ray CT sinograms in the presence of electronic noise background.

Science.gov (United States)

Ma, Jianhua; Liang, Zhengrong; Fan, Yi; Liu, Yan; Huang, Jing; Chen, Wufan; Lu, Hongbing

2012-07-01

Low-dose x-ray computed tomography (CT) is clinically desired. Accurate noise modeling is a fundamental issue for low-dose CT image reconstruction via statistics-based sinogram restoration or statistical iterative image reconstruction. In this paper, the authors analyzed the statistical moments of low-dose CT data in the presence of electronic noise background. The authors first studied the statistical moment properties of detected signals in CT transmission domain, where the noise of detected signals is considered as quanta fluctuation upon electronic noise background. Then the authors derived, via the Taylor expansion, a new formula for the mean-variance relationship of the detected signals in CT sinogram domain, wherein the image formation becomes a linear operation between the sinogram data and the unknown image, rather than a nonlinear operation in the CT transmission domain. To get insight into the derived new formula by experiments, an anthropomorphic torso phantom was scanned repeatedly by a commercial CT scanner at five different mAs levels from 100 down to 17. The results demonstrated that the electronic noise background is significant when low-mAs (or low-dose) scan is performed. The influence of the electronic noise background should be considered in low-dose CT imaging.

Metal artifact reduction using a patch-based reconstruction for digital breast tomosynthesis

Science.gov (United States)

Borges, Lucas R.; Bakic, Predrag R.; Maidment, Andrew D. A.; Vieira, Marcelo A. C.

2017-03-01

Digital breast tomosynthesis (DBT) is rapidly emerging as the main clinical tool for breast cancer screening. Although several reconstruction methods for DBT are described by the literature, one common issue is the interplane artifacts caused by out-of-focus features. For breasts containing highly attenuating features, such as surgical clips and large calcifications, the artifacts are even more apparent and can limit the detection and characterization of lesions by the radiologist. In this work, we propose a novel method of combining backprojected data into tomographic slices using a patch-based approach, commonly used in denoising. Preliminary tests were performed on a geometry phantom and on an anthropomorphic phantom containing metal inserts. The reconstructed images were compared to a commercial reconstruction solution. Qualitative assessment of the reconstructed images provides evidence that the proposed method reduces artifacts while maintaining low noise levels. Objective assessment supports the visual findings. The artifact spread function shows that the proposed method is capable of suppressing artifacts generated by highly attenuating features. The signal difference to noise ratio shows that the noise levels of the proposed and commercial methods are comparable, even though the commercial method applies post-processing filtering steps, which were not implemented on the proposed method. Thus, the proposed method can produce tomosynthesis reconstructions with reduced artifacts and low noise levels.

Dynamical response of the Ising model to the time dependent magnetic field with white noise

Science.gov (United States)

Akıncı, Ümit

2018-03-01

The effect of the white noise in time dependent magnetic field on the dynamic behavior of the Ising model has been investigated within the effective field theory based on Glauber type of stochastic process. Discrete white noise has been chosen from both Gaussian and uniform probability distributions. Detailed investigation on probability distribution of dynamical order parameter results that, both type of noise distributions yield the same probability distribution related to the dynamical order parameter, namely Gaussian probability distribution. The variation of the parameters that describe the probability distribution of dynamical order parameter (mean value and standard deviation) with temperature and strength of the noise have been inspected. Also, it has been shown that, rising strength of the noise can induce dynamical phase transition in the system.

A Tunable Low Noise Active Bandpass Filter Using a Noise Canceling Technique

OpenAIRE

Soltani, N.

2016-01-01

A monolithic tunable low noise active bandpass filter is presented in this study. Biasing voltages can control the center frequency and quality factor. By keeping the gain constant, the center frequency shift is 300 MHz. The quality factor can range from 90 to 290 at the center frequency. By using a noise cancelling circuit, noise is kept lower than 2.8 dB. The proposed filter is designed using MMIC technology with a center frequency of 2.4 GHz and a power consumption of 180 mW. ED02AH techno...

Effects of random noise in a dynamical model of love

Energy Technology Data Exchange (ETDEWEB)

Xu Yong, E-mail: hsux3@nwpu.edu.cn [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China); Gu Rencai; Zhang Huiqing [Department of Applied Mathematics, Northwestern Polytechnical University, Xi' an 710072 (China)

2011-07-15

Highlights: > We model the complexity and unpredictability of psychology as Gaussian white noise. > The stochastic system of love is considered including bifurcation and chaos. > We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.

Effects of random noise in a dynamical model of love

International Nuclear Information System (INIS)

Xu Yong; Gu Rencai; Zhang Huiqing

2011-01-01

Highlights: → We model the complexity and unpredictability of psychology as Gaussian white noise. → The stochastic system of love is considered including bifurcation and chaos. → We show that noise can both suppress and induce chaos in dynamical models of love. - Abstract: This paper aims to investigate the stochastic model of love and the effects of random noise. We first revisit the deterministic model of love and some basic properties are presented such as: symmetry, dissipation, fixed points (equilibrium), chaotic behaviors and chaotic attractors. Then we construct a stochastic love-triangle model with parametric random excitation due to the complexity and unpredictability of the psychological system, where the randomness is modeled as the standard Gaussian noise. Stochastic dynamics under different three cases of 'Romeo's romantic style', are examined and two kinds of bifurcations versus the noise intensity parameter are observed by the criteria of changes of top Lyapunov exponent and shape of stationary probability density function (PDF) respectively. The phase portraits and time history are carried out to verify the proposed results, and the good agreement can be found. And also the dual roles of the random noise, namely suppressing and inducing chaos are revealed.

A capacitor cross-coupled common-gate low-noise amplifier

NARCIS (Netherlands)

Zhuo, W.; Li, X.; Shekhar, S.; Embabi, S.H.K.; Pineda de Gyvez, J.; Allstot, D.J.; Sanchez-Sinencio, E.

2005-01-01

The conventional common-gate low-noise amplifier (CGLNA) exhibits a relatively high noise figure (NF) at low operating frequencies relative to the MOSFET fT, which has limited its adoption notwithstanding its superior linearity, input matching, and stability compared to the inductively degenerated

Regional absolute conductivity reconstruction using projected current density in MREIT

International Nuclear Information System (INIS)

Sajib, Saurav Z K; Kim, Hyung Joong; Woo, Eung Je; Kwon, Oh In

2012-01-01

Magnetic resonance electrical impedance tomography (MREIT) is a non-invasive technique for imaging the internal conductivity distribution in tissue within an MRI scanner, utilizing the magnetic flux density, which is introduced when a current is injected into the tissue from external electrodes. This magnetic flux alters the MRI signal, so that appropriate reconstruction can provide a map of the additional z-component of the magnetic field (B z ) as well as the internal current density distribution that created it. To extract the internal electrical properties of the subject, including the conductivity and/or the current density distribution, MREIT techniques use the relationship between the external injection current and the z-component of the magnetic flux density B = (B x , B y , B z ). The tissue studied typically contains defective regions, regions with a low MRI signal and/or low MRI signal-to-noise-ratio, due to the low density of nuclear magnetic resonance spins, short T 2 or T* 2 relaxation times, as well as regions with very low electrical conductivity, through which very little current traverses. These defective regions provide noisy B z data, which can severely degrade the overall reconstructed conductivity distribution. Injecting two independent currents through surface electrodes, this paper proposes a new direct method to reconstruct a regional absolute isotropic conductivity distribution in a region of interest (ROI) while avoiding the defective regions. First, the proposed method reconstructs the contrast of conductivity using the transversal J-substitution algorithm, which blocks the propagation of severe accumulated noise from the defective region to the ROI. Second, the proposed method reconstructs the regional projected current density using the relationships between the internal current density, which stems from a current injection on the surface, and the measured B z data. Combining the contrast conductivity distribution in the entire imaging

A Fully Reconfigurable Low-Noise Biopotential Sensing Amplifier With 1.96 Noise Efficiency Factor.

Science.gov (United States)

Tzu-Yun Wang; Min-Rui Lai; Twigg, Christopher M; Sheng-Yu Peng

2014-06-01

A fully reconfigurable biopotential sensing amplifier utilizing floating-gate transistors is presented in this paper. By using the complementary differential pairs along with the current reuse technique, the theoretical limit for the noise efficiency factor of the proposed amplifier is below 1.5. Without consuming any extra power, floating-gate transistors are employed to program the low-frequency cutoff corner of the amplifier and to implement the common-mode feedback. A concept proving prototype chip was designed and fabricated in a 0.35 μm CMOS process occupying 0.17 mm (2) silicon area. With a supply voltage of 2.5 V, the measured midband gain is 40.7 dB and the measured input-referred noise is 2.8 μVrms. The chip was tested under several configurations with the amplifier bandwidth being programmed to 100 Hz, 1 kHz , and 10 kHz. The measured noise efficiency factors in these bandwidth settings are 1.96, 2.01, and 2.25, respectively, which are among the best numbers reported to date. The measured common-mode rejection and the supply rejection are above 70 dB . When the bandwidth is configured to be 10 kHz, the dynamic range measured at 1 kHz is 60 dB with total harmonic distortion less than 0.1%. The proposed amplifier is also demonstrated by recording electromyography (EMG), electrocardiography (ECG), electrooculography (EOG), and electroencephalography (EEG) signals from human bodies.

The use of compressive sensing and peak detection in the reconstruction of microtubules length time series in the process of dynamic instability.

Science.gov (United States)

Mahrooghy, Majid; Yarahmadian, Shantia; Menon, Vineetha; Rezania, Vahid; Tuszynski, Jack A

2015-10-01

Microtubules (MTs) are intra-cellular cylindrical protein filaments. They exhibit a unique phenomenon of stochastic growth and shrinkage, called dynamic instability. In this paper, we introduce a theoretical framework for applying Compressive Sensing (CS) to the sampled data of the microtubule length in the process of dynamic instability. To reduce data density and reconstruct the original signal with relatively low sampling rates, we have applied CS to experimental MT lament length time series modeled as a Dichotomous Markov Noise (DMN). The results show that using CS along with the wavelet transform significantly reduces the recovery errors comparing in the absence of wavelet transform, especially in the low and the medium sampling rates. In a sampling rate ranging from 0.2 to 0.5, the Root-Mean-Squared Error (RMSE) decreases by approximately 3 times and between 0.5 and 1, RMSE is small. We also apply a peak detection technique to the wavelet coefficients to detect and closely approximate the growth and shrinkage of MTs for computing the essential dynamic instability parameters, i.e., transition frequencies and specially growth and shrinkage rates. The results show that using compressed sensing along with the peak detection technique and wavelet transform in sampling rates reduces the recovery errors for the parameters. Copyright © 2015 Elsevier Ltd. All rights reserved.

The use of the partial coherence function technique for the investigation of BWR noise dynamics

International Nuclear Information System (INIS)

Kostic, Lj.

1983-01-01

The extensive experimental investigations, at the last time, indicate that the partial coherence function technique can be a powerful method of the investigation of BWR noise dynamics. Symple BWR noise dynamics model for the global noise study, based on different noise phenomena, is proposed in this paper. (author)

Spatio-temporal diffusion of dynamic PET images

International Nuclear Information System (INIS)

Tauber, C; Chalon, S; Guilloteau, D; Stute, S; Buvat, I; Chau, M; Spiteri, P

2011-01-01

Positron emission tomography (PET) images are corrupted by noise. This is especially true in dynamic PET imaging where short frames are required to capture the peak of activity concentration after the radiotracer injection. High noise results in a possible bias in quantification, as the compartmental models used to estimate the kinetic parameters are sensitive to noise. This paper describes a new post-reconstruction filter to increase the signal-to-noise ratio in dynamic PET imaging. It consists in a spatio-temporal robust diffusion of the 4D image based on the time activity curve (TAC) in each voxel. It reduces the noise in homogeneous areas while preserving the distinct kinetics in regions of interest corresponding to different underlying physiological processes. Neither anatomical priors nor the kinetic model are required. We propose an automatic selection of the scale parameter involved in the diffusion process based on a robust statistical analysis of the distances between TACs. The method is evaluated using Monte Carlo simulations of brain activity distributions. We demonstrate the usefulness of the method and its superior performance over two other post-reconstruction spatial and temporal filters. Our simulations suggest that the proposed method can be used to significantly increase the signal-to-noise ratio in dynamic PET imaging.

Wide Band Low Noise Love Wave Magnetic Field Sensor System.

Science.gov (United States)

Kittmann, Anne; Durdaut, Phillip; Zabel, Sebastian; Reermann, Jens; Schmalz, Julius; Spetzler, Benjamin; Meyners, Dirk; Sun, Nian X; McCord, Jeffrey; Gerken, Martina; Schmidt, Gerhard; Höft, Michael; Knöchel, Reinhard; Faupel, Franz; Quandt, Eckhard

2018-01-10

We present a comprehensive study of a magnetic sensor system that benefits from a new technique to substantially increase the magnetoelastic coupling of surface acoustic waves (SAW). The device uses shear horizontal acoustic surface waves that are guided by a fused silica layer with an amorphous magnetostrictive FeCoSiB thin film on top. The velocity of these so-called Love waves follows the magnetoelastically-induced changes of the shear modulus according to the magnetic field present. The SAW sensor is operated in a delay line configuration at approximately 150 MHz and translates the magnetic field to a time delay and a related phase shift. The fundamentals of this sensor concept are motivated by magnetic and mechanical simulations. They are experimentally verified using customized low-noise readout electronics. With an extremely low magnetic noise level of ≈100 pT/[Formula: see text], a bandwidth of 50 kHz and a dynamic range of 120 dB, this magnetic field sensor system shows outstanding characteristics. A range of additional measures to further increase the sensitivity are investigated with simulations.

Reconstruction dynamics of recorded holograms in photochromic glass

Energy Technology Data Exchange (ETDEWEB)

Mihailescu, Mona; Pavel, Eugen; Nicolae, Vasile B.

2011-06-20

We have investigated the dynamics of the record-erase process of holograms in photochromic glass using continuum Nd:YVO{sub 4} laser radiation ({lambda}=532 nm). A bidimensional microgrid pattern was formed and visualized in photochromic glass, and its diffraction efficiency decay versus time (during reconstruction step) gave us information (D, {Delta}n) about the diffusion process inside the material. The recording and reconstruction processes were carried out in an off-axis setup, and the images of the reconstructed object were recorded by a CCD camera. Measurements realized on reconstructed object images using holograms recorded at a different incident power laser have shown a two-stage process involved in silver atom kinetics.

Ultra Low Noise Poroelastic Road Surfaces

Directory of Open Access Journals (Sweden)

Jerzy A. Ejsmont

2016-04-01

Full Text Available Noise is one of the most important environmental problems related to road traffic. During the last decades, the noise emitted by the engines and powertrains of vehicles was greatly reduced and tires became a clearly dominant noise source. The article describes the concept of low noise poroelastic road surfaces that are composed of mineral and rubber aggregate bound by polyurethane resin. Those surfaces have a porous structure and are much more flexible than standard asphalt or cement concrete pavements due to high content of rubber aggregate and elastic binder. Measurements performed in several European countries indicate that such surfaces decrease tire/road noise between 7 dB and 12 dB with respect to reference surfaces such as dense asphalt concrete or stone matrix asphalt. Furthermore, poroelastic road surfaces ascertain the rolling resistance of car tires, which is comparable to classic pavements. One of the unforeseen properties of the poroelastic road surfaces is their ability to decrease the risks related to car fires with fuel spills. The article presents the road and laboratory results of noise, rolling resistance, and fire tests performed on a few types of poroelastic road surfaces.

