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

Energy Technology Data Exchange (ETDEWEB)

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

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean

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

Purpose: The authors have recently developed a preconditioned alternating projection algorithm (PAPA) with total variation (TV) regularizer for solving the penalized-likelihood optimization model for single-photon emission computed tomography (SPECT) reconstruction. This algorithm belongs to a novel class of fixed-point proximity methods. The goal of this work is to investigate how PAPA performs while dealing with realistic noisy SPECT data, to compare its performance with more conventional methods, and to address issues with TV artifacts by proposing a novel form of the algorithm invoking high-order TV regularization, denoted as HOTV-PAPA, which has been explored and studied extensively in the present work. Methods: Using Monte Carlo methods, the authors simulate noisy SPECT data from two water cylinders; one contains lumpy “warm” background and “hot” lesions of various sizes with Gaussian activity distribution, and the other is a reference cylinder without hot lesions. The authors study the performance of HOTV-PAPA and compare it with PAPA using first-order TV regularization (TV-PAPA), the Panin–Zeng–Gullberg one-step-late method with TV regularization (TV-OSL), and an expectation–maximization algorithm with Gaussian postfilter (GPF-EM). The authors select penalty-weights (hyperparameters) by qualitatively balancing the trade-off between resolution and image noise separately for TV-PAPA and TV-OSL. However, the authors arrived at the same penalty-weight value for both of them. The authors set the first penalty-weight in HOTV-PAPA equal to the optimal penalty-weight found for TV-PAPA. The second penalty-weight needed for HOTV-PAPA is tuned by balancing resolution and the severity of staircase artifacts. The authors adjust the Gaussian postfilter to approximately match the local point spread function of GPF-EM and HOTV-PAPA. The authors examine hot lesion detectability, study local spatial resolution, analyze background noise properties, estimate mean

Several rotor noise sources and treatments

Energy Technology Data Exchange (ETDEWEB)

Tangler, J. [National Renewable Energy Laboratory, Golden, CO (United States)

1997-12-31

Noise has been a design consideration in the development of advanced blades and turbines at the National Renewable Energy Laboratory. During atmospheric testing associated with these efforts various types of aeroacoustic noise have been encountered. This presentation discusses several of these noise sources and treatments used to mitigate or eliminate the noise. Tonal noise resulting from tip-vortex/trailing-edge interaction and laminar separation bubbles was found to be easily eliminated. Impulsive noise resulting from blade/vortex interaction for rotors that furl and that due to tower shadow can be mitigated by various means. (au)

Dose reduction in pediatric abdominal CT: use of iterative reconstruction techniques across different CT platforms

International Nuclear Information System (INIS)

Khawaja, Ranish Deedar Ali; Singh, Sarabjeet; Otrakji, Alexi; Padole, Atul; Lim, Ruth; Nimkin, Katherine; Westra, Sjirk; Kalra, Mannudeep K.; Gee, Michael S.

2015-01-01

Dose reduction in children undergoing CT scanning is an important priority for the radiology community and public at large. Drawbacks of radiation reduction are increased image noise and artifacts, which can affect image interpretation. Iterative reconstruction techniques have been developed to reduce noise and artifacts from reduced-dose CT examinations, although reconstruction algorithm, magnitude of dose reduction and effects on image quality vary. We review the reconstruction principles, radiation dose potential and effects on image quality of several iterative reconstruction techniques commonly used in clinical settings, including 3-D adaptive iterative dose reduction (AIDR-3D), adaptive statistical iterative reconstruction (ASIR), iDose, sinogram-affirmed iterative reconstruction (SAFIRE) and model-based iterative reconstruction (MBIR). We also discuss clinical applications of iterative reconstruction techniques in pediatric abdominal CT. (orig.)

Dose reduction in pediatric abdominal CT: use of iterative reconstruction techniques across different CT platforms

Energy Technology Data Exchange (ETDEWEB)

Khawaja, Ranish Deedar Ali; Singh, Sarabjeet; Otrakji, Alexi; Padole, Atul; Lim, Ruth; Nimkin, Katherine; Westra, Sjirk; Kalra, Mannudeep K.; Gee, Michael S. [MGH Imaging, Massachusetts General Hospital, Harvard Medical School, Boston, MA (United States)

2015-07-15

Dose reduction in children undergoing CT scanning is an important priority for the radiology community and public at large. Drawbacks of radiation reduction are increased image noise and artifacts, which can affect image interpretation. Iterative reconstruction techniques have been developed to reduce noise and artifacts from reduced-dose CT examinations, although reconstruction algorithm, magnitude of dose reduction and effects on image quality vary. We review the reconstruction principles, radiation dose potential and effects on image quality of several iterative reconstruction techniques commonly used in clinical settings, including 3-D adaptive iterative dose reduction (AIDR-3D), adaptive statistical iterative reconstruction (ASIR), iDose, sinogram-affirmed iterative reconstruction (SAFIRE) and model-based iterative reconstruction (MBIR). We also discuss clinical applications of iterative reconstruction techniques in pediatric abdominal CT. (orig.)

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

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

Noise affects resource assessment in an invertebrate.

Science.gov (United States)

Walsh, Erin P; Arnott, Gareth; Kunc, Hansjoerg P

2017-04-01

Anthropogenic noise is a global pollutant, affecting animals across taxa. However, how noise pollution affects resource acquisition is unknown. Hermit crabs ( Pagurus bernhardus ) engage in detailed assessment and decision-making when selecting a critical resource, their shell; this is crucial as individuals in poor shells suffer lower reproductive success and higher mortality. We experimentally exposed hermit crabs to anthropogenic noise during shell selection. When exposed to noise, crabs approached the shell faster, spent less time investigating it, and entered it faster. Our results demonstrate that changes in the acoustic environment affect the behaviour of hermit crabs by modifying the selection process of a vital resource. This is all the more remarkable given that the known cues used in shell selection involve chemical, visual and tactile sensory channels. Thus, our study provides rare evidence for a cross-modal impact of noise pollution. © 2017 The Author(s).

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.

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

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

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

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

High-order noise analysis for low dose iterative image reconstruction methods: ASIR, IRIS, and MBAI

Science.gov (United States)

Do, Synho; Singh, Sarabjeet; Kalra, Mannudeep K.; Karl, W. Clem; Brady, Thomas J.; Pien, Homer

2011-03-01

Iterative reconstruction techniques (IRTs) has been shown to suppress noise significantly in low dose CT imaging. However, medical doctors hesitate to accept this new technology because visual impression of IRT images are different from full-dose filtered back-projection (FBP) images. Most common noise measurements such as the mean and standard deviation of homogeneous region in the image that do not provide sufficient characterization of noise statistics when probability density function becomes non-Gaussian. In this study, we measure L-moments of intensity values of images acquired at 10% of normal dose and reconstructed by IRT methods of two state-of-art clinical scanners (i.e., GE HDCT and Siemens DSCT flash) by keeping dosage level identical to each other. The high- and low-dose scans (i.e., 10% of high dose) were acquired from each scanner and L-moments of noise patches were calculated for the comparison.

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.

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.

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.)

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.

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.)

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.

The use of wavelet filters for reducing noise in posterior fossa Computed Tomography images

International Nuclear Information System (INIS)

Pita-Machado, Reinado; Perez-Diaz, Marlen; Lorenzo-Ginori, Juan V.; Bravo-Pino, Rolando

2014-01-01

Wavelet transform based de-noising like wavelet shrinkage, gives the good results in CT. This procedure affects very little the spatial resolution. Some applications are reconstruction methods, while others are a posteriori de-noising methods. De-noising after reconstruction is very difficult because the noise is non-stationary and has unknown distribution. Therefore, methods which work on the sinogram-space don’t have this problem, because they always work over a known noise distribution at this point. On the other hand, the posterior fossa in a head CT is a very complex region for physicians, because it is commonly affected by artifacts and noise which are not eliminated during the reconstruction procedure. This can leads to some false positive evaluations. The purpose of our present work is to compare different wavelet shrinkage de-noising filters to reduce noise, particularly in images of the posterior fossa within CT scans in the sinogram-space. This work describes an experimental search for the best wavelets, to reduce Poisson noise in Computed Tomography (CT) scans. Results showed that de-noising with wavelet filters improved the quality of posterior fossa region in terms of an increased CNR, without noticeable structural distortions

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...

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.

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

Seismic interferometry : Reconstructing the earth's reflection response

NARCIS (Netherlands)

Draganov, D.S.; Wapenaar, C.P.A.; Thorbecke, J.W.

2006-01-01

In 1968, Jon Claerbout showed that the reflection response of a 1D acoustic medium can be reconstructed by autocorrelating the transmission response. Since then, several authors have derived relationships for reconstructing Green's functions at the surface, using crosscorrelations of (noise)

Statistical noise with the weighted backprojection method for single photon emission computed tomography

International Nuclear Information System (INIS)

Murayama, Hideo; Tanaka, Eiichi; Toyama, Hinako.

1985-01-01

The weighted backprojection (WBP) method and the radial post-correction (RPC) method were compared with other several attenuation correction methods for single photon emission computed tomography by computer simulation. These methods are the pre-correction method with arithmetic means of opposing projections, the post-correction method with a correction matrix, and the inverse attenuated Randon transform method. Statistical mean square noise in a reconstructed image was formulated, and was displayed two-dimensionally for typical simulated phantoms. The noise image for the WBP method was dependent on several parameters, namely, size of an attenuating object, distribution of activity, the attenuation coefficient, and choise of the reconstruction index, k and position of the reconstruction origin. The noise image for the WBP method with k=0 was almost the same for the RPC method. It has been shown that position of the reconstruction origin has to be chosen appropriately in order to improve the noise properties of the reconstructed image for the WBP method as well as the RPC method. Comparision of the different attenuation correction methods accomplished by using both the reconstructed images and the statistical noise images with the same mathematical phantom and convolving function concluded that the WBP method and the RPC method were more amenable to any radioisotope distributions than the other methods, and had the advantage of flexibility to improve image noise of any local positions. (author)

Noise Maps for Quantitative and Clinical Severity Towards Long-Term ECG Monitoring.

Science.gov (United States)

Everss-Villalba, Estrella; Melgarejo-Meseguer, Francisco Manuel; Blanco-Velasco, Manuel; Gimeno-Blanes, Francisco Javier; Sala-Pla, Salvador; Rojo-Álvarez, José Luis; García-Alberola, Arcadi

2017-10-25

Noise and artifacts are inherent contaminating components and are particularly present in Holter electrocardiogram (ECG) monitoring. The presence of noise is even more significant in long-term monitoring (LTM) recordings, as these are collected for several days in patients following their daily activities; hence, strong artifact components can temporarily impair the clinical measurements from the LTM recordings. Traditionally, the noise presence has been dealt with as a problem of non-desirable component removal by means of several quantitative signal metrics such as the signal-to-noise ratio (SNR), but current systems do not provide any information about the true impact of noise on the ECG clinical evaluation. As a first step towards an alternative to classical approaches, this work assesses the ECG quality under the assumption that an ECG has good quality when it is clinically interpretable. Therefore, our hypotheses are that it is possible (a) to create a clinical severity score for the effect of the noise on the ECG, (b) to characterize its consistency in terms of its temporal and statistical distribution, and (c) to use it for signal quality evaluation in LTM scenarios. For this purpose, a database of external event recorder (EER) signals is assembled and labeled from a clinical point of view for its use as the gold standard of noise severity categorization. These devices are assumed to capture those signal segments more prone to be corrupted with noise during long-term periods. Then, the ECG noise is characterized through the comparison of these clinical severity criteria with conventional quantitative metrics taken from traditional noise-removal approaches, and noise maps are proposed as a novel representation tool to achieve this comparison. Our results showed that neither of the benchmarked quantitative noise measurement criteria represent an accurate enough estimation of the clinical severity of the noise. A case study of long-term ECG is reported

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

Traffic noise affects forest bird species in a protected tropical forest

Directory of Open Access Journals (Sweden)

J. Edgardo Arévalo

2011-06-01

Full Text Available The construction of roads near protected forest areas alters ecosystem function by creating habitat fragmentation and through several direct and indirect negative effects such as increased pollution, animal mortality through collisions, disturbance caused by excessive noise and wind turbulence. Noise in particular may have strong negative effects on animal groups such as frogs and birds, that rely on sound for communication as it can negatively interfere with vocalizations used for territorial defense or courtship. Thus, birds are expected to be less abundant close to the road where noise levels are high. In this study, we examined the effects of road traffic noise levels on forest bird species in a protected tropical forest in Costa Rica. Data collection was conducted in a forest segment of the Carara National Park adjacent to the Coastal Highway. We carried out 120 ten minute bird surveys and measured road noise levels 192 times from the 19th to the 23rd of April and from the 21st to the 28th of November, 2008. To maximize bird detection for the species richness estimates we operated six 12m standard mist nets simultaneously with the surveys. The overall mist-netting effort was 240net/h. In addition, we estimated traffic volumes by tallying the number of vehicles passing by the edge of the park using 24 one hour counts throughout the study. We found that the relative abundance of birds and bird species richness decreased significantly with the increasing traffic noise in the dry and wet season. Noise decreased significantly and in a logarithmic way with distance from the road in both seasons. However, noise levels at any given distance were significantly higher in the dry compared to the wet season. Our results suggest that noise might be an important factor influencing road bird avoidance as measured by species richness and relative abundance. Since the protected forest in question is located in a national park subjected to tourist visitation

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)

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.

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.)

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.

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.

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

Block Compressed Sensing of Images Using Adaptive Granular Reconstruction

Directory of Open Access Journals (Sweden)

Ran Li

2016-01-01

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

Evaluation of speech transmission in open public spaces affected by combined noises.

Science.gov (United States)

Lee, Pyoung Jik; Jeon, Jin Yong

2011-07-01

In the present study, the effects of interference from combined noises on speech transmission were investigated in a simulated open public space. Sound fields for dominant noises were predicted using a typical urban square model surrounded by buildings. Then road traffic noise and two types of construction noises, corresponding to stationary and impulsive noises, were selected as background noises. Listening tests were performed on a group of adults, and the quality of speech transmission was evaluated using listening difficulty as well as intelligibility scores. During the listening tests, two factors that affect speech transmission performance were considered: (1) temporal characteristics of construction noise (stationary or impulsive) and (2) the levels of the construction and road traffic noises. The results indicated that word intelligibility scores and listening difficulty ratings were affected by the temporal characteristics of construction noise due to fluctuations in the background noise level. It was also observed that listening difficulty is unable to describe the speech transmission in noisy open public spaces showing larger variation than did word intelligibility scores. © 2011 Acoustical Society of America

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.

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)

Environmental noise levels affect the activity budget of the Florida manatee

Science.gov (United States)

Miksis-Olds, Jennifer L.; Donaghay, Percy L.; Miller, James H.; Tyack, Peter L.

2005-09-01

Manatees inhabit coastal bays, lagoons, and estuaries because they are dependent on the aquatic vegetation that grows in shallow waters. Food requirements force manatees to occupy the same areas in which human activities are the greatest. Noise produced from human activities has the potential to affect these animals by eliciting responses ranging from mild behavioral changes to extreme aversion. This study quantifies the behavioral responses of manatees to both changing levels of ambient noise and transient noise sources. Results indicate that elevated environmental noise levels do affect the overall activity budget of this species. The proportion of time manatees spend feeding, milling, and traveling in critical habitats changed as a function of noise level. More time was spent in the directed, goal-oriented behaviors of feeding and traveling, while less time was spent milling when noise levels were highest. The animals also responded to the transient noise of approaching vessels with changes in behavioral state and movements out of the geographical area. This suggests that manatees detect and respond to changes in environmental noise levels. Whether these changes legally constitute harassment and produce biologically significant effects need to be addressed with hypothesis-driven experiments and long-term monitoring. [For Animal Bioacoustics Best Student Paper Award.

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.

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.

MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

International Nuclear Information System (INIS)

Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J

2015-01-01

Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features

MO-FG-204-04: How Iterative Reconstruction Algorithms Affect the NPS of CT Images

Energy Technology Data Exchange (ETDEWEB)

Li, G; Liu, X; Dodge, C; Jensen, C; Rong, J [UT MD Anderson Cancer Center, Houston, TX (United States)

2015-06-15

Purpose: To evaluate how the third generation model based iterative reconstruction (MBIR) compares with filtered back-projection (FBP), adaptive statistical iterative reconstruction (ASiR), and the second generation MBIR based on noise power spectrum (NPS) analysis over a wide range of clinically applicable dose levels. Methods: The Catphan 600 CTP515 module, surrounded by an oval, fat-equivalent ring to mimic patient size/shape, was scanned on a GE HD750 CT scanner at 1, 2, 3, 6, 12 and 19mGy CTDIvol levels with typical patient scan parameters: 120kVp, 0.8s, 40mm beam width, large SFOV, 0.984 pitch and reconstructed thickness 2.5mm (VEO3.0: Abd/Pelvis with Texture and NR05). At each CTDIvol level, 10 repeated scans were acquired for achieving sufficient data sampling. The images were reconstructed using Standard kernel with FBP; 20%, 40% and 70% ASiR; and two versions of MBIR (VEO2.0 and 3.0). For evaluating the effect of the ROI spatial location to the Result of NPS, 4 ROI groups were categorized based on their distances from the center of the phantom. Results: VEO3.0 performed inferiorly comparing to VEO2.0 over all dose levels. On the other hand, at low dose levels (less than 3 mGy), it clearly outperformed ASiR and FBP, in NPS values. Therefore, the lower the dose level, the relative performance of MBIR improves. However, the shapes of the NPS show substantial differences in horizontal and vertical sampling dimensions. These differences may determine the characteristics of the noise/texture features in images, and hence, play an important role in image interpretation. Conclusion: The third generation MBIR did not improve over the second generation MBIR in term of NPS analysis. The overall performance of both versions of MBIR improved as compared to other reconstruction algorithms when dose was reduced. The shapes of the NPS curves provided additional value for future characterization of the image noise/texture features.

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.

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.)

Influence of sinogram affirmed iterative reconstruction of CT data on image noise characteristics and low-contrast detectability: an objective approach.

Directory of Open Access Journals (Sweden)

Christian von Falck

Full Text Available OBJECTIVES: To utilize a novel objective approach combining a software phantom and an image quality metric to systematically evaluate the influence of sinogram affirmed iterative reconstruction (SAFIRE of multidetector computed tomography (MDCT data on image noise characteristics and low-contrast detectability (LCD. MATERIALS AND METHODS: A low-contrast and a high-contrast phantom were examined on a 128-slice scanner at different dose levels. The datasets were reconstructed using filtered back projection (FBP and SAFIRE and virtual low-contrast lesions (-20HU were inserted. LCD was evaluated using the multiscale structural similarity index (MS-SIM*. Image noise texture and spatial resolution were objectively evaluated. RESULTS: The use of SAFIRE led to an improvement of LCD for all dose levels and lesions sizes. The relative improvement of LCD was inversely related to the dose level, declining from 208%(±37%, 259%(±30% and 309%(±35% at 25mAs to 106%(±6%, 119%(±9% and 123%(±8% at 200mAs for SAFIRE filter strengths of 1, 3 and 5 (p<0.05. SAFIRE reached at least the LCD of FBP at a relative dose of 50%. There was no statistically significant difference in spatial resolution. The use of SAFIRE led to coarser image noise granularity. CONCLUSION: A novel objective approach combining a software phantom and the MS-SSIM* image quality metric was used to analyze the detectability of virtual low-contrast lesions against the background of image noise as created using SAFIRE in comparison to filtered back-projection. We found, that image noise characteristics using SAFIRE at 50% dose were comparable to the use of FBP at 100% dose with respect to lesion detectability. The unfamiliar imaging appearance of iteratively reconstructed datasets may in part be explained by a different, coarser noise characteristic as demonstrated by a granulometric analysis.

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

Noise can affect acoustic communication and subsequent spawning success in fish.

Science.gov (United States)

de Jong, Karen; Amorim, M Clara P; Fonseca, Paulo J; Fox, Clive J; Heubel, Katja U

2018-06-01

There are substantial concerns that increasing levels of anthropogenic noise in the oceans may impact aquatic animals. Noise can affect animals physically, physiologically and behaviourally, but one of the most obvious effects is interference with acoustic communication. Acoustic communication often plays a crucial role in reproductive interactions and over 800 species of fish have been found to communicate acoustically. There is very little data on whether noise affects reproduction in aquatic animals, and none in relation to acoustic communication. In this study we tested the effect of continuous noise on courtship behaviour in two closely-related marine fishes: the two-spotted goby (Gobiusculus flavescens) and the painted goby (Pomatoschistus pictus) in aquarium experiments. Both species use visual and acoustic signals during courtship. In the two-spotted goby we used a repeated-measures design testing the same individuals in the noise and the control treatment, in alternating order. For the painted goby we allowed females to spawn, precluding a repeated-measures design, but permitting a test of the effect of noise on female spawning decisions. Males of both species reduced acoustic courtship, but only painted gobies also showed less visual courtship in the noise treatment compared to the control. Female painted gobies were less likely to spawn in the noise treatment. Thus, our results provide experimental evidence for negative effects of noise on acoustic communication and spawning success. Spawning is a crucial component of reproduction. Therefore, even though laboratory results should not be extrapolated directly to field populations, our results suggest that reproductive success may be sensitive to noise pollution, potentially reducing fitness. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

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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.)

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)

SU-G-IeP4-13: PET Image Noise Variability and Its Consequences for Quantifying Tumor Hypoxia

Energy Technology Data Exchange (ETDEWEB)

Kueng, R [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern (Switzerland); Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario (Canada); Manser, P; Fix, M K [Division of Medical Radiation Physics and Department of Radiation Oncology, Inselspital, Bern University Hospital, and University of Bern (Switzerland); Driscoll, B; Keller, H [Radiation Medicine Program, Princess Margaret Cancer Centre, University Health Network, Toronto, Ontario (Canada); Stampanoni, M F M [Institute for Biomedical Engineering, University of Zurich and Swiss Federal Institute of Technology (ETH) (Switzerland)

2016-06-15

Purpose: The values in a PET image which represent activity concentrations of a radioactive tracer are influenced by a large number of parameters including patient conditions as well as image acquisition and reconstruction. This work investigates noise characteristics in PET images for various image acquisition and image reconstruction parameters. Methods: Different phantoms with homogeneous activity distributions were scanned using several acquisition parameters and reconstructed with numerous sets of reconstruction parameters. Images from six PET scanners from different vendors were analyzed and compared with respect to quantitative noise characteristics. Local noise metrics, which give rise to a threshold value defining the metric of hypoxic fraction, as well as global noise measures in terms of noise power spectra (NPS) were computed. In addition to variability due to different reconstruction parameters, spatial variability of activity distribution and its noise metrics were investigated. Patient data from clinical trials were mapped onto phantom scans to explore the impact of the scanner’s intrinsic noise variability on quantitative clinical analysis. Results: Local noise metrics showed substantial variability up to an order of magnitude for different reconstruction parameters. Investigations of corresponding NPS revealed reconstruction dependent structural noise characteristics. For the acquisition parameters, noise metrics were guided by Poisson statistics. Large spatial non-uniformity of the noise was observed in both axial and radial direction of a PET image. In addition, activity concentrations in PET images of homogeneous phantom scans showed intriguing spatial fluctuations for most scanners. The clinical metric of the hypoxic fraction was shown to be considerably influenced by the PET scanner’s spatial noise characteristics. Conclusion: We showed that a hypoxic fraction metric based on noise characteristics requires careful consideration of the

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)

Block matching 3D random noise filtering for absorption optical projection tomography

International Nuclear Information System (INIS)

Fumene Feruglio, P; Vinegoni, C; Weissleder, R; Gros, J; Sbarbati, A

2010-01-01

B on severe noise-affected reconstructions revealing original-noise-hidden-image details. These results show the utility of the BM3D approach for OPT under typical conditions of very low light absorption, suggesting its implementation as an efficient alternative to other filtering schemes such as for example the median filter.

Computed Tomography Imaging of a Hip Prosthesis Using Iterative Model-Based Reconstruction and Orthopaedic Metal Artefact Reduction: A Quantitative Analysis.

Science.gov (United States)

Wellenberg, Ruud H H; Boomsma, Martijn F; van Osch, Jochen A C; Vlassenbroek, Alain; Milles, Julien; Edens, Mireille A; Streekstra, Geert J; Slump, Cornelis H; Maas, Mario

To quantify the combined use of iterative model-based reconstruction (IMR) and orthopaedic metal artefact reduction (O-MAR) in reducing metal artefacts and improving image quality in a total hip arthroplasty phantom. Scans acquired at several dose levels and kVps were reconstructed with filtered back-projection (FBP), iterative reconstruction (iDose) and IMR, with and without O-MAR. Computed tomography (CT) numbers, noise levels, signal-to-noise-ratios and contrast-to-noise-ratios were analysed. Iterative model-based reconstruction results in overall improved image quality compared to iDose and FBP (P < 0.001). Orthopaedic metal artefact reduction is most effective in reducing severe metal artefacts improving CT number accuracy by 50%, 60%, and 63% (P < 0.05) and reducing noise by 1%, 62%, and 85% (P < 0.001) whereas improving signal-to-noise-ratios by 27%, 47%, and 46% (P < 0.001) and contrast-to-noise-ratios by 16%, 25%, and 19% (P < 0.001) with FBP, iDose, and IMR, respectively. The combined use of IMR and O-MAR strongly improves overall image quality and strongly reduces metal artefacts in the CT imaging of a total hip arthroplasty phantom.

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.

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

Implant salvage in breast reconstruction with severe peri-prosthetic infection.

Science.gov (United States)

Meybodi, Farid; Sedaghat, Negin; French, James; Keighley, Caitlin; Mitchell, David; Elder, Elisabeth

2017-12-01

Although treatment of mild peri-prosthetic infection in implant-based breast reconstruction results in high rates of resolution, successful management of severe peri-prosthetic infection remains a significant challenge. In this case series, a protocol utilizing a novel dressing - negative pressure wound therapy with instillation (NPWTi) - for the management of severe peri-prosthetic infection in breast reconstruction patients is described. This is an operative technique involving: (i) explantation of the breast prosthesis and application of the NPWTi dressing to the implant pocket; (ii) change of the NPWTi dressing; (iii) intraoperative fluid/tissue cultures; and (iv) reimplantation of the breast prosthesis when cultures yield no growth. This protocol was utilized in six cases of severe peri-prosthetic infection in five patients with immediate breast reconstruction for breast cancer or risk-reducing surgery. Cultures of fluid/tissue grew typical and/or unusual organisms. Only one case did not yield an organism. The hospital length of stay upon completion of the protocol ranged from 7-16 days (mean, 12 days). Successful implant salvage was achieved in five of six cases. The protocol was aborted in one case to allow for completion of adjuvant chemotherapy. Early findings from this case series suggest that in cases of severe peri-prosthetic infection this novel operative protocol may result in successful implant salvage for breast reconstruction patients. Further studies are needed to more fully elaborate the role of NPWTi to achieve implant salvage in challenging cases of peri-prosthetic infection. © 2015 Royal Australasian College of Surgeons.

Determination of signal intensity affected by Gaussian noise

International Nuclear Information System (INIS)

Blostein, Jeronimo J.; Bennun, Leonardo

1999-01-01

A methodology based on maximum likelihood criteria, to identify and quantify an arbitrary signal affected by Gaussian noise is shown. To use this methodology it is necessary to know the position in the spectrum where the signal of interest should appear, and the shape of the signal when the background is null or unappreciable. (author)

Does severity of femoral trochlear dysplasia affect outcome in patellofemoral instability treated by medial patellofemoral ligament reconstruction and anterior tibial tuberosity transfer?

Science.gov (United States)

Moitrel, G; Roumazeille, T; Arnould, A; Migaud, H; Putman, S; Ramdane, N; Pasquier, G

2015-10-01

Medial patellofemoral ligament (MPFL) reconstruction associated to anterior tibial tuberosity transfer (ATTT) is recommended in objective patellofemoral instability (PFI). Efficacy, however, has not been precisely determined in trochlear dysplasia with spur. A case-control study was performed in a PFI population, comparing groups with trochlear dysplasia with and without spur (S+ vs. S-) to assess the impact of trochlear dysplasia on (1) patellofemoral stability, (2) functional results and complications, and (3) patellofemoral cartilage status on MRI. Trochlear spur does not affect outcome in PFI managed by MPFL reconstruction and ATTT. Twenty-eight knees (26 patients) with PFI were analyzed retrospectively and divided into 2 groups of 14 knees each according to presence of trochlear spur (S+ vs. S-). All 28 knees had undergone ATTT and MPFL reconstruction by semitendinosus autograft. Results were assessed on Lille and IKDC functional scores, and cartilage status was determined on MRI at last follow-up. At a mean 24 months' follow-up (range, 12-52 months), there was no recurrence of dislocation. IKDC and Lille scores tended to improve in both groups, although the only significant improvement was in IKDC score (S- gain, 21.3±16; S+ gain, 18.1±14) (P=0.01). IKDC scores at last follow-up were better in the S+ than S- group (79±19 [range, 21-92] vs. 68±13 [range, 35-84], respectively; P=0.012). Lille scores showed no significant inter-group differences in mean gain (P=0.492) or mean value (P=0.381). The S+ group showed more cartilage lesions (n=14/14 knees, including 12/14 with grade≥2 lesions) than the S- group (n=9/14 knees, all grade≤2). MPFL reconstruction with ATTT provided good short-term patellofemoral stability independently of the severity of trochlear dysplasia. Functional results and gain on IKDC, however, were poorer in case of dysplasia with trochlear spur. This is probably due to cartilage lesions, observed more frequently pre- and post

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.

Performance comparison between total variation (TV)-based compressed sensing and statistical iterative reconstruction algorithms

International Nuclear Information System (INIS)

Tang Jie; Nett, Brian E; Chen Guanghong

2009-01-01

Of all available reconstruction methods, statistical iterative reconstruction algorithms appear particularly promising since they enable accurate physical noise modeling. The newly developed compressive sampling/compressed sensing (CS) algorithm has shown the potential to accurately reconstruct images from highly undersampled data. The CS algorithm can be implemented in the statistical reconstruction framework as well. In this study, we compared the performance of two standard statistical reconstruction algorithms (penalized weighted least squares and q-GGMRF) to the CS algorithm. In assessing the image quality using these iterative reconstructions, it is critical to utilize realistic background anatomy as the reconstruction results are object dependent. A cadaver head was scanned on a Varian Trilogy system at different dose levels. Several figures of merit including the relative root mean square error and a quality factor which accounts for the noise performance and the spatial resolution were introduced to objectively evaluate reconstruction performance. A comparison is presented between the three algorithms for a constant undersampling factor comparing different algorithms at several dose levels. To facilitate this comparison, the original CS method was formulated in the framework of the statistical image reconstruction algorithms. Important conclusions of the measurements from our studies are that (1) for realistic neuro-anatomy, over 100 projections are required to avoid streak artifacts in the reconstructed images even with CS reconstruction, (2) regardless of the algorithm employed, it is beneficial to distribute the total dose to more views as long as each view remains quantum noise limited and (3) the total variation-based CS method is not appropriate for very low dose levels because while it can mitigate streaking artifacts, the images exhibit patchy behavior, which is potentially harmful for medical diagnosis.

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

Quantitative SPECT reconstruction of iodine-123 data

International Nuclear Information System (INIS)

Gilland, D.R.; Jaszczak, R.J.; Greer, K.L.; Coleman, R.E.

1991-01-01

Many clinical and research studies in nuclear medicine require quantitation of iodine-123 ( 123 I) distribution for the determination of kinetics or localization. The objective of this study was to implement several reconstruction methods designed for single-photon emission computed tomography (SPECT) using 123 I and to evaluate their performance in terms of quantitative accuracy, image artifacts, and noise. The methods consisted of four attenuation and scatter compensation schemes incorporated into both the filtered backprojection/Chang (FBP) and maximum likelihood-expectation maximization (ML-EM) reconstruction algorithms. The methods were evaluated on data acquired of a phantom containing a hot sphere of 123 I activity in a lower level background 123 I distribution and nonuniform density media. For both reconstruction algorithms, nonuniform attenuation compensation combined with either scatter subtraction or Metz filtering produced images that were quantitatively accurate to within 15% of the true value. The ML-EM algorithm demonstrated quantitative accuracy comparable to FBP and smaller relative noise magnitude for all compensation schemes

Noise propagation in resolution modeled PET imaging and its impact on detectability

International Nuclear Information System (INIS)

Rahmim, Arman; Tang, Jing

2013-01-01

Positron emission tomography imaging is affected by a number of resolution degrading phenomena, including positron range, photon non-collinearity and inter-crystal blurring. An approach to this issue is to model some or all of these effects within the image reconstruction task, referred to as resolution modeling (RM). This approach is commonly observed to yield images of higher resolution and subsequently contrast, and can be thought of as improving the modulation transfer function. Nonetheless, RM can substantially alter the noise distribution. In this work, we utilize noise propagation models in order to accurately characterize the noise texture of reconstructed images in the presence of RM. Furthermore we consider the task of lesion or defect detection, which is highly determined by the noise distribution as quantified using the noise power spectrum. Ultimately, we use this framework to demonstrate why conventional trade-off analyses (e.g. contrast versus noise, using simplistic noise metrics) do not provide a complete picture of the impact of RM and that improved performance of RM according to such analyses does not necessarily translate to the superiority of RM in detection task performance. (paper)

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.

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

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.

Theoretical evaluation of the detectability of random lesions in bayesian emission reconstruction

International Nuclear Information System (INIS)

Qi, Jinyi

2003-01-01

Detecting cancerous lesion is an important task in positron emission tomography (PET). Bayesian methods based on the maximum a posteriori principle (also called penalized maximum likelihood methods) have been developed to deal with the low signal to noise ratio in the emission data. Similar to the filter cut-off frequency in the filtered backprojection method, the prior parameters in Bayesian reconstruction control the resolution and noise trade-off and hence affect detectability of lesions in reconstructed images. Bayesian reconstructions are difficult to analyze because the resolution and noise properties are nonlinear and object-dependent. Most research has been based on Monte Carlo simulations, which are very time consuming. Building on the recent progress on the theoretical analysis of image properties of statistical reconstructions and the development of numerical observers, here we develop a theoretical approach for fast computation of lesion detectability in Bayesian reconstruction. The results can be used to choose the optimum hyperparameter for the maximum lesion detectability. New in this work is the use of theoretical expressions that explicitly model the statistical variation of the lesion and background without assuming that the object variation is (locally) stationary. The theoretical results are validated using Monte Carlo simulations. The comparisons show good agreement between the theoretical predications and the Monte Carlo results

Image quality in children with low-radiation chest CT using adaptive statistical iterative reconstruction and model-based iterative reconstruction.