Hybrid spectral CT reconstruction.

Directory of Open Access Journals (Sweden)

Darin P Clark

Full Text Available Current photon counting x-ray detector (PCD technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID. In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM. Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with

Hybrid spectral CT reconstruction

Science.gov (United States)

Clark, Darin P.

2017-01-01

Current photon counting x-ray detector (PCD) technology faces limitations associated with spectral fidelity and photon starvation. One strategy for addressing these limitations is to supplement PCD data with high-resolution, low-noise data acquired with an energy-integrating detector (EID). In this work, we propose an iterative, hybrid reconstruction technique which combines the spectral properties of PCD data with the resolution and signal-to-noise characteristics of EID data. Our hybrid reconstruction technique is based on an algebraic model of data fidelity which substitutes the EID data into the data fidelity term associated with the PCD reconstruction, resulting in a joint reconstruction problem. Within the split Bregman framework, these data fidelity constraints are minimized subject to additional constraints on spectral rank and on joint intensity-gradient sparsity measured between the reconstructions of the EID and PCD data. Following a derivation of the proposed technique, we apply it to the reconstruction of a digital phantom which contains realistic concentrations of iodine, barium, and calcium encountered in small-animal micro-CT. The results of this experiment suggest reliable separation and detection of iodine at concentrations ≥ 5 mg/ml and barium at concentrations ≥ 10 mg/ml in 2-mm features for EID and PCD data reconstructed with inherent spatial resolutions of 176 μm and 254 μm, respectively (point spread function, FWHM). Furthermore, hybrid reconstruction is demonstrated to enhance spatial resolution within material decomposition results and to improve low-contrast detectability by as much as 2.6 times relative to reconstruction with PCD data only. The parameters of the simulation experiment are based on an in vivo micro-CT experiment conducted in a mouse model of soft-tissue sarcoma. Material decomposition results produced from this in vivo data demonstrate the feasibility of distinguishing two K-edge contrast agents with a spectral

Assessment of noise reduction potential and image quality improvement of a new generation adaptive statistical iterative reconstruction (ASIR-V) in chest CT.

Science.gov (United States)

Tang, Hui; Yu, Nan; Jia, Yongjun; Yu, Yong; Duan, Haifeng; Han, Dong; Ma, Guangming; Ren, Chenglong; He, Taiping

2018-01-01

To evaluate the image quality improvement and noise reduction in routine dose, non-enhanced chest CT imaging by using a new generation adaptive statistical iterative reconstruction (ASIR-V) in comparison with ASIR algorithm. 30 patients who underwent routine dose, non-enhanced chest CT using GE Discovery CT750HU (GE Healthcare, Waukesha, WI) were included. The scan parameters included tube voltage of 120 kVp, automatic tube current modulation to obtain a noise index of 14HU, rotation speed of 0.6 s, pitch of 1.375:1 and slice thickness of 5 mm. After scanning, all scans were reconstructed with the recommended level of 40%ASIR for comparison purpose and different percentages of ASIR-V from 10% to 100% in a 10% increment. The CT attenuation values and SD of the subcutaneous fat, back muscle and descending aorta were measured at the level of tracheal carina of all reconstructed images. The signal-to-noise ratio (SNR) was calculated with SD representing image noise. The subjective image quality was independently evaluated by two experienced radiologists. For all ASIR-V images, the objective image noise (SD) of fat, muscle and aorta decreased and SNR increased along with increasing ASIR-V percentage. The SD of 30% ASIR-V to 100% ASIR-V was significantly lower than that of 40% ASIR (p ASIR-V reconstructions had good diagnostic acceptability. However, the 50% ASIR-V to 70% ASIR-V series showed significantly superior visibility of small structures when compared with the 40% ASIR and ASIR-V of other percentages (p ASIR-V was the best series of all ASIR-V images, with a highest subjective image quality. The image sharpness was significantly decreased in images reconstructed by 80% ASIR-V and higher. In routine dose, non-enhanced chest CT, ASIR-V shows greater potential in reducing image noise and artefacts and maintaining image sharpness when compared to the recommended level of 40%ASIR algorithm. Combining both the objective and subjective evaluation of images, non

Measurement of low-frequency noise in rooms

DEFF Research Database (Denmark)

Pedersen, Steffen; Møller, Henrik; Persson-Waye, Kerstin

2006-01-01

Measurement of low-frequency noise in rooms is problematic due to standing wave patterns. The spatial variation in the sound pressure level can typically be as much as 20-30 dB. For assessment of annoyance from low-frequency noise in dwellings, it is important to measure a level close...... rooms. The sound pressure level was measured 1) in three-dimensional corners and 2) according to current Swedish and Danish measurement methods. Furthermore, the entire sound pressure distributions were measured by scanning. The Swedish and Danish measurement methods include a corner measurement...... to the highest level present in a room, rather than a room average level. In order to ensure representative noise measurements, different positions were investigated based on theoretical considerations and observations from numerical room simulations. In addition measurements were performed in three different...

Ocean dynamic noise energy flux directivity in the 400 Hz to 700 Hz frequency band

Institute of Scientific and Technical Information of China (English)

Vladimir A. Shchurov; Galina F. Ivanova; Marianna V. Kuyanova; Helen S. Tkachenko

2007-01-01

Results of field studies of underwater dynamic noise energy flux directivity at two wind speeds, 6 m/s and 12 m/s, in the 400 Hz to 700 Hz frequency band in the deep open ocean are presented. The measurements were made by a freely drifting telemetric combined system at 500 m depth. Statistical characteristics of the horizontal and vertical dynamic noise energy flux directivity are considered as functions of wind speed and direction. Correlation between the horizontal dynamic noise energy flux direction and that of the wind was determined; a mechanism of the horizontal dynamic noise energy flux generation is related to the initial noise field scattering on ocean surface waves.

Low noise InP-based MMIC receivers for W-band

Science.gov (United States)

Leonard, Regis F.

1991-01-01

A program to develop a monolithic W-band low noise amplifier (a critical element in any W-band communications, sensors, or radar application) is described. Goals of the program include a completely monolithic low noise amplifier, less than a 3.5 dB noise figure, and a monolithic mixer suitable for integration with the LNA.

Effect of noise on estimation of Lyapunov exponents from a time series

Energy Technology Data Exchange (ETDEWEB)

Serletis, Apostolos [Department of Economics, University of Calgary, Calgary, Alta., T2N 1N4 (Canada)]. E-mail: http://econ.ucalgary.ca/serletis.htm; Shahmoradi, Asghar [Department of Economics, University of Calgary, Calgary, Alta., T2N 1N4 (Canada); Serletis, Demitre [Division of Neurosurgery, University of Toronto, Toronto, ON, M5G 1L5 (Canada)

2007-04-15

We argue that dynamical noise can dramatically change the dynamics of low-dimensional chaotic systems. Moreover, we show that chaos tests are highly sensitive to dynamical noise and this becomes worse when the intensity of the noise increases.

Predicting the Noise of High Power Fluid Targets Using Computational Fluid Dynamics

Science.gov (United States)

Moore, Michael; Covrig Dusa, Silviu

The 2.5 kW liquid hydrogen (LH2) target used in the Qweak parity violation experiment is the highest power LH2 target in the world and the first to be designed with Computational Fluid Dynamics (CFD) at Jefferson Lab. The Qweak experiment determined the weak charge of the proton by measuring the parity-violating elastic scattering asymmetry of longitudinally polarized electrons from unpolarized liquid hydrogen at small momentum transfer (Q2 = 0 . 025 GeV2). This target satisfied the design goals of bench-marked with the Qweak target data. This work is an essential component in future designs of very high power low noise targets like MOLLER (5 kW, target noise asymmetry contribution < 25 ppm) and MESA (4.5 kW).

Characterization and Impact of Low Frequency Wind Turbine Noise Emissions

Science.gov (United States)

Finch, James

Wind turbine noise is a complex issue that requires due diligence to minimize any potential impact on quality of life. This study enhances existing knowledge of wind turbine noise through focused analyses of downwind sound propagation, directionality, and the low frequency component of the noise. Measurements were conducted at four wind speeds according to a design of experiments at incremental distances and angles. Wind turbine noise is shown to be highly directional, while downwind sound propagation is spherical with limited ground absorption. The noise is found to have a significant low frequency component that is largely independent of wind speed over the 20-250 Hz range. The generated low frequency noise is shown to be audible above 40 Hz at the MOE setback distance of 550 m. Infrasound levels exhibit higher dependency on wind speed, but remain below audible levels up to 15 m/s.

Improved CEEMDAN-wavelet transform de-noising method and its application in well logging noise reduction

Science.gov (United States)

Zhang, Jingxia; Guo, Yinghai; Shen, Yulin; Zhao, Difei; Li, Mi

2018-06-01

The use of geophysical logging data to identify lithology is an important groundwork in logging interpretation. Inevitably, noise is mixed in during data collection due to the equipment and other external factors and this will affect the further lithological identification and other logging interpretation. Therefore, to get a more accurate lithological identification it is necessary to adopt de-noising methods. In this study, a new de-noising method, namely improved complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN)-wavelet transform, is proposed, which integrates the superiorities of improved CEEMDAN and wavelet transform. Improved CEEMDAN, an effective self-adaptive multi-scale analysis method, is used to decompose non-stationary signals as the logging data to obtain the intrinsic mode function (IMF) of N different scales and one residual. Moreover, one self-adaptive scale selection method is used to determine the reconstruction scale k. Simultaneously, given the possible frequency aliasing problem between adjacent IMFs, a wavelet transform threshold de-noising method is used to reduce the noise of the (k-1)th IMF. Subsequently, the de-noised logging data are reconstructed by the de-noised (k-1)th IMF and the remaining low-frequency IMFs and the residual. Finally, empirical mode decomposition, improved CEEMDAN, wavelet transform and the proposed method are applied for analysis of the simulation and the actual data. Results show diverse performance of these de-noising methods with regard to accuracy for lithological identification. Compared with the other methods, the proposed method has the best self-adaptability and accuracy in lithological identification.

External Peltier Cooler For Low-Noise Amplifier

Science.gov (United States)

Soper, Terry A.

1990-01-01

Inexpensive Peltier-effect cooling module made of few commercially available parts used to reduce thermal noise in microwave amplifier. Retrofitted to almost any microwave low-noise amplifier or receiver preamplifier used in communication, telemetry, or radar. Includes copper or aluminum cold plate held tightly against unit to be cooled by strap-type worm-gear clamps.

Regulation of Cortical Dynamic Range by Background Synaptic Noise and Feedforward Inhibition.

Science.gov (United States)

Khubieh, Ayah; Ratté, Stéphanie; Lankarany, Milad; Prescott, Steven A

2016-08-01

The cortex encodes a broad range of inputs. This breadth of operation requires sensitivity to weak inputs yet non-saturating responses to strong inputs. If individual pyramidal neurons were to have a narrow dynamic range, as previously claimed, then staggered all-or-none recruitment of those neurons would be necessary for the population to achieve a broad dynamic range. Contrary to this explanation, we show here through dynamic clamp experiments in vitro and computer simulations that pyramidal neurons have a broad dynamic range under the noisy conditions that exist in the intact brain due to background synaptic input. Feedforward inhibition capitalizes on those noise effects to control neuronal gain and thereby regulates the population dynamic range. Importantly, noise allows neurons to be recruited gradually and occludes the staggered recruitment previously attributed to heterogeneous excitation. Feedforward inhibition protects spike timing against the disruptive effects of noise, meaning noise can enable the gain control required for rate coding without compromising the precise spike timing required for temporal coding. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

A Tunable Low Noise Active Bandpass Filter Using a Noise Canceling Technique

Directory of Open Access Journals (Sweden)

N. Soltani

2016-12-01

Full Text Available A monolithic tunable low noise active bandpass filter is presented in this study. Biasing voltages can control the center frequency and quality factor. By keeping the gain constant, the center frequency shift is 300 MHz. The quality factor can range from 90 to 290 at the center frequency. By using a noise cancelling circuit, noise is kept lower than 2.8 dB. The proposed filter is designed using MMIC technology with a center frequency of 2.4 GHz and a power consumption of 180 mW. ED02AH technology is used to simulate the circuit elements.

Noise reduction by sparse representation in learned dictionaries for application to blind tip reconstruction problem

International Nuclear Information System (INIS)

Jóźwiak, Grzegorz

2017-01-01

Scanning probe microscopy (SPM) is a well known tool used for the investigation of phenomena in objects in the nanometer size range. However, quantitative results are limited by the size and the shape of the nanoprobe used in experiments. Blind tip reconstruction (BTR) is a very popular method used to reconstruct the upper boundary on the shape of the probe. This method is known to be very sensitive to all kinds of interference in the atomic force microscopy (AFM) image. Due to mathematical morphology calculus, the interference makes the BTR results biased rather than randomly disrupted. For this reason, the careful choice of methods used for image enhancement and denoising, as well as the shape of a calibration sample are very important. In the paper, the results of thorough investigations on the shape of a calibration standard are shown. A novel shape is proposed and a tool for the simulation of AFM images of this calibration standard was designed. It was shown that careful choice of the initial tip allows us to use images of hole structures to blindly reconstruct the shape of a probe. The simulator was used to test the impact of modern filtration algorithms on the BTR process. These techniques are based on sparse approximation with function dictionaries learned on the basis of an image itself. Various learning algorithms and parameters were tested to determine the optimal combination for sparse representation. It was observed that the strong reduction of noise does not guarantee strong reduction in reconstruction errors. It seems that further improvements will be possible by the combination of BTR and a noise reduction procedure. (paper)

A Denoising Scheme for Randomly Clustered Noise Removal in ICCD Sensing Image

Directory of Open Access Journals (Sweden)

Fei Wang

2017-01-01

Full Text Available An Intensified Charge-Coupled Device (ICCD image is captured by the ICCD image sensor in extremely low-light conditions. Its noise has two distinctive characteristics. (a Different from the independent identically distributed (i.i.d. noise in natural image, the noise in the ICCD sensing image is spatially clustered, which induces unexpected structure information; (b The pattern of the clustered noise is formed randomly. In this paper, we propose a denoising scheme to remove the randomly clustered noise in the ICCD sensing image. First, we decompose the image into non-overlapped patches and classify them into flat patches and structure patches according to if real structure information is included. Then, two denoising algorithms are designed for them, respectively. For each flat patch, we simulate multiple similar patches for it in pseudo-time domain and remove its noise by averaging all the simulated patches, considering that the structure information induced by the noise varies randomly over time. For each structure patch, we design a structure-preserved sparse coding algorithm to reconstruct the real structure information. It reconstructs each patch by describing it as a weighted summation of its neighboring patches and incorporating the weights into the sparse representation of the current patch. Based on all the reconstructed patches, we generate a reconstructed image. After that, we repeat the whole process by changing relevant parameters, considering that blocking artifacts exist in a single reconstructed image. Finally, we obtain the reconstructed image by merging all the generated images into one. Experiments are conducted on an ICCD sensing image dataset, which verifies its subjective performance in removing the randomly clustered noise and preserving the real structure information in the ICCD sensing image.

Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

International Nuclear Information System (INIS)

Brady, S. L.; Yee, B. S.; Kaufman, R. A.

2012-01-01

Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR™) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR™. Empirically derived dose reduction limits were established for ASiR™ for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%–100% ASiR™ blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR™ implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR™ reconstruction to maintain noise equivalence of the 0% ASiR™ image. Results: The ASiR™ algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR™ reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR™ presented a more smoothed appearance than the pre-ASiR™ 100% FBP image. Finally, relative to non-ASiR™ images with 100% of standard dose across the

Direct Patlak Reconstruction From Dynamic PET Data Using the Kernel Method With MRI Information Based on Structural Similarity.

Science.gov (United States)

Gong, Kuang; Cheng-Liao, Jinxiu; Wang, Guobao; Chen, Kevin T; Catana, Ciprian; Qi, Jinyi

2018-04-01

Positron emission tomography (PET) is a functional imaging modality widely used in oncology, cardiology, and neuroscience. It is highly sensitive, but suffers from relatively poor spatial resolution, as compared with anatomical imaging modalities, such as magnetic resonance imaging (MRI). With the recent development of combined PET/MR systems, we can improve the PET image quality by incorporating MR information into image reconstruction. Previously, kernel learning has been successfully embedded into static and dynamic PET image reconstruction using either PET temporal or MRI information. Here, we combine both PET temporal and MRI information adaptively to improve the quality of direct Patlak reconstruction. We examined different approaches to combine the PET and MRI information in kernel learning to address the issue of potential mismatches between MRI and PET signals. Computer simulations and hybrid real-patient data acquired on a simultaneous PET/MR scanner were used to evaluate the proposed methods. Results show that the method that combines PET temporal information and MRI spatial information adaptively based on the structure similarity index has the best performance in terms of noise reduction and resolution improvement.

Image-Based Reconstruction and Analysis of Dynamic Scenes in a Landslide Simulation Facility

Science.gov (United States)

Scaioni, M.; Crippa, J.; Longoni, L.; Papini, M.; Zanzi, L.

2017-12-01

The application of image processing and photogrammetric techniques to dynamic reconstruction of landslide simulations in a scaled-down facility is described. Simulations are also used here for active-learning purpose: students are helped understand how physical processes happen and which kinds of observations may be obtained from a sensor network. In particular, the use of digital images to obtain multi-temporal information is presented. On one side, using a multi-view sensor set up based on four synchronized GoPro 4 Black® cameras, a 4D (3D spatial position and time) reconstruction of the dynamic scene is obtained through the composition of several 3D models obtained from dense image matching. The final textured 4D model allows one to revisit in dynamic and interactive mode a completed experiment at any time. On the other side, a digital image correlation (DIC) technique has been used to track surface point displacements from the image sequence obtained from the camera in front of the simulation facility. While the 4D model may provide a qualitative description and documentation of the experiment running, DIC analysis output quantitative information such as local point displacements and velocities, to be related to physical processes and to other observations. All the hardware and software equipment adopted for the photogrammetric reconstruction has been based on low-cost and open-source solutions.

IMAGE-BASED RECONSTRUCTION AND ANALYSIS OF DYNAMIC SCENES IN A LANDSLIDE SIMULATION FACILITY

Directory of Open Access Journals (Sweden)

M. Scaioni

2017-12-01

Full Text Available The application of image processing and photogrammetric techniques to dynamic reconstruction of landslide simulations in a scaled-down facility is described. Simulations are also used here for active-learning purpose: students are helped understand how physical processes happen and which kinds of observations may be obtained from a sensor network. In particular, the use of digital images to obtain multi-temporal information is presented. On one side, using a multi-view sensor set up based on four synchronized GoPro 4 Black® cameras, a 4D (3D spatial position and time reconstruction of the dynamic scene is obtained through the composition of several 3D models obtained from dense image matching. The final textured 4D model allows one to revisit in dynamic and interactive mode a completed experiment at any time. On the other side, a digital image correlation (DIC technique has been used to track surface point displacements from the image sequence obtained from the camera in front of the simulation facility. While the 4D model may provide a qualitative description and documentation of the experiment running, DIC analysis output quantitative information such as local point displacements and velocities, to be related to physical processes and to other observations. All the hardware and software equipment adopted for the photogrammetric reconstruction has been based on low-cost and open-source solutions.

Ultralow dose dentomaxillofacial CT imaging and iterative reconstruction techniques: variability of Hounsfield units and contrast-to-noise ratio

Science.gov (United States)

Bischel, Alexander; Stratis, Andreas; Kakar, Apoorv; Bosmans, Hilde; Jacobs, Reinhilde; Gassner, Eva-Maria; Puelacher, Wolfgang; Pauwels, Ruben

2016-01-01

Objective: The aim of this study was to evaluate whether application of ultralow dose protocols and iterative reconstruction technology (IRT) influence quantitative Hounsfield units (HUs) and contrast-to-noise ratio (CNR) in dentomaxillofacial CT imaging. Methods: A phantom with inserts of five types of materials was scanned using protocols for (a) a clinical reference for navigated surgery (CT dose index volume 36.58 mGy), (b) low-dose sinus imaging (18.28 mGy) and (c) four ultralow dose imaging (4.14, 2.63, 0.99 and 0.53 mGy). All images were reconstructed using: (i) filtered back projection (FBP); (ii) IRT: adaptive statistical iterative reconstruction-50 (ASIR-50), ASIR-100 and model-based iterative reconstruction (MBIR); and (iii) standard (std) and bone kernel. Mean HU, CNR and average HU error after recalibration were determined. Each combination of protocols was compared using Friedman analysis of variance, followed by Dunn's multiple comparison test. Results: Pearson's sample correlation coefficients were all >0.99. Ultralow dose protocols using FBP showed errors of up to 273 HU. Std kernels had less HU variability than bone kernels. MBIR reduced the error value for the lowest dose protocol to 138 HU and retained the highest relative CNR. ASIR could not demonstrate significant advantages over FBP. Conclusions: Considering a potential dose reduction as low as 1.5% of a std protocol, ultralow dose protocols and IRT should be further tested for clinical dentomaxillofacial CT imaging. Advances in knowledge: HU as a surrogate for bone density may vary significantly in CT ultralow dose imaging. However, use of std kernels and MBIR technology reduce HU error values and may retain the highest CNR. PMID:26859336

Impact of environmental colored noise in single-species population dynamics

Science.gov (United States)

Spanio, Tommaso; Hidalgo, Jorge; Muñoz, Miguel A.

2017-10-01

Variability on external conditions has important consequences for the dynamics and the organization of biological systems. In many cases, the characteristic timescale of environmental changes as well as their correlations play a fundamental role in the way living systems adapt and respond to it. A proper mathematical approach to understand population dynamics, thus, requires approaches more refined than, e.g., simple white-noise approximations. To shed further light onto this problem, in this paper we propose a unifying framework based on different analytical and numerical tools available to deal with "colored" environmental noise. In particular, we employ a "unified colored noise approximation" to map the original problem into an effective one with white noise, and then we apply a standard path integral approach to gain analytical understanding. For the sake of specificity, we present our approach using as a guideline a variation of the contact process—which can also be seen as a birth-death process of the Malthus-Verhulst class—where the propagation or birth rate varies stochastically in time. Our approach allows us to tackle in a systematic manner some of the relevant questions concerning population dynamics under environmental variability, such as determining the stationary population density, establishing the conditions under which a population may become extinct, and estimating extinction times. We focus on the emerging phase diagram and its possible phase transitions, underlying how these are affected by the presence of environmental noise time-correlations.

Feasibility of low-dose CT with model-based iterative image reconstruction in follow-up of patients with testicular cancer

International Nuclear Information System (INIS)

Murphy, Kevin P.; Crush, Lee; O’Neill, Siobhan B.; Foody, James; Breen, Micheál; Brady, Adrian; Kelly, Paul J.; Power, Derek G.; Sweeney, Paul; Bye, Jackie; O’Connor, Owen J.; Maher, Michael M.; O’Regan, Kevin N.

2016-01-01

•Radiologists should endeavour to minimise radiation exposure to patients with testicular cancer.•Iterative reconstruction algorithms permit CT imaging at lower radiation doses.•Image quality for reduced-dose CT–MBIR is at least comparable to conventional dose.•No loss of diagnostic accuracy apparent with reduced-dose CT–MBIR. Radiologists should endeavour to minimise radiation exposure to patients with testicular cancer. Iterative reconstruction algorithms permit CT imaging at lower radiation doses. Image quality for reduced-dose CT–MBIR is at least comparable to conventional dose. No loss of diagnostic accuracy apparent with reduced-dose CT–MBIR. We examine the performance of pure model-based iterative reconstruction with reduced-dose CT in follow-up of patients with early-stage testicular cancer. Sixteen patients (mean age 35.6 ± 7.4 years) with stage I or II testicular cancer underwent conventional dose (CD) and low-dose (LD) CT acquisition during CT surveillance. LD data was reconstructed with model-based iterative reconstruction (LD–MBIR). Datasets were objectively and subjectively analysed at 8 anatomical levels. Two blinded clinical reads were compared to gold-standard assessment for diagnostic accuracy. Mean radiation dose reduction of 67.1% was recorded. Mean dose measurements for LD–MBIR were: thorax – 66 ± 11 mGy cm (DLP), 1.0 ± 0.2 mSv (ED), 2.0 ± 0.4 mGy (SSDE); abdominopelvic – 128 ± 38 mGy cm (DLP), 1.9 ± 0.6 mSv (ED), 3.0 ± 0.6 mGy (SSDE). Objective noise and signal-to-noise ratio values were comparable between the CD and LD–MBIR images. LD–MBIR images were superior (p < 0.001) with regard to subjective noise, streak artefact, 2-plane contrast resolution, 2-plane spatial resolution and diagnostic acceptability. All patients were correctly categorised as positive, indeterminate or negative for metastatic disease by 2 readers on LD–MBIR and CD datasets. MBIR facilitated a 67% reduction in radiation dose whilst

Reconstruction of dynamical systems from interspike intervals

International Nuclear Information System (INIS)

Sauer, T.

1994-01-01

Attractor reconstruction from interspike interval (ISI) data is described, in rough analogy with Taken's theorem for attractor reconstruction from time series. Assuming a generic integrate-and-fire model coupling the dynamical system to the spike train, there is a one-to-one correspondence between the system states and interspike interval vectors of sufficiently large dimension. The correspondence has an important implication: interspike intervals can be forecast from past history. We show that deterministically driven ISI series can be distinguished from stochastically driven ISI series on the basis of prediction error

NASA's Pursuit of Low-Noise Propulsion for Low-Boom Commercial Supersonic Vehicles

Science.gov (United States)

Bridges, James; Brown, Clifford A.; Seidel, Jonathan A.

2018-01-01

Since 2006, when the Fundamental Aeronautics Program was instituted within NASA's Aeronautics Mission Directorate, there has been a Project looking at the technical barriers to commercial supersonic flight. Among the barriers is the noise produced by aircraft during landing and takeoff. Over the years that followed, research was carried out at NASA aeronautics research centers, often in collaboration with academia and industry, addressing the problem. In 2013, a high-level milestone was established, described as a Technical Challenge, with the objective of demonstrating the feasibility of a low-boom supersonic airliner that could meet current airport noise regulations. The Technical Challenge was formally called "Low Noise Propulsion for Low Boom Aircraft", and was completed in late 2016. This paper reports the technical findings from this Technical Challenge, reaching back almost 10 years to review the technologies and tools that were developed along the way. It also discusses the final aircraft configuration and propulsion systems required for a supersonic civilian aircraft to meet noise regulations using the technologies available today. Finally, the paper documents the model-scale tests that validated the acoustic performance of the study aircraft.

Effects on Performance and Work Quality due to Low Frequency Ventilation Noise

Science.gov (United States)

Persson Waye, K.; Rylander, R.; Benton, S.; Leventhall, H. G.

1997-08-01

A pilot study was carried out to assess method evaluating effects of low frequency noise on performance. Of special interest was to study objective and subjective effects over time. Two ventilation noises were used, one of a predominantly mid frequency character and the other of a predominantly low frequency character. Both had an NC value of 35. For the study, 50 students were recruited and 30 selected on the basis of subjective reports of pressure on the eardrum after exposure to a low frequency noise. Of these, 14 randomly selected subjects aged 21 and 34 took part. The subjects performed three computerized cognitive tests in the mid frequency or the low frequency noise condition alternatively. Tests I and II were performed together with a secondary task.Questionnaires were used to evaluate subjective symptoms, effects on mood and estimated interference with the test results due to temperature, light and noise. The results showed that the subjective estimations of noise interference with performance were higher for the low frequency noise (psocial orientation (pstudied. The results further indicate that the NC curves do not fully assess the negative effects of low frequency noise on work performance.

Evaluation of analytical reconstruction with a new gap-filling method in comparison to iterative reconstruction in [11C]-raclopride PET studies

International Nuclear Information System (INIS)

Tuna, U.; Johansson, J.; Ruotsalainen, U.

2014-01-01

The aim of the study was (1) to evaluate the reconstruction strategies with dynamic [ 11 C]-raclopride human positron emission tomography (PET) studies acquired from ECAT high-resolution research tomograph (HRRT) scanner and (2) to justify for the selected gap-filling method for analytical reconstruction with simulated phantom data. A new transradial bicubic interpolation method has been implemented to enable faster analytical 3D-reprojection (3DRP) reconstructions for the ECAT HRRT PET scanner data. The transradial bicubic interpolation method was compared to the other gap-filling methods visually and quantitatively using the numerical Shepp-Logan phantom. The performance of the analytical 3DRP reconstruction method with this new gap-filling method was evaluated in comparison with the iterative statistical methods: ordinary Poisson ordered subsets expectation maximization (OPOSEM) and resolution modeled OPOSEM methods. The image reconstruction strategies were evaluated using human data at different count statistics and consequently at different noise levels. In the assessments, 14 [ 11 C]-raclopride dynamic PET studies (test-retest studies of 7 healthy subjects) acquired from the HRRT PET scanner were used. Besides the visual comparisons of the methods, we performed regional quantitative evaluations over the cerebellum, caudate and putamen structures. We compared the regional time-activity curves (TACs), areas under the TACs and binding potential (BP ND ) values. The results showed that the new gap-filling method preserves the linearity of the 3DRP method. Results with the 3DRP after gap-filling method exhibited hardly any dependency on the count statistics (noise levels) in the sinograms while we observed changes in the quantitative results with the EM-based methods for different noise contamination in the data. With this study, we showed that 3DRP with transradial bicubic gap-filling method is feasible for the reconstruction of high-resolution PET data with

Iterative Reconstruction Techniques in Abdominopelvic CT: Technical Concepts and Clinical Implementation.