Directory of Open Access Journals (Sweden)

Jihang Sun

Full Text Available OBJECTIVE: To evaluate noise reduction and image quality improvement in low-radiation dose chest CT images in children using adaptive statistical iterative reconstruction (ASIR and a full model-based iterative reconstruction (MBIR algorithm. METHODS: Forty-five children (age ranging from 28 days to 6 years, median of 1.8 years who received low-dose chest CT scans were included. Age-dependent noise index (NI was used for acquisition. Images were retrospectively reconstructed using three methods: MBIR, 60% of ASIR and 40% of conventional filtered back-projection (FBP, and FBP. The subjective quality of the images was independently evaluated by two radiologists. Objective noises in the left ventricle (LV, muscle, fat, descending aorta and lung field at the layer with the largest cross-section area of LV were measured, with the region of interest about one fourth to half of the area of descending aorta. Optimized signal-to-noise ratio (SNR was calculated. RESULT: In terms of subjective quality, MBIR images were significantly better than ASIR and FBP in image noise and visibility of tiny structures, but blurred edges were observed. In terms of objective noise, MBIR and ASIR reconstruction decreased the image noise by 55.2% and 31.8%, respectively, for LV compared with FBP. Similarly, MBIR and ASIR reconstruction increased the SNR by 124.0% and 46.2%, respectively, compared with FBP. CONCLUSION: Compared with FBP and ASIR, overall image quality and noise reduction were significantly improved by MBIR. MBIR image could reconstruct eligible chest CT images in children with lower radiation dose.

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.

Arterial cross-section reconstruction from bi-plane X-ray shadowgraphs

International Nuclear Information System (INIS)

Fenster, P.; Barba, J.; Suardiaz, M.; Wong, K.K.; Herrold, E.M.; Kenet, R.O.; Borer, J.S.

1987-01-01

An iterative algorithm was used to reconstruct the cross-section of a crescent-shaped vessel lumen. The accuracy of this method was evaluated by comparing reconstruction error in the presence of Gaussian noise of different magnitudes. The sensitivity of the reconstruction algorithm to initial boundary constraint error was also evaluated. Using this algorithm, the reconstruction error was 1.7% when applied to crescent shaped lumen. This error was found to increase significantly with increasing Gaussian noise (error range: 5.75 - 20.75% for noise variance 1-8 pixels). Median filtering of the noise-degraded density profiles improved the reconstruction error (error range: 3.25 - 10.5% for noise variance 1-8 pixels). The mean reconstruction error was not strongly influenced by initial boundary constraint error. The algorithm provided reasonable reconstruction results when applied to X-ray image derived density profiles of known luminal shapes

Incomplete projection reconstruction of computed tomography based on the modified discrete algebraic reconstruction technique

Science.gov (United States)

Yang, Fuqiang; Zhang, Dinghua; Huang, Kuidong; Gao, Zongzhao; Yang, YaFei

2018-02-01

Based on the discrete algebraic reconstruction technique (DART), this study aims to address and test a new improved algorithm applied to incomplete projection data to generate a high quality reconstruction image by reducing the artifacts and noise in computed tomography. For the incomplete projections, an augmented Lagrangian based on compressed sensing is first used in the initial reconstruction for segmentation of the DART to get higher contrast graphics for boundary and non-boundary pixels. Then, the block matching 3D filtering operator was used to suppress the noise and to improve the gray distribution of the reconstructed image. Finally, simulation studies on the polychromatic spectrum were performed to test the performance of the new algorithm. Study results show a significant improvement in the signal-to-noise ratios (SNRs) and average gradients (AGs) of the images reconstructed from incomplete data. The SNRs and AGs of the new images reconstructed by DART-ALBM were on average 30%-40% and 10% higher than the images reconstructed by DART algorithms. Since the improved DART-ALBM algorithm has a better robustness to limited-view reconstruction, which not only makes the edge of the image clear but also makes the gray distribution of non-boundary pixels better, it has the potential to improve image quality from incomplete projections or sparse projections.

Noise texture and signal detectability in propagation-based x-ray phase-contrast tomography

International Nuclear Information System (INIS)

Chou, Cheng-Ying; Anastasio, Mark A.

2010-01-01

Purpose: X-ray phase-contrast tomography (PCT) is a rapidly emerging imaging modality for reconstructing estimates of an object's three-dimensional x-ray refractive index distribution. Unlike conventional x-ray computed tomography methods, the statistical properties of the reconstructed images in PCT remain unexplored. The purpose of this work is to quantitatively investigate noise propagation in PCT image reconstruction. Methods: The authors derived explicit expressions for the autocovariance of the reconstructed absorption and refractive index images to characterize noise texture and understand how the noise properties are influenced by the imaging geometry. Concepts from statistical detection theory were employed to understand how the imaging geometry-dependent statistical properties affect the signal detection performance in a signal-known-exactly/background-known-exactly task. Results: The analytical formulas for the phase and absorption autocovariance functions were implemented numerically and compared to the corresponding empirical values, and excellent agreement was found. They observed that the reconstructed refractive images are highly spatially correlated, while the absorption images are not. The numerical results confirm that the strength of the covariance is scaled by the detector spacing. Signal detection studies were conducted, employing a numerical observer. The detection performance was found to monotonically increase as the detector-plane spacing was increased. Conclusions: The authors have conducted the first quantitative investigation of noise propagation in PCT image reconstruction. The reconstructed refractive images were found to be highly spatially correlated, while absorption images were not. This is due to the presence of a Fourier space singularity in the reconstruction formula for the refraction images. The statistical analysis may facilitate the use of task-based image quality measures to further develop and optimize this emerging

Noise texture and signal detectability in propagation-based x-ray phase-contrast tomography

Energy Technology Data Exchange (ETDEWEB)

Chou, Cheng-Ying; Anastasio, Mark A. [Department of Bio-Industrial Mechatronics Engineering, National Taiwan University, 1, Section 4, Roosevelt Road, Taipei, Taiwan 106, Taiwan (China); Department of Biomedical Engineering, Medical Imaging Research Center, Illinois Institute of Technology, 3440 S. Dearborn Street, E1-116, Chicago, Illinois 60616 (United States)

2010-01-15

Purpose: X-ray phase-contrast tomography (PCT) is a rapidly emerging imaging modality for reconstructing estimates of an object's three-dimensional x-ray refractive index distribution. Unlike conventional x-ray computed tomography methods, the statistical properties of the reconstructed images in PCT remain unexplored. The purpose of this work is to quantitatively investigate noise propagation in PCT image reconstruction. Methods: The authors derived explicit expressions for the autocovariance of the reconstructed absorption and refractive index images to characterize noise texture and understand how the noise properties are influenced by the imaging geometry. Concepts from statistical detection theory were employed to understand how the imaging geometry-dependent statistical properties affect the signal detection performance in a signal-known-exactly/background-known-exactly task. Results: The analytical formulas for the phase and absorption autocovariance functions were implemented numerically and compared to the corresponding empirical values, and excellent agreement was found. They observed that the reconstructed refractive images are highly spatially correlated, while the absorption images are not. The numerical results confirm that the strength of the covariance is scaled by the detector spacing. Signal detection studies were conducted, employing a numerical observer. The detection performance was found to monotonically increase as the detector-plane spacing was increased. Conclusions: The authors have conducted the first quantitative investigation of noise propagation in PCT image reconstruction. The reconstructed refractive images were found to be highly spatially correlated, while absorption images were not. This is due to the presence of a Fourier space singularity in the reconstruction formula for the refraction images. The statistical analysis may facilitate the use of task-based image quality measures to further develop and optimize this emerging

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 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.

Weight Multispectral Reconstruction Strategy for Enhanced Reconstruction Accuracy and Stability With Cerenkov Luminescence Tomography.

Science.gov (United States)

Hongbo Guo; Xiaowei He; Muhan Liu; Zeyu Zhang; Zhenhua Hu; Jie Tian

2017-06-01

Cerenkov luminescence tomography (CLT) provides a novel technique for 3-D noninvasive detection of radiopharmaceuticals in living subjects. However, because of the severe scattering of Cerenkov light, the reconstruction accuracy and stability of CLT is still unsatisfied. In this paper, a modified weight multispectral CLT (wmCLT) reconstruction strategy was developed which split the Cerenkov radiation spectrum into several sub-spectral bands and weighted the sub-spectral results to obtain the final result. To better evaluate the property of the wmCLT reconstruction strategy in terms of accuracy, stability and practicability, several numerical simulation experiments and in vivo experiments were conducted and the results obtained were compared with the traditional multispectral CLT (mCLT) and hybrid-spectral CLT (hCLT) reconstruction strategies. The numerical simulation results indicated that wmCLT strategy significantly improved the accuracy of Cerenkov source localization and intensity quantitation and exhibited good stability in suppressing noise in numerical simulation experiments. And the comparison of the results achieved from different in vivo experiments further indicated significant improvement of the wmCLT strategy in terms of the shape recovery of the bladder and the spatial resolution of imaging xenograft tumors. Overall the strategy reported here will facilitate the development of nuclear and optical molecular tomography in theoretical study.

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.

Traffic noise affects forest bird species in a protected tropical forest

Directory of Open Access Journals (Sweden)

J. Edgardo Arévalo

2011-06-01

Full Text Available The construction of roads near protected forest areas alters ecosystem function by creating habitat fragmentation and through several direct and indirect negative effects such as increased pollution, animal mortality through collisions, disturbance caused by excessive noise and wind turbulence. Noise in particular may have strong negative effects on animal groups such as frogs and birds, that rely on sound for communication as it can negatively interfere with vocalizations used for territorial defense or courtship. Thus, birds are expected to be less abundant close to the road where noise levels are high. In this study, we examined the effects of road traffic noise levels on forest bird species in a protected tropical forest in Costa Rica. Data collection was conducted in a forest segment of the Carara National Park adjacent to the Coastal Highway. We carried out 120 ten minute bird surveys and measured road noise levels 192 times from the 19th to the 23rd of April and from the 21st to the 28th of November, 2008. To maximize bird detection for the species richness estimates we operated six 12m standard mist nets simultaneously with the surveys. The overall mist-netting effort was 240net/h. In addition, we estimated traffic volumes by tallying the number of vehicles passing by the edge of the park using 24 one hour counts throughout the study. We found that the relative abundance of birds and bird species richness decreased significantly with the increasing traffic noise in the dry and wet season. Noise decreased significantly and in a logarithmic way with distance from the road in both seasons. However, noise levels at any given distance were significantly higher in the dry compared to the wet season. Our results suggest that noise might be an important factor influencing road bird avoidance as measured by species richness and relative abundance. Since the protected forest in question is located in a national park subjected to tourist visitation

Mitigating Wind Induced Noise in Outdoor Microphone Signals Using a Singular Spectral Subspace Method

Directory of Open Access Journals (Sweden)

Omar Eldwaik

2018-01-01

Full Text Available Wind induced noise is one of the major concerns of outdoor acoustic signal acquisition. It affects many field measurement and audio recording scenarios. Filtering such noise is known to be difficult due to its broadband and time varying nature. In this paper, a new method to mitigate wind induced noise in microphone signals is developed. Instead of applying filtering techniques, wind induced noise is statistically separated from wanted signals in a singular spectral subspace. The paper is presented in the context of handling microphone signals acquired outdoor for acoustic sensing and environmental noise monitoring or soundscapes sampling. The method includes two complementary stages, namely decomposition and reconstruction. The first stage decomposes mixed signals in eigen-subspaces, selects and groups the principal components according to their contributions to wind noise and wanted signals in the singular spectrum domain. The second stage reconstructs the signals in the time domain, resulting in the separation of wind noise and wanted signals. Results show that microphone wind noise is separable in the singular spectrum domain evidenced by the weighted correlation. The new method might be generalized to other outdoor sound acquisition applications.

Liquid Argon TPC Signal Formation, Signal Processing and Hit Reconstruction

Energy Technology Data Exchange (ETDEWEB)

Baller, Bruce [Fermilab

2017-03-11

This document describes the early stage of the reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions requires knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise.

Localization of Vibrating Noise Sources in Nuclear Reactor Cores

International Nuclear Information System (INIS)

Hultqvist, Pontus

2004-09-01

In this thesis the possibility of locating vibrating noise sources in a nuclear reactor core from the neutron noise has been investigated using different localization methods. The influence of the vibrating noise source has been considered to be a small perturbation of the neutron flux inside the reactor. Linear perturbation theory has been used to construct the theoretical framework upon which the localization methods are based. Two different cases have been considered: one where a one-dimensional one-group model has been used and another where a two-dimensional two-energy group noise simulator has been used. In the first case only one localization method is able to determine the position with good accuracy. This localization method is based on finding roots of an equation and is sensitive to other perturbations of the neutron flux. It will therefore work better with the assistance of approximative methods that reconstruct the noise source to determine if the results are reliable or not. In the two-dimensional case the results are more promising. There are several different localization techniques that reproduce both the vibrating noise source position and the direction of vibration with enough precision. The approximate methods that reconstruct the noise source are substantially better and are able to support the root finding method in a more constructive way. By combining the methods, the results will be more reliable

Occupational noise-induced tinnitus: does it affect workers' quality of life?

Science.gov (United States)

Muluk, Nuray Bayar; Oguztürk, Omer

2008-02-01

This prospective study aimed to investigate the quality of life of workers in a steel factory. The study group was composed of 16 male workers with tinnitus and 30 ears. Fifteen male workers without tinnitus and 30 ears were included into the control group. Workers were evaluated by questionnaire, pure-tone audiometry, and the SF-36 Health Survey. In the study group, tinnitus loudness levels (TLLs) were found. In the study group, the domains general mental health and role limitations owing to emotional problems were significantly lower than in the control group. Older age, industrial noise exposure over a long period, higher noise exposure during work, and hearing loss secondary to occupational noise caused workers to experience higher TLLs. Earheadings protected workers more than earplugs, and TLLs were lower. Important factors that affect workers' quality of life are maximum exposed noise levels, daily and total noise exposure time, and exposure to continuous noise. Occupational noise-induced tinnitus mainly causes emotional disability rather than physical disability. Emotionally impaired QOL results may be due to tinnitus-related psychological problems. Workers should have knowledge about the hazardous effects of noise. Periodic health checkups and regular seminars have great importance. Workers must be aware of other ototoxic factors, such as medications and noisy music. In the future, researchers should develop a screening method to detect those with a more hereditary affinity to hearing loss.

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.

Reconstruction of convex bodies from surface tensors

DEFF Research Database (Denmark)

Kousholt, Astrid; Kiderlen, Markus

2016-01-01

We present two algorithms for reconstruction of the shape of convex bodies in the two-dimensional Euclidean space. The first reconstruction algorithm requires knowledge of the exact surface tensors of a convex body up to rank s for some natural number s. When only measurements subject to noise...... of surface tensors are available for reconstruction, we recommend to use certain values of the surface tensors, namely harmonic intrinsic volumes instead of the surface tensors evaluated at the standard basis. The second algorithm we present is based on harmonic intrinsic volumes and allows for noisy...... measurements. From a generalized version of Wirtinger's inequality, we derive stability results that are utilized to ensure consistency of both reconstruction procedures. Consistency of the reconstruction procedure based on measurements subject to noise is established under certain assumptions on the noise...

Model-based image reconstruction for four-dimensional PET

International Nuclear Information System (INIS)

Li Tianfang; Thorndyke, Brian; Schreibmann, Eduard; Yang Yong; Xing Lei

2006-01-01

Positron emission tonography (PET) is useful in diagnosis and radiation treatment planning for a variety of cancers. For patients with cancers in thoracic or upper abdominal region, the respiratory motion produces large distortions in the tumor shape and size, affecting the accuracy in both diagnosis and treatment. Four-dimensional (4D) (gated) PET aims to reduce the motion artifacts and to provide accurate measurement of the tumor volume and the tracer concentration. A major issue in 4D PET is the lack of statistics. Since the collected photons are divided into several frames in the 4D PET scan, the quality of each reconstructed frame degrades as the number of frames increases. The increased noise in each frame heavily degrades the quantitative accuracy of the PET imaging. In this work, we propose a method to enhance the performance of 4D PET by developing a new technique of 4D PET reconstruction with incorporation of an organ motion model derived from 4D-CT images. The method is based on the well-known maximum-likelihood expectation-maximization (ML-EM) algorithm. During the processes of forward- and backward-projection in the ML-EM iterations, all projection data acquired at different phases are combined together to update the emission map with the aid of deformable model, the statistics is therefore greatly improved. The proposed algorithm was first evaluated with computer simulations using a mathematical dynamic phantom. Experiment with a moving physical phantom was then carried out to demonstrate the accuracy of the proposed method and the increase of signal-to-noise ratio over three-dimensional PET. Finally, the 4D PET reconstruction was applied to a patient case

Estimating local noise power spectrum from a few FBP-reconstructed CT scans

Energy Technology Data Exchange (ETDEWEB)

Zeng, Rongping, E-mail: rongping.zeng@fda.hhs.gov; Gavrielides, Marios A.; Petrick, Nicholas; Sahiner, Berkman; Li, Qin; Myers, Kyle J. [Division of Imaging, Diagnostics, and Software Reliability, Office of Science and Engineering Laboratories, CDRH, FDA, Silver Spring, Maryland 20993 (United States)

2016-01-15

Purpose: Traditional ways to estimate 2D CT noise power spectrum (NPS) involve an ensemble average of the power spectrums of many noisy scans. When only a few scans are available, regions of interest are often extracted from different locations to obtain sufficient samples to estimate the NPS. Using image samples from different locations ignores the nonstationarity of CT noise and thus cannot accurately characterize its local properties. The purpose of this work is to develop a method to estimate local NPS using only a few fan-beam CT scans. Methods: As a result of FBP reconstruction, the CT NPS has the same radial profile shape for all projection angles, with the magnitude varying with the noise level in the raw data measurement. This allows a 2D CT NPS to be factored into products of a 1D angular and a 1D radial function in polar coordinates. The polar separability of CT NPS greatly reduces the data requirement for estimating the NPS. The authors use this property and derive a radial NPS estimation method: in brief, the radial profile shape is estimated from a traditional NPS based on image samples extracted at multiple locations. The amplitudes are estimated by fitting the traditional local NPS to the estimated radial profile shape. The estimated radial profile shape and amplitudes are then combined to form a final estimate of the local NPS. We evaluate the accuracy of the radial NPS method and compared it to traditional NPS methods in terms of normalized mean squared error (NMSE) and signal detectability index. Results: For both simulated and real CT data sets, the local NPS estimated with no more than six scans using the radial NPS method was very close to the reference NPS, according to the metrics of NMSE and detectability index. Even with only two scans, the radial NPS method was able to achieve a fairly good accuracy. Compared to those estimated using traditional NPS methods, the accuracy improvement was substantial when a few scans were available

An Lq–Lp optimization framework for image reconstruction of electrical resistance tomography

International Nuclear Information System (INIS)

Zhao, Jia; Xu, Yanbin; Dong, Feng

2014-01-01

Image reconstruction in electrical resistance tomography (ERT) is an ill-posed and nonlinear problem, which is easily affected by measurement noise. The regularization method with L 2 constraint term or L 1 constraint term is often used to solve the inverse problem of ERT. It shows that the reconstruction method with L 2 regularization puts smoothness to obtain stability in the image reconstruction process, which is blurry at the interface of different conductivities. The regularization method with L 1 norm is powerful at dealing with the over-smoothing effects, which is beneficial in obtaining a sharp transaction in conductivity distribution. To find the reason for these effects, an L q –L p optimization framework (1 ⩽ q ⩽ 2, 1 ⩽ p ⩽ 2) for the image reconstruction of ERT is presented in this paper. The L q –L p optimization framework is solved based on an approximation handling with Gauss–Newton iteration algorithm. The optimization framework is tested for image reconstruction of ERT with different models and the effects of the L p regularization term on the quality of the reconstructed images are discussed with both simulation and experiment. By comparing the reconstructed results with different p in the regularization term, it is found that a large penalty is implemented on small data in the solution when p is small and a lesser penalty is implemented on small data in the solution when p is larger. It also makes the reconstructed images smoother and more easily affected by noise when p is larger. (paper)

Task-based assessment of breast tomosynthesis: Effect of acquisition parameters and quantum noise1

OpenAIRE

Reiser, I.; Nishikawa, R. M.

2010-01-01

Purpose: Tomosynthesis is a promising modality for breast imaging. The appearance of the tomosynthesis reconstructed image is greatly affected by the choice of acquisition and reconstruction parameters. The purpose of this study was to investigate the limitations of tomosynthesis breast imaging due to scan parameters and quantum noise. Tomosynthesis image quality was assessed based on performance of a mathematical observer model in a signal-known exactly (SKE) detection task.

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...

Denoising of B1+ field maps for noise-robust image reconstruction in electrical properties tomography

International Nuclear Information System (INIS)

Michel, Eric; Hernandez, Daniel; Cho, Min Hyoung; Lee, Soo Yeol

2014-01-01

Purpose: To validate the use of adaptive nonlinear filters in reconstructing conductivity and permittivity images from the noisy B 1 + maps in electrical properties tomography (EPT). Methods: In EPT, electrical property images are computed by taking Laplacian of the B 1 + maps. To mitigate the noise amplification in computing the Laplacian, the authors applied adaptive nonlinear denoising filters to the measured complex B 1 + maps. After the denoising process, they computed the Laplacian by central differences. They performed EPT experiments on phantoms and a human brain at 3 T along with corresponding EPT simulations on finite-difference time-domain models. They evaluated the EPT images comparing them with the ones obtained by previous EPT reconstruction methods. Results: In both the EPT simulations and experiments, the nonlinear filtering greatly improved the EPT image quality when evaluated in terms of the mean and standard deviation of the electrical property values at the regions of interest. The proposed method also improved the overall similarity between the reconstructed conductivity images and the true shapes of the conductivity distribution. Conclusions: The nonlinear denoising enabled us to obtain better-quality EPT images of the phantoms and the human brain at 3 T

The Huber’s Method-based Gas Concentration Reconstruction in Multicomponent Gas Mixtures from Multispectral Laser Measurements under Noise Overshoot Conditions

Directory of Open Access Journals (Sweden)

V. A. Gorodnichev

2016-01-01

Full Text Available Laser gas analysers are the most promising for the rapid quantitative analysis of gaseous air pollution. A laser gas analysis problem is that there are instable results in reconstruction of gas mixture components concentration under real noise in the recorded laser signal. This necessitates using the special processing algorithms. When reconstructing the quantitative composition of multi-component gas mixtures from the multispectral laser measurements are efficiently used methods such as Tikhonov regularization, quasi-solution search, and finding of Bayesian estimators. These methods enable using the single measurement results to determine the quantitative composition of gas mixtures under measurement noise. In remote sensing the stationary gas formations or in laboratory analysis of the previously selected (when the gas mixture is stationary air samples the reconstruction procedures under measurement noise of gas concentrations in multicomponent mixtures can be much simpler. The paper considers a problem of multispectral laser analysis of stationary gas mixtures for which it is possible to conduct a series of measurements. With noise overshoots in the recorded laser signal (and, consequently, overshoots of gas concentrations determined by a single measurement must be used stable (robust estimation techniques for substantial reducing an impact of the overshoots on the estimate of required parameters. The paper proposes the Huber method to determine gas concentrations in multicomponent mixtures under signal overshoot. To estimate the value of Huber parameter and the efficiency of Huber's method to find the stable estimates of gas concentrations in multicomponent stationary mixtures from the laser measurements the mathematical modelling was conducted. Science & Education of the Bauman MSTU 108 The mathematical modelling results show that despite the considerable difference among the errors of the mixture gas components themselves a character of

Photoplethysmograph signal reconstruction based on a novel motion artifact detection-reduction approach. Part II: Motion and noise artifact removal.

Science.gov (United States)

Salehizadeh, S M A; Dao, Duy K; Chong, Jo Woon; McManus, David; Darling, Chad; Mendelson, Yitzhak; Chon, Ki H

2014-11-01

We introduce a new method to reconstruct motion and noise artifact (MNA) contaminated photoplethysmogram (PPG) data. A method to detect MNA corrupted data is provided in a companion paper. Our reconstruction algorithm is based on an iterative motion artifact removal (IMAR) approach, which utilizes the singular spectral analysis algorithm to remove MNA artifacts so that the most accurate estimates of uncorrupted heart rates (HRs) and arterial oxygen saturation (SpO2) values recorded by a pulse oximeter can be derived. Using both computer simulations and three different experimental data sets, we show that the proposed IMAR approach can reliably reconstruct MNA corrupted data segments, as the estimated HR and SpO2 values do not significantly deviate from the uncorrupted reference measurements. Comparison of the accuracy of reconstruction of the MNA corrupted data segments between our IMAR approach and the time-domain independent component analysis (TD-ICA) is made for all data sets as the latter method has been shown to provide good performance. For simulated data, there were no significant differences in the reconstructed HR and SpO2 values starting from 10 dB down to -15 dB for both white and colored noise contaminated PPG data using IMAR; for TD-ICA, significant differences were observed starting at 10 dB. Two experimental PPG data sets were created with contrived MNA by having subjects perform random forehead and rapid side-to-side finger movements show that; the performance of the IMAR approach on these data sets was quite accurate as non-significant differences in the reconstructed HR and SpO2 were found compared to non-contaminated reference values, in most subjects. In comparison, the accuracy of the TD-ICA was poor as there were significant differences in reconstructed HR and SpO2 values in most subjects. For non-contrived MNA corrupted PPG data, which were collected with subjects performing walking and stair climbing tasks, the IMAR significantly

Suppression of intensity transition artifacts in statistical x-ray computer tomography reconstruction through Radon inversion initialization

International Nuclear Information System (INIS)

Zbijewski, Wojciech; Beekman, Freek J.

2004-01-01

Statistical reconstruction (SR) methods provide a general and flexible framework for obtaining tomographic images from projections. For several applications SR has been shown to outperform analytical algorithms in terms of resolution-noise trade-off achieved in the reconstructions. A disadvantage of SR is the long computational time required to obtain the reconstructions, in particular when large data sets characteristic for x-ray computer tomography (CT) are involved. As was shown recently, by combining statistical methods with block iterative acceleration schemes [e.g., like in the ordered subsets convex (OSC) algorithm], the reconstruction time for x-ray CT applications can be reduced by about two orders of magnitude. There are, however, some factors lengthening the reconstruction process that hamper both accelerated and standard statistical algorithms to similar degree. In this simulation study based on monoenergetic and scatter-free projection data, we demonstrate that one of these factors is the extremely high number of iterations needed to remove artifacts that can appear around high-contrast structures. We also show (using the OSC method) that these artifacts can be adequately suppressed if statistical reconstruction is initialized with images generated by means of Radon inversion algorithms like filtered back projection (FBP). This allows the reconstruction time to be shortened by even as much as one order of magnitude. Although the initialization of the statistical algorithm with FBP image introduces some additional noise into the first iteration of OSC reconstruction, the resolution-noise trade-off and the contrast-to-noise ratio of final images are not markedly compromised

Optimizing CT technique to reduce radiation dose: effect of changes in kVp, iterative reconstruction, and noise index on dose and noise in a human cadaver.

Science.gov (United States)

Chang, Kevin J; Collins, Scott; Li, Baojun; Mayo-Smith, William W

2017-06-01

For assessment of the effect of varying the peak kilovoltage (kVp), the adaptive statistical iterative reconstruction technique (ASiR), and automatic dose modulation on radiation dose and image noise in a human cadaver, a cadaver torso underwent CT scanning at 80, 100, 120 and 140 kVp, each at ASiR settings of 0, 30 and 50 %, and noise indices (NIs) of 5.5, 11 and 22. The volume CT dose index (CTDI vol ), image noise, and attenuation values of liver and fat were analyzed for 20 data sets. Size-specific dose estimates (SSDEs) and liver-to-fat contrast-to-noise ratios (CNRs) were calculated. Values for different combinations of kVp, ASiR, and NI were compared. The CTDI vol varied by a power of 2 with kVp values between 80 and 140 without ASiR. Increasing ASiR levels allowed a larger decrease in CTDI vol and SSDE at higher kVp than at lower kVp while image noise was held constant. In addition, CTDI vol and SSDE decreased with increasing NI at each kVp, but the decrease was greater at higher kVp than at lower kVp. Image noise increased with decreasing kVp despite a fixed NI; however, this noise could be offset with the use of ASiR. The CT number of the liver remained unchanged whereas that of fat decreased as the kVp decreased. Image noise and dose vary in a complicated manner when the kVp, ASiR, and NI are varied in a human cadaver. Optimization of CT protocols will require balancing of the effects of each of these parameters to maximize image quality while minimizing dose.

Do Aging and Tactile Noise Stimulation Affect Responses to Support Surface Translations in Healthy Adults?

Directory of Open Access Journals (Sweden)

Marius Dettmer

2016-01-01

Full Text Available Appropriate neuromuscular responses to support surface perturbations are crucial to prevent falls, but aging-related anatomical and physiological changes affect the appropriateness and efficiency of such responses. Low-level noise application to sensory receptors has shown to be effective for postural improvement in a variety of different balance tasks, but it is unknown whether this intervention may have value for improvement of corrective postural responses. Ten healthy younger and ten healthy older adults were exposed to sudden backward translations of the support surface. Low-level noise (mechanical vibration to the foot soles was added during random trials and temporal (response latency and spatial characteristics (maximum center-of-pressure excursion and anterior-posterior path length of postural responses were assessed. Mixed-model ANOVA was applied for analysis of postural response differences based on age and vibration condition. Age affected postural response characteristics, but older adults were well able to maintain balance when exposed to a postural perturbation. Low-level noise application did not affect any postural outcomes. Healthy aging affects some specific measures of postural stability, and in high-functioning older individuals, a low-level noise intervention may not be valuable. More research is needed to investigate if recurring fallers and neuropathy patients could benefit from the intervention in postural perturbation tasks.

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

Transonic Performance Characteristics of Several Jet Noise Suppressors

Science.gov (United States)

Schmeer, James W.; Salters, Leland B., Jr.; Cassetti, Marlowe D.

1960-01-01

An investigation of the transonic performance characteristics of several noise-suppressor configurations has been conducted in the Langley 16-foot transonic tunnel. The models were tested statically and over a Mach number range from 0.70 to 1.05 at an angle of attack of 0 deg. The primary jet total-pressure ratio was varied from 1.0 (jet off) to about 4.5. The effect of secondary air flow on the performance of two of the configurations was investigated. A hydrogen peroxide turbojet-engine simulator was used to supply the hot-jet exhaust. An 8-lobe afterbody with centerbody, short shroud, and secondary air had the highest thrust-minus-drag coefficients of the six noise-suppressor configurations tested. The 12-tube and 12-lobe afterbodies had the lowest internal losses. The presence of an ejector shroud partially shields the external pressure distribution of the 8-lobe after-body from the influence of the primary jet. A ring-airfoil shroud increased the static thrust of the annular nozzle but generally decreased the thrust minus drag at transonic Mach numbers.

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.

Loading Effect on Tire Noise Radiation

OpenAIRE

Cao, Rui; Bolton, J Stuart

2016-01-01

Noise radiated by tires is a prominent noise pollution source and it is affected by many different parameters. Here, the effect of static load on tire noise radiation in a laboratory environment was investigated. The measurement was conducted by using the Tire Pavement Testing Apparatus (TPTA), on which a loaded tire can be run at speeds up to 50 km/hr; the tire noise was measured using a nearfield microphone method. The tire loading was varied from 500 to 900 pounds, and several different co...

Use of a hybrid iterative reconstruction technique to reduce image noise and improve image quality in obese patients undergoing computed tomographic pulmonary angiography.

Science.gov (United States)

Kligerman, Seth; Mehta, Dhruv; Farnadesh, Mahmmoudreza; Jeudy, Jean; Olsen, Kathryn; White, Charles

2013-01-01

To determine whether an iterative reconstruction (IR) technique (iDose, Philips Healthcare) can reduce image noise and improve image quality in obese patients undergoing computed tomographic pulmonary angiography (CTPA). The study was Health Insurance Portability and Accountability Act compliant and approved by our institutional review board. A total of 33 obese patients (average body mass index: 42.7) underwent CTPA studies following standard departmental protocols. The data were reconstructed with filtered back projection (FBP) and 3 iDose strengths (iDoseL1, iDoseL3, and iDoseL5) for a total of 132 studies. FBP data were collected from 33 controls (average body mass index: 22) undergoing CTPA. Regions of interest were drawn at 6 identical levels in the pulmonary artery (PA), from the main PA to a subsegmental branch, in both the control group and study groups using each algorithm. Noise and attenuation were measured at all PA levels. Three thoracic radiologists graded each study on a scale of 1 (very poor) to 5 (ideal) by 4 categories: image quality, noise, PA enhancement, and "plastic" appearance. Statistical analysis was performed using an unpaired t test, 1-way analysis of variance, and linear weighted κ. Compared with the control group, there was significantly higher noise with FBP, iDoseL1, and iDoseL3 algorithms (Pnoise in the control group and iDoseL5 algorithm in the study group. Analysis within the study group showed a significant and progressive decrease in noise and increase in the contrast-to-noise ratio as the level of IR was increased (Pnoise and PA enhancement with increasing levels of iDose. The use of an IR technique leads to qualitative and quantitative improvements in image noise and image quality in obese patients undergoing CTPA.

Resolution improvement and noise reduction in human pinhole SPECT using a multi-ray approach and the SHINE method

International Nuclear Information System (INIS)

Seret, A.; Vanhove, C.; Defrise, M.

2009-01-01

Purpose: This work aimed at quantifying the gains in spatial resolution and noise that could be achieved when using resolution modelling based on a multi-ray approach and additionally the Statistical and Heuristic Noise Extraction (SHINE) method in human pinhole single photon emission tomography (PH-SPECT). Methods: PH-SPECT of two line phantoms and one homogeneous cylinder were recorded using parameters suited for studies of the human neck area. They were reconstructed using pinhole dedicated ordered subsets expectation maximisation algorithm including a resolution recovery technique based on 7 or 21 rays. Optionally, the SPECT data were SHINE pre-processed. Transverse and axial full widths at half-maximum (FWHM) were obtained from the line phantoms. The noise was quantified using the coefficient of variation (COV) derived from the uniform phantom. Two human PH-SPECT studies of the thyroid (a hot nodule and a very low uptake) were processed with the same algorithms. Results: Depending on the number of iterations, FWHM decreased by 30 to 50% when using the multi-ray approach in the reconstruction process. The SHINE method did not affect the resolution but decreased the COV by at least 20% and by 45% when combined with the multi-ray method. The two human studies illustrated the gain in spatial resolution and the decrease in noise afforded both by the multi-ray reconstruction and the SHINE method. Conclusion: Iterative reconstruction with resolution modelling allows to obtain high resolution human PH-SPECT studies with reduced noise content. The SHINE method affords an additional noise reduction without compromising the resolution. (orig.)

How biological (fish) noise affects the performance of shallow water passive array system

Digital Repository Service at National Institute of Oceanography (India)

Fernandes, W.A.; Chakraborty, B.; Haris, K.; Vijayakumar, K.; Sundar, D.; Luis, R.A.A.; Mahanty, M.M.; Latha, G.

=UTF-8 How biological (fish) noise affects the performance of shallow water passive array system William Fernandes, Bishwajit Chakraborty, K. Haris, K. Vijaykumar, D. Sundar, R.A.A. Luis CSIR-National Institute of Oceanography, Dona Paula... source distribution as well as the environmental parameters (i.e., water depth, sound speed profile, and seafloor properties). In a waveguide bounded by sea surface and seabed, multipath propagation prevails and the spatial structure of the noise...

Penalised Maximum Likelihood Simultaneous Longitudinal PET Image Reconstruction with Difference-Image Priors.

Science.gov (United States)

Ellis, Sam; Reader, Andrew J

2018-04-26

reconstructions with increased counts levels. In tumour regions each method produces subtly different results in terms of preservation of tumour quantification and reconstruction root mean-squared error (RMSE). In particular, in the two-scan simulations, the DE-PML method produced tumour means in close agreement with MLEM reconstructions, while the DTV-PML method produced the lowest errors due to noise reduction within the tumour. Across a range of tumour responses and different numbers of scans, similar results were observed, with DTV-PML producing the lowest errors of the three priors and DE-PML producing the lowest bias. Similar improvements were observed in the reconstructions of the real longitudinal datasets, although imperfect alignment of the two PET images resulted in additional changes in the difference image that affected the performance of the proposed methods. Reconstruction of longitudinal datasets by penalising difference images between pairs of scans from a data series allows for noise reduction in all reconstructed images. An appropriate choice of penalty term and penalty strength allows for this noise reduction to be achieved while maintaining reconstruction performance in regions of change, either in terms of quantification of mean intensity via DE-PML, or in terms of tumour RMSE via DTV-PML. Overall, improving the image quality of longitudinal datasets via simultaneous reconstruction has the potential to improve upon currently used methods, allow dose reduction, or reduce scan time while maintaining image quality at current levels. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Charge reconstruction in large-area photomultipliers

Science.gov (United States)

Grassi, M.; Montuschi, M.; Baldoncini, M.; Mantovani, F.; Ricci, B.; Andronico, G.; Antonelli, V.; Bellato, M.; Bernieri, E.; Brigatti, A.; Brugnera, R.; Budano, A.; Buscemi, M.; Bussino, S.; Caruso, R.; Chiesa, D.; Corti, D.; Dal Corso, F.; Ding, X. F.; Dusini, S.; Fabbri, A.; Fiorentini, G.; Ford, R.; Formozov, A.; Galet, G.; Garfagnini, A.; Giammarchi, M.; Giaz, A.; Insolia, A.; Isocrate, R.; Lippi, I.; Longhitano, F.; Lo Presti, D.; Lombardi, P.; Marini, F.; Mari, S. M.; Martellini, C.; Meroni, E.; Mezzetto, M.; Miramonti, L.; Monforte, S.; Nastasi, M.; Ortica, F.; Paoloni, A.; Parmeggiano, S.; Pedretti, D.; Pelliccia, N.; Pompilio, R.; Previtali, E.; Ranucci, G.; Re, A. C.; Romani, A.; Saggese, P.; Salamanna, G.; Sawy, F. H.; Settanta, G.; Sisti, M.; Sirignano, C.; Spinetti, M.; Stanco, L.; Strati, V.; Verde, G.; Votano, L.

2018-02-01

Large-area PhotoMultiplier Tubes (PMT) allow to efficiently instrument Liquid Scintillator (LS) neutrino detectors, where large target masses are pivotal to compensate for neutrinos' extremely elusive nature. Depending on the detector light yield, several scintillation photons stemming from the same neutrino interaction are likely to hit a single PMT in a few tens/hundreds of nanoseconds, resulting in several photoelectrons (PEs) to pile-up at the PMT anode. In such scenario, the signal generated by each PE is entangled to the others, and an accurate PMT charge reconstruction becomes challenging. This manuscript describes an experimental method able to address the PMT charge reconstruction in the case of large PE pile-up, providing an unbiased charge estimator at the permille level up to 15 detected PEs. The method is based on a signal filtering technique (Wiener filter) which suppresses the noise due to both PMT and readout electronics, and on a Fourier-based deconvolution able to minimize the influence of signal distortions—such as an overshoot. The analysis of simulated PMT waveforms shows that the slope of a linear regression modeling the relation between reconstructed and true charge values improves from 0.769 ± 0.001 (without deconvolution) to 0.989 ± 0.001 (with deconvolution), where unitary slope implies perfect reconstruction. A C++ implementation of the charge reconstruction algorithm is available online at [1].

Three-dimensional dictionary-learning reconstruction of (23)Na MRI data.

Science.gov (United States)

Behl, Nicolas G R; Gnahm, Christine; Bachert, Peter; Ladd, Mark E; Nagel, Armin M

2016-04-01

To reduce noise and artifacts in (23)Na MRI with a Compressed Sensing reconstruction and a learned dictionary as sparsifying transform. A three-dimensional dictionary-learning compressed sensing reconstruction algorithm (3D-DLCS) for the reconstruction of undersampled 3D radial (23)Na data is presented. The dictionary used as the sparsifying transform is learned with a K-singular-value-decomposition (K-SVD) algorithm. The reconstruction parameters are optimized on simulated data, and the quality of the reconstructions is assessed with peak signal-to-noise ratio (PSNR) and structural similarity (SSIM). The performance of the algorithm is evaluated in phantom and in vivo (23)Na MRI data of seven volunteers and compared with nonuniform fast Fourier transform (NUFFT) and other Compressed Sensing reconstructions. The reconstructions of simulated data have maximal PSNR and SSIM for an undersampling factor (USF) of 10 with numbers of averages equal to the USF. For 10-fold undersampling, the PSNR is increased by 5.1 dB compared with the NUFFT reconstruction, and the SSIM by 24%. These results are confirmed by phantom and in vivo (23)Na measurements in the volunteers that show markedly reduced noise and undersampling artifacts in the case of 3D-DLCS reconstructions. The 3D-DLCS algorithm enables precise reconstruction of undersampled (23)Na MRI data with markedly reduced noise and artifact levels compared with NUFFT reconstruction. Small structures are well preserved. © 2015 Wiley Periodicals, Inc.

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.

Coherent noise reduction in digital holographic microscopy by averaging multiple holograms recorded with a multimode laser.

Science.gov (United States)

Pan, Feng; Yang, Lizhi; Xiao, Wen

2017-09-04

In digital holographic microscopy (DHM), it is undesirable to observe coherent noise in the reconstructed images. The sources of the noise are mainly the parasitic interference fringes caused by multiple reflections and the speckle pattern caused by the optical scattering on the object surface. Here we propose a noise reduction approach in DHM by averaging multiple holograms recorded with a multimode laser. Based on the periodicity of the temporal coherence of a multimode semiconductor laser, we acquire a series of holograms by changing the optical path length difference between the reference beam and object beam. Because of the use of low coherence light, we can remove the parasitic interference fringes caused by multiple reflections in the holograms. In addition, the coherent noise patterns change in this process due to the different optical paths. Therefore, the coherent noise can be reduced by averaging the multiple reconstructions with uncorrelated noise patterns. Several experiments have been carried out to validate the effectiveness of the proposed approach for coherent noise reduction in DHM. It is shown a remarkable improvement both in amplitude imaging quality and phase measurement accuracy.

Individual differences in language and working memory affect children's speech recognition in noise.

Science.gov (United States)

McCreery, Ryan W; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc

2017-05-01

We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Ninety-six children with normal hearing, who were between 5 and 12 years of age. Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Working memory and language both influence children's speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child's auditory skills, consistent with the Ease of Language Understanding model.

Liquid argon TPC signal formation, signal processing and reconstruction techniques

Science.gov (United States)

Baller, B.

2017-07-01

This document describes a reconstruction chain that was developed for the ArgoNeuT and MicroBooNE experiments at Fermilab. These experiments study accelerator neutrino interactions that occur in a Liquid Argon Time Projection Chamber. Reconstructing the properties of particles produced in these interactions benefits from the knowledge of the micro-physics processes that affect the creation and transport of ionization electrons to the readout system. A wire signal deconvolution technique was developed to convert wire signals to a standard form for hit reconstruction, to remove artifacts in the electronics chain and to remove coherent noise. A unique clustering algorithm reconstructs line-like trajectories and vertices in two dimensions which are then matched to create of 3D objects. These techniques and algorithms are available to all experiments that use the LArSoft suite of software.

Pediatric 320-row cardiac computed tomography using electrocardiogram-gated model-based full iterative reconstruction

Energy Technology Data Exchange (ETDEWEB)

Shirota, Go; Maeda, Eriko; Namiki, Yoko; Bari, Razibul; Abe, Osamu [The University of Tokyo, Department of Radiology, Graduate School of Medicine, Tokyo (Japan); Ino, Kenji [The University of Tokyo Hospital, Imaging Center, Tokyo (Japan); Torigoe, Rumiko [Toshiba Medical Systems, Tokyo (Japan)

2017-10-15

Full iterative reconstruction algorithm is available, but its diagnostic quality in pediatric cardiac CT is unknown. To compare the imaging quality of two algorithms, full and hybrid iterative reconstruction, in pediatric cardiac CT. We included 49 children with congenital cardiac anomalies who underwent cardiac CT. We compared quality of images reconstructed using the two algorithms (full and hybrid iterative reconstruction) based on a 3-point scale for the delineation of the following anatomical structures: atrial septum, ventricular septum, right atrium, right ventricle, left atrium, left ventricle, main pulmonary artery, ascending aorta, aortic arch including the patent ductus arteriosus, descending aorta, right coronary artery and left main trunk. We evaluated beam-hardening artifacts from contrast-enhancement material using a 3-point scale, and we evaluated the overall image quality using a 5-point scale. We also compared image noise, signal-to-noise ratio and contrast-to-noise ratio between the algorithms. The overall image quality was significantly higher with full iterative reconstruction than with hybrid iterative reconstruction (3.67±0.79 vs. 3.31±0.89, P=0.0072). The evaluation scores for most of the gross structures were higher with full iterative reconstruction than with hybrid iterative reconstruction. There was no significant difference between full and hybrid iterative reconstruction for the presence of beam-hardening artifacts. Image noise was significantly lower in full iterative reconstruction, while signal-to-noise ratio and contrast-to-noise ratio were significantly higher in full iterative reconstruction. The diagnostic quality was superior in images with cardiac CT reconstructed with electrocardiogram-gated full iterative reconstruction. (orig.)

Pediatric 320-row cardiac computed tomography using electrocardiogram-gated model-based full iterative reconstruction

International Nuclear Information System (INIS)

Shirota, Go; Maeda, Eriko; Namiki, Yoko; Bari, Razibul; Abe, Osamu; Ino, Kenji; Torigoe, Rumiko

2017-01-01

Full iterative reconstruction algorithm is available, but its diagnostic quality in pediatric cardiac CT is unknown. To compare the imaging quality of two algorithms, full and hybrid iterative reconstruction, in pediatric cardiac CT. We included 49 children with congenital cardiac anomalies who underwent cardiac CT. We compared quality of images reconstructed using the two algorithms (full and hybrid iterative reconstruction) based on a 3-point scale for the delineation of the following anatomical structures: atrial septum, ventricular septum, right atrium, right ventricle, left atrium, left ventricle, main pulmonary artery, ascending aorta, aortic arch including the patent ductus arteriosus, descending aorta, right coronary artery and left main trunk. We evaluated beam-hardening artifacts from contrast-enhancement material using a 3-point scale, and we evaluated the overall image quality using a 5-point scale. We also compared image noise, signal-to-noise ratio and contrast-to-noise ratio between the algorithms. The overall image quality was significantly higher with full iterative reconstruction than with hybrid iterative reconstruction (3.67±0.79 vs. 3.31±0.89, P=0.0072). The evaluation scores for most of the gross structures were higher with full iterative reconstruction than with hybrid iterative reconstruction. There was no significant difference between full and hybrid iterative reconstruction for the presence of beam-hardening artifacts. Image noise was significantly lower in full iterative reconstruction, while signal-to-noise ratio and contrast-to-noise ratio were significantly higher in full iterative reconstruction. The diagnostic quality was superior in images with cardiac CT reconstructed with electrocardiogram-gated full iterative reconstruction. (orig.)

Thermal Depth Profiling Reconstruction by Multilayer Thermal Quadrupole Modeling and Particle Swarm Optimization

International Nuclear Information System (INIS)

Zhao-Jiang, Chen; Shu-Yi, Zhang

2010-01-01

A new hybrid inversion method for depth profiling reconstruction of thermal conductivities of inhomogeneous solids is proposed based on multilayer quadrupole formalism of thermal waves, particle swarm optimization and sequential quadratic programming. The reconstruction simulations for several thermal conductivity profiles are performed to evaluate the applicability of the method. The numerical simulations demonstrate that the precision and insensitivity to noise of the inversion method are very satisfactory. (condensed matter: structure, mechanical and thermal properties)

CONTROLLING RISK DUE TO NOISE ON FERRY BOAT

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Aleksandar Nikolic

2013-07-01

Full Text Available Environmental and occupational noise is common nuisance that affects the health of employees. Performed health checks of employees engaged by Company “Pomorski Saobraćaj” showed that 5% of examined sailors had hearing loss. The results were a trigger for starting experiment on noise risk assessment with objective to discover possibilities of noise pollution presence, precise significant noise sources and describe solutions for eliminating negative effects. Several measurements on five positions were performed on ferry boat “KAMENARI”, according to EC Physical Agents Directive and Merchant Shipping and Fishing Vessels Regulations 2007. Noise on selected positions exceeded the limit for about 1-5dB. Noise exposure level was 84.5dB. Diesel engine, exhaust system and structural noise were main sources of excessive noise. Experiment shows noise presence as nuisance that affects sailors. Noise presents a serious threat for sailor’s health. It interferes with crew communication and jeopardizes navigation safety. Technical measures, crew health checks and noise monitoring could prevent all negative effects.

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.)

Total Variation Based Parameter-Free Model for Impulse Noise Removal

DEFF Research Database (Denmark)

Sciacchitano, Federica; Dong, Yiqiu; Andersen, Martin Skovgaard

2017-01-01

We propose a new two-phase method for reconstruction of blurred images corrupted by impulse noise. In the first phase, we use a noise detector to identify the pixels that are contaminated by noise, and then, in the second phase, we reconstruct the noisy pixels by solving an equality constrained...... total variation minimization problem that preserves the exact values of the noise-free pixels. For images that are only corrupted by impulse noise (i. e., not blurred) we apply the semismooth Newton's method to a reduced problem, and if the images are also blurred, we solve the equality constrained...... reconstruction problem using a first-order primal-dual algorithm. The proposed model improves the computational efficiency (in the denoising case) and has the advantage of being regularization parameter-free. Our numerical results suggest that the method is competitive in terms of its restoration capabilities...

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

The effects of noise reduction technologies on the acceptance of background noise.

Science.gov (United States)

Lowery, Kristy Jones; Plyler, Patrick N

2013-09-01

Directional microphones (D-Mics) and digital noise reduction (DNR) algorithms are used in hearing aids to reduce the negative effects of background noise on performance. Directional microphones attenuate sounds arriving from anywhere other than the front of the listener while DNR attenuates sounds with physical characteristics of noise. Although both noise reduction technologies are currently available in hearing aids, it is unclear if the use of these technologies in isolation or together affects acceptance of noise and/or preference for the end user when used in various types of background noise. The purpose of the research was to determine the effects of D-Mic, DNR, or the combination of D-Mic and DNR on acceptance of noise and preference when listening in various types of background noise. An experimental study in which subjects were exposed to a repeated measures design was utilized. Thirty adult listeners with mild sloping to moderately severe sensorineural hearing loss participated (mean age 67 yr). Acceptable noise levels (ANLs) were obtained using no noise reduction technologies, D-Mic only, DNR only, and the combination of the two technologies (Combo) for three different background noises (single-talker speech, speech-shaped noise, and multitalker babble) for each listener. In addition, preference rankings of the noise reduction technologies were obtained within each background noise (1 = best, 3 = worst). ANL values were significantly better for each noise reduction technology than baseline; and benefit increased significantly from DNR to D-Mic to Combo. Listeners with higher (worse) baseline ANLs received more benefit from noise reduction technologies than listeners with lower (better) baseline ANLs. Neither ANL values nor ANL benefit values were significantly affected by background noise type; however, ANL benefit with D-Mic and Combo was similar when speech-like noise was present while ANL benefit was greatest for Combo when speech spectrum noise was

Full Mouth Reconstruction of a Patient with Severely Worn Dentition: A Clinical Report

Directory of Open Access Journals (Sweden)

Ramin Negahdari

2016-01-01

Full Text Available If remained untreated, progressive dental wear can lead to pulpal pathology, occlusal disharmony, and impaired function and esthetics. This case report describes prosthetic rehabilitation of a 53 year-old man with the loss of anterior guidance, severe wear of dentition and vertical dimension loss. Oral rehabilitation was performed by reconstruction of vertical dimension, crown lengthening, conventional implants, and custom cast gold post and cores as well as porcelain fused to metal restorations. Full mouth reconstruction of the patient with severely worn dentition was found to be successful after 4 years of follow up.   Keywords: mouth rehabilitation, tooth wear, vertical dimension

Noise sensitivity, rather than noise level, predicts the non-auditory effects of noise in community samples: a population-based survey

Directory of Open Access Journals (Sweden)

Jangho Park

2017-04-01

Full Text Available Abstract Background Excessive noise affects human health and interferes with daily activities. Although environmental noise may not directly cause mental illness, it may accelerate and intensify the development of latent mental disorders. Noise sensitivity (NS is considered a moderator of non-auditory noise effects. In the present study, we aimed to assess whether NS is associated with non-auditory effects. Methods We recruited a community sample of 1836 residents residing in Ulsan and Seoul, South Korea. From July to November 2015, participants were interviewed regarding their demographic characteristics, socioeconomic status, medical history, and NS. The non-auditory effects of noise were assessed using the Center of Epidemiologic Studies Depression, Insomnia Severity index, State Trait Anxiety Inventory state subscale, and Stress Response Inventory-Modified Form. Individual noise levels were recorded from noise maps. A three-model multivariate logistic regression analysis was performed to identify factors that might affect psychiatric illnesses. Results Participants ranged in age from 19 to 91 years (mean: 47.0 ± 16.1 years, and 37.9% (n = 696 were male. Participants with high NS were more likely to have been diagnosed with diabetes and hyperlipidemia and to use psychiatric medication. The multivariable analysis indicated that even after adjusting for noise-related variables, sociodemographic factors, medical illness, and duration of residence, subjects in the high NS group were more than 2 times more likely to experience depression and insomnia and 1.9 times more likely to have anxiety, compared with those in the low NS group. Noise exposure level was not identified as an explanatory value. Conclusions NS increases the susceptibility and hence moderates there actions of individuals to noise. NS, rather than noise itself, is associated with an elevated susceptibility to non-auditory effects.

Optimization of Bayesian Emission tomographic reconstruction for region of interest quantitation

International Nuclear Information System (INIS)

Qi, Jinyi

2003-01-01

Region of interest (ROI) quantitation is an important task in emission tomography (e.g., positron emission tomography and single photon emission computed tomography). It is essential for exploring clinical factors such as tumor activity, growth rate, and the efficacy of therapeutic interventions. Bayesian methods based on the maximum a posteriori principle (or called penalized maximum likelihood methods) have been developed for emission image reconstructions to deal with the low signal to noise ratio of the emission data. Similar to the filter cut-off frequency in the filtered backprojection method, the smoothing parameter of the image prior in Bayesian reconstruction controls the resolution and noise trade-off and hence affects ROI quantitation. In this paper we present an approach for choosing the optimum smoothing parameter in Bayesian reconstruction for ROI quantitation. Bayesian reconstructions are difficult to analyze because the resolution and noise properties are nonlinear and object-dependent. Building on the recent progress on deriving the approximate expressions for the local impulse response function and the covariance matrix, we derived simplied theoretical expressions for the bias, the variance, and the ensemble mean squared error (EMSE) of the ROI quantitation. One problem in evaluating ROI quantitation is that the truth is often required for calculating the bias. This is overcome by using ensemble distribution of the activity inside the ROI and computing the average EMSE. The resulting expressions allow fast evaluation of the image quality for different smoothing parameters. The optimum smoothing parameter of the image prior can then be selected to minimize the EMSE

Fan-beam filtered-backprojection reconstruction without backprojection weight

International Nuclear Information System (INIS)

Dennerlein, Frank; Noo, Frederic; Hornegger, Joachim; Lauritsch, Guenter

2007-01-01

In this paper, we address the problem of two-dimensional image reconstruction from fan-beam data acquired along a full 2π scan. Conventional approaches that follow the filtered-backprojection (FBP) structure require a weighted backprojection with the weight depending on the point to be reconstructed and also on the source position; this weight appears only in the case of divergent beam geometries. Compared to reconstruction from parallel-beam data, the backprojection weight implies an increase in computational effort and is also thought to have some negative impacts on noise properties of the reconstructed images. We demonstrate here that direct FBP reconstruction from full-scan fan-beam data is possible with no backprojection weight. Using computer-simulated, realistic fan-beam data, we compared our novel FBP formula with no backprojection weight to the use of an FBP formula based on equal weighting of all data. Comparisons in terms of signal-to-noise ratio, spatial resolution and computational efficiency are presented. These studies show that the formula we suggest yields images with a reduced noise level, at almost identical spatial resolution. This effect increases quickly with the distance from the center of the field of view, from 0% at the center to 20% less noise at 20 cm, and to 40% less noise at 25 cm. Furthermore, the suggested method is computationally less demanding and reduces computation time with a gain that was found to vary between 12% and 43% on the computers used for evaluation

Non-Stationary Rician Noise Estimation in Parallel MRI Using a Single Image: A Variance-Stabilizing Approach.

Science.gov (United States)

Pieciak, Tomasz; Aja-Fernandez, Santiago; Vegas-Sanchez-Ferrero, Gonzalo

2017-10-01

Parallel magnetic resonance imaging (pMRI) techniques have gained a great importance both in research and clinical communities recently since they considerably accelerate the image acquisition process. However, the image reconstruction algorithms needed to correct the subsampling artifacts affect the nature of noise, i.e., it becomes non-stationary. Some methods have been proposed in the literature dealing with the non-stationary noise in pMRI. However, their performance depends on information not usually available such as multiple acquisitions, receiver noise matrices, sensitivity coil profiles, reconstruction coefficients, or even biophysical models of the data. Besides, some methods show an undesirable granular pattern on the estimates as a side effect of local estimation. Finally, some methods make strong assumptions that just hold in the case of high signal-to-noise ratio (SNR), which limits their usability in real scenarios. We propose a new automatic noise estimation technique for non-stationary Rician noise that overcomes the aforementioned drawbacks. Its effectiveness is due to the derivation of a variance-stabilizing transformation designed to deal with any SNR. The method was compared to the main state-of-the-art methods in synthetic and real scenarios. Numerical results confirm the robustness of the method and its better performance for the whole range of SNRs.

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

Science.gov (United States)

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

2015-01-01

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

Accurate reconstruction in digital holographic microscopy using Fresnel dual-tree complex wavelet transform

Science.gov (United States)

Zhang, Xiaolei; Zhang, Xiangchao; Yuan, He; Zhang, Hao; Xu, Min

2018-02-01

Digital holography is a promising measurement method in the fields of bio-medicine and micro-electronics. But the captured images of digital holography are severely polluted by the speckle noise because of optical scattering and diffraction. Via analyzing the properties of Fresnel diffraction and the topographies of micro-structures, a novel reconstruction method based on the dual-tree complex wavelet transform (DT-CWT) is proposed. This algorithm is shiftinvariant and capable of obtaining sparse representations for the diffracted signals of salient features, thus it is well suited for multiresolution processing of the interferometric holograms of directional morphologies. An explicit representation of orthogonal Fresnel DT-CWT bases and a specific filtering method are developed. This method can effectively remove the speckle noise without destroying the salient features. Finally, the proposed reconstruction method is compared with the conventional Fresnel diffraction integration and Fresnel wavelet transform with compressive sensing methods to validate its remarkable superiority on the aspects of topography reconstruction and speckle removal.

The Protocol of Fixed Reconstruction for Severely Worn Teeth Combined with Anterior Deep Bite

Directory of Open Access Journals (Sweden)

Ya-Wen Zhao

2017-01-01

Full Text Available Full mouth reconstruction is one of the most effective methods to restore severe worn teeth that have suffered reduced vertical dimension. Although the use of the overlay splint restoration for a trial period allowing the patient to adapt to an increased vertical dimension is the recognized method, the specific protocol from the transitional splint to the fixed reconstruction is yet to be established. This case report describes a 50-year-old female patient who has severely worn teeth combined with an anterior deep bite and chewing pain. The protocol of the treatment process is described.

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

Investigation of the influence of image reconstruction filter and scan parameters on operation of automatic tube current modulation systems for different CT scanners

International Nuclear Information System (INIS)

Sookpeng, Supawitoo; Martin, Colin J.; Gentle, David J.

2015-01-01

Variation in the user selected CT scanning parameters under automatic tube current modulation (ATCM) between hospitals has a substantial influence on the radiation doses and image quality for patients. The aim of this study was to investigate the effect of changing image reconstruction filter and scan parameter settings on tube current, dose and image quality for various CT scanners operating under ATCM. The scan parameters varied were pitch factor, rotation time, collimator configuration, kVp, image thickness and image filter convolution (FC) used for reconstruction. The Toshiba scanner varies the tube current to achieve a set target noise. Changes in the FC setting and image thickness for the first reconstruction were the major factors affecting patient dose. A two-step change in FC from smoother to sharper filters doubles the dose, but is counterbalanced by an improvement in spatial resolution. In contrast, Philips and Siemens scanners maintained tube current values similar to those for a reference image and patient, and the tube current only varied slightly for changes in individual CT scan parameters. The selection of a sharp filter increased the image noise, while use of iDose iterative reconstruction reduced the noise. Since the principles used by CT manufacturers for ATCM vary, it is important that parameters which affect patient dose and image quality for each scanner are made clear to operator to aid in optimisation. (authors)

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.

Individual differences in language and working memory affect children’s speech recognition in noise

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McCreery, Ryan W.; Spratford, Meredith; Kirby, Benjamin; Brennan, Marc

2017-01-01

Objective We examined how cognitive and linguistic skills affect speech recognition in noise for children with normal hearing. Children with better working memory and language abilities were expected to have better speech recognition in noise than peers with poorer skills in these domains. Design As part of a prospective, cross-sectional study, children with normal hearing completed speech recognition in noise for three types of stimuli: (1) monosyllabic words, (2) syntactically correct but semantically anomalous sentences and (3) semantically and syntactically anomalous word sequences. Measures of vocabulary, syntax and working memory were used to predict individual differences in speech recognition in noise. Study sample Ninety-six children with normal hearing, who were between 5 and 12 years of age. Results Higher working memory was associated with better speech recognition in noise for all three stimulus types. Higher vocabulary abilities were associated with better recognition in noise for sentences and word sequences, but not for words. Conclusions Working memory and language both influence children’s speech recognition in noise, but the relationships vary across types of stimuli. These findings suggest that clinical assessment of speech recognition is likely to reflect underlying cognitive and linguistic abilities, in addition to a child’s auditory skills, consistent with the Ease of Language Understanding model. PMID:27981855

MO-DE-207A-12: Toward Patient-Specific 4DCT Reconstruction Using Adaptive Velocity Binning

International Nuclear Information System (INIS)

Morris, E.D.; Glide-Hurst, C.; Klahr, P.

2016-01-01

Purpose: While 4DCT provides organ/tumor motion information, it often samples data over 10–20 breathing cycles. For patients presenting with compromised pulmonary function, breathing patterns can change over the acquisition time, potentially leading to tumor delineation discrepancies. This work introduces a novel adaptive velocity-modulated binning (AVB) 4DCT algorithm that modulates the reconstruction based on the respiratory waveform, yielding a patient-specific 4DCT solution. Methods: AVB was implemented in a research reconstruction configuration. After filtering the respiratory waveform, the algorithm examines neighboring data to a phase reconstruction point and the temporal gate is widened until the difference between the reconstruction point and waveform exceeds a threshold value—defined as percent difference between maximum/minimum waveform amplitude. The algorithm only impacts reconstruction if the gate width exceeds a set minimum temporal width required for accurate reconstruction. A sensitivity experiment of threshold values (0.5, 1, 5, 10, and 12%) was conducted to examine the interplay between threshold, signal to noise ratio (SNR), and image sharpness for phantom and several patient 4DCT cases using ten-phase reconstructions. Individual phase reconstructions were examined. Subtraction images and regions of interest were compared to quantify changes in SNR. Results: AVB increased signal in reconstructed 4DCT slices for respiratory waveforms that met the prescribed criteria. For the end-exhale phases, where the respiratory velocity is low, patient data revealed a threshold of 0.5% demonstrated increased SNR in the AVB reconstructions. For intermediate breathing phases, threshold values were required to be >10% to notice appreciable changes in CT intensity with AVB. AVB reconstructions exhibited appreciably higher SNR and reduced noise in regions of interest that were photon deprived such as the liver. Conclusion: We demonstrated that patient

MO-DE-207A-12: Toward Patient-Specific 4DCT Reconstruction Using Adaptive Velocity Binning

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Morris, E.D.; Glide-Hurst, C. [Henry Ford Health System, Detroit, MI (United States); Wayne State University, Detroit, MI (United States); Klahr, P. [Philips Healthcare, Cleveland, Ohio (United States)

2016-06-15

Purpose: While 4DCT provides organ/tumor motion information, it often samples data over 10–20 breathing cycles. For patients presenting with compromised pulmonary function, breathing patterns can change over the acquisition time, potentially leading to tumor delineation discrepancies. This work introduces a novel adaptive velocity-modulated binning (AVB) 4DCT algorithm that modulates the reconstruction based on the respiratory waveform, yielding a patient-specific 4DCT solution. Methods: AVB was implemented in a research reconstruction configuration. After filtering the respiratory waveform, the algorithm examines neighboring data to a phase reconstruction point and the temporal gate is widened until the difference between the reconstruction point and waveform exceeds a threshold value—defined as percent difference between maximum/minimum waveform amplitude. The algorithm only impacts reconstruction if the gate width exceeds a set minimum temporal width required for accurate reconstruction. A sensitivity experiment of threshold values (0.5, 1, 5, 10, and 12%) was conducted to examine the interplay between threshold, signal to noise ratio (SNR), and image sharpness for phantom and several patient 4DCT cases using ten-phase reconstructions. Individual phase reconstructions were examined. Subtraction images and regions of interest were compared to quantify changes in SNR. Results: AVB increased signal in reconstructed 4DCT slices for respiratory waveforms that met the prescribed criteria. For the end-exhale phases, where the respiratory velocity is low, patient data revealed a threshold of 0.5% demonstrated increased SNR in the AVB reconstructions. For intermediate breathing phases, threshold values were required to be >10% to notice appreciable changes in CT intensity with AVB. AVB reconstructions exhibited appreciably higher SNR and reduced noise in regions of interest that were photon deprived such as the liver. Conclusion: We demonstrated that patient

A Pseudoproxy-Ensemble Study of Late-Holocene Climate Field Reconstructions Using CCA

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Amrhein, D. E.; Smerdon, J. E.

2009-12-01

Recent evaluations of late-Holocene multi-proxy reconstruction methods have used pseudoproxy experiments derived from millennial General Circulation Model (GCM) integrations. These experiments assess the performance of a reconstruction technique by comparing pseudoproxy reconstructions, which use restricted subsets of model data, against complete GCM data fields. Most previous studies have tested methodologies using different pseudoproxy noise levels, but only with single realizations for each noise classification. A more robust evaluation of performance is to create an ensemble of pseudoproxy networks with distinct sets of noise realizations and a corresponding reconstruction ensemble that can be evaluated for consistency and sensitivity to random error. This work investigates canonical correlation analysis (CCA) as a late-Holocene climate field reconstruction (CFR) technique using ensembles of pseudoproxy experiments derived from the NCAR CSM 1.4 millennial integration. Three 200-member reconstruction ensembles are computed using pseudoproxies with signal-to-noise ratios (by standard deviation) of 1, 0.5, and 0.25 and locations that approximate the spatial distribution of real-world multiproxy networks. An important component of these ensemble calculations is the independent optimization of the three CCA truncation parameters for each ensemble member. This task is accomplished using an inexpensive discrete optimization algorithm that minimizes both RMS error in the calibration interval and the number of free parameters in the reconstruction model to avoid artificial skill. Within this framework, CCA is investigated for its sensitivity to the level of noise in the pseudoproxy network and the spatial distribution of the network. Warm biases, variance losses, and validation-interval error increase with noise level and vary spatially within the reconstructed fields. Reconstruction skill, measured as grid-point correlations during the validation interval, is lowest in

Digital filtering and reconstruction of coded aperture images

International Nuclear Information System (INIS)

Tobin, K.W. Jr.