Science.gov (United States)

Patino, Manuel; Fuentes, Jorge M; Singh, Sarabjeet; Hahn, Peter F; Sahani, Dushyant V

2015-07-01

This article discusses the clinical challenge of low-radiation-dose examinations, the commonly used approaches for dose optimization, and their effect on image quality. We emphasize practical aspects of the different iterative reconstruction techniques, along with their benefits, pitfalls, and clinical implementation. The widespread use of CT has raised concerns about potential radiation risks, motivating diverse strategies to reduce the radiation dose associated with CT. CT manufacturers have developed alternative reconstruction algorithms intended to improve image quality on dose-optimized CT studies, mainly through noise and artifact reduction. Iterative reconstruction techniques take unique approaches to noise reduction and provide distinct strength levels or settings.

Reconstructing the competitive dynamics of mixed-oak neighborhoods

Science.gov (United States)

Eric K. Zenner; Daniel J. Heggenstaller; Patrick H. Brose; JeriLynn E. Peck; Kim C. Steiner

2012-01-01

The disparity between the potential for latent oak dominance within a stand and their region-wide decline in importance value raises questions about the competitiveness of oaks in early stand dynamics. We reconstructed tree height growth dynamics in mixed-species neighborhoods to determine if currently dominant oaks were ever shorter than their competitors and at what...

Evaluation of noise and blur effects with SIRT-FISTA-TV reconstruction algorithm: Application to fast environmental transmission electron tomography.

Science.gov (United States)

Banjak, Hussein; Grenier, Thomas; Epicier, Thierry; Koneti, Siddardha; Roiban, Lucian; Gay, Anne-Sophie; Magnin, Isabelle; Peyrin, Françoise; Maxim, Voichita

2018-06-01

Fast tomography in Environmental Transmission Electron Microscopy (ETEM) is of a great interest for in situ experiments where it allows to observe 3D real-time evolution of nanomaterials under operating conditions. In this context, we are working on speeding up the acquisition step to a few seconds mainly with applications on nanocatalysts. In order to accomplish such rapid acquisitions of the required tilt series of projections, a modern 4K high-speed camera is used, that can capture up to 100 images per second in a 2K binning mode. However, due to the fast rotation of the sample during the tilt procedure, noise and blur effects may occur in many projections which in turn would lead to poor quality reconstructions. Blurred projections make classical reconstruction algorithms inappropriate and require the use of prior information. In this work, a regularized algebraic reconstruction algorithm named SIRT-FISTA-TV is proposed. The performance of this algorithm using blurred data is studied by means of a numerical blur introduced into simulated images series to mimic possible mechanical instabilities/drifts during fast acquisitions. We also present reconstruction results from noisy data to show the robustness of the algorithm to noise. Finally, we show reconstructions with experimental datasets and we demonstrate the interest of fast tomography with an ultra-fast acquisition performed under environmental conditions, i.e. gas and temperature, in the ETEM. Compared to classically used SIRT and SART approaches, our proposed SIRT-FISTA-TV reconstruction algorithm provides higher quality tomograms allowing easier segmentation of the reconstructed volume for a better final processing and analysis. Copyright © 2018 Elsevier B.V. All rights reserved.

Design of low noise transimpedance amplifier for intravascular ultrasound

KAUST Repository

Reda, Dina

2009-11-01

In this paper, we study transimpedance amplifiers for capacitive sensing applications with a focus on Intravascular Ultra Sound (IVUS). We employ RF noise cancellation technique on capacitive feedback based transimpedance amplifiers. This technique eliminates the input-referred noise of TIAs completely and enhances the dynamic range of front-end electronics. Simulation results verify the proposed technique used in two different TIA topologies employing shunt-shunt feedback. ©2009 IEEE.

The Majorana Low-noise Low-background Front-end Electronics

Science.gov (United States)

Abgrall, N.; Aguayo, E.; Avignone, F. T.; Barabash, A. S.; Bertrand, F. E.; Boswell, M.; Brudanin, V.; Busch, M.; Byram, D.; Caldwell, A. S.; Chan, Y.-D.; Christofferson, C. D.; Combs, D. C.; Cuesta, C.; Detwiler, J. A.; Doe, P. J.; Efremenko, Yu.; Egorov, V.; Ejiri, H.; Elliott, S. R.; Fast, J. E.; Finnerty, P.; Fraenkle, F. M.; Galindo-Uribarri, A.; Giovanetti, G. K.; Goett, J.; Green, M. P.; Gruszko, J.; Guiseppe, V. E.; Gusev, K.; Hallin, A. L.; Hazama, R.; Hegai, A.; Henning, R.; Hoppe, E. W.; Howard, S.; Howe, M. A.; Keeter, K. J.; Kidd, M. F.; Kochetov, O.; Konovalov, S. I.; Kouzes, R. T.; LaFerriere, B. D.; Leon, J.; Leviner, L. E.; Loach, J. C.; MacMullin, J.; MacMullin, S.; Martin, R. D.; Meijer, S.; Mertens, S.; Nomachi, M.; Orrell, J. L.; O'Shaughnessy, C.; Overman, N. R.; Phillips, D. G.; Poon, A. W. P.; Pushkin, K.; Radford, D. C.; Rager, J.; Rielage, K.; Robertson, R. G. H.; Romero-Romero, E.; Ronquest, M. C.; Schubert, A. G.; Shanks, B.; Shima, T.; Shirchenko, M.; Snavely, K. J.; Snyder, N.; Suriano, A. M.; Thompson, J.; Timkin, V.; Tornow, W.; Trimble, J. E.; Varner, R. L.; Vasilyev, S.; Vetter, K.; Vorren, K.; White, B. R.; Wilkerson, J. F.; Wiseman, C.; Xu, W.; Yakushev, E.; Young, A. R.; Yu, C.-H.; Yumatov, V.

The MAJORANA DEMONSTRATOR will search for the neutrinoless double beta decay (ββ(0ν)) of the isotope 76Ge with a mixed array of enriched and natural germanium detectors. In view of the next generation of tonne-scale germanium-based ββ(0ν)-decay searches, a major goal of the MAJORANA DEMONSTRATOR is to demonstrate a path forward to achieving a background rate at or below 1 cnt/(ROI-t-y) in the 4 keV region of interest (ROI) around the 2039-keV Q-value of the 76Ge ββ(0ν)-decay. Such a requirement on the background level significantly constrains the design of the readout electronics, which is further driven by noise and energy resolution performances. We present here the low-noise low- background front-end electronics developed for the low-capacitance p-type point contact (P-PC) germanium detectors of the MAJORANA DEMONSTRATOR. This resistive-feedback front-end, specifically designed to have low mass, is fabricated on a radioassayed fused-silica substrate where the feedback resistor consists of a sputtered thin film of high purity amorphous germanium and the feedback capacitor is based on the capacitance between gold conductive traces.

Neutral dynamics with environmental noise: Age-size statistics and species lifetimes

Science.gov (United States)

Kessler, David; Suweis, Samir; Formentin, Marco; Shnerb, Nadav M.

2015-08-01

Neutral dynamics, where taxa are assumed to be demographically equivalent and their abundance is governed solely by the stochasticity of the underlying birth-death process, has proved itself as an important minimal model that accounts for many empirical datasets in genetics and ecology. However, the restriction of the model to demographic [O (√{N }) ] noise yields relatively slow dynamics that appears to be in conflict with both short-term and long-term characteristics of the observed systems. Here we analyze two of these problems—age-size relationships and species extinction time—in the framework of a neutral theory with both demographic and environmental stochasticity. It turns out that environmentally induced variations of the demographic rates control the long-term dynamics and modify dramatically the predictions of the neutral theory with demographic noise only, yielding much better agreement with empirical data. We consider two prototypes of "zero mean" environmental noise, one which is balanced with regard to the arithmetic abundance, another balanced in the logarithmic (fitness) space, study their species lifetime statistics, and discuss their relevance to realistic models of community dynamics.

Low-noise audio amplifiers and preamplifier for use with intrinsic thermocouples

International Nuclear Information System (INIS)

Langner, G.C.; Sachs, R.D.; Stewart, F.L.

1979-03-01

Two simple, low-noise audio amplifiers and one low-noise preamplifier for use with intrinsic thermocouples were designed, built, and tested. The amplifiers and the preamplifier have different front end designs. One amplifier uses ultralow-noise operational amplifiers; the other amplifier uses a hybrid component. The preamplifier uses ultralow-noise discrete components. The amplifiers' equivalent noise inputs, at maximum gain, are 4.09 nV and 50 nV; the preamplifier's input is 4.05 μV. Their bandwidths are 15 600 Hz, 550 Hz, and 174 kHz, respectively. the amplifiers' equivalent noise inputs were measured from approx. 0 to 100 Hz, whereas the preamplifier's equivalent noise input was measured from approx. 0 to 174 kHz

An ultra low noise AC beam transformer for deceleration and diagnostics of low intensity beams

CERN Document Server

González, C

1999-01-01

The design of a broad band ultra-low noise ferrite loaded AC beam transformer is presented. It is designed for use in the CERN Antiproton Decelerator (AD), where beams of a few 107 charges must be decelerated from 3.5 GeV/c to 100 MeV/c. It is used in the RF beam-phase loop, and for intensity and bunch shape measurements during deceleration. When the beam is debunched for cooling on magnetic flat tops, the pick-up is used for measurements of intensity and momentum distribution by means of longitudinal Schottky scans. When used as Schottky pick-up, the signal to noise ratio should be better by about 40 dB than the existing stripline based longitudinal Schottky pick-up. The integrated design of pick-up and associated low-noise amplifier is presented. The achieved noise performance of a few from 1 to 3 MHz is obtained by attaching a low-noise, high-impedance silicon JFET (junction field effect transistor) amplifier to a high-Q resonant ferrite loaded cavity, and then eliminating the resonant response by low-nois...

The optimal monochromatic spectral computed tomographic imaging plus adaptive statistical iterative reconstruction algorithm can improve the superior mesenteric vessel image quality

Energy Technology Data Exchange (ETDEWEB)

Yin, Xiao-Ping; Zuo, Zi-Wei; Xu, Ying-Jin; Wang, Jia-Ning [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Liu, Huai-Jun, E-mail: hebeiliu@outlook.com [Department of Medical Imaging, The Second Hospital of Hebei Medical University, Shijiazhuang, Hebei, 050000 (China); Liang, Guang-Lu [CT/MRI room, Affiliated Hospital of Hebei University, Baoding, Hebei, 071000 (China); Gao, Bu-Lang, E-mail: browngao@163.com [Department of Medical Research, Shijiazhuang First Hospital, Shijiazhuang, Hebei, 050011 (China)

2017-04-15

Objective: To investigate the effect of the optimal monochromatic spectral computed tomography (CT) plus adaptive statistical iterative reconstruction on the improvement of the image quality of the superior mesenteric artery and vein. Materials and methods: The gemstone spectral CT angiographic data of 25 patients were reconstructed in the following three groups: 70 KeV, the optimal monochromatic imaging, and the optimal monochromatic plus 40%iterative reconstruction mode. The CT value, image noises (IN), background CT value and noises, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR) and image scores of the vessels and surrounding tissues were analyzed. Results: In the 70 KeV, the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group, the mean scores of image quality were 3.86, 4.24 and 4.25 for the superior mesenteric artery and 3.46, 3.78 and 3.81 for the superior mesenteric vein, respectively. The image quality scores for the optimal monochromatic and the optimal monochromatic plus 40% iterative reconstruction groups were significantly greater than for the 70 KeV group (P < 0.05). The vascular CT value, image noise, background noise, CNR and SNR were significantly (P < 0.001) greater in the optimal monochromatic and the optimal monochromatic images plus 40% iterative reconstruction group than in the 70 KeV group. The optimal monochromatic plus 40% iterative reconstruction group had significantly (P < 0.05) lower image and background noise but higher CNR and SNR than the other two groups. Conclusion: The optimal monochromatic imaging combined with 40% iterative reconstruction using low-contrast agent dosage and low injection rate can significantly improve the image quality of the superior mesenteric artery and vein.

Low-noise kinetic inductance traveling-wave amplifier using three-wave mixing

Energy Technology Data Exchange (ETDEWEB)

Vissers, M. R.; Erickson, R. P.; Ku, H.-S.; Vale, Leila; Wu, Xian; Hilton, G. C.; Pappas, D. P., E-mail: David.Pappas@NIST.gov [National Institute of Standards and Technology, Boulder, Colorado 80305 (United States)

2016-01-04

We have fabricated a wide-bandwidth, high dynamic range, low-noise cryogenic amplifier based on a superconducting kinetic inductance traveling-wave device. The device was made from NbTiN and consisted of a long, coplanar waveguide on a silicon chip. By adding a DC current and an RF pump tone, we are able to generate parametric amplification using three-wave mixing (3WM). The devices exhibit gain of more than 15 dB across an instantaneous bandwidth from 4 to 8 GHz. The total usable gain bandwidth, including both sides of the signal-idler gain region, is more than 6 GHz. The noise referred to the input of the devices approaches the quantum limit, with less than 1 photon excess noise. We compare these results directly to the four-wave mixing amplification mode, i.e., without DC-biasing. We find that the 3WM mode allows operation with the pump at lower RF power and at frequencies far from the signal. We have used this knowledge to redesign the amplifiers to utilize primarily 3WM amplification, thereby allowing for direct integration into large scale qubit and detector applications.

Low-noise kinetic inductance traveling-wave amplifier using three-wave mixing

Science.gov (United States)

Vissers, M. R.; Erickson, R. P.; Ku, H.-S.; Vale, Leila; Wu, Xian; Hilton, G. C.; Pappas, D. P.

2016-01-01

We have fabricated a wide-bandwidth, high dynamic range, low-noise cryogenic amplifier based on a superconducting kinetic inductance traveling-wave device. The device was made from NbTiN and consisted of a long, coplanar waveguide on a silicon chip. By adding a DC current and an RF pump tone, we are able to generate parametric amplification using three-wave mixing (3WM). The devices exhibit gain of more than 15 dB across an instantaneous bandwidth from 4 to 8 GHz. The total usable gain bandwidth, including both sides of the signal-idler gain region, is more than 6 GHz. The noise referred to the input of the devices approaches the quantum limit, with less than 1 photon excess noise. We compare these results directly to the four-wave mixing amplification mode, i.e., without DC-biasing. We find that the 3WM mode allows operation with the pump at lower RF power and at frequencies far from the signal. We have used this knowledge to redesign the amplifiers to utilize primarily 3WM amplification, thereby allowing for direct integration into large scale qubit and detector applications.

Ultra-low-dose lung screening CT with model-based iterative reconstruction: an assessment of image quality and lesion conspicuity.