1987-01-01

The real-time neutron radiography facility at the University of Virginia has been used for both transmission radiography and computed tomography. Recently, a coded aperture system has been developed to permit the extraction of three dimensional information from a low intensity field of radiation scattered by an extended object. Short wave-length radiations (e.g. neutrons) are not easily image because of the difficulties in achieving diffraction and refraction with a conventional lens imaging system. By using a coded aperture approach, an imaging system has been developed that records and reconstructs an object from an intensity distribution. This system has a signal-to-noise ratio that is proportional to the total open area of the aperture making it ideal for imaging with a limiting intensity radiation field. The main goal of this research was to develope and implement the digital methods and theory necessary for the reconstruction process. Several real-time video systems, attached to an Intellect-100 image processor, a DEC PDP-11 micro-computer, and a Convex-1 parallel processing mainframe were employed. This system, coupled with theoretical extensions and improvements, allowed for retrieval of information previously unobtainable by earlier optical methods. The effect of thermal noise, shot noise, and aperture related artifacts were examined so that new digital filtering techniques could be constructed and implemented. Results of image data filtering prior to and following the reconstruction process are reported. Improvements related to the different signal processing methods are emphasized. The application and advantages of this imaging technique to the field of non-destructive testing are also discussed

Effects of Piecewise Spatial Smoothing in 4-D SPECT Reconstruction

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Qi, Wenyuan; Yang, Yongyi; King, Michael A.

2014-02-01

In nuclear medicine, cardiac gated SPECT images are known to suffer from significantly increased noise owing to limited data counts. Consequently, spatial (and temporal) smoothing has been indispensable for suppressing the noise artifacts in SPECT reconstruction. However, recently we demonstrated that the benefit of spatial processing in motion-compensated reconstruction of gated SPECT (aka 4-D) could be outweighed by its adverse effects on the myocardium, which included degraded wall motion and perfusion defect detectability. In this work, we investigate whether we can alleviate these adverse effects by exploiting an alternative spatial smoothing prior in 4-D based on image total variation (TV). TV based prior is known to induce piecewise smoothing which can preserve edge features (such as boundaries of the heart wall) in reconstruction. However, it is not clear whether such a property would necessarily be beneficial for improving the accuracy of the myocardium in 4-D reconstruction. In particular, it is unknown whether it would adversely affect the detectability of perfusion defects that are small in size or low in contrast. In our evaluation study, we first use Monte Carlo simulated imaging with 4-D NURBS-based cardiac-torso (NCAT) phantom wherein the ground truth is known for quantitative comparison. We evaluated the accuracy of the reconstructed myocardium using a number of metrics, including regional and overall accuracy of the myocardium, accuracy of the phase activity curve (PAC) of the LV wall for wall motion, uniformity and spatial resolution of the LV wall, and detectability of perfusion defects using a channelized Hotelling observer (CHO). For lesion detection, we simulated perfusion defects with different sizes and contrast levels with the focus being on perfusion defects that are subtle. As a preliminary demonstration, we also tested on three sets of clinical acquisitions. From the quantitative results, it was demonstrated that TV smoothing could

Right adrenal vein: comparison between adaptive statistical iterative reconstruction and model-based iterative reconstruction.

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Noda, Y; Goshima, S; Nagata, S; Miyoshi, T; Kawada, H; Kawai, N; Tanahashi, Y; Matsuo, M

2018-06-01

To compare right adrenal vein (RAV) visualisation and contrast enhancement degree on adrenal venous phase images reconstructed using adaptive statistical iterative reconstruction (ASiR) and model-based iterative reconstruction (MBIR) techniques. This prospective study was approved by the institutional review board, and written informed consent was waived. Fifty-seven consecutive patients who underwent adrenal venous phase imaging were enrolled. The same raw data were reconstructed using ASiR 40% and MBIR. The expert and beginner independently reviewed computed tomography (CT) images. RAV visualisation rates, background noise, and CT attenuation of the RAV, right adrenal gland, inferior vena cava (IVC), hepatic vein, and bilateral renal veins were compared between the two reconstruction techniques. RAV visualisation rates were higher with MBIR than with ASiR (95% versus 88%, p=0.13 in expert and 93% versus 75%, p=0.002 in beginner, respectively). RAV visualisation confidence ratings with MBIR were significantly greater than with ASiR (pASiR (pASiR (p=0.0013 and 0.02). Reconstruction of adrenal venous phase images using MBIR significantly reduces background noise, leading to an improvement in the RAV visualisation compared with ASiR. Copyright © 2018 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

Noise Considerations for V/STOL Transports

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Kenyon, George C.

1968-01-01

Noise consideration may well be as important a factor in future aircraft concept selection as such economic factors as operating cost and profitability. The impact of noise on some of the design and operational aspects of future V/STOL transports is examined in detail, including consideration of configuration, attitude-control system, lift system, and terminal flight pattern. Extended vertical rise of VTOL aircraft as a method of limiting the intense noise exposure to the terminal area is shown to be only partially effective as well as costly. Comparisons are made of noise contours for conceptual V/STOL transports for several PNdB criteria. The variation in extent of affected area with configuration and criterion emphasizes the importance of establishing an "acceptable" noise level for "city-center" operation.

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

Comparison of pure and hybrid iterative reconstruction techniques with conventional filtered back projection: Image quality assessment in the cervicothoracic region

International Nuclear Information System (INIS)

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

2013-01-01

Objectives: To evaluate the impact on image quality of three different image reconstruction techniques in the cervicothoracic region: model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP). Methods: Forty-four patients underwent unenhanced standard-of-care clinical computed tomography (CT) examinations which included the cervicothoracic region with a 64-row multidetector CT scanner. Images were reconstructed with FBP, 50% ASIR-FBP blending (ASIR50), and MBIR. Two radiologists assessed the cervicothoracic region in a blinded manner for streak artifacts, pixilated blotchy appearances, critical reproduction of visually sharp anatomical structures (thyroid gland, common carotid artery, and esophagus), and overall diagnostic acceptability. Objective image noise was measured in the internal jugular vein. Data were analyzed using the sign test and pair-wise Student's t-test. Results: MBIR images had significant lower quantitative image noise (8.88 ± 1.32) compared to ASIR images (18.63 ± 4.19, P 0.9 for ASIR vs. FBP for both readers). MBIR images were all diagnostically acceptable. Unique features of MBIR images included pixilated blotchy appearances, which did not adversely affect diagnostic acceptability. Conclusions: MBIR significantly improves image noise and streak artifacts of the cervicothoracic region over ASIR and FBP. MBIR is expected to enhance the value of CT examinations for areas where image noise and streak artifacts are problematic

Accelerated numerical processing of electronically recorded holograms with reduced speckle noise.

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Trujillo, Carlos; Garcia-Sucerquia, Jorge

2013-09-01

The numerical reconstruction of digitally recorded holograms suffers from speckle noise. An accelerated method that uses general-purpose computing in graphics processing units to reduce that noise is shown. The proposed methodology utilizes parallelized algorithms to record, reconstruct, and superimpose multiple uncorrelated holograms of a static scene. For the best tradeoff between reduction of the speckle noise and processing time, the method records, reconstructs, and superimposes six holograms of 1024 × 1024 pixels in 68 ms; for this case, the methodology reduces the speckle noise by 58% compared with that exhibited by a single hologram. The fully parallelized method running on a commodity graphics processing unit is one order of magnitude faster than the same technique implemented on a regular CPU using its multithreading capabilities. Experimental results are shown to validate the proposal.

Increasing signal-to-noise ratio of swept-source optical coherence tomography by oversampling in k-space

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Nagib, Karim; Mezgebo, Biniyam; Thakur, Rahul; Fernando, Namal; Kordi, Behzad; Sherif, Sherif

2018-03-01

Optical coherence tomography systems suffer from noise that could reduce ability to interpret reconstructed images correctly. We describe a method to increase the signal-to-noise ratio of swept-source optical coherence tomography (SSOCT) using oversampling in k-space. Due to this oversampling, information redundancy would be introduced in the measured interferogram that could be used to reduce white noise in the reconstructed A-scan. We applied our novel scaled nonuniform discrete Fourier transform to oversampled SS-OCT interferograms to reconstruct images of a salamander egg. The peak-signal-to-noise (PSNR) between the reconstructed images using interferograms sampled at 250MS/s andz50MS/s demonstrate that this oversampling increased the signal-to-noise ratio by 25.22 dB.

Noise suppressed partial volume correction for cardiac SPECT/CT

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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

Wavelet-based regularization and edge preservation for submillimetre 3D list-mode reconstruction data from a high resolution small animal PET system

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Jesus Ochoa Dominguez, Humberto de, E-mail: hochoa@uacj.mx [Departamento de Ingenieria Eectrica y Computacion, Universidad Autonoma de Ciudad Juarez, Avenida del Charro 450 Norte, C.P. 32310 Ciudad Juarez, Chihuahua (Mexico); Ortega Maynez, Leticia; Osiris Vergara Villegas, Osslan; Gordillo Castillo, Nelly; Guadalupe Cruz Sanchez, Vianey; Gutierrez Casas, Efren David [Departamento de Ingenieria Eectrica y Computacion, Universidad Autonoma de Ciudad Juarez, Avenida del Charro 450 Norte, C.P. 32310 Ciudad Juarez, Chihuahua (Mexico)

2011-10-01

The data obtained from a PET system tend to be noisy because of the limitations of the current instrumentation and the detector efficiency. This problem is particularly severe in images of small animals as the noise contaminates areas of interest within small organs. Therefore, denoising becomes a challenging task. In this paper, a novel wavelet-based regularization and edge preservation method is proposed to reduce such noise. To demonstrate this method, image reconstruction using a small mouse {sup 18}F NEMA phantom and a {sup 18}F mouse was performed. Investigation on the effects of the image quality was addressed for each reconstruction case. Results show that the proposed method drastically reduces the noise and preserves the image details.

Spectral reconstruction for shifted-excitation Raman difference spectroscopy (SERDS).

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Guo, Shuxia; Chernavskaia, Olga; Popp, Jürgen; Bocklitz, Thomas

2018-08-15

Fluorescence emission is one of the major obstacles to apply Raman spectroscopy in biological investigations. It is usually several orders more intense than Raman scattering and hampers further analysis. In cases where the fluorescence emission is too intense to be efficiently removed via routine mathematical baseline correction algorithms, an alternative approach is needed. One alternative approach is shifted-excitation Raman difference spectroscopy (SERDS), where two Raman spectra are recorded with two slightly different excitation wavelengths. Ideally, the fluorescence emission at the two excitations does not change while the Raman spectrum shifts according to the excitation wavelength. Hence the fluorescence is removed in the difference of the two recorded Raman spectra. For better interpretability a spectral reconstruction procedure is necessary to recover the fluorescence-free Raman spectrum. This is challenging due to the intensity variations between the two recorded Raman spectra caused by unavoidable experimental changes as well as the presence of noise. Existent approaches suffer from drawbacks like spectral resolution loss, fluorescence residual, and artefacts. In this contribution, we proposed a reconstruction method based on non-negative least squares (NNLS), where the intensity variations between the two measurements are utilized in the reconstruction model. The method achieved fluorescence-free reconstruction on three real-world SERDS datasets without significant information loss. Thereafter, we quantified the performance of the reconstruction based on artificial datasets from four aspects: reconstructed spectral resolution, precision of reconstruction, signal-to-noise-ratio (SNR), and fluorescence residual. The artificial datasets were constructed with varied Raman to fluorescence intensity ratio (RFIR), SNR, full-width at half-maximum (FWHM), excitation wavelength shift, and fluorescence variation between the two spectra. It was demonstrated that

PET reconstruction via nonlocal means induced prior.

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Hou, Qingfeng; Huang, Jing; Bian, Zhaoying; Chen, Wufan; Ma, Jianhua

2015-01-01

The traditional Bayesian priors for maximum a posteriori (MAP) reconstruction methods usually incorporate local neighborhood interactions that penalize large deviations in parameter estimates for adjacent pixels; therefore, only local pixel differences are utilized. This limits their abilities of penalizing the image roughness. To achieve high-quality PET image reconstruction, this study investigates a MAP reconstruction strategy by incorporating a nonlocal means induced (NLMi) prior (NLMi-MAP) which enables utilizing global similarity information of image. The present NLMi prior approximates the derivative of Gibbs energy function by an NLM filtering process. Specially, the NLMi prior is obtained by subtracting the current image estimation from its NLM filtered version and feeding the residual error back to the reconstruction filter to yield the new image estimation. We tested the present NLMi-MAP method with simulated and real PET datasets. Comparison studies with conventional filtered backprojection (FBP) and a few iterative reconstruction methods clearly demonstrate that the present NLMi-MAP method performs better in lowering noise, preserving image edge and in higher signal to noise ratio (SNR). Extensive experimental results show that the NLMi-MAP method outperforms the existing methods in terms of cross profile, noise reduction, SNR, root mean square error (RMSE) and correlation coefficient (CORR).

Noise and pile-up in liquid sampling calorimeters

International Nuclear Information System (INIS)

Franzini, P.

1988-01-01

The design and construction of detectors for the SSC presents new challenges and requires electronics of priorly unavailable performance. Most detector elements produce minute signals which can be lost in the ever present noise from thermal fluctuation and the finite charge of the electron. The author presents in these notes a pedagogical introduction to noise and pile-up, as applicable to liquid sampling calorimeters, beginning with a brief, only descriptive, introduction to amplifiers and the physical origins of noise. He then studies the particular case of noise in charge measurements, in particular for calorimeters, where parallel noise is usually negligible. By a physical example he discusses optimal filtering, proving that gaussian filters are not optimal. The scaling laws of noise versus source capacitance and filter bandwidth or shaping time, are emphasized. An explicit example for pulse shapes peaking at 1 μs is computed and extrapolated to 0.1 μs, more appropriate for an SSC detector. Solutions for the several problems arising at short shaping times are discussed and the conditions for optimal preamp-detector matching (for minimum noise) are derived. He also briefly discusses pile-up and its scaling laws. Correlations between signal samples at different times are considered and computed for an example. Correlations are necessary to compute the noise in signals reconstructed from sampling

Filtering of SPECT reconstructions made using Bellini's attenuation correction method

International Nuclear Information System (INIS)

Glick, S.J.; Penney, B.C.; King, M.A.

1991-01-01

This paper evaluates a three-dimensional (3D) Wiener filter which is used to restore SPECT reconstructions which were made using Bellini's method of attenuation correction. Its performance is compared to that of several pre-reconstruction filers: the one-dimensional (1D) Butterworth, the two-dimensional (2D) Butterworth, and a 2D Wiener filer. A simulation study is used to compare the four filtering methods. An approximation to a clinical liver spleen study was used as the source distribution and algorithm which accounts for the depth and distance dependent blurring in SPECT was used to compute noise free projections. To study the effect of filtering method on tumor detection accuracy, a 2 cm diameter, cool spherical tumor (40% contrast) was placed at a known, but random, location with the liver. Projection sets for ten tumor locations were computed and five noise realizations of each set were obtained by introducing Poisson noise. The simulated projections were either: filtered with the 1D or 2D Butterworth or the 2D Wiener and then reconstructed using Bellini's intrinsic attenuation correction, or reconstructed first, then filtered with the 3D Wiener. The criteria used for comparison were: normalized mean square error (NMSE), cold spot contrast, and accuracy of tumor detection with an automated numerical method. Results indicate that restorations obtained with 3D Wiener filtering yielded significantly higher lesion contrast and lower NMSE values compared to the other methods of processing. The Wiener restoration filters and the 2D Butterworth all provided similar measures of detectability, which were noticeably higher than that obtained with 1D Butterworth smoothing

Pinhole single-photon emission tomography reconstruction based on median root prior

International Nuclear Information System (INIS)

Sohlberg, Antti; Kuikka, Jyrki T.; Ruotsalainen, Ulla

2003-01-01

The maximum likelihood expectation maximisation (ML-EM) algorithm can be used to reduce reconstruction artefacts produced by filtered backprojection (FBP) methods in pinhole single-photon emission tomography (SPET). However, ML-EM suffers from noise propagation along iterations, which leads to quantitatively unpleasant reconstruction results. To avoid this increase in noise, the median root prior (MRP) algorithm for pinhole SPET was implemented. Projection data of a line source and Picker's thyroid phantom were collected using a single-head gamma camera with a pinhole collimator. MRP was added to existing pinhole ML-EM reconstruction algorithm and the phantom studies were reconstructed using MRP, ML-EM and FBP for comparison. Coefficients of variation, contrasts and full-widths at half-maximum were calculated and showed a clear reduction in noise without significant loss of resolution or decrease in contrast when MRP was applied. MRP also produced visually pleasing images even with high iteration numbers, free of the checkerboard-type noise patterns which are typical of ML-EM images. (orig.)

Accelerated median root prior reconstruction for pinhole single-photon emission tomography (SPET)

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Sohlberg, Antti [Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, PO Box 1777 FIN-70211, Kuopio (Finland); Ruotsalainen, Ulla [Institute of Signal Processing, DMI, Tampere University of Technology, PO Box 553 FIN-33101, Tampere (Finland); Watabe, Hiroshi [National Cardiovascular Center Research Institute, 5-7-1 Fujisihro-dai, Suita City, Osaka 565-8565 (Japan); Iida, Hidehiro [National Cardiovascular Center Research Institute, 5-7-1 Fujisihro-dai, Suita City, Osaka 565-8565 (Japan); Kuikka, Jyrki T [Department of Clinical Physiology and Nuclear Medicine, Kuopio University Hospital, PO Box 1777 FIN-70211, Kuopio (Finland)

2003-07-07

Pinhole collimation can be used to improve spatial resolution in SPET. However, the resolution improvement is achieved at the cost of reduced sensitivity, which leads to projection images with poor statistics. Images reconstructed from these projections using the maximum likelihood expectation maximization (ML-EM) algorithms, which have been used to reduce the artefacts generated by the filtered backprojection (FBP) based reconstruction, suffer from noise/bias trade-off: noise contaminates the images at high iteration numbers, whereas early abortion of the algorithm produces images that are excessively smooth and biased towards the initial estimate of the algorithm. To limit the noise accumulation we propose the use of the pinhole median root prior (PH-MRP) reconstruction algorithm. MRP is a Bayesian reconstruction method that has already been used in PET imaging and shown to possess good noise reduction and edge preservation properties. In this study the PH-MRP algorithm was accelerated with the ordered subsets (OS) procedure and compared to the FBP, OS-EM and conventional Bayesian reconstruction methods in terms of noise reduction, quantitative accuracy, edge preservation and visual quality. The results showed that the accelerated PH-MRP algorithm was very robust. It provided visually pleasing images with lower noise level than the FBP or OS-EM and with smaller bias and sharper edges than the conventional Bayesian methods.

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

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

2015-01-01

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

Characterization of a computed tomography iterative reconstruction algorithm by image quality evaluations with an anthropomorphic phantom

International Nuclear Information System (INIS)

Rampado, O.; Bossi, L.; Garabello, D.; Davini, O.; Ropolo, R.

2012-01-01

Objective: This study aims to investigate the consequences on dose and image quality of the choices of different combinations of NI and adaptive statistical iterative reconstruction (ASIR) percentage, the image quality parameters of GE CT equipment. Methods: An anthropomorphic phantom was used to simulate the chest and upper abdomen of a standard weight patient. Images were acquired with tube current modulation and different values of noise index, in the range 10–22 for a slice thickness of 5 mm and a tube voltage of 120 kV. For each selected noise index, several image series were reconstructed using different percentages of ASIR (0, 40, 50, 60, 70, 100). Quantitative noise was assessed at different phantom locations. Computed tomography dose index (CTDI) and dose length products (DLP) were recorded. Three radiologists reviewed the images in a blinded and randomized manner and assessed the subjective image quality by comparing the image series with the one acquired with the reference protocol (noise index 14, ASIR 40%). The perceived noise, contrast, edge sharpness and overall quality were graded on a scale from −2 (much worse) to +2 (much better). Results: A repeatable trend of noise reduction versus the percentage of ASIR was observed for different noise levels and phantom locations. The different combinations of noise index and percentage of ASIR to obtain a desired dose reduction were assessed. The subjective image quality evaluation evidenced a possible dose reduction between 24 and 40% as a consequence of an increment of ASIR percentage to 50 or 70%, respectively. Conclusion: These results highlighted that the same patient dose reduction can be obtained with several combinations of noise index and percentages of ASIR, providing a model with which to choose these acquisition parameters in future optimization studies, with the aim of reducing patient dose by maintaining image quality in diagnostic levels.

Characterization of a computed tomography iterative reconstruction algorithm by image quality evaluations with an anthropomorphic phantom

Energy Technology Data Exchange (ETDEWEB)

Rampado, O., E-mail: orampado@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Bossi, L., E-mail: laura-bossi@hotmail.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Garabello, D., E-mail: dgarabello@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Davini, O., E-mail: odavini@molinette.piemonte.it [S.C. Radiodiagnostica DEA, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy); Ropolo, R., E-mail: rropolo@molinette.piemonte.it [S.C. Fisica Sanitaria, San Giovanni Battista Hospital of Turin, Corso Bramante 88, Torino 10126 (Italy)

2012-11-15

Objective: This study aims to investigate the consequences on dose and image quality of the choices of different combinations of NI and adaptive statistical iterative reconstruction (ASIR) percentage, the image quality parameters of GE CT equipment. Methods: An anthropomorphic phantom was used to simulate the chest and upper abdomen of a standard weight patient. Images were acquired with tube current modulation and different values of noise index, in the range 10-22 for a slice thickness of 5 mm and a tube voltage of 120 kV. For each selected noise index, several image series were reconstructed using different percentages of ASIR (0, 40, 50, 60, 70, 100). Quantitative noise was assessed at different phantom locations. Computed tomography dose index (CTDI) and dose length products (DLP) were recorded. Three radiologists reviewed the images in a blinded and randomized manner and assessed the subjective image quality by comparing the image series with the one acquired with the reference protocol (noise index 14, ASIR 40%). The perceived noise, contrast, edge sharpness and overall quality were graded on a scale from -2 (much worse) to +2 (much better). Results: A repeatable trend of noise reduction versus the percentage of ASIR was observed for different noise levels and phantom locations. The different combinations of noise index and percentage of ASIR to obtain a desired dose reduction were assessed. The subjective image quality evaluation evidenced a possible dose reduction between 24 and 40% as a consequence of an increment of ASIR percentage to 50 or 70%, respectively. Conclusion: These results highlighted that the same patient dose reduction can be obtained with several combinations of noise index and percentages of ASIR, providing a model with which to choose these acquisition parameters in future optimization studies, with the aim of reducing patient dose by maintaining image quality in diagnostic levels.

Evaluation of reconstruction algorithms in SPECT neuroimaging: Pt. 1

International Nuclear Information System (INIS)

Heejoung Kim; Zeeberg, B.R.; Reba, R.C.

1993-01-01

In the presence of statistical noise, an iterative reconstruction algorithm (IRA) for the quantitative reconstruction of single-photon-emission computed tomographic (SPECT) brain images overcomes major limitations of applying the standard filtered back projection (FBP) reconstruction algorithm to projection data which have been degraded by convolution of the true radioactivity distribution with a finite-resolution distance-dependent detector response: (a) the non-uniformity within the grey (or white) matter voxels which results even though the true model is uniform within these voxels; (b) a significantly lower ratio of grey/white matter voxel values than in the true model; and (c) an inability to detect an altered radioactivity value within the grey (or white) matter voxels. It is normally expected that an algorithm which improves spatial resolution and quantitative accuracy might also increase the magnitude of the statistical noise in the reconstructed image. However, the noise properties in the IRA images are very similar to those in the FBP images. (Author)

Gravitational wave searches with pulsar timing arrays: Cancellation of clock and ephemeris noises

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Tinto, Massimo

2018-04-01

We propose a data processing technique to cancel monopole and dipole noise sources (such as clock and ephemeris noises, respectively) in pulsar timing array searches for gravitational radiation. These noises are the dominant sources of correlated timing fluctuations in the lower-part (≈10-9-10-8 Hz ) of the gravitational wave band accessible by pulsar timing experiments. After deriving the expressions that reconstruct these noises from the timing data, we estimate the gravitational wave sensitivity of our proposed processing technique to single-source signals to be at least one order of magnitude higher than that achievable by directly processing the timing data from an equal-size array. Since arrays can generate pairs of clock and ephemeris-free timing combinations that are no longer affected by correlated noises, we implement with them the cross-correlation statistic to search for an isotropic stochastic gravitational wave background. We find the resulting optimal signal-to-noise ratio to be more than one order of magnitude larger than that obtainable by correlating pairs of timing data from arrays of equal size.

Noise and contrast detection in computed tomography images

International Nuclear Information System (INIS)

Faulkner, K.; Moores, B.M.

1984-01-01

A discrete representation of the reconstruction process is used in an analysis of noise in computed tomography (CT) images. This model is consistent with the method of data collection in actual machines. An expression is derived which predicts the variance on the measured linear attenuation coefficient of a single pixel in an image. The dependence of the variance on various CT scanner design parameters such as pixel size, slice width, scan time, number of detectors, etc., is then described. The variation of noise with sampling area is theoretically explained. These predictions are in good agreement with a set of experimental measurements made on a range of CT scanners. The equivalent sampling aperture of the CT process is determined and the effect of the reconstruction filter on the variance of the linear attenuation coefficient is also noted, in particular, the choice and its consequences for reconstructed images and noise behaviour. The theory has been extended to include contrast detail behaviour, and these predictions compare favourably with experimental measurements. The theory predicts that image smoothing will have little effect on the contrast-detail detectability behaviour of reconstructed images. (author)

Reduction of Poisson noise in measured time-resolved data for time-domain diffuse optical tomography.

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Okawa, S; Endo, Y; Hoshi, Y; Yamada, Y

2012-01-01

A method to reduce noise for time-domain diffuse optical tomography (DOT) is proposed. Poisson noise which contaminates time-resolved photon counting data is reduced by use of maximum a posteriori estimation. The noise-free data are modeled as a Markov random process, and the measured time-resolved data are assumed as Poisson distributed random variables. The posterior probability of the occurrence of the noise-free data is formulated. By maximizing the probability, the noise-free data are estimated, and the Poisson noise is reduced as a result. The performances of the Poisson noise reduction are demonstrated in some experiments of the image reconstruction of time-domain DOT. In simulations, the proposed method reduces the relative error between the noise-free and noisy data to about one thirtieth, and the reconstructed DOT image was smoothed by the proposed noise reduction. The variance of the reconstructed absorption coefficients decreased by 22% in a phantom experiment. The quality of DOT, which can be applied to breast cancer screening etc., is improved by the proposed noise reduction.

Industrial dynamic tomographic reconstruction

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Oliveira, Eric Ferreira de

2016-01-01

The state of the art methods applied to industrial processes is currently based on the principles of classical tomographic reconstructions developed for tomographic patterns of static distributions, or is limited to cases of low variability of the density distribution function of the tomographed object. Noise and motion artifacts are the main problems caused by a mismatch in the data from views acquired in different instants. All of these add to the known fact that using a limited amount of data can result in the presence of noise, artifacts and some inconsistencies with the distribution under study. One of the objectives of the present work is to discuss the difficulties that arise from implementing reconstruction algorithms in dynamic tomography that were originally developed for static distributions. Another objective is to propose solutions that aim at reducing a temporal type of information loss caused by employing regular acquisition systems to dynamic processes. With respect to dynamic image reconstruction it was conducted a comparison between different static reconstruction methods, like MART and FBP, when used for dynamic scenarios. This comparison was based on a MCNPx simulation as well as an analytical setup of an aluminum cylinder that moves along the section of a riser during the process of acquisition, and also based on cross section images from CFD techniques. As for the adaptation of current tomographic acquisition systems for dynamic processes, this work established a sequence of tomographic views in a just-in-time fashion for visualization purposes, a form of visually disposing density information as soon as it becomes amenable to image reconstruction. A third contribution was to take advantage of the triple color channel necessary to display colored images in most displays, so that, by appropriately scaling the acquired values of each view in the linear system of the reconstruction, it was possible to imprint a temporal trace into the regularly

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

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

2015-10-01

To investigate whether reduced radiation dose abdominal CT images reconstructed with adaptive statistical iterative reconstruction V (ASIR-V) compromise the depiction of clinically competent features when compared with the currently used routine radiation dose CT images reconstructed with ASIR. 27 consecutive patients (mean body mass index: 23.55 kg m(-2) underwent CT of the abdomen at two time points. At the first time point, abdominal CT was scanned at 21.45 noise index levels of automatic current modulation at 120 kV. Images were reconstructed with 40% ASIR, the routine protocol of Dong-A University Hospital. At the second time point, follow-up scans were performed at 30 noise index levels. Images were reconstructed with filtered back projection (FBP), 40% ASIR, 30% ASIR-V, 50% ASIR-V and 70% ASIR-V for the reduced radiation dose. Both quantitative and qualitative analyses of image quality were conducted. The CT dose index was also recorded. At the follow-up study, the mean dose reduction relative to the currently used common radiation dose was 35.37% (range: 19-49%). The overall subjective image quality and diagnostic acceptability of the 50% ASIR-V scores at the reduced radiation dose were nearly identical to those recorded when using the initial routine-dose CT with 40% ASIR. Subjective ratings of the qualitative analysis revealed that of all reduced radiation dose CT series reconstructed, 30% ASIR-V and 50% ASIR-V were associated with higher image quality with lower noise and artefacts as well as good sharpness when compared with 40% ASIR and FBP. However, the sharpness score at 70% ASIR-V was considered to be worse than that at 40% ASIR. Objective image noise for 50% ASIR-V was 34.24% and 46.34% which was lower than 40% ASIR and FBP. Abdominal CT images reconstructed with ASIR-V facilitate radiation dose reductions of to 35% when compared with the ASIR. This study represents the first clinical research experiment to use ASIR-V, the newest version of

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

Reconstruction in oral malignancy: Factors affecting morbidity of various procedures

Science.gov (United States)

Chakrabarti, Suvadip; Chakrabarti, Preeti Rihal; Desai, Sanjay M.; Agrawal, Deepak; Mehta, Dharmendra Y.; Pancholi, Mayank

2015-01-01

Aims and Objective: (1) To study the age and sex distribution of patient with oral malignancies. (2) To analyze various types of surgery performed. (3) Evaluation of reconstruction and factors affecting complications and its relation to the type of reconstruction. Materials and Methods: Cases of oral malignancies, undergoing surgery for the same in Sri Aurobindo Medical College and PG Institute, Indore from the period from October 1, 2012, to March 31, 2015. Results: Out of analysis of 111 cases of oral malignancy, 31 (27.9%) cases were in the fifth decade of life with male to female ratio 1.9:1. The commonest site of cancer was buccal mucosa. Forty-seven cases (43.2%) were in stage IVa. Diabetes was the most common co-morbidity reported, accounting for 53.9% of cases with reported morbidity. Tobacco chewing was the common entity in personal habits. All the cases underwent neck dissection along with resection of the primary. Hemimandibulectomy was the most preferred form of primary resection accounting for 53.15% (59 cases), followed by wide resection of primary 27% (30 cases). Pectoralis major myocutaneous (PMMC) flap only was the most common reconstruction across the study population. PMMC alone accounted for 38.7% (43 cases). The infection rate was 16.21%. PMMC alone accounted for 5 out of 18 (27.8%) of total infection rate, and 4.5% of the total study population. PMMC + deltopectoral accounted for 5 out of 18 (27.8%) of total infection rate, and 4.5% of the total study population. Conclusion: PMMC is a major workhorse for reconstruction with better functional outcome and acceptance among operated patients. PMID:26981469

Coronary artery plaques: Cardiac CT with model-based and adaptive-statistical iterative reconstruction technique

International Nuclear Information System (INIS)

Scheffel, Hans; Stolzmann, Paul; Schlett, Christopher L.; Engel, Leif-Christopher; Major, Gyöngi Petra; Károlyi, Mihály; Do, Synho; Maurovich-Horvat, Pál; Hoffmann, Udo

2012-01-01

Objectives: To compare image quality of coronary artery plaque visualization at CT angiography with images reconstructed with filtered back projection (FBP), adaptive statistical iterative reconstruction (ASIR), and model based iterative reconstruction (MBIR) techniques. Methods: The coronary arteries of three ex vivo human hearts were imaged by CT and reconstructed with FBP, ASIR and MBIR. Coronary cross-sectional images were co-registered between the different reconstruction techniques and assessed for qualitative and quantitative image quality parameters. Readers were blinded to the reconstruction algorithm. Results: A total of 375 triplets of coronary cross-sectional images were co-registered. Using MBIR, 26% of the images were rated as having excellent overall image quality, which was significantly better as compared to ASIR and FBP (4% and 13%, respectively, all p < 0.001). Qualitative assessment of image noise demonstrated a noise reduction by using ASIR as compared to FBP (p < 0.01) and further noise reduction by using MBIR (p < 0.001). The contrast-to-noise-ratio (CNR) using MBIR was better as compared to ASIR and FBP (44 ± 19, 29 ± 15, 26 ± 9, respectively; all p < 0.001). Conclusions: Using MBIR improved image quality, reduced image noise and increased CNR as compared to the other available reconstruction techniques. This may further improve the visualization of coronary artery plaque and allow radiation reduction.

A new iterative reconstruction technique for attenuation correction in high-resolution positron emission tomography

International Nuclear Information System (INIS)

Knesaurek, K.; Machac, J.; Vallabhajosula, S.; Buchsbaum, M.S.