Science.gov (United States)

Ju, Yun Hye; Lee, Geewon; Lee, Ji Won; Hong, Seung Baek; Suh, Young Ju; Jeong, Yeon Joo

2018-05-01

Background Reducing radiation dose inevitably increases image noise, and thus, it is important in low-dose computed tomography (CT) to maintain image quality and lesion detection performance. Purpose To assess image quality and lesion conspicuity of ultra-low-dose CT with model-based iterative reconstruction (MBIR) and to determine a suitable protocol for lung screening CT. Material and Methods A total of 120 heavy smokers underwent lung screening CT and were randomly and equally assigned to one of five groups: group 1 = 120 kVp, 25 mAs, with FBP reconstruction; group 2 = 120 kVp, 10 mAs, with MBIR; group 3 = 100 kVp, 15 mAs, with MBIR; group 4 = 100 kVp, 10 mAs, with MBIR; and group 5 = 100 kVp, 5 mAs, with MBIR. Two radiologists evaluated intergroup differences with respect to radiation dose, image noise, image quality, and lesion conspicuity using the Kruskal-Wallis test and the Chi-square test. Results Effective doses were 61-87% lower in groups 2-5 than in group 1. Image noises in groups 1 and 5 were significantly higher than in the other groups ( P image quality was best in group 1, but diagnostic acceptability of overall image qualities in groups 1-3 was not significantly different (all P values > 0.05). Lesion conspicuities were similar in groups 1-4, but were significantly poorer in group 5. Conclusion Lung screening CT with MBIR obtained at 100 kVp and 15 mAs enables a ∼60% reduction in radiation dose versus low-dose CT, while maintaining image quality and lesion conspicuity.

Numerical simulation of nonlinear dynamical systems driven by commutative noise

International Nuclear Information System (INIS)

Carbonell, F.; Biscay, R.J.; Jimenez, J.C.; Cruz, H. de la

2007-01-01

The local linearization (LL) approach has become an effective technique for the numerical integration of ordinary, random and stochastic differential equations. One of the reasons for this success is that the LL method achieves a convenient trade-off between numerical stability and computational cost. Besides, the LL method reproduces well the dynamics of nonlinear equations for which other classical methods fail. However, in the stochastic case, most of the reported works has been focused in Stochastic Differential Equations (SDE) driven by additive noise. This limits the applicability of the LL method since there is a number of interesting dynamics observed in equations with multiplicative noise. On the other hand, recent results show that commutative noise SDEs can be transformed into a random differential equation (RDE) by means of a random diffeomorfism (conjugacy). This paper takes advantages of such conjugacy property and the LL approach for defining a LL scheme for SDEs driven by commutative noise. The performance of the proposed method is illustrated by means of numerical simulations

Signal and noise modeling in confocal laser scanning fluorescence microscopy.

Science.gov (United States)

Herberich, Gerlind; Windoffer, Reinhard; Leube, Rudolf E; Aach, Til

2012-01-01

Fluorescence confocal laser scanning microscopy (CLSM) has revolutionized imaging of subcellular structures in biomedical research by enabling the acquisition of 3D time-series of fluorescently-tagged proteins in living cells, hence forming the basis for an automated quantification of their morphological and dynamic characteristics. Due to the inherently weak fluorescence, CLSM images exhibit a low SNR. We present a novel model for the transfer of signal and noise in CLSM that is both theoretically sound as well as corroborated by a rigorous analysis of the pixel intensity statistics via measurement of the 3D noise power spectra, signal-dependence and distribution. Our model provides a better fit to the data than previously proposed models. Further, it forms the basis for (i) the simulation of the CLSM imaging process indispensable for the quantitative evaluation of CLSM image analysis algorithms, (ii) the application of Poisson denoising algorithms and (iii) the reconstruction of the fluorescence signal.

Measuring low-frequency noise indoors

DEFF Research Database (Denmark)

Pedersen, Steffen; Møller, Henrik; Persson-Waye, Kerstin

2008-01-01

that is exceeded in 10% of the volume of a room (L10) is proposed as a rational and objective target for a measurement method. In Sweden and Denmark rules exist for measuring low-frequency noise indoors. The performance of these procedures was investigated in three rooms. The results from the Swedish method were...

A Low Noise Electronic Circuit

NARCIS (Netherlands)

Annema, Anne J.; Leenaerts, Dominicus M.W.; de Vreede, Petrus W.H.

2002-01-01

An electronic circuit, which can be used as a Low Noise Amplifier (LNA), comprises two complementary Field Effect Transistors (M1, M2; M5, M6), each having a gate, a source and a drain. The gates are connected together as a common input terminal, and the drains are connected together as a

Influence of ASIR (Adaptative Statistical Iterative Reconstruction) variation in the image noise of computerized tomography for high voltage

International Nuclear Information System (INIS)

Mendes, L.M.M.; Pereira, W.B.R.; Vieira, J.G.; Lamounier, C.S.; Gonçalves, D.A.; Carvalho, G.N.P.; Santana, P.C.; Oliveira, P.M.C.; Reis, L.P.

2017-01-01

Computed tomography had great advances in the equipment used in the diagnostic practice, directly influencing the levels of radiation for the patient. It is essential to optimize techniques that must be employed to comply with the ALARA (As Low As Reasonably Achievable) principle of radioprotection. The relationship of ASIR (Adaptive Statistical Iterative Reconstruction) with image noise was studied. Central images of a homogeneous water simulator were obtained in a 20 mm scan using a 64-channel Lightspeed VCT tomograph of General Electric in helical acquisitions with a rotation time of 0.5 seconds, Pitch 0.984: 1, and thickness of cut 0.625 mm. All these constant parameters varying the voltage in two distinct values: 120 and 140 kV with use of the automatic current by the CAE (Automatic Exposure Control), ranging from 50 to 675 mA (120 kV) and from 50 to 610 mA (140kV), minimum and maximum values, respectively allowed for each voltage. Image noise was determined through ImageJ free software. The analysis of the obtained data compared the percentage variation of the noise in the image based on the ASIR value of 10%, concluding that there is a variation of approximately 50% when compared to the values of ASIR (100%) in both tensions. Dose evaluation is required in future studies to better utilize the relationship between dose and image quality

Noise simulation in cone beam CT imaging with parallel computing

International Nuclear Information System (INIS)

Tu, S.-J.; Shaw, Chris C; Chen, Lingyun

2006-01-01

We developed a computer noise simulation model for cone beam computed tomography imaging using a general purpose PC cluster. This model uses a mono-energetic x-ray approximation and allows us to investigate three primary performance components, specifically quantum noise, detector blurring and additive system noise. A parallel random number generator based on the Weyl sequence was implemented in the noise simulation and a visualization technique was accordingly developed to validate the quality of the parallel random number generator. In our computer simulation model, three-dimensional (3D) phantoms were mathematically modelled and used to create 450 analytical projections, which were then sampled into digital image data. Quantum noise was simulated and added to the analytical projection image data, which were then filtered to incorporate flat panel detector blurring. Additive system noise was generated and added to form the final projection images. The Feldkamp algorithm was implemented and used to reconstruct the 3D images of the phantoms. A 24 dual-Xeon PC cluster was used to compute the projections and reconstructed images in parallel with each CPU processing 10 projection views for a total of 450 views. Based on this computer simulation system, simulated cone beam CT images were generated for various phantoms and technique settings. Noise power spectra for the flat panel x-ray detector and reconstructed images were then computed to characterize the noise properties. As an example among the potential applications of our noise simulation model, we showed that images of low contrast objects can be produced and used for image quality evaluation

Chaotic dynamics of flexible beams driven by external white noise

Science.gov (United States)

Awrejcewicz, J.; Krysko, A. V.; Papkova, I. V.; Zakharov, V. M.; Erofeev, N. P.; Krylova, E. Yu.; Mrozowski, J.; Krysko, V. A.

2016-10-01

Mathematical models of continuous structural members (beams, plates and shells) subjected to an external additive white noise are studied. The structural members are considered as systems with infinite number of degrees of freedom. We show that in mechanical structural systems external noise can not only lead to quantitative changes in the system dynamics (that is obvious), but also cause the qualitative, and sometimes surprising changes in the vibration regimes. Furthermore, we show that scenarios of the transition from regular to chaotic regimes quantified by Fast Fourier Transform (FFT) can lead to erroneous conclusions, and a support of the wavelet analysis is needed. We have detected and illustrated the modifications of classical three scenarios of transition from regular vibrations to deterministic chaos. The carried out numerical experiment shows that the white noise lowers the threshold for transition into spatio-temporal chaotic dynamics. A transition into chaos via the proposed modified scenarios developed in this work is sensitive to small noise and significantly reduces occurrence of periodic vibrations. Increase of noise intensity yields decrease of the duration of the laminar signal range, i.e., time between two successive turbulent bursts decreases. Scenario of transition into chaos of the studied mechanical structures essentially depends on the control parameters, and it can be different in different zones of the constructed charts (control parameter planes). Furthermore, we found an interesting phenomenon, when increase of the noise intensity yields surprisingly the vibrational characteristics with a lack of noisy effect (chaos is destroyed by noise and windows of periodicity appear).

Numerical results on noise-induced dynamics in the subthreshold regime for thermoacoustic systems

Science.gov (United States)

Gupta, Vikrant; Saurabh, Aditya; Paschereit, Christian Oliver; Kabiraj, Lipika

2017-03-01

Thermoacoustic instability is a serious issue in practical combustion systems. Such systems are inherently noisy, and hence the influence of noise on the dynamics of thermoacoustic instability is an aspect of practical importance. The present work is motivated by a recent report on the experimental observation of coherence resonance, or noise-induced coherence with a resonance-like dependence on the noise intensity as the system approaches the stability margin, for a prototypical premixed laminar flame combustor (Kabiraj et al., Phys. Rev. E, 4 (2015)). We numerically investigate representative thermoacoustic models for such noise-induced dynamics. Similar to the experiments, we study variation in system dynamics in response to variations in the noise intensity and in a critical control parameter as the systems approach their stability margins. The qualitative match identified between experimental results and observations in the representative models investigated here confirms that coherence resonance is a feature of thermoacoustic systems. We also extend the experimental results, which were limited to the case of subcritical Hopf bifurcation, to the case of supercritical Hopf bifurcation. We identify that the phenomenon has qualitative differences for the systems undergoing transition via subcritical and supercritical Hopf bifurcations. Two important practical implications are associated with the findings. Firstly, the increase in noise-induced coherence as the system approaches the onset of thermoacoustic instability can be considered as a precursor to the instability. Secondly, the dependence of noise-induced dynamics on the bifurcation type can be utilised to distinguish between subcritical and supercritical bifurcation prior to the onset of the instability.

Effect of noise on fractal structure

Energy Technology Data Exchange (ETDEWEB)

Serletis, Demitre [Division of Neurosurgery, Hospital for Sick Children, 1504-555 University Avenue, Toronto, Ont., M5G 1X8 (Canada)], E-mail: demitre.serletis@utoronto.ca

2008-11-15

In this paper, I investigate the effect of dynamical noise on the estimation of the Hurst exponent and the fractal dimension of time series. Recently, Serletis et al. [Serletis, Apostolos, Asghar Shahmoradi, Demitre Serletis. Effect of noise on estimation of Lyapunov exponents from a time series. Chaos, Solitons and Fractals, forthcoming] have shown that dynamical noise can make the detection of chaotic dynamics very difficult, and Serletis et al. [Serletis, Apostolos, Asghar Shahmoradi, Demitre Serletis. Effect of noise on the bifurcation behavior of dynamical systems. Chaos, Solitons and Fractals, forthcoming] have shown that dynamical noise can also shift bifurcation points and produce noise-induced transitions, making the determination of bifurcation boundaries difficult. Here I apply the detrending moving average (DMA) method, recently developed by Alessio et al. [Alessio E, Carbone A, Castelli G, Frappietro V. Second-order moving average and scaling of stochastic time series. The Eur Phys J B 2002;27:197-200] and Carbone et al. [Carbone A, Castelli G, Stanley HE. Time-dependent Hurst exponent in financial time series. Physica A 2004;344:267-71; Carbone A, Castelli G, Stanley HE. Analysis of clusters formed by the moving average of a long-range correlated time series. Phys Rev E 2004;69:026105], to estimate the Hurst exponent of a Brownian walk with a Hurst exponent of 0.5, coupled with low and high intensity noise, and show that dynamical noise has no effect on fractal structure.

A pseudoproxy assessment of data assimilation for reconstructing the atmosphere-ocean dynamics of hydroclimate extremes

Science.gov (United States)

Steiger, Nathan J.; Smerdon, Jason E.

2017-10-01

Because of the relatively brief observational record, the climate dynamics that drive multiyear to centennial hydroclimate variability are not adequately characterized and understood. Paleoclimate reconstructions based on data assimilation (DA) optimally fuse paleoclimate proxies with the dynamical constraints of climate models, thus providing a coherent dynamical picture of the past. DA is therefore an important new tool for elucidating the mechanisms of hydroclimate variability over the last several millennia. But DA has so far remained untested for global hydroclimate reconstructions. Here we explore whether or not DA can be used to skillfully reconstruct global hydroclimate variability along with the driving climate dynamics. Through a set of idealized pseudoproxy experiments, we find that an established DA reconstruction approach can in principle be used to reconstruct hydroclimate at both annual and seasonal timescales. We find that the skill of such reconstructions is generally highest near the proxy sites. This set of reconstruction experiments is specifically designed to estimate a realistic upper bound for the skill of this DA approach. Importantly, this experimental framework allows us to see where and for what variables the reconstruction approach may never achieve high skill. In particular for tree rings, we find that hydroclimate reconstructions depend critically on moisture-sensitive trees, while temperature reconstructions depend critically on temperature-sensitive trees. Real-world DA-based reconstructions will therefore likely require a spatial mixture of temperature- and moisture-sensitive trees to reconstruct both temperature and hydroclimate variables. Additionally, we illustrate how DA can be used to elucidate the dynamical mechanisms of drought with two examples: tropical drivers of multiyear droughts in the North American Southwest and in equatorial East Africa. This work thus provides a foundation for future DA-based hydroclimate

Noise-sustained fluctuations in stochastic dynamics with a delay.

Science.gov (United States)

D'Odorico, Paolo; Laio, Francesco; Ridolfi, Luca

2012-04-01

Delayed responses to external drivers are ubiquitous in environmental, social, and biological processes. Delays may induce oscillations, Hopf bifurcations, and instabilities in deterministic systems even in the absence of nonlinearities. Despite recent advances in the study of delayed stochastic differential equations, the interaction of random drivers with delays remains poorly understood. In particular, it is unclear whether noise-induced behaviors may emerge from these interactions. Here we show that noise may enhance and sustain transient periodic oscillations inherent to deterministic delayed systems. We investigate the conditions conducive to the emergence and disappearance of these dynamics in a linear system in the presence of both additive and multiplicative noise.

Can low-dose CT with iterative reconstruction reduce both the radiation dose and the amount of iodine contrast medium in a dynamic CT study of the liver?