1996-01-01

A new interative reconstruction technique (NIRT) for positron emission computed tomography (PET), which uses transmission data for nonuniform attenuation correction, is described. Utilizing the general inverse problem theory, a cost functional which includes a noise term was derived. The cost functional was minimized using a weighted-least-square maximum a posteriori conjugate gradient (CG) method. The procedure involves a change in the Hessian of the cost function by adding an additional term. Two phantoms were used in a real data acquisition. The first was a cylinder phantom filled with uniformly distributed activity of 74 MBq of fluorine-18. Two different inserts were placed in the phantom. The second was a Hoffman brain phantom filled with uniformly distributed activity of 7.4 MBq of 18 F. Resulting reconstructed images were used to test and compare a new interative reconstruction technique with a standard filtered backprojection (FBP) method. The results confirmed that NIRT, based on the conjugate gradient method, converges rapidly and provides good reconstructed images. In comaprison with standard results obtained by the FBP method, the images reconstructed by NIRT showed better noise properties. The noise was measured as rms% noise and was less, by a factor of 1.75, in images reconstructed by NIRT than in the same images reconstructed by FBP. The distance between the Hoffman brain slice created from the MRI image was 0.526, while the same distance for the Hoffman brain slice reconstructed by NIRT was 0.328. The NIRT method suppressed the propagation of the noise without visible loss of resolution in the reconstructed PET images. (orig.)

Radiation dose reduction using 100-kVp and a sinogram-affirmed iterative reconstruction algorithm in adolescent head CT: Impact on grey-white matter contrast and image noise

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Nagayama, Yasunori [Kumamoto City Hospital, Department of Radiology, Kumamoto (Japan); Kumamoto University, Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto (Japan); Nakaura, Takeshi; Yuki, Hideaki; Hirarta, Kenichiro; Kidoh, Masafumi; Oda, Seitaro; Utsunomiya, Daisuke; Yamashita, Yasuyuki [Kumamoto University, Department of Diagnostic Radiology, Graduate School of Medical Sciences, Kumamoto (Japan); Tsuji, Akinori; Urata, Joji; Furusawa, Mitsuhiro [Kumamoto City Hospital, Department of Radiology, Kumamoto (Japan)

2017-07-15

To retrospectively evaluate the image quality and radiation dose of 100-kVp scans with sinogram-affirmed iterative reconstruction (IR) for unenhanced head CT in adolescents. Sixty-nine patients aged 12-17 years underwent head CT under 120- (n = 34) or 100-kVp (n = 35) protocols. The 120-kVp images were reconstructed with filtered back-projection (FBP), 100-kVp images with FBP (100-kVp-F) and sinogram-affirmed IR (100-kVp-S). We compared the effective dose (ED), grey-white matter (GM-WM) contrast, image noise, and contrast-to-noise ratio (CNR) between protocols in supratentorial (ST) and posterior fossa (PS). We also assessed GM-WM contrast, image noise, sharpness, artifacts, and overall image quality on a four-point scale. ED was 46% lower with 100- than 120-kVp (p < 0.001). GM-WM contrast was higher, and image noise was lower, on 100-kVp-S than 120-kVp at ST (p < 0.001). CNR of 100-kVp-S was higher than of 120-kVp (p < 0.001). GM-WM contrast of 100-kVp-S was subjectively rated as better than of 120-kVp (p < 0.001). There were no significant differences in the other criteria between 100-kVp-S and 120-kVp (p = 0.072-0.966). The 100-kVp with sinogram-affirmed IR facilitated dramatic radiation reduction and better GM-WM contrast without increasing image noise in adolescent head CT. (orig.)

Relationships of clinical protocols and reconstruction kernels with image quality and radiation dose in a 128-slice CT scanner: Study with an anthropomorphic and water phantom

International Nuclear Information System (INIS)

Paul, Jijo; Krauss, B.; Banckwitz, R.; Maentele, W.; Bauer, R.W.; Vogl, T.J.

2012-01-01

Research highlights: ► Clinical protocol, reconstruction kernel, reconstructed slice thickness, phantom diameter or the density of material it contains directly affects the image quality of DSCT. ► Dual energy protocol shows the lowest DLP compared to all other protocols examined. ► Dual-energy fused images show excellent image quality and the noise is same as that of single- or high-pitch mode protocol images. ► Advanced CT technology improves image quality and considerably reduce radiation dose. ► An important finding is the comparatively higher DLP of the dual-source high-pitch protocol compared to other single- or dual-energy protocols. - Abstract: Purpose: The aim of this study was to explore the relationship of scanning parameters (clinical protocols), reconstruction kernels and slice thickness with image quality and radiation dose in a DSCT. Materials and methods: The chest of an anthropomorphic phantom was scanned on a DSCT scanner (Siemens Somatom Definition flash) using different clinical protocols, including single- and dual-energy modes. Four scan protocols were investigated: 1) single-source 120 kV, 110 mA s, 2) single-source 100 kV, 180 mA s, 3) high-pitch 120 kV, 130 mA s and 4) dual-energy with 100/Sn140 kV, eff.mA s 89, 76. The automatic exposure control was switched off for all the scans and the CTDIvol selected was in between 7.12 and 7.37 mGy. The raw data were reconstructed using the reconstruction kernels B31f, B80f and B70f, and slice thicknesses were 1.0 mm and 5.0 mm. Finally, the same parameters and procedures were used for the scanning of water phantom. Friedman test and Wilcoxon-Matched-Pair test were used for statistical analysis. Results: The DLP based on the given CTDIvol values showed significantly lower exposure for protocol 4, when compared to protocol 1 (percent difference 5.18%), protocol 2 (percent diff. 4.51%), and protocol 3 (percent diff. 8.81%). The highest change in Hounsfield Units was observed with dual

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

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.

Pseudoproxy Experiments Using the BARCAST Reconstruction Technique: Effects on Spatiotemporal Persistence Properties

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Nilsen, T.; Divine, D.; Rypdal, M.; Werner, J.; Rypdal, K.

2016-12-01

A modified two-dimensional stochastic-diffusive energy balance model (EBM) defined on a sphere was used for generating pseudoproxy/instrumental data and target data for surface temperature. The EBM is described in Rypdal et al. (2015). The target field has prescribed long-range memory (LRM) properties in time, and a frequency-dependent autocorrelation function in space. The Bayesian hierarchical model BARCAST, was used to generate surface temperature field reconstructions of an area corresponding to the European landmass for the past millennium. BARCAST has a built-in multivariate AR(1) model for the evolution of the temperature field, with an exponential, spatial covariance function, (Tingley & Huybers, 2010). The AR(1) process has a short-range memory, and we seek to find out how the competing spatiotemporal models influence the persistence of the reconstruction. A number of pseudoproxy experiments were performed with a fixed proxy network, using different signal-to-noise ratios (SNR) and colors of noise, (white/red). To study the persistence properties, the power-law relation of the power spectral density for LRM processes was used: S(f) f-β. The spectral exponent β was estimated both for local data and the spatial mean of the full region. The local β for the target varies between (0.1, 0.4), and for the spatial mean β 0.6. Results for the reconstructions show that the local and global memory is influenced by the noise color and level. Low noise levels or absence of noise results in reconstructions that exhibit similar properties as the target, while for higher noise levels the reconstructions have memory properties of a white/red character, (SNR=0.3 by standard deviation). Since an SNR of 0.5-0.25 is considered realistic for real proxy records, this implies that estimates of temporal persistence from proxy-based reconstructions reflect the proxy noise to a high degree, and not the signal as desired. Rypdal et al., 2015: Spatiotemporal Long-Range Persistence

Radiation dose reduction in soft tissue neck CT using adaptive statistical iterative reconstruction (ASIR)

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Vachha, Behroze, E-mail: bvachha@partners.org [Neuroradiology Division, Massachusetts General Hospital, Harvard Medical School, 55 Fruit Street, Boston, MA 02114 (United States); Brodoefel, Harald; Wilcox, Carol; Hackney, David B.; Moonis, Gul [Department of Radiology, Beth Israel Deaconess Medical Center, Harvard Medical School, 330 Brookline Avenue, Boston, MA 02215 (United States)

2013-12-01

Purpose: To compare objective and subjective image quality in neck CT images acquired at different tube current–time products (275 mA s and 340 mA s) and reconstructed with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR). Materials and methods: HIPAA-compliant study with IRB approval and waiver of informed consent. 66 consecutive patients were randomly assigned to undergo contrast-enhanced neck CT at a standard tube-current–time-product (340 mA s; n = 33) or reduced tube-current–time-product (275 mA s, n = 33). Data sets were reconstructed with FBP and 2 levels (30%, 40%) of ASIR-FBP blending at 340 mA s and 275 mA s. Two neuroradiologists assessed subjective image quality in a blinded and randomized manner. Volume CT dose index (CTDIvol), dose-length-product (DLP), effective dose, and objective image noise were recorded. Signal-to-noise ratio (SNR) was computed as mean attenuation in a region of interest in the sternocleidomastoid muscle divided by image noise. Results: Compared with FBP, ASIR resulted in a reduction of image noise at both 340 mA s and 275 mA s. Reduction of tube current from 340 mA s to 275 mA s resulted in an increase in mean objective image noise (p = 0.02) and a decrease in SNR (p = 0.03) when images were reconstructed with FBP. However, when the 275 mA s images were reconstructed using ASIR, the mean objective image noise and SNR were similar to those of the standard 340 mA s CT images reconstructed with FBP (p > 0.05). Subjective image noise was ranked by both raters as either average or less-than-average irrespective of the tube current and iterative reconstruction technique. Conclusion: Adapting ASIR into neck CT protocols reduced effective dose by 17% without compromising image quality.

Radiation dose reduction in soft tissue neck CT using adaptive statistical iterative reconstruction (ASIR)

International Nuclear Information System (INIS)

Vachha, Behroze; Brodoefel, Harald; Wilcox, Carol; Hackney, David B.; Moonis, Gul

2013-01-01

Purpose: To compare objective and subjective image quality in neck CT images acquired at different tube current–time products (275 mA s and 340 mA s) and reconstructed with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR). Materials and methods: HIPAA-compliant study with IRB approval and waiver of informed consent. 66 consecutive patients were randomly assigned to undergo contrast-enhanced neck CT at a standard tube-current–time-product (340 mA s; n = 33) or reduced tube-current–time-product (275 mA s, n = 33). Data sets were reconstructed with FBP and 2 levels (30%, 40%) of ASIR-FBP blending at 340 mA s and 275 mA s. Two neuroradiologists assessed subjective image quality in a blinded and randomized manner. Volume CT dose index (CTDIvol), dose-length-product (DLP), effective dose, and objective image noise were recorded. Signal-to-noise ratio (SNR) was computed as mean attenuation in a region of interest in the sternocleidomastoid muscle divided by image noise. Results: Compared with FBP, ASIR resulted in a reduction of image noise at both 340 mA s and 275 mA s. Reduction of tube current from 340 mA s to 275 mA s resulted in an increase in mean objective image noise (p = 0.02) and a decrease in SNR (p = 0.03) when images were reconstructed with FBP. However, when the 275 mA s images were reconstructed using ASIR, the mean objective image noise and SNR were similar to those of the standard 340 mA s CT images reconstructed with FBP (p > 0.05). Subjective image noise was ranked by both raters as either average or less-than-average irrespective of the tube current and iterative reconstruction technique. Conclusion: Adapting ASIR into neck CT protocols reduced effective dose by 17% without compromising image quality

Radiation dose reduction in soft tissue neck CT using adaptive statistical iterative reconstruction (ASIR).

Science.gov (United States)

Vachha, Behroze; Brodoefel, Harald; Wilcox, Carol; Hackney, David B; Moonis, Gul

2013-12-01

To compare objective and subjective image quality in neck CT images acquired at different tube current-time products (275 mAs and 340 mAs) and reconstructed with filtered-back-projection (FBP) and adaptive statistical iterative reconstruction (ASIR). HIPAA-compliant study with IRB approval and waiver of informed consent. 66 consecutive patients were randomly assigned to undergo contrast-enhanced neck CT at a standard tube-current-time-product (340 mAs; n = 33) or reduced tube-current-time-product (275 mAs, n = 33). Data sets were reconstructed with FBP and 2 levels (30%, 40%) of ASIR-FBP blending at 340 mAs and 275 mAs. Two neuroradiologists assessed subjective image quality in a blinded and randomized manner. Volume CT dose index (CTDIvol), dose-length-product (DLP), effective dose, and objective image noise were recorded. Signal-to-noise ratio (SNR) was computed as mean attenuation in a region of interest in the sternocleidomastoid muscle divided by image noise. Compared with FBP, ASIR resulted in a reduction of image noise at both 340 mAs and 275 mAs. Reduction of tube current from 340 mAs to 275 mAs resulted in an increase in mean objective image noise (p=0.02) and a decrease in SNR (p = 0.03) when images were reconstructed with FBP. However, when the 275 mAs images were reconstructed using ASIR, the mean objective image noise and SNR were similar to those of the standard 340 mAs CT images reconstructed with FBP (p>0.05). Subjective image noise was ranked by both raters as either average or less-than-average irrespective of the tube current and iterative reconstruction technique. Adapting ASIR into neck CT protocols reduced effective dose by 17% without compromising image quality. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Adaptive statistical iterative reconstruction improves image quality without affecting perfusion CT quantitation in primary colorectal cancer

Directory of Open Access Journals (Sweden)

D. Prezzi

Full Text Available Objectives: To determine the effect of Adaptive Statistical Iterative Reconstruction (ASIR on perfusion CT (pCT parameter quantitation and image quality in primary colorectal cancer. Methods: Prospective observational study. Following institutional review board approval and informed consent, 32 patients with colorectal adenocarcinoma underwent pCT (100 kV, 150 mA, 120 s acquisition, axial mode. Tumour regional blood flow (BF, blood volume (BV, mean transit time (MTT and permeability surface area product (PS were determined using identical regions-of-interests for ASIR percentages of 0%, 20%, 40%, 60%, 80% and 100%. Image noise, contrast-to-noise ratio (CNR and pCT parameters were assessed across ASIR percentages. Coefficients of variation (CV, repeated measures analysis of variance (rANOVA and Spearman’ rank order correlation were performed with statistical significance at 5%. Results: With increasing ASIR percentages, image noise decreased by 33% while CNR increased by 61%; peak tumour CNR was greater than 1.5 with 60% ASIR and above. Mean BF, BV, MTT and PS differed by less than 1.8%, 2.9%, 2.5% and 2.6% across ASIR percentages. CV were 4.9%, 4.2%, 3.3% and 7.9%; rANOVA P values: 0.85, 0.62, 0.02 and 0.81 respectively. Conclusions: ASIR improves image noise and CNR without altering pCT parameters substantially. Keywords: Perfusion imaging, Multidetector computed tomography, Colorectal neoplasms, Computer-assisted image processing, Radiation dosage

Reducing Statistical Noise in Airborne Gamma-Ray Data

DEFF Research Database (Denmark)

Hovgaard, Jens; Grasty, R. L.

1997-01-01

By using the Noise Adjusted Singular Value Decomposition (NASVD) technique it is possible to reconstruct the measured airborne gamma-ray spectra with a noise content that is significant smaller than the noise contained in the original measured spectra. The method can be used for improving the out...... the output of the data processing for example mapping of Th, U, and K distribution....

Radiation dose reduction using 100-kVp and a sinogram-affirmed iterative reconstruction algorithm in adolescent head CT: Impact on grey-white matter contrast and image noise.

Science.gov (United States)

Nagayama, Yasunori; Nakaura, Takeshi; Tsuji, Akinori; Urata, Joji; Furusawa, Mitsuhiro; Yuki, Hideaki; Hirarta, Kenichiro; Kidoh, Masafumi; Oda, Seitaro; Utsunomiya, Daisuke; Yamashita, Yasuyuki

2017-07-01

To retrospectively evaluate the image quality and radiation dose of 100-kVp scans with sinogram-affirmed iterative reconstruction (IR) for unenhanced head CT in adolescents. Sixty-nine patients aged 12-17 years underwent head CT under 120- (n = 34) or 100-kVp (n = 35) protocols. The 120-kVp images were reconstructed with filtered back-projection (FBP), 100-kVp images with FBP (100-kVp-F) and sinogram-affirmed IR (100-kVp-S). We compared the effective dose (ED), grey-white matter (GM-WM) contrast, image noise, and contrast-to-noise ratio (CNR) between protocols in supratentorial (ST) and posterior fossa (PS). We also assessed GM-WM contrast, image noise, sharpness, artifacts, and overall image quality on a four-point scale. ED was 46% lower with 100- than 120-kVp (p < 0.001). GM-WM contrast was higher, and image noise was lower, on 100-kVp-S than 120-kVp at ST (p < 0.001). CNR of 100-kVp-S was higher than of 120-kVp (p < 0.001). GM-WM contrast of 100-kVp-S was subjectively rated as better than of 120-kVp (p < 0.001). There were no significant differences in the other criteria between 100-kVp-S and 120-kVp (p = 0.072-0.966). The 100-kVp with sinogram-affirmed IR facilitated dramatic radiation reduction and better GM-WM contrast without increasing image noise in adolescent head CT. • 100-kVp head CT provides 46% radiation dose reduction compared with 120-kVp. • 100-kVp scanning improves subjective and objective GM-WM contrast. • Sinogram-affirmed IR decreases head CT image noise, especially in supratentorial region. • 100-kVp protocol with sinogram-affirmed IR is suited for adolescent head CT.

MMSE Estimator for Children’s Speech with Car and Weather Noise

Science.gov (United States)

Sayuthi, V.

2018-04-01

Previous research mentioned that most people need and use vehicles for various purposes, in this recent time and future, as a means of traveling. Many ways can be done in a vehicle, such as for enjoying entertainment, and doing work, so vehicles not just only as a means of traveling. In this study, we will examine the children’s speech from a girl in the vehicle that affected by noise disturbances from the sound source of car noise and the weather sound noise around it, in this case, the rainy weather noise. Vehicle sounds may be from car engine or car air conditioner. The minimum mean square error (MMSE) estimator is used as an attempt to obtain or detect the children’s clear speech by representing simulation research as random process signal that factored by the autocorrelation of both the child’s voice and the disturbance noise signal. This MMSE estimator can be considered as wiener filter as the clear sound are reconstructed again. We expected that the results of this study can help as the basis for development of entertainment or communication technology for passengers of vehicles in the future, particularly using MMSE estimators.

Improvement of image quality and dose management in CT fluoroscopy by iterative 3D image reconstruction

Energy Technology Data Exchange (ETDEWEB)

Grosser, Oliver S.; Kupitz, Dennis; Powerski, Maciej; Mohnike, Konrad; Ricke, Jens [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Wybranski, Christian [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Cologne (Germany); Pech, Maciej [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Medical University of Gdansk, Second Department of Radiology, Gdansk (Poland); Amthauer, Holger [University Hospital Magdeburg, Department of Radiology and Nuclear Medicine, Magdeburg (Germany); Charite, Department of Nuclear Medicine, Berlin (Germany)

2017-09-15

The objective of this study was to assess the influence of an iterative CT reconstruction algorithm (IA), newly available for CT-fluoroscopy (CTF), on image noise, readers' confidence and effective dose compared to filtered back projection (FBP). Data from 165 patients (FBP/IA = 82/74) with CTF in the thorax, abdomen and pelvis were included. Noise was analysed in a large-diameter vessel. The impact of reconstruction and variables (e.g. X-ray tube current I) influencing noise and effective dose were analysed by ANOVA and a pairwise t-test with Bonferroni-Holm correction. Noise and readers' confidence were evaluated by three readers. Noise was significantly influenced by reconstruction, I, body region and circumference (all p ≤ 0.0002). IA reduced the noise significantly compared to FBP (p = 0.02). The effect varied for body regions and circumferences (p ≤ 0.001). The effective dose was influenced by the reconstruction, body region, interventional procedure and I (all p ≤ 0.02). The inter-rater reliability for noise and readers' confidence was good (W ≥ 0.75, p < 0.0001). Noise and readers' confidence were significantly better in AIDR-3D compared to FBP (p ≤ 0.03). Generally, IA yielded a significant reduction of the median effective dose. The CTF reconstruction by IA showed a significant reduction in noise and effective dose while readers' confidence increased. (orig.)

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

On the Impact of Anomalous Noise Events on Road Traffic Noise Mapping in Urban and Suburban Environments.

Science.gov (United States)

Orga, Ferran; Alías, Francesc; Alsina-Pagès, Rosa Ma

2017-12-23

Noise pollution is a critical factor affecting public health, the relationship between road traffic noise (RTN) and several diseases in urban areas being especially disturbing. The Environmental Noise Directive 2002/49/EC and the CNOSSOS-EU framework are the main instruments of the European Union to identify and combat noise pollution, requiring Member States to compose and publish noise maps and noise management action plans every five years. Nowadays, the noise maps are starting to be tailored by means of Wireless Acoustic Sensor Networks (WASN). In order to exclusively monitor the impact of RTN on the well-being of citizens through WASN-based approaches, those noise sources unrelated to RTN denoted as Anomalous Noise Events (ANEs) should be removed from the noise map generation. This paper introduces an analysis methodology considering both Signal-to-Noise Ratio (SNR) and duration of ANEs to evaluate their impact on the A-weighted equivalent RTN level calculation for different integration times. The experiments conducted on 9 h of real-life data from the WASN-based DYNAMAP project show that both individual high-impact events and aggregated medium-impact events bias significantly the equivalent noise levels of the RTN map, making any derived study about public health impact inaccurate.

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

Application of Symmetry Adapted Function Method for Three-Dimensional Reconstruction of Octahedral Biological Macromolecules

Directory of Open Access Journals (Sweden)

Songjun Zeng

2010-01-01

Full Text Available A method for three-dimensional (3D reconstruction of macromolecule assembles, that is, octahedral symmetrical adapted functions (OSAFs method, was introduced in this paper and a series of formulations for reconstruction by OSAF method were derived. To verify the feasibility and advantages of the method, two octahedral symmetrical macromolecules, that is, heat shock protein Degp24 and the Red-cell L Ferritin, were utilized as examples to implement reconstruction by the OSAF method. The schedule for simulation was designed as follows: 2000 random orientated projections of single particles with predefined Euler angles and centers of origins were generated, then different levels of noises that is signal-to-noise ratio (S/N =0.1,0.5, and 0.8 were added. The structures reconstructed by the OSAF method were in good agreement with the standard models and the relative errors of the structures reconstructed by the OSAF method to standard structures were very little even for high level noise. The facts mentioned above account for that the OSAF method is feasible and efficient approach to reconstruct structures of macromolecules and have ability to suppress the influence of noise.

State-of-the-Art Review on Sustainable Design and Construction of Quieter Pavements—Part 2: Factors Affecting Tire-Pavement Noise and Prediction Models

Directory of Open Access Journals (Sweden)

Okan Sirin

2016-07-01

Full Text Available Traffic noise is a combination of noises produced from a number of sources. Of all the traffic noise sources, tire-pavement noise, which is emitted as a result of the interaction of rolling, slipping, or dragging tires and the pavement surface, is the dominant contributor of overall noise, particularly when vehicles are moving at higher speeds. Therefore, a number of research studies have been conducted to identify and analyze the factors affecting the generation of tire-pavement interaction noise. This helps in identifying and selecting appropriate noise mitigation techniques. In this paper, an extensive literature survey on the factors affecting tire-pavement noise is presented, and different views on the impact of each individual factor are discussed. From the literature survey, it is also evident that there is a potential correlation between pavement’s material characteristics and tire-pavement noise. A comprehensive discussion about this correlation is presented in the paper. In addition, this paper discusses various mathematical models for predicting pavement noise, and their advantages and shortcomings.

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

Factors Affecting Sentence-in-Noise Recognition for Normal Hearing Listeners and Listeners with Hearing Loss.

Science.gov (United States)

Hwang, Jung Sun; Kim, Kyung Hyun; Lee, Jae Hee

2017-07-01

affecting sentence-in-noise recognition performance differed between NH and HI listeners. The working memory was the primary predictor of the sentence-in-noise scores for the NH individuals. In contrast, a combination of factors seemed to contributed to speech-in-noise understanding for the HI listeners. Given this, we must be careful not to generalize findings from the NH listeners to the HI individuals.

Heuristic optimization in penumbral image for high resolution reconstructed image

International Nuclear Information System (INIS)

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

2010-01-01

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

Spiral CT of the pancreas. The value of small field-of-view targeted reconstruction

International Nuclear Information System (INIS)

Nishiharu, T.; Yamashita, Y.; Ogata, I.; Sumi, S.; Mitsuzaki, K.; Takahashi, M.

1998-01-01

Purpose: To compare the value of a retrospective targeted high-resolution spiral CT to the standard reconstruction technique in the assessment of pancreatic diseases. Material and methods: Spiral CT pancreatic images of a standard-size reconstruction protocol were compared prospectively with those of a retrospective targeted high-spatial-resolution reconstruction protocol in 30 patients. Prior to clinical evaluation, a phantom study was performed to evaluate the spatial resolution and signal-to-noise ratio of both protocols. Results: The high-resolution protocol achieved a good signal-to-noise ratio with acceptable spatial resolution. Phantom studies revealed increased image noise (+17%) with an increase in spatial resolution (+100%). In patients studied with the high-resolution protocol, the increase in noise was not significant but there was a marked improvement in the definition of small details. Conclusion: Images obtained with a targeted high-spatial-resolution reconstruction protocol showed superior lesion definition and vascular opacification compared with those obtained with a standard-size reconstruction protocol. This technique may have potential in the evaluation of small pancreatic abnormalities. (orig.)

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

Characterization and simulation of noise in PET images reconstructed with OSEM: Development of a method for the generation of synthetic images.

Science.gov (United States)

Castro, P; Huerga, C; Chamorro, P; Garayoa, J; Roch, M; Pérez, L

2018-04-17

The goals of the study are to characterize imaging properties in 2D PET images reconstructed with the iterative algorithm ordered-subset expectation maximization (OSEM) and to propose a new method for the generation of synthetic images. The noise is analyzed in terms of its magnitude, spatial correlation, and spectral distribution through standard deviation, autocorrelation function, and noise power spectrum (NPS), respectively. Their variations with position and activity level are also analyzed. This noise analysis is based on phantom images acquired from 18 F uniform distributions. Experimental recovery coefficients of hot spheres in different backgrounds are employed to study the spatial resolution of the system through point spread function (PSF). The NPS and PSF functions provide the baseline for the proposed simulation method: convolution with PSF as kernel and noise addition from NPS. The noise spectral analysis shows that the main contribution is of random nature. It is also proven that attenuation correction does not alter noise texture but it modifies its magnitude. Finally, synthetic images of 2 phantoms, one of them an anatomical brain, are quantitatively compared with experimental images showing a good agreement in terms of pixel values and pixel correlations. Thus, the contrast to noise ratio for the biggest sphere in the NEMA IEC phantom is 10.7 for the synthetic image and 8.8 for the experimental image. The properties of the analyzed OSEM-PET images can be described by NPS and PSF functions. Synthetic images, even anatomical ones, are successfully generated by the proposed method based on the NPS and PSF. Copyright © 2018 Sociedad Española de Medicina Nuclear e Imagen Molecular. Publicado por Elsevier España, S.L.U. All rights reserved.

The use of adaptive statistical iterative reconstruction in pediatric head CT: a feasibility study.

Science.gov (United States)

Vorona, G A; Zuccoli, G; Sutcavage, T; Clayton, B L; Ceschin, R C; Panigrahy, A

2013-01-01

Iterative reconstruction techniques facilitate CT dose reduction; though to our knowledge, no group has explored using iterative reconstruction with pediatric head CT. Our purpose was to perform a feasibility study to assess the use of ASIR in a small group of pediatric patients undergoing head CT. An Alderson-Rando head phantom was scanned at decreasing 10% mA intervals relative to our standard protocol, and each study was then reconstructed at 10% ASIR intervals. An intracranial region of interest was consistently placed to estimate noise. Our ventriculoperitoneal shunt CT protocol was subsequently modified, and patients were scanned at 20% ASIR with approximately 20% mA reductions. ASIR studies were anonymously compared with older non-ASIR studies from the same patients by 2 attending pediatric neuroradiologists for diagnostic utility, sharpness, noise, and artifacts. The phantom study demonstrated similar noise at 100% mA/0% ASIR (3.9) and 80% mA/20% ASIR (3.7). Twelve pediatric patients were scanned at reduced dose at 20% ASIR. The average CTDI(vol) and DLP values of the 20% ASIR studies were 22.4 mGy and 338.4 mGy-cm, and for the non-ASIR studies, they were 28.8 mGy and 444.5 mGy-cm, representing statistically significant decreases in the CTDI(vol) (22.1%, P = .00007) and DLP (23.9%, P = .0005) values. There were no significant differences between the ASIR studies and non-ASIR studies with respect to diagnostic acceptability, sharpness, noise, or artifacts. Our findings suggest that 20% ASIR can provide approximately 22% dose reduction in pediatric head CT without affecting image quality.

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

Optimization of Rb-82 PET acquisition and reconstruction protocols for myocardial perfusion defect detection

Science.gov (United States)

Tang, Jing; Rahmim, Arman; Lautamäki, Riikka; Lodge, Martin A.; Bengel, Frank M.; Tsui, Benjamin M. W.

2009-05-01

The purpose of this study is to optimize the dynamic Rb-82 cardiac PET acquisition and reconstruction protocols for maximum myocardial perfusion defect detection using realistic simulation data and task-based evaluation. Time activity curves (TACs) of different organs under both rest and stress conditions were extracted from dynamic Rb-82 PET images of five normal patients. Combined SimSET-GATE Monte Carlo simulation was used to generate nearly noise-free cardiac PET data from a time series of 3D NCAT phantoms with organ activities modeling different pre-scan delay times (PDTs) and total acquisition times (TATs). Poisson noise was added to the nearly noise-free projections and the OS-EM algorithm was applied to generate noisy reconstructed images. The channelized Hotelling observer (CHO) with 32× 32 spatial templates corresponding to four octave-wide frequency channels was used to evaluate the images. The area under the ROC curve (AUC) was calculated from the CHO rating data as an index for image quality in terms of myocardial perfusion defect detection. The 0.5 cycle cm-1 Butterworth post-filtering on OS-EM (with 21 subsets) reconstructed images generates the highest AUC values while those from iteration numbers 1 to 4 do not show different AUC values. The optimized PDTs for both rest and stress conditions are found to be close to the cross points of the left ventricular chamber and myocardium TACs, which may promote an individualized PDT for patient data processing and image reconstruction. Shortening the TATs for <~3 min from the clinically employed acquisition time does not affect the myocardial perfusion defect detection significantly for both rest and stress studies.

Simulated annealing image reconstruction for positron emission tomography

International Nuclear Information System (INIS)

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

1994-01-01

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

Tomographic reconstruction with B-splines surfaces

International Nuclear Information System (INIS)

Oliveira, Eric F.; Dantas, Carlos C.; Melo, Silvio B.; Mota, Icaro V.; Lira, Mailson

2011-01-01

Algebraic reconstruction techniques when applied to a limited number of data usually suffer from noise caused by the process of correction or by inconsistencies in the data coming from the stochastic process of radioactive emission and oscillation equipment. The post - processing of the reconstructed image with the application of filters can be done to mitigate the presence of noise. In general these processes also attenuate the discontinuities present in edges that distinguish objects or artifacts, causing excessive blurring in the reconstructed image. This paper proposes a built-in noise reduction at the same time that it ensures adequate smoothness level in the reconstructed surface, representing the unknowns as linear combinations of elements of a piecewise polynomial basis, i.e. a B-splines basis. For that, the algebraic technique ART is modified to accommodate the first, second and third degree bases, ensuring C 0 , C 1 and C 2 smoothness levels, respectively. For comparisons, three methodologies are applied: ART, ART post-processed with regular B-splines filters (ART*) and the proposed method with the built-in B-splines filter (BsART). Simulations with input data produced from common mathematical phantoms were conducted. For the phantoms used the BsART method consistently presented the smallest errors, among the three methods. This study has shown the superiority of the change made to embed the filter in the ART when compared to the post-filtered ART. (author)

Does Acellular Dermal Matrix Thickness Affect Complication Rate in Tissue Expander Based Breast Reconstruction?

Directory of Open Access Journals (Sweden)

Jessica F. Rose

2016-01-01

Full Text Available Background. While the benefits of using acellular dermal matrices (ADMs in breast reconstruction are well described, their use has been associated with additional complications. The purpose of this study was to determine if ADM thickness affects complications in breast reconstruction. Methods. A retrospective chart review was performed including all tissue expander based breast reconstructions with AlloDerm (LifeCell, Branchburg, NJ over 4 years. We evaluated preoperative characteristics and assessed postoperative complications including seroma, hematoma, infection, skin necrosis, and need for reintervention. We reviewed ADM thickness and time to Jackson-Pratt (JP drain removal. Results. Fifty-five patients underwent 77 ADM-associated tissue expander based breast reconstructions, with average age of 48.1 years and average BMI of 25.9. Average ADM thickness was 1.21 mm. We found higher complication rates in the thick ADM group. Significant associations were found between smokers and skin necrosis (p<0.0001 and seroma and prolonged JP drainage (p=0.0004; radiated reconstructed breasts were more likely to suffer infections (p=0.0085, and elevated BMI is a significant predictor for increased infection rate (p=0.0037. Conclusion. We found a trend toward increased complication rates with thicker ADMs. In the future, larger prospective studies evaluating thickness may provide more information.

40 CFR Table 1 to Subpart Oooo of... - Emission Limits for New or Reconstructed and Existing Affected Sources in the Printing, Coating...

Science.gov (United States)

2010-07-01

... Reconstructed and Existing Affected Sources in the Printing, Coating and Dyeing of Fabrics and Other Textiles... SOURCE CATEGORIES National Emission Standards for Hazardous Air Pollutants: Printing, Coating, and Dyeing...—Emission Limits for New or Reconstructed and Existing Affected Sources in the Printing, Coating and Dyeing...