Energy Technology Data Exchange (ETDEWEB)

Takahashi, Hiroto; Okada, Masahiro; Hyodo, Tomoko; Hidaka, Syojiro; Kagawa, Yuki; Matsuki, Mitsuru; Tsurusaki, Masakatsu; Murakami, Takamichi, E-mail: murakami@med.kindai.ac.jp

2014-04-15

Purpose: To investigate whether low-dose dynamic CT of the liver with iterative reconstruction can reduce both the radiation dose and the amount of contrast medium. Materials and methods: This study was approved by our institutional review board. 113 patients were randomly assigned to one of two groups. Group A/group B (fifty-eight/fifty-five patients) underwent liver dynamic CT at 120/100 kV, with 0/40% adaptive statistical iterative reconstruction (ASIR), with a contrast dose of 600/480 mg I/kg, respectively. Radiation exposure was estimated based on the manufacturer's phantom data. The enhancement value of the hepatic parenchyma, vessels and the tumor-to-liver contrast of hepatocellular carcinomas (HCCs) were compared between two groups. Two readers independently assessed the CT images of the hepatic parenchyma and HCCs. Results: The mean CT dose indices: 6.38/4.04 mGy, the dose-length products: 194.54/124.57 mGy cm, for group A/group B. The mean enhancement value of the hepatic parenchyma and the tumor-to-liver contrast of HCCs with diameters greater than 1 cm in the post-contrast all phases did not differ significantly between two groups (P > 0.05). The enhancement values of vessels in group B were significantly higher than that in group A in the delayed phases (P < 0.05). Two reader's confidence levels for the hepatic parenchyma in the delayed phases and HCCs did not differ significantly between the groups (P > 0.05). Conclusions: Low-dose dynamic CT with ASIR can reduce both the radiation dose and the amount of contrast medium without image quality degradation, compared to conventional dynamic CT without ASIR.

Measurement and analysis of noise power spectrum of computerized tomography in images

International Nuclear Information System (INIS)

Castro Tejero, P.; Garayoa Roca, J.

2013-01-01

This paper examines the implementation of the spectrum of powers of the noise, NPS, as metric to characterize the noise, both in magnitude and in texture, for CT scans. The NPS found show that you for convolution filters that assume a greater softening in the reconstructed image, spectrum is concentrated in the low frequencies, while for filters sharp, the spectrum extends to high frequencies. In the analyzed cases, there is a low frequency component, largely due to the structure-borne noise, which can be a potential negative effect on the detectability of injuries. (Author)

Generative Adversarial Networks for Noise Reduction in Low-Dose CT.

Science.gov (United States)

Wolterink, Jelmer M; Leiner, Tim; Viergever, Max A; Isgum, Ivana

2017-12-01

Noise is inherent to low-dose CT acquisition. We propose to train a convolutional neural network (CNN) jointly with an adversarial CNN to estimate routine-dose CT images from low-dose CT images and hence reduce noise. A generator CNN was trained to transform low-dose CT images into routine-dose CT images using voxelwise loss minimization. An adversarial discriminator CNN was simultaneously trained to distinguish the output of the generator from routine-dose CT images. The performance of this discriminator was used as an adversarial loss for the generator. Experiments were performed using CT images of an anthropomorphic phantom containing calcium inserts, as well as patient non-contrast-enhanced cardiac CT images. The phantom and patients were scanned at 20% and 100% routine clinical dose. Three training strategies were compared: the first used only voxelwise loss, the second combined voxelwise loss and adversarial loss, and the third used only adversarial loss. The results showed that training with only voxelwise loss resulted in the highest peak signal-to-noise ratio with respect to reference routine-dose images. However, CNNs trained with adversarial loss captured image statistics of routine-dose images better. Noise reduction improved quantification of low-density calcified inserts in phantom CT images and allowed coronary calcium scoring in low-dose patient CT images with high noise levels. Testing took less than 10 s per CT volume. CNN-based low-dose CT noise reduction in the image domain is feasible. Training with an adversarial network improves the CNNs ability to generate images with an appearance similar to that of reference routine-dose CT images.

Noise-tolerance analysis for detection and reconstruction of absorbing inhomogeneities with diffuse optical tomography using single- and phase-correlated dual-source schemes

International Nuclear Information System (INIS)

Kanmani, B; Vasu, R M

2007-01-01

An iterative reconstruction procedure is used to invert intensity data from both single- and phase-correlated dual-source illuminations for absorption inhomogeneities. The Jacobian for the dual source is constructed by an algebraic addition of the Jacobians estimated for the two sources separately. By numerical simulations, it is shown that the dual-source scheme performs superior to the single-source system in regard to (i) noise tolerance in data and (ii) ability to reconstruct smaller and lower contrast objects. The quality of reconstructions from single-source data, as indicated by mean-square error at convergence, is markedly poorer compared to their dual-source counterpart, when noise in data was in excess of 2%. With fixed contrast and decreasing inhomogeneity diameter, our simulations showed that, for diameters below 7 mm, the dual-source scheme has a higher percentage contrast recovery compared to the single-source scheme. Similarly, the dual-source scheme reconstructs to a higher percentage contrast recovery from lower contrast inhomogeneity, in comparison to the single-source scheme

Lévy stable noise-induced transitions: stochastic resonance, resonant activation and dynamic hysteresis

International Nuclear Information System (INIS)

Dybiec, Bartłomiej; Gudowska-Nowak, Ewa

2009-01-01

A standard approach to analysis of noise-induced effects in stochastic dynamics assumes a Gaussian character of the noise term describing interaction of the analyzed system with its complex surroundings. An additional assumption about the existence of timescale separation between the dynamics of the measured observable and the typical timescale of the noise allows external fluctuations to be modeled as temporally uncorrelated and therefore white. However, in many natural phenomena the assumptions concerning the above mentioned properties of 'Gaussianity' and 'whiteness' of the noise can be violated. In this context, in contrast to the spatiotemporal coupling characterizing general forms of non-Markovian or semi-Markovian Lévy walks, so called Lévy flights correspond to the class of Markov processes which can still be interpreted as white, but distributed according to a more general, infinitely divisible, stable and non-Gaussian law. Lévy noise-driven non-equilibrium systems are known to manifest interesting physical properties and have been addressed in various scenarios of physical transport exhibiting a superdiffusive behavior. Here we present a brief overview of our recent investigations aimed at understanding features of stochastic dynamics under the influence of Lévy white noise perturbations. We find that the archetypal phenomena of noise-induced ordering are robust and can be detected also in systems driven by memoryless, non-Gaussian, heavy-tailed fluctuations with infinite variance

The normalized interaural correlation : accounting for NoSp thresholds obtained with Gaussian and 'low-noise' masking noise

NARCIS (Netherlands)

Bernstein, L.R.; Par, van de S.L.J.D.E.; Trahiotis, C.T.

1999-01-01

Recently, [J. Acoust. Soc. Am. 103, 2578–2589 (1998)] and [J. Acoust. Soc. Am. 103, 2573–2577 (1998)] independently reported that greater masking of interaurally phase-reversed (Sp) tones was produced by diotic low-noise noise than by diotic Gaussian noise. Based on quantitative analyses, Eddins and

Low-Noise Operation of All-Fiber Femtosecond Cherenkov Laser

DEFF Research Database (Denmark)

Liu, Xiaomin; Villanueva Ibáñez, Guillermo Eduardo; Lægsgaard, Jesper

2013-01-01

We investigate the noise properties of a femtosecond all-fiber Cherenkov radiation source with emission wavelength around 600 nm, based on an Yb-fiber laser and a highly-nonlinear photonic crystal fiber. A relative intensity noise as low as - 103 dBc/Hz, corresponding to 2.48 % pulse-to-pulse...... fluctuation in energy, was observed at the Cherenkov radiation output power of 4.3 mW, or 150 pJ pulse energy. This pulse-to-pulse fluctuation is at least 10.6 dB lower compared to spectrally-sliced supercontinuum sources traditionally used for ultrafast fiberbased generation at visible wavelengths. Low noise...... makes allfiber Cherenkov sources promising for biophotonics applications such as multi-photon microscopy, where minimum pulse-to-pulse energy fluctuation is required. We present the dependency of the noise figure on both the Cherenkov radiation output power and its spectrum....

Direct Reconstruction of CT-based Attenuation Correction Images for PET with Cluster-Based Penalties

Science.gov (United States)

Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Asma, Evren; Kinahan, Paul E.

2015-01-01

Extremely low-dose CT acquisitions for the purpose of PET attenuation correction will have a high level of noise and biasing artifacts due to factors such as photon starvation. This work explores a priori knowledge appropriate for CT iterative image reconstruction for PET attenuation correction. We investigate the maximum a posteriori (MAP) framework with cluster-based, multinomial priors for the direct reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction was modeled as a Poisson log-likelihood with prior terms consisting of quadratic (Q) and mixture (M) distributions. The attenuation map is assumed to have values in 4 clusters: air+background, lung, soft tissue, and bone. Under this assumption, the MP was a mixture probability density function consisting of one exponential and three Gaussian distributions. The relative proportion of each cluster was jointly estimated during each voxel update of direct iterative coordinate decent (dICD) method. Noise-free data were generated from NCAT phantom and Poisson noise was added. Reconstruction with FBP (ramp filter) was performed on the noise-free (ground truth) and noisy data. For the noisy data, dICD reconstruction was performed with the combination of different prior strength parameters (β and γ) of Q- and M-penalties. The combined quadratic and mixture penalties reduces the RMSE by 18.7% compared to post-smoothed iterative reconstruction and only 0.7% compared to quadratic alone. For direct PET attenuation map reconstruction from ultra-low dose CT acquisitions, the combination of quadratic and mixture priors offers regularization of both variance and bias and is a potential method to derive attenuation maps with negligible patient dose. However, the small improvement in quantitative accuracy relative to the substantial increase in algorithm complexity does not currently justify the use of mixture-based PET attenuation priors for reconstruction of CT

Hysteretic behavior of spin-crossover noise driven system

Energy Technology Data Exchange (ETDEWEB)

Gudyma, Iurii [Department of General Physics, Chernivtsi National University, Chernivtsi 58012 (Ukraine); Maksymov, Artur, E-mail: maxyartur@gmail.com [Department of General Physics, Chernivtsi National University, Chernivtsi 58012 (Ukraine); Advanced Materials Research Institute, University of New Orleans, LA 70148 (United States); Dimian, Mihai [Department of Electrical and Computer Engineering, Howard University, Washington DC, 20059 (United States); Faculty of Electrical Engineering and Computer Science, Stefan cel Mare University, Suceava 720229 (Romania)

2016-04-01

The influence of white Gaussian noise on hysteretic behavior of spin-crossover system is analyzed in the framework of stochastic Langevin dynamics. Various stochastic simulations are performed and several important properties of spin-transition in spin-crossover system driven by noise are reproduced. The numerical results are tested against the stationary probability function and the associated dynamic potential obtained from Fokker–Planck equation corresponding to spin-crossover Langevin dynamics. The dependence of light-induced optical hysteresis width and non-hysteretic transition curve slope on the noise intensity is illustrated. The role of low-spin and high-spin phase stabilities in the hysteretic behavior of noise-driven spin-crossover system is discussed.

A high and low noise model for strong motion accelerometers

Science.gov (United States)

Clinton, J. F.; Cauzzi, C.; Olivieri, M.

2010-12-01

We present reference noise models for high-quality strong motion accelerometer installations. We use continuous accelerometer data acquired by the Swiss Seismological Service (SED) since 2006 and other international high-quality accelerometer network data to derive very broadband (50Hz-100s) high and low noise models. The proposed noise models are compared to the Peterson (1993) low and high noise models designed for broadband seismometers; the datalogger self-noise; background noise levels at existing Swiss strong motion stations; and typical earthquake signals recorded in Switzerland and worldwide. The standard strong motion station operated by the SED consists of a Kinemetrics Episensor (2g clip level; flat acceleration response from 200 Hz to DC; insulated sensor / datalogger systems placed in vault quality sites. At all frequencies, there is at least one order of magnitude between the ALNM and the AHNM; at high frequencies (> 1Hz) this extends to 2 orders of magnitude. This study provides remarkable confirmation of the capability of modern strong motion accelerometers to record low-amplitude ground motions with seismic observation quality. In particular, an accelerometric station operating at the ALNM is capable of recording the full spectrum of near source earthquakes, out to 100 km, down to M2. Of particular interest for the SED, this study provides acceptable noise limits for candidate sites for the on-going Strong Motion Network modernisation.

Low noise signal-to-noise ratio enhancing readout circuit for current-mediated active pixel sensors

International Nuclear Information System (INIS)

Ottaviani, Tony; Karim, Karim S.; Nathan, Arokia; Rowlands, John A.

2006-01-01

Diagnostic digital fluoroscopic applications continuously expose patients to low doses of x-ray radiation, posing a challenge to both the digital imaging pixel and readout electronics when amplifying small signal x-ray inputs. Traditional switch-based amorphous silicon imaging solutions, for instance, have produced poor signal-to-noise ratios (SNRs) at low exposure levels owing to noise sources from the pixel readout circuitry. Current-mediated amorphous silicon pixels are an improvement over conventional pixel amplifiers with an enhanced SNR across the same low-exposure range, but whose output also becomes nonlinear with increasing dosage. A low-noise SNR enhancing readout circuit has been developed that enhances the charge gain of the current-mediated active pixel sensor (C-APS). The solution takes advantage of the current-mediated approach, primarily integrating the signal input at the desired frequency necessary for large-area imaging, while adding minimal noise to the signal readout. Experimental data indicates that the readout circuit can detect pixel outputs over a large bandwidth suitable for real-time digital diagnostic x-ray fluoroscopy. Results from hardware testing indicate that the minimum achievable C-APS output current that can be discerned at the digital fluoroscopic output from the enhanced SNR readout circuit is 0.341 nA. The results serve to highlight the applicability of amorphous silicon current-mediated pixel amplifiers for large-area flat panel x-ray imagers

Complex Nonlinear Dynamic System of Oligopolies Price Game with Heterogeneous Players Under Noise

Science.gov (United States)

Liu, Feng; Li, Yaguang

A nonlinear four oligopolies price game with heterogeneous players, that are boundedly rational and adaptive, is built using two different special demand costs. Based on the theory of complex discrete dynamical system, the stability and the existing equilibrium point are investigated. The complex dynamic behavior is presented via bifurcation diagrams, the Lyapunov exponents to show equilibrium state, bifurcation and chaos with the variation in parameters. As disturbance is ubiquitous in economic systems, this paper focuses on the analysis of delay feedback control method under noise circumstances. Stable dynamics is confirmed to depend mainly on the low price adjustment speed, and if all four players have limited opportunities to stabilize the market, the new adaptive player facing profits of scale are found to be higher than the incumbents of bounded rational.

Grey signal processing and data reconstruction in the non-diffracting beam triangulation measurement system

Science.gov (United States)

Meng, Hao; Wang, Zhongyu; Fu, Jihua

2008-12-01

The non-diffracting beam triangulation measurement system possesses the advantages of longer measurement range, higher theoretical measurement accuracy and higher resolution over the traditional laser triangulation measurement system. Unfortunately the measurement accuracy of the system is greatly degraded due to the speckle noise, the CCD photoelectric noise and the background light noise in practical applications. Hence, some effective signal processing methods must be applied to improve the measurement accuracy. In this paper a novel effective method for removing the noises in the non-diffracting beam triangulation measurement system is proposed. In the method the grey system theory is used to process and reconstruct the measurement signal. Through implementing the grey dynamic filtering based on the dynamic GM(1,1), the noises can be effectively removed from the primary measurement data and the measurement accuracy of the system can be improved as a result.