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

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

Evaluation of the spline reconstruction technique for PET

Energy Technology Data Exchange (ETDEWEB)

Kastis, George A., E-mail: gkastis@academyofathens.gr; Kyriakopoulou, Dimitra [Research Center of Mathematics, Academy of Athens, Athens 11527 (Greece); Gaitanis, Anastasios [Biomedical Research Foundation of the Academy of Athens (BRFAA), Athens 11527 (Greece); Fernández, Yolanda [Centre d’Imatge Molecular Experimental (CIME), CETIR-ERESA, Barcelona 08950 (Spain); Hutton, Brian F. [Institute of Nuclear Medicine, University College London, London NW1 2BU (United Kingdom); Fokas, Athanasios S. [Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB30WA (United Kingdom)

2014-04-15

Purpose: The spline reconstruction technique (SRT), based on the analytic formula for the inverse Radon transform, has been presented earlier in the literature. In this study, the authors present an improved formulation and numerical implementation of this algorithm and evaluate it in comparison to filtered backprojection (FBP). Methods: The SRT is based on the numerical evaluation of the Hilbert transform of the sinogram via an approximation in terms of “custom made” cubic splines. By restricting reconstruction only within object pixels and by utilizing certain mathematical symmetries, the authors achieve a reconstruction time comparable to that of FBP. The authors have implemented SRT in STIR and have evaluated this technique using simulated data from a clinical positron emission tomography (PET) system, as well as real data obtained from clinical and preclinical PET scanners. For the simulation studies, the authors have simulated sinograms of a point-source and three digital phantoms. Using these sinograms, the authors have created realizations of Poisson noise at five noise levels. In addition to visual comparisons of the reconstructed images, the authors have determined contrast and bias for different regions of the phantoms as a function of noise level. For the real-data studies, sinograms of an{sup 18}F-FDG injected mouse, a NEMA NU 4-2008 image quality phantom, and a Derenzo phantom have been acquired from a commercial PET system. The authors have determined: (a) coefficient of variations (COV) and contrast from the NEMA phantom, (b) contrast for the various sections of the Derenzo phantom, and (c) line profiles for the Derenzo phantom. Furthermore, the authors have acquired sinograms from a whole-body PET scan of an {sup 18}F-FDG injected cancer patient, using the GE Discovery ST PET/CT system. SRT and FBP reconstructions of the thorax have been visually evaluated. Results: The results indicate an improvement in FWHM and FWTM in both simulated and real

Image quality of CT angiography in young children with congenital heart disease: a comparison between the sinogram-affirmed iterative reconstruction (SAFIRE) and advanced modelled iterative reconstruction (ADMIRE) algorithms.

Science.gov (United States)

Nam, S B; Jeong, D W; Choo, K S; Nam, K J; Hwang, J-Y; Lee, J W; Kim, J Y; Lim, S J

2017-12-01

To compare the image quality of computed tomography angiography (CTA) reconstructed by sinogram-affirmed iterative reconstruction (SAFIRE) with that of advanced modelled iterative reconstruction (ADMIRE) in children with congenital heart disease (CHD). Thirty-one children (8.23±13.92 months) with CHD who underwent CTA were enrolled. Images were reconstructed using SAFIRE (strength 5) and ADMIRE (strength 5). Objective image qualities (attenuation, noise) were measured in the great vessels and heart chambers. Two radiologists independently calculated the contrast-to-noise ratio (CNR) by measuring the intensity and noise of the myocardial walls. Subjective noise, diagnostic confidence, and sharpness at the level prior to the first branch of the main pulmonary artery were also graded by the two radiologists independently. The objective image noise of ADMIRE was significantly lower than that of SAFIRE in the right atrium, right ventricle, and myocardial wall (p0.05). The mean CNR values were 21.56±10.80 for ADMIRE and 18.21±6.98 for SAFIRE, which were significantly different (p0.05). CTA using ADMIRE was superior to SAFIRE when comparing the objective and subjective image quality in children with CHD. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.

A Kalman filter technique applied for medical image reconstruction

International Nuclear Information System (INIS)

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

2011-01-01

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

Simulated annealing image reconstruction for positron emission tomography

Energy Technology Data Exchange (ETDEWEB)

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

1994-12-31

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

Image reconstruction by domain-transform manifold learning

Science.gov (United States)

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

2018-03-01

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

How far can the radiation dose be lowered in head CT with iterative reconstruction? Analysis of imaging quality and diagnostic accuracy

Energy Technology Data Exchange (ETDEWEB)

Wu, Tung-Hsin; Sun, Jing-Yi [National Yang-Ming University, Department of Biomedical Imaging and Radiological Sciences, Taipei (China); Hung, Sheng-Che; Lin, Chung-Jung; Chiu, Chen Fen; Liu, Min-Jsuan; Teng, Michael Mu Huo; Guo, Wan-Yuo; Chang, Cheng-Yen [Taipei Veterans General Hospital, Department of Radiology, Taipei (China); National Yang-Ming University, School of Medicine, Taipei (China); Lin, Chung-Hsien [National Taiwan University, Graduate Institute of Epidemiology and Preventive Medicine, Taipei (China)

2013-09-15

To evaluate the imaging quality of head CT at lowered radiation dose by combining filtered back projection (FBP) and iterative reconstruction (IR) algorithms. Experimental group A (n = 66) underwent CT with 43 % tube current reduction, and group B (n = 58) received an equivalent reduced dose by lowering the tube voltage. An age- and sex-matched control group (n = 72) receiving the conventional radiation dose was retrospectively collected. Imaging for the control group was reconstructed by FBP only, while images for groups A and B were reconstructed by FBP and IR. The signal-to-noise ratios (SNRs), contrast-to-noise ratios (CNRs), sharpness, number of infarcts and severity of subcortical arteriosclerotic encephalopathy (SAE) were compared to assess imaging quality and diagnostic accuracy. There were no significant differences in SNRs and CNRs between group A and the control group. There were significantly decreased SNRs and increased CNRs in group B. Image sharpness decreased in both groups. Correlations between detected infarcts and severity of SAE across FBP and IR were high (r = 0.73-0.93). Head diameter was the only significant factor inversely correlated with infratentorial imaging quality. Head CT with 43 % reduced tube current reconstructed by IR provides diagnostic imaging quality for outpatient management. (orig.)

An approach to reconstruction of a natural crack using signals of eddy current testing. 1. Reconstruction of an idealized natural crack

International Nuclear Information System (INIS)

Chen, Zhenmao

1998-12-01

In this paper, an approach to the reconstruction of an idealized natural crack of non-vanishing conductivity is proposed with use of signals of eddy current testing. Two numerical models are introduced at first for modeling a Stress Corrosion Crack (SCC) in order it possibly to be represented by a set of crack parameters. A method for rapid prediction of the eddy current testing signals arisen from these idealized cracks is given then by extending a knowledge based fast forward solver developed by authors to the case of a non-vanishing conductivity. On the other hand, the inverse algorithm of conjugate gradient method is improved to reconstruct the crack parameters and is implemented with the pick-up signals and gradients calculated by using the rapid forward solver. Several examples are presented finally for validating the proposed strategy. The results verified that both of the models can give reasonable reconstruction results in case of a low noise level. The model concerning the touch of crack surfaces with a conducting band region surrounded by the crack edge, however, is proved more efficient that the model using a conductivity distribution from the point of view of both reconstruction speed and accuracy. (author)

Evaluation of penalized likelihood estimation reconstruction on a digital time-of-flight PET/CT scanner for 18F-FDG whole-body examinations.

Science.gov (United States)

Lindström, Elin; Sundin, Anders; Trampal, Carlos; Lindsjö, Lars; Ilan, Ezgi; Danfors, Torsten; Antoni, Gunnar; Sörensen, Jens; Lubberink, Mark

2018-02-15

Resolution and quantitative accuracy of positron emission tomography (PET) are highly influenced by the reconstruction method. Penalized likelihood estimation algorithms allow for fully convergent iterative reconstruction, generating a higher image contrast while limiting noise compared to ordered subsets expectation maximization (OSEM). In this study, block-sequential regularized expectation maximization (BSREM) was compared to time-of-flight OSEM (TOF-OSEM). Various strengths of noise penalization factor β were tested along with scan durations and transaxial field of views (FOVs) with the aim to evaluate the performance and clinical use of BSREM for 18 F-FDG-PET-computed tomography (CT), both in quantitative terms and in a qualitative visual evaluation. Methods: Eleven clinical whole-body 18 F-FDG-PET/CT examinations acquired on a digital TOF PET/CT scanner were included. The data were reconstructed using BSREM with point spread function (PSF) recovery and β 133, 267, 400 and 533, and TOF-OSEM with PSF, for various acquisition times/bed position (bp) and FOVs. Noise, signal-to-noise ratio (SNR), signal-to-background ratio (SBR), and standardized uptake values (SUVs) were analysed. A blinded visual image quality evaluation, rating several aspects, performed by two nuclear medicine physicians complemented the analysis. Results: The lowest levels of noise were reached with the highest β resulting in the highest SNR, which in turn resulted in the lowest SBR. Noise equivalence to TOF-OSEM was found with β 400 but produced a significant increase of SUV max (11%), SNR (22%) and SBR (12%) compared to TOF-OSEM. BSREM with β 533 at decreased acquisition (2 min/bp) was comparable to TOF-OSEM at full acquisition duration (3 min/bp). Reconstructed FOV had an impact on BSREM outcome measures, SNR increased while SBR decreased when shifting FOV from 70 to 50 cm. The visual image quality evaluation resulted in similar scores for reconstructions although β 400 obtained the

Noise and dose modeling for pediatric CT optimization: preliminary results

International Nuclear Information System (INIS)

Miller Clemente, Rafael A.; Perez Diaz, Marlen; Mora Reyes, Yudel; Rodriguez Garlobo, Maikel; Castillo Salazar, Rafael

2008-01-01

Full text: A Multiple Linear Regression Model was developed to predict noise and dose in computed tomography pediatric imaging for head and abdominal examinations. Relative values of Noise and Volumetric Computed Tomography Dose Index was used to estimate de model respectively. 54 images of physical phantoms were performed. Independent variables considered included: phantom diameter, tube current and kilovolts, x ray beam collimation, reconstruction diameter and equipment's post processing filters. Predicted values show good agreement with measurements, which were better in noise model (R 2 adjusted =0.953) than the dose model (R 2 adjusted =0.744). Tube current, object diameter, beam collimation and reconstruction filter were identified as the most influencing factors in models. (author)

Adaptive Statistical Iterative Reconstruction-V Versus Adaptive Statistical Iterative Reconstruction: Impact on Dose Reduction and Image Quality in Body Computed Tomography.

Science.gov (United States)

Gatti, Marco; Marchisio, Filippo; Fronda, Marco; Rampado, Osvaldo; Faletti, Riccardo; Bergamasco, Laura; Ropolo, Roberto; Fonio, Paolo

The aim of this study was to evaluate the impact on dose reduction and image quality of the new iterative reconstruction technique: adaptive statistical iterative reconstruction (ASIR-V). Fifty consecutive oncologic patients acted as case controls undergoing during their follow-up a computed tomography scan both with ASIR and ASIR-V. Each study was analyzed in a double-blinded fashion by 2 radiologists. Both quantitative and qualitative analyses of image quality were conducted. Computed tomography scanner radiation output was 38% (29%-45%) lower (P ASIR-V examinations than for the ASIR ones. The quantitative image noise was significantly lower (P ASIR-V. Adaptive statistical iterative reconstruction-V had a higher performance for the subjective image noise (P = 0.01 for 5 mm and P = 0.009 for 1.25 mm), the other parameters (image sharpness, diagnostic acceptability, and overall image quality) being similar (P > 0.05). Adaptive statistical iterative reconstruction-V is a new iterative reconstruction technique that has the potential to provide image quality equal to or greater than ASIR, with a dose reduction around 40%.

Do Local Elites Capture Natural Disaster Reconstruction Funds?

OpenAIRE

Yoshito Takasaki

2009-01-01

This paper examines the allocation of natural disaster reconstruction funds among cyclone victims in rural Fiji. During post-emergency periods, when good information about cyclone damage is available, do local elites, a powerful minority, capture housing construction materials? With effective targeting in both receipt and the amount received, local elites do not capture larger benefits. More severely affected victims are not early recipients, though, because the supply of reconstruction funds...

Single-shot speckle reduction in numerical reconstruction of digitally recorded holograms.

Science.gov (United States)

Hincapie, Diego; Herrera-Ramírez, Jorge; Garcia-Sucerquia, Jorge

2015-04-15

A single-shot method to reduce the speckle noise in the numerical reconstructions of electronically recorded holograms is presented. A recorded hologram with the dimensions N×M is split into S=T×T sub-holograms. The uncorrelated superposition of the individually reconstructed sub-holograms leads to an image with the speckle noise reduced proportionally to the 1/S law. The experimental results are presented to support the proposed methodology.

Detecting impact signal in mechanical fault diagnosis under chaotic and Gaussian background noise

Science.gov (United States)

Hu, Jinfeng; Duan, Jie; Chen, Zhuo; Li, Huiyong; Xie, Julan; Chen, Hanwen

2018-01-01

In actual fault diagnosis, useful information is often submerged in heavy noise, and the feature information is difficult to extract. Traditional methods, such like stochastic resonance (SR), which using noise to enhance weak signals instead of suppressing noise, failed in chaotic background. Neural network, which use reference sequence to estimate and reconstruct the background noise, failed in white Gaussian noise. To solve these problems, a novel weak signal detection method aimed at the problem of detecting impact signal buried under heavy chaotic and Gaussian background noise is proposed. First, the proposed method obtains the virtual reference sequence by constructing the Hankel data matrix. Then an M-order optimal FIR filter is designed, which can minimize the output power of background noise and pass the weak periodic signal undistorted. Finally, detection and reconstruction of the weak periodic signal are achieved from the output SBNR (signal to background noise ratio). The simulation shows, compared with the stochastic resonance (SR) method, the proposed method can detect the weak periodic signal in chaotic noise background while stochastic resonance (SR) method cannot. Compared with the neural network method, (a) the proposed method does not need a reference sequence while neural network method needs one; (b) the proposed method can detect the weak periodic signal in white Gaussian noise background while the neural network method fails, in chaotic noise background, the proposed method can detect the weak periodic signal under a lower SBNR (about 8-17 dB lower) than the neural network method; (c) the proposed method can reconstruct the weak periodic signal precisely.

Impulse noise estimation and removal for OFDM systems

KAUST Repository

Al-Naffouri, Tareq Y.

2014-03-01

Orthogonal Frequency Division Multiplexing (OFDM) is a modulation scheme that is widely used in wired and wireless communication systems. While OFDM is ideally suited to deal with frequency selective channels and AWGN, its performance may be dramatically impacted by the presence of impulse noise. In fact, very strong noise impulses in the time domain might result in the erasure of whole OFDM blocks of symbols at the receiver. Impulse noise can be mitigated by considering it as a sparse signal in time, and using recently developed algorithms for sparse signal reconstruction. We propose an algorithm that utilizes the guard band subcarriers for the impulse noise estimation and cancellation. Instead of relying on ℓ1 minimization as done in some popular general-purpose compressive sensing schemes, the proposed method jointly exploits the specific structure of this problem and the available a priori information for sparse signal recovery. The computational complexity of the proposed algorithm is very competitive with respect to sparse signal reconstruction schemes based on ℓ1 minimization. The proposed method is compared with respect to other state-of-the-art methods in terms of achievable rates for an OFDM system with impulse noise and AWGN. © 2014 IEEE.

Impulse noise estimation and removal for OFDM systems

KAUST Repository

Al-Naffouri, Tareq Y.; Quadeer, Ahmed Abdul; Caire, Giuseppe

2014-01-01

Orthogonal Frequency Division Multiplexing (OFDM) is a modulation scheme that is widely used in wired and wireless communication systems. While OFDM is ideally suited to deal with frequency selective channels and AWGN, its performance may be dramatically impacted by the presence of impulse noise. In fact, very strong noise impulses in the time domain might result in the erasure of whole OFDM blocks of symbols at the receiver. Impulse noise can be mitigated by considering it as a sparse signal in time, and using recently developed algorithms for sparse signal reconstruction. We propose an algorithm that utilizes the guard band subcarriers for the impulse noise estimation and cancellation. Instead of relying on ℓ1 minimization as done in some popular general-purpose compressive sensing schemes, the proposed method jointly exploits the specific structure of this problem and the available a priori information for sparse signal recovery. The computational complexity of the proposed algorithm is very competitive with respect to sparse signal reconstruction schemes based on ℓ1 minimization. The proposed method is compared with respect to other state-of-the-art methods in terms of achievable rates for an OFDM system with impulse noise and AWGN. © 2014 IEEE.

A temporal and spatial analysis of anthropogenic noise sources affecting SNMR

Science.gov (United States)

Dalgaard, E.; Christiansen, P.; Larsen, J. J.; Auken, E.

2014-11-01

One of the biggest challenges when using the surface nuclear magnetic resonance (SNMR) method in urban areas is a relatively low signal level compared to a high level of background noise. To understand the temporal and spatial behavior of anthropogenic noise sources like powerlines and electric fences, we have developed a multichannel instrument, noiseCollector (nC), which measures the full noise spectrum up to 10 kHz. Combined with advanced signal processing we can interpret the noise as seen by a SNMR instrument and also obtain insight into the more fundamental behavior of the noise. To obtain a specified acceptable noise level for a SNMR sounding the stack size can be determined by quantifying the different noise sources. Two common noise sources, electromagnetic fields stemming from powerlines and fences are analyzed and show a 1/r2 dependency in agreement with theoretical relations. A typical noise map, obtained with the nC instrument prior to a SNMR field campaign, clearly shows the location of noise sources, and thus we can efficiently determine the optimal location for the SNMR sounding from a noise perspective.

Active noise control in a duct to cancel broadband noise

Science.gov (United States)

Chen, Kuan-Chun; Chang, Cheng-Yuan; Kuo, Sen M.

2017-09-01

The paper presents cancelling duct noises by using the active noise control (ANC) techniques. We use the single channel feed forward algorithm with feedback neutralization to realize ANC. Several kinds of ducts noises including tonal noises, sweep tonal signals, and white noise had investigated. Experimental results show that the proposed ANC system can cancel these noises in a PVC duct very well. The noise reduction of white noise can be up to 20 dB.

Amplitude-based data selection for optimal retrospective reconstruction in micro-SPECT

Science.gov (United States)

Breuilly, M.; Malandain, G.; Guglielmi, J.; Marsault, R.; Pourcher, T.; Franken, P. R.; Darcourt, J.

2013-04-01

Respiratory motion can blur the tomographic reconstruction of positron emission tomography or single-photon emission computed tomography (SPECT) images, which subsequently impair quantitative measurements, e.g. in the upper abdomen area. Respiratory signal phase-based gated reconstruction addresses this problem, but deteriorates the signal-to-noise ratio (SNR) and other intensity-based quality measures. This paper proposes a 3D reconstruction method dedicated to micro-SPECT imaging of mice. From a 4D acquisition, the phase images exhibiting motion are identified and the associated list-mode data are discarded, which enables the reconstruction of a 3D image without respiratory artefacts. The proposed method allows a motion-free reconstruction exhibiting both satisfactory count statistics and accuracy of measures. With respect to standard 3D reconstruction (non-gated 3D reconstruction) without breathing motion correction, an increase of 14.6% of the mean standardized uptake value has been observed, while, with respect to a gated 4D reconstruction, up to 60% less noise and an increase of up to 124% of the SNR have been demonstrated.

A neural network image reconstruction technique for electrical impedance tomography

International Nuclear Information System (INIS)

Adler, A.; Guardo, R.

1994-01-01

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

Full dose reduction potential of statistical iterative reconstruction for head CT protocols in a predominantly pediatric population

Science.gov (United States)

Mirro, Amy E.; Brady, Samuel L.; Kaufman, Robert. A.

2016-01-01

Purpose To implement the maximum level of statistical iterative reconstruction that can be used to establish dose-reduced head CT protocols in a primarily pediatric population. Methods Select head examinations (brain, orbits, sinus, maxilla and temporal bones) were investigated. Dose-reduced head protocols using an adaptive statistical iterative reconstruction (ASiR) were compared for image quality with the original filtered back projection (FBP) reconstructed protocols in phantom using the following metrics: image noise frequency (change in perceived appearance of noise texture), image noise magnitude, contrast-to-noise ratio (CNR), and spatial resolution. Dose reduction estimates were based on computed tomography dose index (CTDIvol) values. Patient CTDIvol and image noise magnitude were assessed in 737 pre and post dose reduced examinations. Results Image noise texture was acceptable up to 60% ASiR for Soft reconstruction kernel (at both 100 and 120 kVp), and up to 40% ASiR for Standard reconstruction kernel. Implementation of 40% and 60% ASiR led to an average reduction in CTDIvol of 43% for brain, 41% for orbits, 30% maxilla, 43% for sinus, and 42% for temporal bone protocols for patients between 1 month and 26 years, while maintaining an average noise magnitude difference of 0.1% (range: −3% to 5%), improving CNR of low contrast soft tissue targets, and improving spatial resolution of high contrast bony anatomy, as compared to FBP. Conclusion The methodology in this study demonstrates a methodology for maximizing patient dose reduction and maintaining image quality using statistical iterative reconstruction for a primarily pediatric population undergoing head CT examination. PMID:27056425

X-ray dose reduction in abdominal computed tomography using advanced iterative reconstruction algorithms.

Directory of Open Access Journals (Sweden)

Peigang Ning

Full Text Available OBJECTIVE: This work aims to explore the effects of adaptive statistical iterative reconstruction (ASiR and model-based iterative reconstruction (MBIR algorithms in reducing computed tomography (CT radiation dosages in abdominal imaging. METHODS: CT scans on a standard male phantom were performed at different tube currents. Images at the different tube currents were reconstructed with the filtered back-projection (FBP, 50% ASiR and MBIR algorithms and compared. The CT value, image noise and contrast-to-noise ratios (CNRs of the reconstructed abdominal images were measured. Volumetric CT dose indexes (CTDIvol were recorded. RESULTS: At different tube currents, 50% ASiR and MBIR significantly reduced image noise and increased the CNR when compared with FBP. The minimal tube current values required by FBP, 50% ASiR, and MBIR to achieve acceptable image quality using this phantom were 200, 140, and 80 mA, respectively. At the identical image quality, 50% ASiR and MBIR reduced the radiation dose by 35.9% and 59.9% respectively when compared with FBP. CONCLUSIONS: Advanced iterative reconstruction techniques are able to reduce image noise and increase image CNRs. Compared with FBP, 50% ASiR and MBIR reduced radiation doses by 35.9% and 59.9%, respectively.

Random resampling masks: a non-Bayesian one-shot strategy for noise reduction in digital holography.

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Bianco, V; Paturzo, M; Memmolo, P; Finizio, A; Ferraro, P; Javidi, B

2013-03-01

Holographic imaging may become severely degraded by a mixture of speckle and incoherent additive noise. Bayesian approaches reduce the incoherent noise, but prior information is needed on the noise statistics. With no prior knowledge, one-shot reduction of noise is a highly desirable goal, as the recording process is simplified and made faster. Indeed, neither multiple acquisitions nor a complex setup are needed. So far, this result has been achieved at the cost of a deterministic resolution loss. Here we propose a fast non-Bayesian denoising method that avoids this trade-off by means of a numerical synthesis of a moving diffuser. In this way, only one single hologram is required as multiple uncorrelated reconstructions are provided by random complementary resampling masks. Experiments show a significant incoherent noise reduction, close to the theoretical improvement bound, resulting in image-contrast improvement. At the same time, we preserve the resolution of the unprocessed image.

Motion tolerant iterative reconstruction algorithm for cone-beam helical CT imaging

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Takahashi, Hisashi; Goto, Taiga; Hirokawa, Koichi; Miyazaki, Osamu [Hitachi Medical Corporation, Chiba-ken (Japan). CT System Div.

2011-07-01

We have developed a new advanced iterative reconstruction algorithm for cone-beam helical CT. The features of this algorithm are: (a) it uses separable paraboloidal surrogate (SPS) technique as a foundation for reconstruction to reduce noise and cone-beam artifact, (b) it uses a view weight in the back-projection process to reduce motion artifact. To confirm the improvement of our proposed algorithm over other existing algorithm, such as Feldkamp-Davis-Kress (FDK) or SPS algorithm, we compared the motion artifact reduction, image noise reduction (standard deviation of CT number), and cone-beam artifact reduction on simulated and clinical data set. Our results demonstrate that the proposed algorithm dramatically reduces motion artifacts compared with the SPS algorithm, and decreases image noise compared with the FDK algorithm. In addition, the proposed algorithm potentially improves time resolution of iterative reconstruction. (orig.)

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

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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

Theoretical Study of Penalized-Likelihood Image Reconstruction for Region of Interest Quantification

International Nuclear Information System (INIS)

Qi, Jinyi; Huesman, Ronald H.

2006-01-01

Region of interest (ROI) quantification is an important task in emission tomography (e.g., positron emission tomography and single photon emission computed tomography). It is essential for exploring clinical factors such as tumor activity, growth rate, and the efficacy of therapeutic interventions. Statistical image reconstruction methods based on the penalized maximum-likelihood (PML) or maximum a posteriori principle have been developed for emission tomography to deal with the low signal-to-noise ratio of the emission data. Similar to the filter cut-off frequency in the filtered backprojection method, the regularization parameter in PML reconstruction controls the resolution and noise tradeoff and, hence, affects ROI quantification. In this paper, we theoretically analyze the performance of ROI quantification in PML reconstructions. Building on previous work, we derive simplified theoretical expressions for the bias, variance, and ensemble mean-squared-error (EMSE) of the estimated total activity in an ROI that is surrounded by a uniform background. When the mean and covariance matrix of the activity inside the ROI are known, the theoretical expressions are readily computable and allow for fast evaluation of image quality for ROI quantification with different regularization parameters. The optimum regularization parameter can then be selected to minimize the EMSE. Computer simulations are conducted for small ROIs with variable uniform uptake. The results show that the theoretical predictions match the Monte Carlo results reasonably well

Weak lensing galaxy cluster field reconstruction

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Jullo, E.; Pires, S.; Jauzac, M.; Kneib, J.-P.

2014-02-01

In this paper, we compare three methods to reconstruct galaxy cluster density fields with weak lensing data. The first method called FLens integrates an inpainting concept to invert the shear field with possible gaps, and a multi-scale entropy denoising procedure to remove the noise contained in the final reconstruction, that arises mostly from the random intrinsic shape of the galaxies. The second and third methods are based on a model of the density field made of a multi-scale grid of radial basis functions. In one case, the model parameters are computed with a linear inversion involving a singular value decomposition (SVD). In the other case, the model parameters are estimated using a Bayesian Monte Carlo Markov Chain optimization implemented in the lensing software LENSTOOL. Methods are compared on simulated data with varying galaxy density fields. We pay particular attention to the errors estimated with resampling. We find the multi-scale grid model optimized with Monte Carlo Markov Chain to provide the best results, but at high computational cost, especially when considering resampling. The SVD method is much faster but yields noisy maps, although this can be mitigated with resampling. The FLens method is a good compromise with fast computation, high signal-to-noise ratio reconstruction, but lower resolution maps. All three methods are applied to the MACS J0717+3745 galaxy cluster field, and reveal the filamentary structure discovered in Jauzac et al. We conclude that sensitive priors can help to get high signal-to-noise ratio, and unbiased reconstructions.

Blind spectrum reconstruction algorithm with L0-sparse representation

International Nuclear Information System (INIS)

Liu, Hai; Zhang, Zhaoli; Liu, Sanyan; Shu, Jiangbo; Liu, Tingting; Zhang, Tianxu

2015-01-01

Raman spectrum often suffers from band overlap and Poisson noise. This paper presents a new blind Poissonian Raman spectrum reconstruction method, which incorporates the L 0 -sparse prior together with the total variation constraint into the maximum a posteriori framework. Furthermore, the greedy analysis pursuit algorithm is adopted to solve the L 0 -based minimization problem. Simulated and real spectrum experimental results show that the proposed method can effectively preserve spectral structure and suppress noise. The reconstructed Raman spectra are easily used for interpreting unknown chemical mixtures. (paper)

Comparison of pure and hybrid iterative reconstruction techniques with conventional filtered back projection: Image quality assessment in the cervicothoracic region

Energy Technology Data Exchange (ETDEWEB)

Katsura, Masaki, E-mail: mkatsura-tky@umin.ac.jp [Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 (Japan); Sato, Jiro; Akahane, Masaaki; Matsuda, Izuru; Ishida, Masanori; Yasaka, Koichiro; Kunimatsu, Akira; Ohtomo, Kuni [Department of Radiology, Graduate School of Medicine, The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8655 (Japan)

2013-02-15

Objectives: To evaluate the impact on image quality of three different image reconstruction techniques in the cervicothoracic region: model-based iterative reconstruction (MBIR), adaptive statistical iterative reconstruction (ASIR), and filtered back projection (FBP). Methods: Forty-four patients underwent unenhanced standard-of-care clinical computed tomography (CT) examinations which included the cervicothoracic region with a 64-row multidetector CT scanner. Images were reconstructed with FBP, 50% ASIR-FBP blending (ASIR50), and MBIR. Two radiologists assessed the cervicothoracic region in a blinded manner for streak artifacts, pixilated blotchy appearances, critical reproduction of visually sharp anatomical structures (thyroid gland, common carotid artery, and esophagus), and overall diagnostic acceptability. Objective image noise was measured in the internal jugular vein. Data were analyzed using the sign test and pair-wise Student's t-test. Results: MBIR images had significant lower quantitative image noise (8.88 ± 1.32) compared to ASIR images (18.63 ± 4.19, P < 0.01) and FBP images (26.52 ± 5.8, P < 0.01). Significant improvements in streak artifacts of the cervicothoracic region were observed with the use of MBIR (P < 0.001 each for MBIR vs. the other two image data sets for both readers), while no significant difference was observed between ASIR and FBP (P > 0.9 for ASIR vs. FBP for both readers). MBIR images were all diagnostically acceptable. Unique features of MBIR images included pixilated blotchy appearances, which did not adversely affect diagnostic acceptability. Conclusions: MBIR significantly improves image noise and streak artifacts of the cervicothoracic region over ASIR and FBP. MBIR is expected to enhance the value of CT examinations for areas where image noise and streak artifacts are problematic.

A calibrated iterative reconstruction for quantitative photoacoustic tomography using multi-angle light-sheet illuminations

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Wang, Yihan; Lu, Tong; Zhang, Songhe; Song, Shaoze; Wang, Bingyuan; Li, Jiao; Zhao, Huijuan; Gao, Feng

2018-02-01

Quantitative photoacoustic tomography (q-PAT) is a nontrivial technique can be used to reconstruct the absorption image with a high spatial resolution. Several attempts have been investigated by setting point sources or fixed-angle illuminations. However, in practical applications, these schemes normally suffer from low signal-to-noise ratio (SNR) or poor quantification especially for large-size domains, due to the limitation of the ANSI-safety incidence and incompleteness in the data acquisition. We herein present a q-PAT implementation that uses multi-angle light-sheet illuminations and a calibrated iterative multi-angle reconstruction. The approach can acquire more complete information on the intrinsic absorption and SNR-boosted photoacoustic signals at selected planes from the multi-angle wide-field excitations of light-sheet. Therefore, the sliced absorption maps over whole body can be recovered in a measurementflexible, noise-robust and computation-economic way. The proposed approach is validated by the phantom experiment, exhibiting promising performances in image fidelity and quantitative accuracy.

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

Directory of Open Access Journals (Sweden)

Zhang Liangpei

2007-01-01

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

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

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

Analysis of the Moberg et al. (2005) hemispheric temperature reconstruction

Energy Technology Data Exchange (ETDEWEB)

Moberg, Anders [Stockholm University, Department of Physical Geography and Quaternary Geology, Stockholm (Sweden); Mohammad, Rezwan [Stockholm University, Department of Geology and Geochemistry, Stockholm (Sweden); Mauritsen, Thorsten [Stockholm University, Department of Meteorology, Stockholm (Sweden)

2008-12-15

The Moberg et al. (Nature 433(7026):613-617, 2005. doi:10.1038/nature03265; M05) reconstruction of northern hemisphere temperature variations from proxy data has been criticised; the M05 method may artificially inflate low-frequency variance relative to reality. We test this assertion by undertaking several pseudoproxy experiments in three climate model simulations - one control run and two forced simulations that include several time-varying radiative forcings. The pseudoproxy series are designed to have the same variance spectra as the real M05 proxies, primarily to mimic the low-resolution character of several series. A simple composite-plus-scale (CPS) method is also analysed. In the CPS case all input data behave like annually resolved proxies. The spectral domain performance of both M05 and CPS is found to be dependent on the noise type and noise level in pseudoproxies, on the variance spectrum of the climate model simulation, and on the degree of data smoothing. CPS performs better than M05 in most investigated cases with the control run, but leads to deflated low-frequency variance in some cases. With M05, low-frequency variance tend to be inflated for the control run but not for one of the forced runs and only very slightly with the other forced simulation. Hence, the M05 approach does not routinely inflate low-frequency variance. In our experiment, the M05 approach performs better in the spectral domain than CPS when applied to forced climate model simulations. The results underscore the importance of evaluating the variance spectrum of climate reconstructions. (orig.)

Operational modeling of dose and noise for computed tomography in a pediatric hospital

International Nuclear Information System (INIS)

Miller Clemente, Rafael A.; Perez Diaz, Marlen; Mora Reyes, Yudel; Rodriguez Garlobo, Maikel; Castillo Salazar, Rafael

2008-01-01

Noise becomes a critical factor in Computed Tomography (CT) because most detailed applications on soft tissue show a low contrast nature. Noise establishes an inferior limit to the contrast detectable by the observer. Various pixel noise models had been devised taking into account operational parameters on Single and Multi Detector Slice CT. The aim of this work was to obtain a predictive operational model for image noise addressed to pediatric protocols, taking into account scanning factors with a Single Slice CT unit dedicated to pediatric applications. A multiple linear regression model is proposed to predict noise in images of uniform phantoms equivalent to head and abdomen. A model for reported volumetric Computed Tomography Dose Index (CTDI VOL ) was obtained too for tradeoffs analysis approaching optimization purposes in pediatric applications. Eight independent variables were considered: phantom diameter, reconstruction mode, tube current, tube kVp, collimation, Field of View (FOV), reconstruction filter, and post processing filter. Results show good agreement with measurements, with adjusted coefficients of multiple determination of 0.936 and 0.744 for noise and CTDI VOL models respectively. Tube current, object diameter, collimation and reconstruction filters were the most influencing variables. The model application contributes to identify each factor's influence enhancing the operational possibilities approaching optimization of noise and dose tradeoffs. Acceptable noise levels and optimization strategies can be devised from models obtained towards lower tube current values combined with greater slice thickness and kVp taking into account the doses to pediatric patients. (author)

A clinical perspective of accelerated statistical reconstruction

International Nuclear Information System (INIS)

Hutton, B.F.; Hudson, H.M.; Beekman, F.J.