SU-E-I-41: Dictionary Learning Based Quantitative Reconstruction for Low-Dose Dual-Energy CT (DECT)

International Nuclear Information System (INIS)

Xu, Q; Xing, L; Xiong, G; Elmore, K; Min, J

2015-01-01

Purpose: DECT collects two sets of projection data under higher and lower energies. With appropriates composition methods on linear attenuation coefficients, quantitative information about the object, such as density, can be obtained. In reality, one of the important problems in DECT is the radiation dose due to doubled scans. This work is aimed at establishing a dictionary learning based reconstruction framework for DECT for improved image quality while reducing the imaging dose. Methods: In our method, two dictionaries were learned respectively from the high-energy and lowenergy image datasets of similar objects under normal dose in advance. The linear attenuation coefficient was decomposed into two basis components with material based composition method. An iterative reconstruction framework was employed. Two basis components were alternately updated with DECT datasets and dictionary learning based sparse constraints. After one updating step under the dataset fidelity constraints, both high-energy and low-energy images can be obtained from the two basis components. Sparse constraints based on the learned dictionaries were applied to the high- and low-energy images to update the two basis components. The iterative calculation continues until a pre-set number of iteration was reached. Results: We evaluated the proposed dictionary learning method with dual energy images collected using a DECT scanner. We re-projected the projection data with added Poisson noise to reflect the low-dose situation. The results obtained by the proposed method were compared with that obtained using FBP based method and TV based method. It was found that the proposed approach yield better results than other methods with higher resolution and less noise. Conclusion: The use of dictionary learned from DECT images under normal dose is valuable and leads to improved results with much lower imaging dose

SU-E-I-41: Dictionary Learning Based Quantitative Reconstruction for Low-Dose Dual-Energy CT (DECT)

Energy Technology Data Exchange (ETDEWEB)

Xu, Q [School of Electronic and Information Engineering, Xi’an Jiaotong University, Xi’an, Shaanxi 710049 (China); Department of Radiation Oncology, Stanford University, Stanford, CA 94305 (United States); Xing, L [Department of Radiation Oncology, Stanford University, Stanford, CA 94305 (United States); Xiong, G; Elmore, K; Min, J [Dalio Institute of Cardiovascular Imaging, New York-Presbyterian Hospital and Weill Cornell Medical College, New York, NY (United States)

2015-06-15

Purpose: DECT collects two sets of projection data under higher and lower energies. With appropriates composition methods on linear attenuation coefficients, quantitative information about the object, such as density, can be obtained. In reality, one of the important problems in DECT is the radiation dose due to doubled scans. This work is aimed at establishing a dictionary learning based reconstruction framework for DECT for improved image quality while reducing the imaging dose. Methods: In our method, two dictionaries were learned respectively from the high-energy and lowenergy image datasets of similar objects under normal dose in advance. The linear attenuation coefficient was decomposed into two basis components with material based composition method. An iterative reconstruction framework was employed. Two basis components were alternately updated with DECT datasets and dictionary learning based sparse constraints. After one updating step under the dataset fidelity constraints, both high-energy and low-energy images can be obtained from the two basis components. Sparse constraints based on the learned dictionaries were applied to the high- and low-energy images to update the two basis components. The iterative calculation continues until a pre-set number of iteration was reached. Results: We evaluated the proposed dictionary learning method with dual energy images collected using a DECT scanner. We re-projected the projection data with added Poisson noise to reflect the low-dose situation. The results obtained by the proposed method were compared with that obtained using FBP based method and TV based method. It was found that the proposed approach yield better results than other methods with higher resolution and less noise. Conclusion: The use of dictionary learned from DECT images under normal dose is valuable and leads to improved results with much lower imaging dose.

Design and analysis of high gain and low noise figure CMOS low noise amplifier for Q-band nano-sensor application

Science.gov (United States)

Suganthi, K.; Malarvizhi, S.

2018-03-01

A high gain, low power, low Noise figure (NF) and wide band of milli-meter Wave (mmW) circuits design at 50 GHz are used for Radio Frequency (RF) front end. The fundamental necessity of a receiver front-end includes perfect output and input impedance matching and port-to-port isolation with high gain and low noise over the entire band of interest. In this paper, a design of Cascade-Cascode CMOS LNA circuit at 50 GHz for Q-band application is proposed. The design of Low noise amplifier at 50 GHz using Agilent ADS tool with microstrip lines which provides simplicity in fabrication and less chip area. The low off-leakage current Ioff can be maintained with high K-dielectrics CMOS structure. Nano-scale electronics can be achieved with increased robustness. The design has overall gain of 11.091 dB and noise figure of 2.673 dB for the Q-band of 48.3 GHz to 51.3 GHz. Impedance matching is done by T matching network and the obtained input and output reflection coefficients are S11 = <-10 dB and S22 = <-10 dB. Compared to Silicon (Si) material, Wide Band Gap semiconductor materials used attains higher junction temperatures which is well matched to ceramics used in packaging technology, the protection and reliability also can be achieved with the electronic packaging. The reverse transmission coefficient S21 is less than -21 dB has shown that LNA has better isolation between input and output, Stability factor greater than 1 and Power is also optimized in this design. Layout is designed, power gain of 4.6 dB is achieved and area is optimized which is nearly equal to 502 740 μm2. The observed results show that the proposed Cascade-Cascode LNA design can find its suitability in future milli-meter Wave Radar application.

Evaluation of digital breast tomosynthesis reconstruction algorithms using synchrotron radiation in standard geometry

International Nuclear Information System (INIS)

Bliznakova, K.; Kolitsi, Z.; Speller, R. D.; Horrocks, J. A.; Tromba, G.; Pallikarakis, N.

2010-01-01

Purpose: In this article, the image quality of reconstructed volumes by four algorithms for digital tomosynthesis, applied in the case of breast, is investigated using synchrotron radiation. Methods: An angular data set of 21 images of a complex phantom with heterogeneous tissue-mimicking background was obtained using the SYRMEP beamline at ELETTRA Synchrotron Light Laboratory, Trieste, Italy. The irradiated part was reconstructed using the multiple projection algorithm (MPA) and the filtered backprojection with ramp followed by hamming windows (FBR-RH) and filtered backprojection with ramp (FBP-R). Additionally, an algorithm for reducing the noise in reconstructed planes based on noise mask subtraction from the planes of the originally reconstructed volume using MPA (MPA-NM) has been further developed. The reconstruction techniques were evaluated in terms of calculations and comparison of the contrast-to-noise ratio (CNR) and artifact spread function. Results: It was found that the MPA-NM resulted in higher CNR, comparable with the CNR of FBP-RH for high contrast details. Low contrast objects are well visualized and characterized by high CNR using the simple MPA and the MPA-NM. In addition, the image quality of the reconstructed features in terms of CNR and visual appearance as a function of the initial number of projection images and the reconstruction arc was carried out. Slices reconstructed with more input projection images result in less reconstruction artifacts and higher detail CNR, while those reconstructed from projection images acquired in reduced angular range causes pronounced streak artifacts. Conclusions: Of the reconstruction algorithms implemented, the MPA-NM and MPA are a good choice for detecting low contrast objects, while the FBP-RH, FBP-R, and MPA-NM provide high CNR and well outlined edges in case of microcalcifications.

Patellofemoral pressure changes after static and dynamic medial patellofemoral ligament reconstructions

NARCIS (Netherlands)

Rood, A.; Hannink, G.; Lenting, A.; Groenen, K.; Koëter, S.; Verdonschot, Nicolaas Jacobus Joseph; van Kampen, A.

2015-01-01

Background: Reconstructing the medial patellofemoral ligament (MPFL) has become a key procedure for stabilizing the patella. Different techniques to reconstruct the MPFL have been described: static techniques in which the graft is fixed rigidly to the bone or dynamic techniques with soft tissue

Patellofemoral Pressure Changes After Static and Dynamic Medial Patellofemoral Ligament Reconstructions

NARCIS (Netherlands)

Rood, A.; Hannink, G.; Lenting, A.; Groenen, K.; Koeter, S.; Verdonschot, N.J.; Kampen, A. van

2015-01-01

BACKGROUND: Reconstructing the medial patellofemoral ligament (MPFL) has become a key procedure for stabilizing the patella. Different techniques to reconstruct the MPFL have been described: static techniques in which the graft is fixed rigidly to the bone or dynamic techniques with soft tissue

Characterization of adaptive statistical iterative reconstruction algorithm for dose reduction in CT: A pediatric oncology perspective

Energy Technology Data Exchange (ETDEWEB)

Brady, S. L.; Yee, B. S.; Kaufman, R. A. [Department of Radiological Sciences, St. Jude Children' s Research Hospital, Memphis, Tennessee 38105 (United States)

2012-09-15

Purpose: This study demonstrates a means of implementing an adaptive statistical iterative reconstruction (ASiR Trade-Mark-Sign ) technique for dose reduction in computed tomography (CT) while maintaining similar noise levels in the reconstructed image. The effects of image quality and noise texture were assessed at all implementation levels of ASiR Trade-Mark-Sign . Empirically derived dose reduction limits were established for ASiR Trade-Mark-Sign for imaging of the trunk for a pediatric oncology population ranging from 1 yr old through adolescence/adulthood. Methods: Image quality was assessed using metrics established by the American College of Radiology (ACR) CT accreditation program. Each image quality metric was tested using the ACR CT phantom with 0%-100% ASiR Trade-Mark-Sign blended with filtered back projection (FBP) reconstructed images. Additionally, the noise power spectrum (NPS) was calculated for three common reconstruction filters of the trunk. The empirically derived limitations on ASiR Trade-Mark-Sign implementation for dose reduction were assessed using (1, 5, 10) yr old and adolescent/adult anthropomorphic phantoms. To assess dose reduction limits, the phantoms were scanned in increments of increased noise index (decrementing mA using automatic tube current modulation) balanced with ASiR Trade-Mark-Sign reconstruction to maintain noise equivalence of the 0% ASiR Trade-Mark-Sign image. Results: The ASiR Trade-Mark-Sign algorithm did not produce any unfavorable effects on image quality as assessed by ACR criteria. Conversely, low-contrast resolution was found to improve due to the reduction of noise in the reconstructed images. NPS calculations demonstrated that images with lower frequency noise had lower noise variance and coarser graininess at progressively higher percentages of ASiR Trade-Mark-Sign reconstruction; and in spite of the similar magnitudes of noise, the image reconstructed with 50% or more ASiR Trade-Mark-Sign presented a more

The reduction of image noise and streak artifact in the thoracic inlet during low dose and ultra-low dose thoracic CT

International Nuclear Information System (INIS)

Paul, N S; Prezelj, E; Burey, P; Menezes, R J; Blobel, J; Ursani, A; Kashani, H; Siewerdsen, J H

2010-01-01

Increased pixel noise and streak artifact reduce CT image quality and limit the potential for radiation dose reduction during CT of the thoracic inlet. We propose to quantify the pixel noise of mediastinal structures in the thoracic inlet, during low-dose (LDCT) and ultralow-dose (uLDCT) thoracic CT, and assess the utility of new software (quantum denoising system and BOOST3D) in addressing these limitations. Twelve patients had LDCT (120 kV, 25 mAs) and uLDCT (120 kV, 10 mAs) images reconstructed initially using standard mediastinal and lung filters followed by the quantum denoising system (QDS) to reduce pixel noise and BOOST3D (B3D) software to correct photon starvation noise as follows: group 1 no QDS, no B3D; group 2 B3D alone; group 3 QDS alone and group 4 both QDS and B3D. Nine regions of interest (ROIs) were replicated on mediastinal anatomy in the thoracic inlet, for each patient resulting in 3456 data points to calculate pixel noise and attenuation. QDS reduced pixel noise by 18.4% (lung images) and 15.8% (mediastinal images) at 25 mAs. B3D reduced pixel noise by ∼8% in the posterior thorax and in combination there was a 35.5% reduction in effective radiation dose (E) for LDCT (1.63-1.05 mSv) in lung images and 32.2% (1.55-1.05 mSv) in mediastinal images. The same combination produced 20.7% reduction (0.53-0.42 mSv) in E for uLDCT, for lung images and 17.3% (0.51-0.42) for mediastinal images. This quantitative analysis of image quality confirms the utility of dedicated processing software in targeting image noise and streak artifact in thoracic LDCT and uLDCT images taken in the thoracic inlet. This processing software potentiates substantial reductions in radiation dose during thoracic LDCT and uLDCT.

Comparison of iterative model, hybrid iterative, and filtered back projection reconstruction techniques in low-dose brain CT: impact of thin-slice imaging

Energy Technology Data Exchange (ETDEWEB)

Nakaura, Takeshi; Iyama, Yuji; Kidoh, Masafumi; Yokoyama, Koichi [Amakusa Medical Center, Diagnostic Radiology, Amakusa, Kumamoto (Japan); Kumamoto University, Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto (Japan); Oda, Seitaro; Yamashita, Yasuyuki [Kumamoto University, Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto (Japan); Tokuyasu, Shinichi [Philips Electronics, Kumamoto (Japan); Harada, Kazunori [Amakusa Medical Center, Department of Surgery, Kumamoto (Japan)

2016-03-15

The purpose of this study was to evaluate the utility of iterative model reconstruction (IMR) in brain CT especially with thin-slice images. This prospective study received institutional review board approval, and prior informed consent to participate was obtained from all patients. We enrolled 34 patients who underwent brain CT and reconstructed axial images with filtered back projection (FBP), hybrid iterative reconstruction (HIR) and IMR with 1 and 5 mm slice thicknesses. The CT number, image noise, contrast, and contrast noise ratio (CNR) between the thalamus and internal capsule, and the rate of increase of image noise in 1 and 5 mm thickness images between the reconstruction methods, were assessed. Two independent radiologists assessed image contrast, image noise, image sharpness, and overall image quality on a 4-point scale. The CNRs in 1 and 5 mm slice thickness were significantly higher with IMR (1.2 ± 0.6 and 2.2 ± 0.8, respectively) than with FBP (0.4 ± 0.3 and 1.0 ± 0.4, respectively) and HIR (0.5 ± 0.3 and 1.2 ± 0.4, respectively) (p < 0.01). The mean rate of increasing noise from 5 to 1 mm thickness images was significantly lower with IMR (1.7 ± 0.3) than with FBP (2.3 ± 0.3) and HIR (2.3 ± 0.4) (p < 0.01). There were no significant differences in qualitative analysis of unfamiliar image texture between the reconstruction techniques. IMR offers significant noise reduction and higher contrast and CNR in brain CT, especially for thin-slice images, when compared to FBP and HIR. (orig.)

Adaptive multiresolution method for MAP reconstruction in electron tomography

Energy Technology Data Exchange (ETDEWEB)

Acar, Erman, E-mail: erman.acar@tut.fi [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland); Peltonen, Sari; Ruotsalainen, Ulla [Department of Signal Processing, Tampere University of Technology, P.O. Box 553, FI-33101 Tampere (Finland); BioMediTech, Tampere University of Technology, Biokatu 10, 33520 Tampere (Finland)

2016-11-15

3D image reconstruction with electron tomography holds problems due to the severely limited range of projection angles and low signal to noise ratio of the acquired projection images. The maximum a posteriori (MAP) reconstruction methods have been successful in compensating for the missing information and suppressing noise with their intrinsic regularization techniques. There are two major problems in MAP reconstruction methods: (1) selection of the regularization parameter that controls the balance between the data fidelity and the prior information, and (2) long computation time. One aim of this study is to provide an adaptive solution to the regularization parameter selection problem without having additional knowledge about the imaging environment and the sample. The other aim is to realize the reconstruction using sequences of resolution levels to shorten the computation time. The reconstructions were analyzed in terms of accuracy and computational efficiency using a simulated biological phantom and publically available experimental datasets of electron tomography. The numerical and visual evaluations of the experiments show that the adaptive multiresolution method can provide more accurate results than the weighted back projection (WBP), simultaneous iterative reconstruction technique (SIRT), and sequential MAP expectation maximization (sMAPEM) method. The method is superior to sMAPEM also in terms of computation time and usability since it can reconstruct 3D images significantly faster without requiring any parameter to be set by the user. - Highlights: • An adaptive multiresolution reconstruction method is introduced for electron tomography. • The method provides more accurate results than the conventional reconstruction methods. • The missing wedge and noise problems can be compensated by the method efficiently.

Note: A temperature-stable low-noise transimpedance amplifier for microcurrent measurement

Science.gov (United States)

Xie, Kai; Shi, Xueyou; Zhao, Kai; Guo, Lixin; Zhang, Hanlu

2017-02-01

Temperature stability and noise characteristics often run contradictory in microcurrent (e.g., pA-scale) measurement instruments because low-noise performance requires high-value resistors with relatively poor temperature coefficients. A low-noise transimpedance amplifier with high-temperature stability, which involves an active compensation mechanism to overcome the temperature drift mainly caused by high-value resistors, is presented. The implementation uses a specially designed R-2R compensating network to provide programmable current gain with extra-fine trimming resolution. The temperature drifts of all components (e.g., feedback resistors, operational amplifiers, and the R-2R network itself) are compensated simultaneously. Therefore, both low-temperature drift and ultra-low-noise performance can be achieved. With a current gain of 1011 V/A, the internal current noise density was about 0.4 fA/√Hz, and the average temperature coefficient was 4.3 ppm/K at 0-50 °C. The amplifier module maintains accuracy across a wide temperature range without additional thermal stabilization, and its compact size makes it especially suitable for high-precision, low-current measurement in outdoor environments for applications such as electrochemical emission supervision, air pollution particles analysis, radiation monitoring, and bioelectricity.

Patient-adapted reconstruction and acquisition dynamic imaging method (PARADIGM) for MRI

International Nuclear Information System (INIS)

Aggarwal, Nitin; Bresler, Yoram

2008-01-01

Dynamic magnetic resonance imaging (MRI) is a challenging problem because the MR data acquisition is often not fast enough to meet the combined spatial and temporal Nyquist sampling rate requirements. Current approaches to this problem include hardware-based acceleration of the acquisition, and model-based image reconstruction techniques. In this paper we propose an alternative approach, called PARADIGM, which adapts both the acquisition and reconstruction to the spatio-temporal characteristics of the imaged object. The approach is based on time-sequential sampling theory, addressing the problem of acquiring a spatio-temporal signal under the constraint that only a limited amount of data can be acquired at a time instant. PARADIGM identifies a model class for the particular imaged object using a scout MR scan or auxiliary data. This object-adapted model is then used to optimize MR data acquisition, such that the imaging constraints are met, acquisition speed requirements are minimized, essentially perfect reconstruction of any object in the model class is guaranteed, and the inverse problem of reconstructing the dynamic object has a condition number of one. We describe spatio-temporal object models for various dynamic imaging applications including cardiac imaging. We present the theory underlying PARADIGM and analyze its performance theoretically and numerically. We also propose a practical MR imaging scheme for 2D dynamic cardiac imaging based on the theory. For this application, PARADIGM is predicted to provide a 10–25 × acceleration compared to the optimal non-adaptive scheme. Finally we present generalized optimality criteria and extend the scheme to dynamic imaging with three spatial dimensions

A priori motion models for four-dimensional reconstruction in gated cardiac SPECT

International Nuclear Information System (INIS)

Lalush, D.S.; Tsui, B.M.W.; Cui, Lin

1996-01-01

We investigate the benefit of incorporating a priori assumptions about cardiac motion in a fully four-dimensional (4D) reconstruction algorithm for gated cardiac SPECT. Previous work has shown that non-motion-specific 4D Gibbs priors enforcing smoothing in time and space can control noise while preserving resolution. In this paper, we evaluate methods for incorporating known heart motion in the Gibbs prior model. The new model is derived by assigning motion vectors to each 4D voxel, defining the movement of that volume of activity into the neighboring time frames. Weights for the Gibbs cliques are computed based on these open-quotes most likelyclose quotes motion vectors. To evaluate, we employ the mathematical cardiac-torso (MCAT) phantom with a new dynamic heart model that simulates the beating and twisting motion of the heart. Sixteen realistically-simulated gated datasets were generated, with noise simulated to emulate a real Tl-201 gated SPECT study. Reconstructions were performed using several different reconstruction algorithms, all modeling nonuniform attenuation and three-dimensional detector response. These include ML-EM with 4D filtering, 4D MAP-EM without prior motion assumption, and 4D MAP-EM with prior motion assumptions. The prior motion assumptions included both the correct motion model and incorrect models. Results show that reconstructions using the 4D prior model can smooth noise and preserve time-domain resolution more effectively than 4D linear filters. We conclude that modeling of motion in 4D reconstruction algorithms can be a powerful tool for smoothing noise and preserving temporal resolution in gated cardiac studies

The adaptive statistical iterative reconstruction-V technique for radiation dose reduction in abdominal CT: comparison with the adaptive statistical iterative reconstruction technique.

Science.gov (United States)

Kwon, Heejin; Cho, Jinhan; Oh, Jongyeong; Kim, Dongwon; Cho, Junghyun; Kim, Sanghyun; Lee, Sangyun; Lee, Jihyun

2015-10-01

iterative reconstruction. Use of the ASIR-V algorithm decreased image noise and increased image quality when compared with the ASIR and FBP methods. These results suggest that high-quality low-dose CT may represent a new clinical option.

The use of anatomical information for molecular image reconstruction algorithms: Attention/Scatter correction, motion compensation, and noise reduction

Energy Technology Data Exchange (ETDEWEB)

Chun, Se Young [School of Electrical and Computer Engineering, Ulsan National Institute of Science and Technology (UNIST), Ulsan (Korea, Republic of)

2016-03-15

PET and SPECT are important tools for providing valuable molecular information about patients to clinicians. Advances in nuclear medicine hardware technologies and statistical image reconstruction algorithms enabled significantly improved image quality. Sequentially or simultaneously acquired anatomical images such as CT and MRI from hybrid scanners are also important ingredients for improving the image quality of PET or SPECT further. High-quality anatomical information has been used and investigated for attenuation and scatter corrections, motion compensation, and noise reduction via post-reconstruction filtering and regularization in inverse problems. In this article, we will review works using anatomical information for molecular image reconstruction algorithms for better image quality by describing mathematical models, discussing sources of anatomical information for different cases, and showing some examples.

Noise-induced temporal dynamics in Turing systems

KAUST Repository

Schumacher, Linus J.

2013-04-25

We examine the ability of intrinsic noise to produce complex temporal dynamics in Turing pattern formation systems, with particular emphasis on the Schnakenberg kinetics. Using power spectral methods, we characterize the behavior of the system using stochastic simulations at a wide range of points in parameter space and compare with analytical approximations. Specifically, we investigate whether polarity switching of stochastic patterns occurs at a defined frequency. We find that it can do so in individual realizations of a stochastic simulation, but that the frequency is not defined consistently across realizations in our samples of parameter space. Further, we examine the effect of noise on deterministically predicted traveling waves and find them increased in amplitude and decreased in speed. © 2013 American Physical Society.

Noise properties of the EM algorithm. Pt. 1

International Nuclear Information System (INIS)

Barrett, H.H.; Wilson, D.W.; Tsui, B.M.W.

1994-01-01

The expectation-maximisation (EM) algorithm is an important tool for maximum-likelihood (ML) estimation and image reconstruction, especially in medical imaging. It is a non-linear iterative algorithm that attempts to find the ML estimate of the object that produced a data set. The convergence of the algorithm and other deterministic properties are well established, but relatively little is known about how noise in the data influences noise in the final reconstructed image. In this paper we present a detailed treatment of these statistical properties. The specific application we have in mind is image reconstruction in emission tomography, but the results are valid for any application of the EM algorithm in which the data set can be described by Poisson statistics. We show that the probability density function for the grey level at a pixel in the image is well approximated by a log-normal law. An expression is derived for the variance of the grey level and for pixel-to-pixel covariance. The variance increases rapidly with iteration number at first, but eventually saturates as the ML estimate is approached. Moreover, the variance at any iteration number has a factor proportional to the square of the mean image (though other factors may also depend on the mean image), so a map of the standard deviation resembles the object itself. Thus low-intensity regions of the image tend to have low noise. (author)

Predictable nonlinear dynamics: Advances and limitations

International Nuclear Information System (INIS)

Anosov, L.A.; Butkovskii, O.Y.; Kravtsov, Y.A.; Surovyatkina, E.D.

1996-01-01

Methods for reconstruction chaotic dynamical system structure directly from experimental time series are described. Effectiveness of general methods is illustrated with the results of numerical simulation. It is of common interest that from the single time series it is possible to reconstruct a set of interconnected variables. Predictive power of dynamical models, provided by the nonlinear dynamics inverse problem solution, is limited firstly by the noise level in the system under study and is characterized by the horizon of predictability. New physical results are presented, concerning nonstationary and bifurcation nonlinear systems: (1) algorithms for revealing of nonstationarity in random-like chaotic time-series are suggested based on discriminant analysis with nonlinear discriminant function; (2) an opportunity is established to predict the final state in bifurcation system with quickly varying control parameters; (3) hysteresis is founded out in bifurcation system with quickly varying parameters; (4) delayed correlation left-angle noise-prediction error right-angle in chaotic systems is revealed. copyright 1996 American Institute of Physics

Correlation between noise and dynamics of cavitation bubbles

International Nuclear Information System (INIS)

Chahine, G.L.; Courbierre, P.; Garnaud, P.

1979-01-01

A correlation between bubble dynamics and emitted noise is made using high-speed photography and two differently located hydrophones. The effect of the proximity of a solid wall is investigated. An amplitude and time analysis is performed and damage observations are made by means of a scanning electron microscope

Low noise SQUIDS

International Nuclear Information System (INIS)

Waal, V.J. de.

1983-01-01

The design, fabrication and limitations of very sensitive SQUID magnetometers are described. The SQUID magnetometer is based on the Josephson effect. A very low-noise niobium SQUID is described. It is fabricated with ultra-small niobium junctions with an overlapping area smaller than 1 μm 2 . The photolithographic technique developed for its fabrication, is described. Also an integrated system with a SQUID and a first-order gradiometer on a single substrate is presented. Calculations of the resolution of a dc SQUID containing ideal Josephson junctions according to the RSJ model are presented including a parasitic capacitance. The usefulness of the fabricated SQUIDS as well as some remarks on their performance is considered. (Auth.)

Signal noise/interferer combiner unit programmable (SINCUP)

Science.gov (United States)

Martinezdepison, Emilio

1988-12-01

The Signal Noise Interferer Combiner Unit Programmable (SINCUP) has been developed to facilitate laboratory performance testing of Very Low Frequency (VLF/Low Frequency (LF) receivers. To accomplish this, the unit allows the combining in controlled amounts of various real-world environmental and manmade interference with an information carrying signal. The externally modulated signal is combined with internally/externally generated Gaussian noise and/or with an internally/externally generated interferer. In order to test modern digital processing techniques, such as Adaptive Null Steering, Eigenvector Sorting, and Widrow-Hoff adaptive filters, SINCUP is capable of generating and meeting much higher signal-to-noise plus interference ratios than earlier channel simulators. The present software has been written to accommodate a dynamic signal-to-noise ratio (SNR) range from -60 to +60 dB. Higher dynamic range units could be implemented.

Dynamics of two competing species in the presence of Lévy noise sources

Science.gov (United States)

La Cognata, A.; Valenti, D.; Dubkov, A. A.; Spagnolo, B.

2010-07-01

We consider a Lotka-Volterra system of two competing species subject to multiplicative α -stable Lévy noise. The interaction parameter between the species is a random process which obeys a stochastic differential equation with a generalized bistable potential in the presence both of a periodic driving term and an additive α -stable Lévy noise. We study the species dynamics, which is characterized by two different regimes, exclusion of one species and coexistence of both. We find quasiperiodic oscillations and stochastic resonance phenomenon in the dynamics of the competing species, analyzing the role of the Lévy noise sources.

A low-cost, ultra-fast and ultra-low noise preamplifier for silicon avalanche photodiodes

Science.gov (United States)

Gasmi, Khaled

2018-02-01

An ultra-fast and ultra-low noise preamplifier for amplifying the fast and weak electrical signals generated by silicon avalanche photodiodes has been designed and developed. It is characterized by its simplicity, compactness, reliability and low cost of construction. A very wide bandwidth of 300 MHz, a very good linearity from 1 kHz to 280 MHz, an ultra-low noise level at the input of only 1.7 nV Hz-1/2 and a very good stability are its key features. The compact size (70 mm  ×  90 mm) and light weight (45 g), as well as its excellent characteristics, make this preamplifier very competitive compared to any commercial preamplifier. The preamplifier, which is a main part of the detection system of a homemade laser remote sensing system, has been successfully tested. In addition, it is versatile and can be used in any optical detection system requiring high speed and very low noise electronics.

Low-noise Collision Operators for Particle-in-cell Simulations

International Nuclear Information System (INIS)

Lewandowski, J.L.V.

2005-01-01

A new method to implement low-noise collision operators in particle-in-cell simulations is presented. The method is based on the fact that relevant collision operators can be included naturally in the Lagrangian formulation that exemplifies the particle-in-cell simulation method. Numerical simulations show that the momentum and energy conservation properties of the simulated plasma associated with the low-noise collision operator are improved as compared with standard collision algorithms based on random numbers

Cross Linked Metal Particles for Low Noise Bolometer Materials

Science.gov (United States)

2016-12-12

Our results indicate that the CLMPs can simultaneously have a high temperature coefficient of resistivity and a low noise, and therefore have a...indicate that the CLMPs can simultaneously have a high temperature co- efficient of resistivity and a low noise, and therefore have a great potential...current as a function of the inverse of applied bias for CLMP films at different temperatures. It is seen that the I-V curves are highly nonlinear as 7 0