1997-01-01

Although the potential benefits of maximum likelihood reconstruction have been recognised for many years, the technique has only recently found widespread popularity in clinical practice. Factors which have contributed to the wider acceptance include improved models for the emission process, better understanding of the properties of the algorithm and, not least, the practicality of application with the development of acceleration schemes and the improved speed of computers. The objective in this article is to present a framework for applying maximum likelihood reconstruction for a wide range of clinically based problems. The article draws particularly on the experience of the three authors in applying an acceleration scheme involving use of ordered subsets to a range of applications. The potential advantages of statistical reconstruction techniques include: (a) the ability to better model the emission and detection process, in order to make the reconstruction converge to a quantitative image, (b) the inclusion of a statistical noise model which results in better noise characteristics, and (c) the possibility to incorporate prior knowledge about the distribution being imaged. The great flexibility in adapting the reconstruction for a specific model results in these techniques having wide applicability to problems in clinical nuclear medicine. (orig.). With 8 figs., 1 tab

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.

Robust Adaptive Beamforming with Sensor Position Errors Using Weighted Subspace Fitting-Based Covariance Matrix Reconstruction.

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Chen, Peng; Yang, Yixin; Wang, Yong; Ma, Yuanliang

2018-05-08

When sensor position errors exist, the performance of recently proposed interference-plus-noise covariance matrix (INCM)-based adaptive beamformers may be severely degraded. In this paper, we propose a weighted subspace fitting-based INCM reconstruction algorithm to overcome sensor displacement for linear arrays. By estimating the rough signal directions, we construct a novel possible mismatched steering vector (SV) set. We analyze the proximity of the signal subspace from the sample covariance matrix (SCM) and the space spanned by the possible mismatched SV set. After solving an iterative optimization problem, we reconstruct the INCM using the estimated sensor position errors. Then we estimate the SV of the desired signal by solving an optimization problem with the reconstructed INCM. The main advantage of the proposed algorithm is its robustness against SV mismatches dominated by unknown sensor position errors. Numerical examples show that even if the position errors are up to half of the assumed sensor spacing, the output signal-to-interference-plus-noise ratio is only reduced by 4 dB. Beam patterns plotted using experiment data show that the interference suppression capability of the proposed beamformer outperforms other tested beamformers.

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.

Three-dimensional total variation norm for SPECT reconstruction

International Nuclear Information System (INIS)

Persson, Mikael; Bone, Dianna; Elmqvist, H.

2001-01-01

The total variation (TV) norm has been described in literature as a method for reducing noise in two-dimensional (2D) images. At the same time, the TV-norm is very good at recovering edges in images, without introducing ringing or edge artefacts. It has also been proposed as a 2D regularisation function in Bayesian reconstruction, implemented in an expectation maximisation (EM) algorithm, and called TV-EM. The TV-EM was developed for 2D SPECT imaging, and the algorithm is capable of smoothing noise while maintaining edges without introducing artefacts. We have extended the TV-norm to take into account the third spatial dimension, and developed an iterative EM algorithm based on the three-dimensional (3D) TV-norm, which we call TV3D-EM. This takes into account the correlation between transaxial sections in SPECT, due to system resolution. We have compared the 2D and 3D algorithms using reconstructed images from simulated projection data. Phantoms used were a homogeneous sphere, and a 3D head phantom based on the Shepp-Logan phantom. The TV3D-EM algorithm yielded somewhat lower noise levels than TV-EM. The noise in the TV3D-EM had similar correlation in transaxial and longitudinal sections, which was not the case for TV-EM, or any 2D reconstruction method. In particular, longitudinal sections from TV3D-EM were perceived as less noisy when compared to TV-EM. The use of 3D reconstruction should also be advantageous if compensation for distant dependent collimator blurring is incorporated in the iterative algorithm

Signal-to-noise contribution of principal component loads in reconstructed near-infrared Raman tissue spectra.

Science.gov (United States)

Grimbergen, M C M; van Swol, C F P; Kendall, C; Verdaasdonk, R M; Stone, N; Bosch, J L H R

2010-01-01

The overall quality of Raman spectra in the near-infrared region, where biological samples are often studied, has benefited from various improvements to optical instrumentation over the past decade. However, obtaining ample spectral quality for analysis is still challenging due to device requirements and short integration times required for (in vivo) clinical applications of Raman spectroscopy. Multivariate analytical methods, such as principal component analysis (PCA) and linear discriminant analysis (LDA), are routinely applied to Raman spectral datasets to develop classification models. Data compression is necessary prior to discriminant analysis to prevent or decrease the degree of over-fitting. The logical threshold for the selection of principal components (PCs) to be used in discriminant analysis is likely to be at a point before the PCs begin to introduce equivalent signal and noise and, hence, include no additional value. Assessment of the signal-to-noise ratio (SNR) at a certain peak or over a specific spectral region will depend on the sample measured. Therefore, the mean SNR over the whole spectral region (SNR(msr)) is determined in the original spectrum as well as for spectra reconstructed from an increasing number of principal components. This paper introduces a method of assessing the influence of signal and noise from individual PC loads and indicates a method of selection of PCs for LDA. To evaluate this method, two data sets with different SNRs were used. The sets were obtained with the same Raman system and the same measurement parameters on bladder tissue collected during white light cystoscopy (set A) and fluorescence-guided cystoscopy (set B). This method shows that the mean SNR over the spectral range in the original Raman spectra of these two data sets is related to the signal and noise contribution of principal component loads. The difference in mean SNR over the spectral range can also be appreciated since fewer principal components can

a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

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Ma, Xin; Xiang, Chengzhi; Gong, Wei

2016-06-01

Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.

Affectively salient meaning in random noise: a task sensitive to psychosis liability.

Science.gov (United States)

Galdos, Mariana; Simons, Claudia; Fernandez-Rivas, Aranzazu; Wichers, Marieke; Peralta, Concepción; Lataster, Tineke; Amer, Guillermo; Myin-Germeys, Inez; Allardyce, Judith; Gonzalez-Torres, Miguel Angel; van Os, Jim

2011-11-01

Stable differences in the tendency to attribute meaning and emotional value to experience may represent an indicator of liability to psychosis. A brief task was developed assessing variation in detecting affectively meaningful speech (speech illusion) in neutral random signals (white noise) and the degree to which this was associated with psychometric and familial vulnerability for psychosis. Thirty patients, 28 of their siblings, and 307 controls participated. The rate of speech illusion was compared between cases and controls. In controls, the association between speech illusion and interview-based positive schizotypy was assessed. The hypothesis of a dose-response increase in rate of speech illusion across increasing levels of familial vulnerability for psychosis (controls, siblings of patients, and patients) was examined. Patients were more likely to display speech illusions than controls (odds ratio [OR] = 4.0, 95% confidence interval [CI] = 1.4-11.7), also after controlling for neurocognitive variables (OR = 3.8, 95% CI = 1.04-14.1). The case-control difference was more accentuated for speech illusion perceived as affectively salient (positively or negatively appraised) than for neutrally appraised speech illusions. Speech illusion in the controls was strongly associated with positive schizotypy but not with negative schizotypy. In addition, the rate of speech illusion increased with increasing level of familial risk for psychotic disorder. The data suggest that the white noise task may be sensitive to psychometric and familial vulnerability for psychosis associated with alterations in top-down processing and/or salience attribution.

Retrofitting reciprocating compressors for noise control

International Nuclear Information System (INIS)

Frank, L.; Qualfe, R.

1992-01-01

The Alberta Energy Resources Conservation Board recently enacted their noise control directive ID 88-1. The effects of this regulation on the operation of an oil and gas facility are discussed, and a specific case history is presented to provide a disciplined strategy for noise attenuation retrofits. An investigation was carried out into sound sources at a reciprocating compressor gas plant, revealing several sound sources: engine exhaust stacks, engine exhaust silencer shells, direct-drive fan cooler inlets, direct drive fan cooler outlets, aerial cooler inlets and aerial cooler outlets. Details are presented of the investigative techniques and order-ranking of sources by decibel level. When controlling engine exhaust noise, silencers or mufflers are the preferred treatment. Choice of type (reactive or absorptive) and specification of acoustical performance of a silencer are discussed. The gas plant achieved noise reductions of 6-13 dB, measured at affected residences, through the use of engine exhaust silencers. 4 figs., 2 tabs

[Occupational noise exposure and work accidents].

Science.gov (United States)

Dias, Adriano; Cordeiro, Ricardo; Gonçalves, Cláudia Giglio de Oliveira

2006-10-01

The purpose of this study was to verify whether occupational noise exposure is a significant risk factor for work accidents in the city of Piracicaba, São Paulo State, Brazil. This hospital-based case-control study included 600 workers aged 15-60 who suffered typical occupational accidents between May and October 2004 and were seen at the Piracicaba Orthopedics and Trauma Center. The control group comprised 822 workers, aged 15-60, who were also seen at the Center, and either had a non-occupational accident or were accompanying someone who had suffered an accident. A multiple logistic regression model was adjusted with work accident as an independent variable, controlled by covariables of interest such as noise exposure. The risk of having a work accident was about twice as high among workers exposed to noise, after controlling for several covariables. Occupational noise exposure not only affected auditory health status but was also a risk factor for work accidents.

Direct EIT reconstructions of complex admittivities on a chest-shaped domain in 2-D.

Science.gov (United States)

Hamilton, Sarah J; Mueller, Jennifer L

2013-04-01

Electrical impedance tomography (EIT) is a medical imaging technique in which current is applied on electrodes on the surface of the body, the resulting voltage is measured, and an inverse problem is solved to recover the conductivity and/or permittivity in the interior. Images are then formed from the reconstructed conductivity and permittivity distributions. In the 2-D geometry, EIT is clinically useful for chest imaging. In this work, an implementation of a D-bar method for complex admittivities on a general 2-D domain is presented. In particular, reconstructions are computed on a chest-shaped domain for several realistic phantoms including a simulated pneumothorax, hyperinflation, and pleural effusion. The method demonstrates robustness in the presence of noise. Reconstructions from trigonometric and pairwise current injection patterns are included.

Maximizing noise energy for noise-masking studies.

Science.gov (United States)

Jules Étienne, Cédric; Arleo, Angelo; Allard, Rémy

2017-08-01

Noise-masking experiments are widely used to investigate visual functions. To be useful, noise generally needs to be strong enough to noticeably impair performance, but under some conditions, noise does not impair performance even when its contrast approaches the maximal displayable limit of 100 %. To extend the usefulness of noise-masking paradigms over a wider range of conditions, the present study developed a noise with great masking strength. There are two typical ways of increasing masking strength without exceeding the limited contrast range: use binary noise instead of Gaussian noise or filter out frequencies that are not relevant to the task (i.e., which can be removed without affecting performance). The present study combined these two approaches to further increase masking strength. We show that binarizing the noise after the filtering process substantially increases the energy at frequencies within the pass-band of the filter given equated total contrast ranges. A validation experiment showed that similar performances were obtained using binarized-filtered noise and filtered noise (given equated noise energy at the frequencies within the pass-band) suggesting that the binarization operation, which substantially reduced the contrast range, had no significant impact on performance. We conclude that binarized-filtered noise (and more generally, truncated-filtered noise) can substantially increase the energy of the noise at frequencies within the pass-band. Thus, given a limited contrast range, binarized-filtered noise can display higher energy levels than Gaussian noise and thereby widen the range of conditions over which noise-masking paradigms can be useful.

Image Reconstruction Based on Homotopy Perturbation Inversion Method for Electrical Impedance Tomography

Directory of Open Access Journals (Sweden)

Jing Wang

2013-01-01

Full Text Available The image reconstruction for electrical impedance tomography (EIT mathematically is a typed nonlinear ill-posed inverse problem. In this paper, a novel iteration regularization scheme based on the homotopy perturbation technique, namely, homotopy perturbation inversion method, is applied to investigate the EIT image reconstruction problem. To verify the feasibility and effectiveness, simulations of image reconstruction have been performed in terms of considering different locations, sizes, and numbers of the inclusions, as well as robustness to data noise. Numerical results indicate that this method can overcome the numerical instability and is robust to data noise in the EIT image reconstruction. Moreover, compared with the classical Landweber iteration method, our approach improves the convergence rate. The results are promising.

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.

Croatian Experience in Road Traffic Noise Management - Concrete Noise Barriers

Directory of Open Access Journals (Sweden)

Ahac Saša

2014-07-01

Full Text Available The paper gives an overview of concrete noise barrier application in several EU countries and in Croatia. It describes a process of introducing different noise protection solutions on Croatian market in the phase of intensive motorway construction in recent years. Namely, an extensive motorway network has been constructed in Croatia in the last 10 years. Following the process of motorway construction, noise protection walls have also been erected. Usage of different building materials and installation processes as well as variations in building expenditures has led to a comparative analysis of several types of noise protection solutions (expanded clay, wood fibre including a new eco-innovative product RUCONBAR, which incorporates rubber granules from recycled waste tyres to form a porous noise absorptive layer.

Recovery after abdominal wall reconstruction

DEFF Research Database (Denmark)

Jensen, Kristian Kiim

2017-01-01

Incisional hernia is a common long-term complication to abdominal surgery, occurring in more than 20% of all patients. Some of these hernias become giant and affect patients in several ways. This patient group often experiences pain, decreased perceived body image, and loss of physical function......, which results in a need for surgical repair of the giant hernia, known as abdominal wall reconstruction. In the current thesis, patients with a giant hernia were examined to achieve a better understanding of their physical and psychological function before and after abdominal wall reconstruction. Study...... was lacking. Study II was a case-control study of the effects of an enhanced recovery after surgery pathway for patients undergoing abdominal wall reconstruction for a giant hernia. Sixteen consecutive patients were included prospectively after the implementation of a new enhanced recovery after surgery...

Vacuum-assisted closure downgrades reconstructive demands in high-risk patients with severe lower extremity injuries.

Science.gov (United States)

Kakagia, D; Karadimas, E; Drosos, G; Ververidis, A; Kazakos, D; Lazarides, M; Verettas, D

2009-01-01

Primary soft tissue reconstruction in complex leg injuries is mandatory in order to protect exposed tissues; however, it may be precluded by the patient's clinical status or by local wound conditions. This retrospective study aims to evaluate the use of negative pressure as an adjunct to delayed soft tissue reconstruction in patients with complex lower limb trauma. Forty-two patients with 49 complex lower limb injuries were treated with Vacuum assisted closure (VAC) 48 hours after bone fixation, vascular repair and surgical debridement. Wound swab cultures were obtained before and after every VAC application. Duration of therapy, wound flora, final reconstructive technique required, outcome and follow-up period were retrieved from medical records. Twenty-four male and eighteen female patients were recruited, with a mean age of 47 years. All were treated with VAC therapy for 15-42 days. Reconstruction was delayed due to the patients' critical condition, advanced age, medical co-morbidities, heavily exuding wounds and questionable viability of soft tissues. Patients were followed up for 90-895 days. Two wounds healed spontaneously, 6 were managed with delayed direct suture, 31 with split thickness skin grafts and 9 required local cutaneous, fasciocutaneous or muscular flaps. One patient died due to fat embolism. Wound bacterial flora progressively decreased in all but one patient. Scar formation was aesthetically acceptable by the patients while function depended on the initial injury. Negative pressure is a safe and effective adjunct to delayed soft tissue reconstruction in high-risk patients with severe lower extremity injuries, minimizing reconstructive requirements and therefore postoperative morbidity.

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

International Nuclear Information System (INIS)

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

2010-01-01

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

Image quality of ct angiography using model-based iterative reconstruction in infants with congenital heart disease: Comparison with filtered back projection and hybrid iterative reconstruction

Energy Technology Data Exchange (ETDEWEB)

Jia, Qianjun, E-mail: jiaqianjun@126.com [Southern Medical University, Guangzhou, Guangdong (China); Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong (China); Department of Catheterization Lab, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong (China); Zhuang, Jian, E-mail: zhuangjian5413@tom.com [Department of Cardiac Surgery, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong (China); Jiang, Jun, E-mail: 81711587@qq.com [Department of Radiology, Shenzhen Second People’s Hospital, Shenzhen, Guangdong (China); Li, Jiahua, E-mail: 970872804@qq.com [Department of Catheterization Lab, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong (China); Huang, Meiping, E-mail: huangmeiping_vip@163.com [Department of Catheterization Lab, Guangdong Cardiovascular Institute, Guangdong Provincial Key Laboratory of South China Structural Heart Disease, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong (China); Southern Medical University, Guangzhou, Guangdong (China); Liang, Changhong, E-mail: cjr.lchh@vip.163.com [Department of Radiology, Guangdong General Hospital, Guangdong Academy of Medical Sciences, Guangzhou, Guangdong (China); Southern Medical University, Guangzhou, Guangdong (China)

2017-01-15

Purpose: To compare the image quality, rate of coronary artery visualization and diagnostic accuracy of 256-slice multi-detector computed tomography angiography (CTA) with prospective electrocardiographic (ECG) triggering at a tube voltage of 80 kVp between 3 reconstruction algorithms (filtered back projection (FBP), hybrid iterative reconstruction (iDose{sup 4}) and iterative model reconstruction (IMR)) in infants with congenital heart disease (CHD). Methods: Fifty-one infants with CHD who underwent cardiac CTA in our institution between December 2014 and March 2015 were included. The effective radiation doses were calculated. Imaging data were reconstructed using the FBP, iDose{sup 4} and IMR algorithms. Parameters of objective image quality (noise, signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR)); subjective image quality (overall image quality, image noise and margin sharpness); coronary artery visibility; and diagnostic accuracy for the three algorithms were measured and compared. Results: The mean effective radiation dose was 0.61 ± 0.32 mSv. Compared to FBP and iDose{sup 4}, IMR yielded significantly lower noise (P < 0.01), higher SNR and CNR values (P < 0.01), and a greater subjective image quality score (P < 0.01). The total number of coronary segments visualized was significantly higher for both iDose{sup 4} and IMR than for FBP (P = 0.002 and P = 0.025, respectively), but there was no significant difference in this parameter between iDose{sup 4} and IMR (P = 0.397). There was no significant difference in the diagnostic accuracy between the FBP, iDose{sup 4} and IMR algorithms (χ{sup 2} = 0.343, P = 0.842). Conclusions: For infants with CHD undergoing cardiac CTA, the IMR reconstruction algorithm provided significantly increased objective and subjective image quality compared with the FBP and iDose{sup 4} algorithms. However, IMR did not improve the diagnostic accuracy or coronary artery visualization compared with iDose{sup 4}.

Analysis of reproducibility of the single photon tomography reconstruction by the method of singular value decomposition

International Nuclear Information System (INIS)

Devaux, J.Y.; Mazelier, L.; Lefkopoulos, D.

1997-01-01

We have earlier shown that the method of singular value decomposition (SVD) allows the image reconstruction in single-photon-tomography with precision higher than the classical method of filtered back-projections. Actually, the establishing of an elementary response matrix which incorporates both the photon attenuation phenomenon, the scattering, the translation non-invariance principle and the detector response, allows to take into account the totality of physical parameters of acquisition. By an non-consecutive optimized truncation of the singular values we have obtained a significant improvement in the efficiency of the regularization of bad conditioning of this problem. The present study aims at verifying the stability of this truncation under modifications of acquisition conditions. Two series of parameters were tested, first, those modifying the geometry of acquisition: the influence of rotation center, the asymmetric disposition of the elementary-volume sources against the detector and the precision of rotation angle, and secondly, those affecting the correspondence between the matrix and the space to be reconstructed: the effect of partial volume and a noise propagation in the experimental model. For the parameters which introduce a spatial distortion, the alteration of reconstruction has been, as expected, comparable to that observed with the classical reconstruction and proportional with the amplitude of shift from the normal one. In exchange, for the effect of partial volume and of noise, the study of truncation signature revealed a variation in the optimal choice of the conserved singular values but with no effect on the global precision of reconstruction

Enhanced 3D PET OSEM reconstruction using inter-update Metz filtering

International Nuclear Information System (INIS)

Jacobson, M.; Levkovitz, R.; Ben-Tal, A.; Thielemans, K.; Spinks, T.; Belluzzo, D.; Pagani, E.; Bettinardi, V.; Gilardi, M.C.; Zverovich, A.; Mitra, G.

2000-01-01

We present an enhancement of the OSEM (ordered set expectation maximization) algorithm for 3D PET reconstruction, which we call the inter-update Metz filtered OSEM (IMF-OSEM). The IMF-OSEM algorithm incorporates filtering action into the image updating process in order to improve the quality of the reconstruction. With this technique, the multiplicative correction image - ordinarily used to update image estimates in plain OSEM - is applied to a Metz-filtered version of the image estimate at certain intervals. In addition, we present a software implementation that employs several high-speed features to accelerate reconstruction. These features include, firstly, forward and back projection functions which make full use of symmetry as well as a fast incremental computation technique. Secondly, the software has the capability of running in parallel mode on several processors. The parallelization approach employed yields a significant speed-up, which is nearly independent of the amount of data. Together, these features lead to reasonable reconstruction times even when using large image arrays and non-axially compressed projection data. The performance of IMF-OSEM was tested on phantom data acquired on the GE Advance scanner. Our results demonstrate that an appropriate choice of Metz filter parameters can improve the contrast-noise balance of certain regions of interest relative to both plain and post-filtered OSEM, and to the GE commercial reprojection algorithm software. (author)

A Comparison of Affect Ratings Obtained with Ecological Momentary Assessment and the Day Reconstruction Method

Science.gov (United States)

Dockray, Samantha; Grant, Nina; Stone, Arthur A.; Kahneman, Daniel; Wardle, Jane; Steptoe, Andrew

2010-01-01

Measurement of affective states in everyday life is of fundamental importance in many types of quality of life, health, and psychological research. Ecological momentary assessment (EMA) is the recognized method of choice, but the respondent burden can be high. The day reconstruction method (DRM) was developed by Kahneman and colleagues ("Science,"…

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

Noise properties of Hilbert transform evaluation

International Nuclear Information System (INIS)

Pavliček, Pavel; Svak, Vojtěch

2015-01-01

The Hilbert transform is a standard method for the calculation of the envelope and phase of a modulated signal in optical measurement methods. Usually, the intensity of light is converted into an electric signal at a detector. Therefore the actual spatially or temporally sampled signal is always affected by noise. Because the noise values of individual samples are independent, the noise can be considered as white. If the envelope and phase are calculated from the noised signal, they will also be affected by the noise. We calculate the variance and spectral density of both the envelope noise and the phase noise. We determine which parameters influence the variance and spectral density of both the envelope noise and the phase noise. Finally, we determine the influence of the noise on the measurement uncertainty in white-light interferometry and fringe-pattern analysis. (paper)

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

Influence of iterative image reconstruction on CT-based calcium score measurements

NARCIS (Netherlands)

van Osch, Jochen A. C.; Mouden, Mohamed; van Dalen, Jorn A.; Timmer, Jorik R.; Reiffers, Stoffer; Knollema, Siert; Greuter, Marcel J. W.; Ottervanger, Jan Paul; Jager, Piet L.

Iterative reconstruction techniques for coronary CT angiography have been introduced as an alternative for traditional filter back projection (FBP) to reduce image noise, allowing improved image quality and a potential for dose reduction. However, the impact of iterative reconstruction on the

Potential benefit of the CT adaptive statistical iterative reconstruction method for pediatric cardiac diagnosis

Science.gov (United States)

Miéville, Frédéric A.; Ayestaran, Paul; Argaud, Christophe; Rizzo, Elena; Ou, Phalla; Brunelle, Francis; Gudinchet, François; Bochud, François; Verdun, Francis R.

2010-04-01

Adaptive Statistical Iterative Reconstruction (ASIR) is a new imaging reconstruction technique recently introduced by General Electric (GE). This technique, when combined with a conventional filtered back-projection (FBP) approach, is able to improve the image noise reduction. To quantify the benefits provided on the image quality and the dose reduction by the ASIR method with respect to the pure FBP one, the standard deviation (SD), the modulation transfer function (MTF), the noise power spectrum (NPS), the image uniformity and the noise homogeneity were examined. Measurements were performed on a control quality phantom when varying the CT dose index (CTDIvol) and the reconstruction kernels. A 64-MDCT was employed and raw data were reconstructed with different percentages of ASIR on a CT console dedicated for ASIR reconstruction. Three radiologists also assessed a cardiac pediatric exam reconstructed with different ASIR percentages using the visual grading analysis (VGA) method. For the standard, soft and bone reconstruction kernels, the SD is reduced when the ASIR percentage increases up to 100% with a higher benefit for low CTDIvol. MTF medium frequencies were slightly enhanced and modifications of the NPS shape curve were observed. However for the pediatric cardiac CT exam, VGA scores indicate an upper limit of the ASIR benefit. 40% of ASIR was observed as the best trade-off between noise reduction and clinical realism of organ images. Using phantom results, 40% of ASIR corresponded to an estimated dose reduction of 30% under pediatric cardiac protocol conditions. In spite of this discrepancy between phantom and clinical results, the ASIR method is as an important option when considering the reduction of radiation dose, especially for pediatric patients.

Sub-Nyquist signal-reconstruction-free operational modal analysis and damage detection in the presence of noise

Science.gov (United States)

Gkoktsi, Kyriaki; Giaralis, Agathoklis; TauSiesakul, Bamrung

2016-04-01

Motivated by a need to reduce energy consumption in wireless sensors for vibration-based structural health monitoring (SHM) associated with data acquisition and transmission, this paper puts forth a novel approach for undertaking operational modal analysis (OMA) and damage localization relying on compressed vibrations measurements sampled at rates well below the Nyquist rate. Specifically, non-uniform deterministic sub-Nyquist multi-coset sampling of response acceleration signals in white noise excited linear structures is considered in conjunction with a power spectrum blind sampling/estimation technique which retrieves/samples the power spectral density matrix from arrays of sensors directly from the sub-Nyquist measurements (i.e., in the compressed domain) without signal reconstruction in the time-domain and without posing any signal sparsity conditions. The frequency domain decomposition algorithm is then applied to the power spectral density matrix to extract natural frequencies and mode shapes as a standard OMA step. Further, the modal strain energy index (MSEI) is considered for damage localization based on the mode shapes extracted directly from the compressed measurements. The effectiveness and accuracy of the proposed approach is numerically assessed by considering simulated vibration data pertaining to a white-noise excited simply supported beam in healthy and in 3 damaged states, contaminated with Gaussian white noise. Good accuracy is achieved in estimating mode shapes (quantified in terms of the modal assurance criterion) and natural frequencies from an array of 15 multi-coset devices sampling at a 70% slower than the Nyquist frequency rate for SNRs as low as 10db. Damage localization of equal level/quality is also achieved by the MSEI applied to mode shapes derived from noisy sub-Nyquist (70% compression) and Nyquist measurements for all damaged states considered. Overall, the furnished numerical results demonstrate that the herein considered sub

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

International Nuclear Information System (INIS)

Shieh, Chun-Chien; Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J.; Kuncic, Zdenka

2014-01-01

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

Image quality in thoracic 4D cone-beam CT: A sensitivity analysis of respiratory signal, binning method, reconstruction algorithm, and projection angular spacing

Energy Technology Data Exchange (ETDEWEB)

Shieh, Chun-Chien [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006, Australia and Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia); Kipritidis, John; O’Brien, Ricky T.; Keall, Paul J., E-mail: paul.keall@sydney.edu.au [Radiation Physics Laboratory, Sydney Medical School, University of Sydney, NSW 2006 (Australia); Kuncic, Zdenka [Institute of Medical Physics, School of Physics, University of Sydney, NSW 2006 (Australia)

2014-04-15

Purpose: Respiratory signal, binning method, and reconstruction algorithm are three major controllable factors affecting image quality in thoracic 4D cone-beam CT (4D-CBCT), which is widely used in image guided radiotherapy (IGRT). Previous studies have investigated each of these factors individually, but no integrated sensitivity analysis has been performed. In addition, projection angular spacing is also a key factor in reconstruction, but how it affects image quality is not obvious. An investigation of the impacts of these four factors on image quality can help determine the most effective strategy in improving 4D-CBCT for IGRT. Methods: Fourteen 4D-CBCT patient projection datasets with various respiratory motion features were reconstructed with the following controllable factors: (i) respiratory signal (real-time position management, projection image intensity analysis, or fiducial marker tracking), (ii) binning method (phase, displacement, or equal-projection-density displacement binning), and (iii) reconstruction algorithm [Feldkamp–Davis–Kress (FDK), McKinnon–Bates (MKB), or adaptive-steepest-descent projection-onto-convex-sets (ASD-POCS)]. The image quality was quantified using signal-to-noise ratio (SNR), contrast-to-noise ratio, and edge-response width in order to assess noise/streaking and blur. The SNR values were also analyzed with respect to the maximum, mean, and root-mean-squared-error (RMSE) projection angular spacing to investigate how projection angular spacing affects image quality. Results: The choice of respiratory signals was found to have no significant impact on image quality. Displacement-based binning was found to be less prone to motion artifacts compared to phase binning in more than half of the cases, but was shown to suffer from large interbin image quality variation and large projection angular gaps. Both MKB and ASD-POCS resulted in noticeably improved image quality almost 100% of the time relative to FDK. In addition, SNR

The Impact of Optimal Respiratory Gating and Image Noise on Evaluation of Intratumor Heterogeneity on 18F-FDG PET Imaging of Lung Cancer.

Science.gov (United States)

Grootjans, Willem; Tixier, Florent; van der Vos, Charlotte S; Vriens, Dennis; Le Rest, Catherine C; Bussink, Johan; Oyen, Wim J G; de Geus-Oei, Lioe-Fee; Visvikis, Dimitris; Visser, Eric P

2016-11-01

Accurate measurement of intratumor heterogeneity using parameters of texture on PET images is essential for precise characterization of cancer lesions. In this study, we investigated the influence of respiratory motion and varying noise levels on quantification of textural parameters in patients with lung cancer. We used an optimal-respiratory-gating algorithm on the list-mode data of 60 lung cancer patients who underwent 18 F-FDG PET. The images were reconstructed using a duty cycle of 35% (percentage of the total acquired PET data). In addition, nongated images of varying statistical quality (using 35% and 100% of the PET data) were reconstructed to investigate the effects of image noise. Several global image-derived indices and textural parameters (entropy, high-intensity emphasis, zone percentage, and dissimilarity) that have been associated with patient outcome were calculated. The clinical impact of optimal respiratory gating and image noise on assessment of intratumor heterogeneity was evaluated using Cox regression models, with overall survival as the outcome measure. The threshold for statistical significance was adjusted for multiple comparisons using Bonferroni correction. In the lower lung lobes, respiratory motion significantly affected quantification of intratumor heterogeneity for all textural parameters (P 0.007). The mean increase in entropy, dissimilarity, zone percentage, and high-intensity emphasis was 1.3% ± 1.5% (P = 0.02), 11.6% ± 11.8% (P = 0.006), 2.3% ± 2.2% (P = 0.002), and 16.8% ± 17.2% (P = 0.006), respectively. No significant differences were observed for lesions in the upper lung lobes (P > 0.007). Differences in the statistical quality of the PET images affected the textural parameters less than respiratory motion, with no significant difference observed. The median follow-up time was 35 mo (range, 7-39 mo). In multivariate analysis for overall survival, total lesion glycolysis and high-intensity emphasis were the two most

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.

A method of background noise cancellation for SQUID applications

International Nuclear Information System (INIS)

He, D F; Yoshizawa, M

2003-01-01

When superconducting quantum inference devices (SQUIDs) operate in low-cost shielding or unshielded environments, the environmental background noise should be reduced to increase the signal-to-noise ratio. In this paper we present a background noise cancellation method based on a spectral subtraction algorithm. We first measure the background noise and estimate the noise spectrum using fast Fourier transform (FFT), then we subtract the spectrum of background noise from that of the observed noisy signal and the signal can be reconstructed by inverse FFT of the subtracted spectrum. With this method, the background noise, especially stationary inferences, can be suppressed well and the signal-to-noise ratio can be increased. Using high-T C radio-frequency SQUID gradiometer and magnetometer, we have measured the magnetic field produced by a watch, which was placed 35 cm under a SQUID. After noise cancellation, the signal-to-noise ratio could be greatly increased. We also used this method to eliminate the vibration noise of a cryocooler SQUID

Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy

International Nuclear Information System (INIS)

Tang, Jing; Rahmim, Arman

2015-01-01

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

Anatomy assisted PET image reconstruction incorporating multi-resolution joint entropy

Science.gov (United States)

Tang, Jing; Rahmim, Arman

2015-01-01

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

Piribedil affects dopamine turnover in cochleas stimulated by white noise.

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Gil-Loyzaga, P; Vicente-Torres, M A; Fernández-Mateos, P; Arce, A; Esquifino, A

1994-09-01

The presence of dopamine (DA) within the cochlea has been previously reported, indicating that its turnover increases under noise stimulation. In the present report, piribedil, a dopaminergic D2 agonist, was used in order to provide evidence of the activity of D2 receptors in the turnover of DA under noise stimulation. Long-Evans rats were intraperitoneally injected with distilled water or with a solution of piribedil one hour previously to either noise or silence exposure. Noise stimulation was performed in an anechoic chamber at 70, 90 or 110 dB SPL for one hour. The animals were then sacrificed and the cochlear contents of DA and its metabolites dihydroxyphenylacetic acid (DOPAC) and homovanillic acid (HVA) were quantified by HPLC with electrochemical detection. The administration of piribedil to animals kept in silence did not modify the cochlear DA, DOPAC and HVA content. Noise stimulation resulted in a decrease of the cochlear DA content and an increase of the cochlear DOPAC and HVA contents in vehicle treated animals. The administration of piribedil resulted in a blockade of this noise induced cochlear DA turnover. These results suggest that piribedil stimulates cochlear D2 receptors controlling the cochlear DA release. Piribedil action on D2 receptors could explain the improvement observed in some cochleo-vestibular diseases signs after piribedil treatment.

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

Science.gov (United States)

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

2011-04-01

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

Type of activity and order of experimental conditions affect noise annoyance by identifiable and unidentifiable transportation noise.

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White, Kim; Bronkhorst, Adelbert W; Meeter, Martijn

2018-04-01

Previous studies have shown that identifiability of sound sources influence noise annoyance levels. The aim of the present experiment was to additionally study the effects of actively performing a task versus a less active pastime on noise annoyance. This was done by asking participants to perform a task (task condition) or read a magazine of their choice (no-task condition), while listening to identifiable and unidentifiable samples of transportation noise at varying sound exposure levels (55-85 ASEL). Annoyance was higher for identifiable samples (recordings) than for unidentifiable transformed samples (with equal spectral energy and envelope). Although there was no main effect of activity type on noise annoyance, for the transformed samples, an interaction was found between activity type and sound exposure levels: annoyance started lower in the no-task condition, but rose more steeply with ascending exposure levels than was the case during task performance (large effect). When assessing order effects, it was found that annoyance was higher when the task condition came first, especially for lower sound exposure levels (large effects). It is therefore concluded that the type of activity and the condition order do influence noise annoyance but in interaction with exposure levels, the type of noise and habituation.

Homotopic non-local regularized reconstruction from sparse positron emission tomography measurements

International Nuclear Information System (INIS)

Wong, Alexander; Liu, Chenyi; Wang, Xiao Yu; Fieguth, Paul; Bie, Hongxia

2015-01-01

Positron emission tomography scanners collect measurements of a patient’s in vivo radiotracer distribution. The system detects pairs of gamma rays emitted indirectly by a positron-emitting radionuclide (tracer), which is introduced into the body on a biologically active molecule, and the tomograms must be reconstructed from projections. The reconstruction of tomograms from the acquired PET data is an inverse problem that requires regularization. The use of tightly packed discrete detector rings, although improves signal-to-noise ratio, are often associated with high costs of positron emission tomography systems. Thus a sparse reconstruction, which would be capable of overcoming the noise effect while allowing for a reduced number of detectors, would have a great deal to offer. In this study, we introduce and investigate the potential of a homotopic non-local regularization reconstruction framework for effectively reconstructing positron emission tomograms from such sparse measurements. Results obtained using the proposed approach are compared with traditional filtered back-projection as well as expectation maximization reconstruction with total variation regularization. A new reconstruction method was developed for the purpose of improving the quality of positron emission tomography reconstruction from sparse measurements. We illustrate that promising reconstruction performance can be achieved for the proposed approach even at low sampling fractions, which allows for the use of significantly fewer detectors and have the potential to reduce scanner costs

Dynamic re-weighted total variation technique and statistic Iterative reconstruction method for x-ray CT metal artifact reduction

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Peng, Chengtao; Qiu, Bensheng; Zhang, Cheng; Ma, Changyu; Yuan, Gang; Li, Ming

2017-07-01

Over the years, the X-ray computed tomography (CT) has been successfully used in clinical diagnosis. However, when the body of the patient to be examined contains metal objects, the image reconstructed would be polluted by severe metal artifacts, which affect the doctor's diagnosis of disease. In this work, we proposed a dynamic re-weighted total variation (DRWTV) technique combined with the statistic iterative reconstruction (SIR) method to reduce the artifacts. The DRWTV method is based on the total variation (TV) and re-weighted total variation (RWTV) techniques, but it provides a sparser representation than TV and protects the tissue details better than RWTV. Besides, the DRWTV can suppress the artifacts and noise, and the SIR convergence speed is also accelerated. The performance of the algorithm is tested on both simulated phantom dataset and clinical dataset, which are the teeth phantom with two metal implants and the skull with three metal implants, respectively. The proposed algorithm (SIR-DRWTV) is compared with two traditional iterative algorithms, which are SIR and SIR constrained by RWTV regulation (SIR-RWTV). The results show that the proposed algorithm has the best performance in reducing metal artifacts and protecting tissue details.

Classifying and assembling two-dimensional X-ray laser diffraction patterns of a single particle to reconstruct the three-dimensional diffraction intensity function: resolution limit due to the quantum noise

International Nuclear Information System (INIS)

Tokuhisa, Atsushi; Taka, Junichiro; Kono, Hidetoshi; Go, Nobuhiro

2012-01-01

A new algorithm is developed for reconstructing the high-resolution three-dimensional diffraction intensity function of a globular biological macromolecule from many quantum-noise-limited two-dimensional X-ray laser diffraction patterns, each for an unknown orientation. The structural resolution is expressed as a function of the incident X-ray intensity and quantities characterizing the target molecule. A new two-step algorithm is developed for reconstructing the three-dimensional diffraction intensity of a globular biological macromolecule from many experimentally measured quantum-noise-limited two-dimensional X-ray laser diffraction patterns, each for an unknown orientation. The first step is classification of the two-dimensional patterns into groups according to the similarity of direction of the incident X-rays with respect to the molecule and an averaging within each group to reduce the noise. The second step is detection of common intersecting circles between the signal-enhanced two-dimensional patterns to identify their mutual location in the three-dimensional wavenumber space. The newly developed algorithm enables one to detect a signal for classification in noisy experimental photon-count data with as low as ∼0.1 photons per effective pixel. The wavenumber of such a limiting pixel determines the attainable structural resolution. From this fact, the resolution limit due to the quantum noise attainable by this new method of analysis as well as two important experimental parameters, the number of two-dimensional patterns to be measured (the load for the detector) and the number of pairs of two-dimensional patterns to be analysed (the load for the computer), are derived as a function of the incident X-ray intensity and quantities characterizing the target molecule

Theory of the Auger effect in an intense acoustic noise field

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Doan Nhat Quang.

1995-10-01

A study is given of the effect on Auger processes produced by an intense acoustic noise flux affecting charge carriers via deformation-potential interaction. The calculation of Auger coefficients is carried out within a semiclassical approach to the acoustic noise field and non-degenerate carrier statistics. Simple analytic expressions are then obtained, which expose an exponential dependence of the Auger coefficients on flux intensity. The Auger recombination is found, in analogy with the case of piezoelectric noise field, to be strongly enhanced as compared to that in no-noise conditions by up to several orders of magnitude at high flux intensity, short acoustic wavelength, small carrier concentration and low temperature. (author). 29 refs, 4 figs, 1 tab

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.)

Adaptive statistical iterative reconstruction use for radiation dose reduction in pediatric lower-extremity CT: impact on diagnostic image quality.

Science.gov (United States)

Shah, Amisha; Rees, Mitchell; Kar, Erica; Bolton, Kimberly; Lee, Vincent; Panigrahy, Ashok

2018-06-01

For the past several years, increased levels of imaging radiation and cumulative radiation to children has been a significant concern. Although several measures have been taken to reduce radiation dose during computed tomography (CT) scan, the newer dose reduction software adaptive statistical iterative reconstruction (ASIR) has been an effective technique in reducing radiation dose. To our knowledge, no studies are published that assess the effect of ASIR on extremity CT scans in children. To compare radiation dose, image noise, and subjective image quality in pediatric lower extremity CT scans acquired with and without ASIR. The study group consisted of 53 patients imaged on a CT scanner equipped with ASIR software. The control group consisted of 37 patients whose CT images were acquired without ASIR. Image noise, Computed Tomography Dose Index (CTDI) and dose length product (DLP) were measured. Two pediatric radiologists rated the studies in subjective categories: image sharpness, noise, diagnostic acceptability, and artifacts. The CTDI (p value = 0.0184) and DLP (p value ASIR compared with non-ASIR studies. However, the subjective ratings for sharpness (p ASIR images (p ASIR CT studies. Adaptive statistical iterative reconstruction reduces radiation dose for lower extremity CTs in children, but at the expense of diagnostic imaging quality. Further studies are warranted to determine the specific utility of ASIR for pediatric musculoskeletal CT imaging.

LOR-OSEM: statistical PET reconstruction from raw line-of-response histograms

International Nuclear Information System (INIS)

Kadrmas, Dan J

2004-01-01

Iterative statistical reconstruction methods are becoming the standard in positron emission tomography (PET). Conventional maximum-likelihood expectation-maximization (MLEM) and ordered-subsets (OSEM) algorithms act on data which have been pre-processed into corrected, evenly-spaced histograms; however, such pre-processing corrupts the Poisson statistics. Recent advances have incorporated attenuation, scatter and randoms compensation into the iterative reconstruction. The objective of this work was to incorporate the remaining pre-processing steps, including arc correction, to reconstruct directly from raw unevenly-spaced line-of-response (LOR) histograms. This exactly preserves Poisson statistics and full spatial information in a manner closely related to listmode ML, making full use of the ML statistical model. The LOR-OSEM algorithm was implemented using a rotation-based projector which maps directly to the unevenly-spaced LOR grid. Simulation and phantom experiments were performed to characterize resolution, contrast and noise properties for 2D PET. LOR-OSEM provided a beneficial noise-resolution tradeoff, outperforming AW-OSEM by about the same margin that AW-OSEM outperformed pre-corrected OSEM. The relationship between LOR-ML and listmode ML algorithms was explored, and implementation differences are discussed. LOR-OSEM is a viable alternative to AW-OSEM for histogram-based reconstruction with improved spatial resolution and noise properties

A heuristic statistical stopping rule for iterative reconstruction in emission tomography

International Nuclear Information System (INIS)

Ben Bouallegue, F.; Mariano-Goulart, D.; Crouzet, J.F.

2013-01-01

We propose a statistical stopping criterion for iterative reconstruction in emission tomography based on a heuristic statistical description of the reconstruction process. The method was assessed for maximum likelihood expectation maximization (MLEM) reconstruction. Based on Monte-Carlo numerical simulations and using a perfectly modeled system matrix, our method was compared with classical iterative reconstruction followed by low-pass filtering in terms of Euclidian distance to the exact object, noise, and resolution. The stopping criterion was then evaluated with realistic PET data of a Hoffman brain phantom produced using the Geant4 application in emission tomography (GATE) platform for different count levels. The numerical experiments showed that compared with the classical method, our technique yielded significant improvement of the noise-resolution tradeoff for a wide range of counting statistics compatible with routine clinical settings. When working with realistic data, the stopping rule allowed a qualitatively and quantitatively efficient determination of the optimal image. Our method appears to give a reliable estimation of the optimal stopping point for iterative reconstruction. It should thus be of practical interest as it produces images with similar or better quality than classical post-filtered iterative reconstruction with a mastered computation time. (author)

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

Energy Technology Data Exchange (ETDEWEB)

Notohamiprodjo, S.; Deak, Z.; Meurer, F.; Maertz, F.; Mueck, F.G.; Geyer, L.L.; Wirth, S. [Ludwig-Maximilians University Hospital of Munich, Institute for Clinical Radiology, Munich (Germany)

2015-01-15

The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01). MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. (orig.)

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

International Nuclear Information System (INIS)

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

2015-01-01

The purpose of this study was to compare cranial CT (CCT) image quality (IQ) of the MBIR algorithm with standard iterative reconstruction (ASiR). In this institutional review board (IRB)-approved study, raw data sets of 100 unenhanced CCT examinations (120 kV, 50-260 mAs, 20 mm collimation, 0.984 pitch) were reconstructed with both ASiR and MBIR. Signal-to-noise (SNR) and contrast-to-noise (CNR) were calculated from attenuation values measured in caudate nucleus, frontal white matter, anterior ventricle horn, fourth ventricle, and pons. Two radiologists, who were blinded to the reconstruction algorithms, evaluated anonymized multiplanar reformations of 2.5 mm with respect to depiction of different parenchymal structures and impact of artefacts on IQ with a five-point scale (0: unacceptable, 1: less than average, 2: average, 3: above average, 4: excellent). MBIR decreased artefacts more effectively than ASiR (p < 0.01). The median depiction score for MBIR was 3, whereas the median value for ASiR was 2 (p < 0.01). SNR and CNR were significantly higher in MBIR than ASiR (p < 0.01). MBIR showed significant improvement of IQ parameters compared to ASiR. As CCT is an examination that is frequently required, the use of MBIR may allow for substantial reduction of radiation exposure caused by medical diagnostics. (orig.)

The effects of iterative reconstruction in CT on low-contrast liver lesion volumetry: a phantom study

Science.gov (United States)

Li, Qin; Berman, Benjamin P.; Schumacher, Justin; Liang, Yongguang; Gavrielides, Marios A.; Yang, Hao; Zhao, Binsheng; Petrick, Nicholas

2017-03-01

Tumor volume measured from computed tomography images is considered a biomarker for disease progression or treatment response. The estimation of the tumor volume depends on the imaging system parameters selected, as well as lesion characteristics. In this study, we examined how different image reconstruction methods affect the measurement of lesions in an anthropomorphic liver phantom with a non-uniform background. Iterative statistics-based and model-based reconstructions, as well as filtered back-projection, were evaluated and compared in this study. Statistics-based and filtered back-projection yielded similar estimation performance, while model-based yielded higher precision but lower accuracy in the case of small lesions. Iterative reconstructions exhibited higher signal-to-noise ratio but slightly lower contrast of the lesion relative to the background. A better understanding of lesion volumetry performance as a function of acquisition parameters and lesion characteristics can lead to its incorporation as a routine sizing tool.

Pilot survey of subway and bus stop noise levels.

Science.gov (United States)

Gershon, Robyn R M; Neitzel, Richard; Barrera, Marissa A; Akram, Muhammad

2006-09-01

Excessive noise exposure is a serious global urban health problem, adversely affecting millions of people. One often cited source of urban noise is mass transit, particularly subway systems. As a first step in determining risk within this context, we recently conducted an environmental survey of noise levels of the New York City transit system. Over 90 noise measurements were made using a sound level meter. Average and maximum noise levels were measured on subway platforms, and maximum levels were measured inside subway cars and at several bus stops for comparison purposes. The average noise level measured on the subway platforms was 86 +/- 4 dBA (decibel-A weighting). Maximum levels of 106, 112, and 89 dBA were measured on subway platforms, inside subway cars, and at bus stops, respectively. These results indicate that noise levels in subway and bus stop environments have the potential to exceed recommended exposure guidelines from the World Health Organization (WHO) and U.S. Environmental Protection Agency (EPA), given sufficient exposure duration. Risk reduction strategies following the standard hierarchy of control measures should be applied, where feasible, to reduce subway noise exposure.

Maximum entropy reconstruction of poloidal magnetic field and radial electric field profiles in tokamaks

Science.gov (United States)

Chen, Yihang; Xiao, Chijie; Yang, Xiaoyi; Wang, Tianbo; Xu, Tianchao; Yu, Yi; Xu, Min; Wang, Long; Lin, Chen; Wang, Xiaogang

2017-10-01

The Laser-driven Ion beam trace probe (LITP) is a new diagnostic method for measuring poloidal magnetic field (Bp) and radial electric field (Er) in tokamaks. LITP injects a laser-driven ion beam into the tokamak, and Bp and Er profiles can be reconstructed using tomography methods. A reconstruction code has been developed to validate the LITP theory, and both 2D reconstruction of Bp and simultaneous reconstruction of Bp and Er have been attained. To reconstruct from experimental data with noise, Maximum Entropy and Gaussian-Bayesian tomography methods were applied and improved according to the characteristics of the LITP problem. With these improved methods, a reconstruction error level below 15% has been attained with a data noise level of 10%. These methods will be further tested and applied in the following LITP experiments. Supported by the ITER-CHINA program 2015GB120001, CHINA MOST under 2012YQ030142 and National Natural Science Foundation Abstract of China under 11575014 and 11375053.

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

Industrial dynamic tomographic reconstruction; Reconstrucao tomografica dinamica industrial

Energy Technology Data Exchange (ETDEWEB)

Oliveira, Eric Ferreira de

2016-07-01

The state of the art methods applied to industrial processes is currently based on the principles of classical tomographic reconstructions developed for tomographic patterns of static distributions, or is limited to cases of low variability of the density distribution function of the tomographed object. Noise and motion artifacts are the main problems caused by a mismatch in the data from views acquired in different instants. All of these add to the known fact that using a limited amount of data can result in the presence of noise, artifacts and some inconsistencies with the distribution under study. One of the objectives of the present work is to discuss the difficulties that arise from implementing reconstruction algorithms in dynamic tomography that were originally developed for static distributions. Another objective is to propose solutions that aim at reducing a temporal type of information loss caused by employing regular acquisition systems to dynamic processes. With respect to dynamic image reconstruction it was conducted a comparison between different static reconstruction methods, like MART and FBP, when used for dynamic scenarios. This comparison was based on a MCNPx simulation as well as an analytical setup of an aluminum cylinder that moves along the section of a riser during the process of acquisition, and also based on cross section images from CFD techniques. As for the adaptation of current tomographic acquisition systems for dynamic processes, this work established a sequence of tomographic views in a just-in-time fashion for visualization purposes, a form of visually disposing density information as soon as it becomes amenable to image reconstruction. A third contribution was to take advantage of the triple color channel necessary to display colored images in most displays, so that, by appropriately scaling the acquired values of each view in the linear system of the reconstruction, it was possible to imprint a temporal trace into the regularly

23 CFR 772.19 - Construction noise.

Science.gov (United States)

2010-04-01

... 23 Highways 1 2010-04-01 2010-04-01 false Construction noise. 772.19 Section 772.19 Highways... ABATEMENT OF HIGHWAY TRAFFIC NOISE AND CONSTRUCTION NOISE § 772.19 Construction noise. The following general... may be affected by noise from construction of the project. The identification is to be performed...

Reconstruction of a direction-dependent primordial power spectrum from Planck CMB data

Science.gov (United States)

Durakovic, Amel; Hunt, Paul; Mukherjee, Suvodip; Sarkar, Subir; Souradeep, Tarun

2018-02-01

We consider the possibility that the primordial curvature perturbation is direction-dependent. To first order this is parameterised by a quadrupolar modulation of the power spectrum and results in statistical anisotropy of the CMB, which can be quantified using `bipolar spherical harmonics'. We compute these for the Planck DR2-2015 SMICA map and estimate the noise covariance from Planck Full Focal Plane 9 simulations. A constant quadrupolar modulation is detected with 2.2 σ significance, dropping to 2σ when the primordial power is assumed to scale with wave number k as a power law. Going beyond previous work we now allow the spectrum to have arbitrary scale-dependence. Our non-parametric reconstruction then suggests several spectral features, the most prominent at k ~ 0.006 Mpc‑1. When a constant quadrupolar modulation is fitted to data in the range 0.005 <= k/Mpc‑1 <= 0.008, its preferred directions are found to be related to the cosmic hemispherical asymmetry and the CMB dipole. To determine the significance we apply two test statistics to our reconstructions of the quadrupolar modulation from data, against reconstructions of realisations of noise only. With a test statistic sensitive only to the amplitude of the modulation, the reconstructions from the multipole range 30 <= l <= 1200 are unusual with 2.1σ significance. With the second test statistic, sensitive also to the direction, the significance rises to 6.9σ. Our approach is easily generalised to include other data sets such as polarisation, large-scale structure and forthcoming 21-cm line observations which will enable these anomalies to be investigated further.

Incidence of severe capsular contracture following implant-based immediate breast reconstruction with or without postoperative chest wall radiotherapy using 40 Gray in 15 fractions

International Nuclear Information System (INIS)

Whitfield, Gillian A.; Horan, Gail; Irwin, Michael S.; Malata, Charles M.; Wishart, Gordon C.; Wilson, Charles B.

2009-01-01

Purpose: To determine the incidence of capsular contracture (CC) requiring revisional surgery in patients receiving postoperative radiotherapy (RT) or no RT following mastectomy and immediate breast reconstruction. Material and methods: One hundred and seventy-eight immediate breast reconstructions performed at the Cambridge Breast Unit between 1.1.2001 and 31.12.2005 were identified. RT was delivered using a standard UK scheme of 40 Gray in 15 fractions over 3 weeks. The influence of hormones and chemotherapy as well as postoperative RT on time to development of severe CC after implant-based reconstruction was explored in univariate and multivariate analysis. Results: One hundred and ten patients had implant-based reconstructions with a median follow-up of 51 months. In the RT group (41 patients), there were 8 patients with severe CC requiring revisional surgery, a crude rate of 19.5%, with actuarial rates of 0%, 5%, 5%, 21%, 30% and 30% at 1, 2, 3, 4, 5 and 6 years follow-up. In the unirradiated group, there were no cases of severe CC. This difference is highly significant (p < 0.001). Hormones and chemotherapy were not significantly associated with severe CC. Conclusions: This series showed a significantly higher rate of severe CC with postoperative RT. This finding has important clinical implications, when counselling patients for immediate breast reconstruction

Resolution effects in reconstructing ancestral genomes.

Science.gov (United States)

Zheng, Chunfang; Jeong, Yuji; Turcotte, Madisyn Gabrielle; Sankoff, David

2018-05-09

The reconstruction of ancestral genomes must deal with the problem of resolution, necessarily involving a trade-off between trying to identify genomic details and being overwhelmed by noise at higher resolutions. We use the median reconstruction at the synteny block level, of the ancestral genome of the order Gentianales, based on coffee, Rhazya stricta and grape, to exemplify the effects of resolution (granularity) on comparative genomic analyses. We show how decreased resolution blurs the differences between evolving genomes, with respect to rate, mutational process and other characteristics.

Evaluating climate field reconstruction techniques using improved emulations of real-world conditions

Science.gov (United States)

Wang, J.; Emile-Geay, J.; Guillot, D.; Smerdon, J. E.; Rajaratnam, B.

2014-01-01

Pseudoproxy experiments (PPEs) have become an important framework for evaluating paleoclimate reconstruction methods. Most existing PPE studies assume constant proxy availability through time and uniform proxy quality across the pseudoproxy network. Real multiproxy networks are, however, marked by pronounced disparities in proxy quality, and a steep decline in proxy availability back in time, either of which may have large effects on reconstruction skill. A suite of PPEs constructed from a millennium-length general circulation model (GCM) simulation is thus designed to mimic these various real-world characteristics. The new pseudoproxy network is used to evaluate four climate field reconstruction (CFR) techniques: truncated total least squares embedded within the regularized EM (expectation-maximization) algorithm (RegEM-TTLS), the Mann et al. (2009) implementation of RegEM-TTLS (M09), canonical correlation analysis (CCA), and Gaussian graphical models embedded within RegEM (GraphEM). Each method's risk properties are also assessed via a 100-member noise ensemble. Contrary to expectation, it is found that reconstruction skill does not vary monotonically with proxy availability, but also is a function of the type and amplitude of climate variability (forced events vs. internal variability). The use of realistic spatiotemporal pseudoproxy characteristics also exposes large inter-method differences. Despite the comparable fidelity in reconstructing the global mean temperature, spatial skill varies considerably between CFR techniques. Both GraphEM and CCA efficiently exploit teleconnections, and produce consistent reconstructions across the ensemble. RegEM-TTLS and M09 appear advantageous for reconstructions on highly noisy data, but are subject to larger stochastic variations across different realizations of pseudoproxy noise. Results collectively highlight the importance of designing realistic pseudoproxy networks and implementing multiple noise realizations of PPEs

Analysis of noise lines in the Virgo C7 data

International Nuclear Information System (INIS)

Acernese, F; Amico, P; Alshourbagy, M

2007-01-01

The paper presents a description of the work of detection and identification of frequency lines in the Virgo dark fringe data from run C7. A number of methods are highlighted by which noise frequency lines are detected by data analysis and measurements in the laboratory. In this paper we give a description of the list of noise line candidates provided by the pulsar search analysis, the investigation of 10 Hz (and harmonics) noise, violin modes, noise from the end station buildings' air conditioners, sidebands in calibration lines and aliasing in the 4 kHz reconstructed data

Analysis of noise lines in the Virgo C7 data

Energy Technology Data Exchange (ETDEWEB)

Acernese, F [INFN, Sezione di Napoli and/or Universita di Napoli ' Federico II' Complesso Universitario di Monte S Angelo, and/or Universita di Salerno, Fisciano (Italy); Amico, P [INFN, Sezione di Perugia and/or Universita di Perugia, Perugia (Italy); Alshourbagy, M [INFN, Sezione di Pisa and/or Universita di Pisa, Pisa (Italy)] (and others)

2007-10-07

The paper presents a description of the work of detection and identification of frequency lines in the Virgo dark fringe data from run C7. A number of methods are highlighted by which noise frequency lines are detected by data analysis and measurements in the laboratory. In this paper we give a description of the list of noise line candidates provided by the pulsar search analysis, the investigation of 10 Hz (and harmonics) noise, violin modes, noise from the end station buildings' air conditioners, sidebands in calibration lines and aliasing in the 4 kHz reconstructed data.

Classical noise, quantum noise and secure communication

International Nuclear Information System (INIS)

Tannous, C; Langlois, J

2016-01-01

Secure communication based on message encryption might be performed by combining the message with controlled noise (called pseudo-noise) as performed in spread-spectrum communication used presently in Wi-Fi and smartphone telecommunication systems. Quantum communication based on entanglement is another route for securing communications as demonstrated by several important experiments described in this work. The central role played by the photon in unifying the description of classical and quantum noise as major ingredients of secure communication systems is highlighted and described on the basis of the classical and quantum fluctuation dissipation theorems. (review)

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

Bayesian PET image reconstruction incorporating anato-functional joint entropy

International Nuclear Information System (INIS)

Tang Jing; Rahmim, Arman

2009-01-01

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

Noise minimization in eukaryotic gene expression.

Directory of Open Access Journals (Sweden)

Hunter B Fraser

2004-06-01

Full Text Available All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or "noise." Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

Noise minimization in eukaryotic gene expression

Energy Technology Data Exchange (ETDEWEB)

Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

2004-01-15

All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection.

Noise minimization in eukaryotic gene expression

International Nuclear Information System (INIS)

Fraser, Hunter B.; Hirsh, Aaron E.; Giaever, Guri; Kumm, Jochen; Eisen, Michael B.

2004-01-01

All organisms have elaborate mechanisms to control rates of protein production. However, protein production is also subject to stochastic fluctuations, or noise. Several recent studies in Saccharomyces cerevisiae and Escherichia coli have investigated the relationship between transcription and translation rates and stochastic fluctuations in protein levels, or more generally, how such randomness is a function of intrinsic and extrinsic factors. However, the fundamental question of whether stochasticity in protein expression is generally biologically relevant has not been addressed, and it remains unknown whether random noise in the protein production rate of most genes significantly affects the fitness of any organism. We propose that organisms should be particularly sensitive to variation in the protein levels of two classes of genes: genes whose deletion is lethal to the organism and genes that encode subunits of multiprotein complexes. Using an experimentally verified model of stochastic gene expression in S. cerevisiae, we estimate the noise in protein production for nearly every yeast gene, and confirm our prediction that the production of essential and complex-forming proteins involves lower levels of noise than does the production of most other genes. Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection

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)

Improving Weak Lensing Mass Map Reconstructions using Gaussian and Sparsity Priors: Application to DES SV

Science.gov (United States)

Jeffrey, N.; Abdalla, F. B.; Lahav, O.; Lanusse, F.; Starck, J.-L.; Leonard, A.; Kirk, D.; Chang, C.; Baxter, E.; Kacprzak, T.; Seitz, S.; Vikram, V.; Whiteway, L.; Abbott, T. M. C.; Allam, S.; Avila, S.; Bertin, E.; Brooks, D.; Rosell, A. Carnero; Kind, M. Carrasco; Carretero, J.; Castander, F. J.; Crocce, M.; Cunha, C. E.; D'Andrea, C. B.; da Costa, L. N.; Davis, C.; De Vicente, J.; Desai, S.; Doel, P.; Eifler, T. F.; Evrard, A. E.; Flaugher, B.; Fosalba, P.; Frieman, J.; García-Bellido, J.; Gerdes, D. W.; Gruen, D.; Gruendl, R. A.; Gschwend, J.; Gutierrez, G.; Hartley, W. G.; Honscheid, K.; Hoyle, B.; James, D. J.; Jarvis, M.; Kuehn, K.; Lima, M.; Lin, H.; March, M.; Melchior, P.; Menanteau, F.; Miquel, R.; Plazas, A. A.; Reil, K.; Roodman, A.; Sanchez, E.; Scarpine, V.; Schubnell, M.; Sevilla-Noarbe, I.; Smith, M.; Soares-Santos, M.; Sobreira, F.; Suchyta, E.; Swanson, M. E. C.; Tarle, G.; Thomas, D.; Walker, A. R.

2018-05-01

Mapping the underlying density field, including non-visible dark matter, using weak gravitational lensing measurements is now a standard tool in cosmology. Due to its importance to the science results of current and upcoming surveys, the quality of the convergence reconstruction methods should be well understood. We compare three methods: Kaiser-Squires (KS), Wiener filter, and GLIMPSE. KS is a direct inversion, not accounting for survey masks or noise. The Wiener filter is well-motivated for Gaussian density fields in a Bayesian framework. GLIMPSE uses sparsity, aiming to reconstruct non-linearities in the density field. We compare these methods with several tests using public Dark Energy Survey (DES) Science Verification (SV) data and realistic DES simulations. The Wiener filter and GLIMPSE offer substantial improvements over smoothed KS with a range of metrics. Both the Wiener filter and GLIMPSE convergence reconstructions show a 12% improvement in Pearson correlation with the underlying truth from simulations. To compare the mapping methods' abilities to find mass peaks, we measure the difference between peak counts from simulated ΛCDM shear catalogues and catalogues with no mass fluctuations (a standard data vector when inferring cosmology from peak statistics); the maximum signal-to-noise of these peak statistics is increased by a factor of 3.5 for the Wiener filter and 9 for GLIMPSE. With simulations we measure the reconstruction of the harmonic phases; the phase residuals' concentration is improved 17% by GLIMPSE and 18% by the Wiener filter. The correlation between reconstructions from data and foreground redMaPPer clusters is increased 18% by the Wiener filter and 32% by GLIMPSE.

Reconstruction of hyperspectral image using matting model for classification

Science.gov (United States)

Xie, Weiying; Li, Yunsong; Ge, Chiru

2016-05-01

Although hyperspectral images (HSIs) captured by satellites provide much information in spectral regions, some bands are redundant or have large amounts of noise, which are not suitable for image analysis. To address this problem, we introduce a method for reconstructing the HSI with noise reduction and contrast enhancement using a matting model for the first time. The matting model refers to each spectral band of an HSI that can be decomposed into three components, i.e., alpha channel, spectral foreground, and spectral background. First, one spectral band of an HSI with more refined information than most other bands is selected, and is referred to as an alpha channel of the HSI to estimate the hyperspectral foreground and hyperspectral background. Finally, a combination operation is applied to reconstruct the HSI. In addition, the support vector machine (SVM) classifier and three sparsity-based classifiers, i.e., orthogonal matching pursuit (OMP), simultaneous OMP, and OMP based on first-order neighborhood system weighted classifiers, are utilized on the reconstructed HSI and the original HSI to verify the effectiveness of the proposed method. Specifically, using the reconstructed HSI, the average accuracy of the SVM classifier can be improved by as much as 19%.

A Literature Survey of Noise Pollution.

Science.gov (United States)

Shih, H. H.

Physically, noise is a complex sound that has little or no periodicity. However, the essential characteristic of noise is its undesirability. Thus, noise can be defined as any annoying or unwanted sound. In recent years, the rapid increase of noise level in our environment has become a national public health hazard. Noise affects man's state of…

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.

Severe difficulties with word recognition in noise after platinum chemotherapy in childhood, and improvements with open-fitting hearing-aids.

Science.gov (United States)

Einarsson, Einar-Jón; Petersen, Hannes; Wiebe, Thomas; Fransson, Per-Anders; Magnusson, Måns; Moëll, Christian

2011-10-01

To investigate word recognition in noise in subjects treated in childhood with chemotherapy, study benefits of open-fitting hearing-aids for word recognition, and investigate whether self-reported hearing-handicap corresponded to subjects' word recognition ability. Subjects diagnosed with cancer and treated with platinum-based chemotherapy in childhood underwent audiometric evaluations. Fifteen subjects (eight females and seven males) fulfilled the criteria set for the study, and four of those received customized open-fitting hearing-aids. Subjects with cisplatin-induced ototoxicity had severe difficulties recognizing words in noise, and scored as low as 54% below reference scores standardized for age and degree of hearing loss. Hearing-impaired subjects' self-reported hearing-handicap correlated significantly with word recognition in a quiet environment but not in noise. Word recognition in noise improved markedly (up to 46%) with hearing-aids, and the self-reported hearing-handicap and disability score were reduced by more than 50%. This study demonstrates the importance of testing word recognition in noise in subjects treated with platinum-based chemotherapy in childhood, and to use specific custom-made questionnaires to evaluate the experienced hearing-handicap. Open-fitting hearing-aids are a good alternative for subjects suffering from poor word recognition in noise.

Reconstructive Surgery for Severe Penile Inadequacy: Phalloplasty with a Free Radial Forearm Flap or a Pedicled Anterolateral Thigh Flap

Directory of Open Access Journals (Sweden)

N. Lumen

2008-01-01

Full Text Available Objectives. Severe penile inadequacy in adolescents is rare. Phallic reconstruction to treat this devastating condition is a major challenge to the reconstructive surgeon. Phallic reconstruction using the free radial forearm flap (RFF or the pedicled anterolateral thigh flap (ALTF has been routinely used in female-to-male transsexuals. Recently we started to use these techniques in the treatment of severe penile inadequacy. Methods. Eleven males (age 15 to 42 years were treated with a phallic reconstruction. The RFF is our method of choice; the ALTF is an alternative when a free flap is contraindicated or less desired by the patient. The RFF was used in 7 patients, the ALTF in 4 patients. Mean followup was 25 months (range: 4–49 months. Aesthetic and functional results were evaluated. Results. There were no complications related to the flap. Aesthetic results were judged as “good” in 9 patients and “moderate” in 2 patients. Sensitivity in the RFF was superior compared to the ALTF. Four patients developed urinary complications (stricture and/or fistula. Six patients underwent erectile implant surgery. In 2 patients the erectile implant had to be removed due to infection or erosion. Conclusion. In case of severe penile inadequacy due to whatever condition, a phalloplasty is the preferred treatment nowadays. The free radial forearm flap is still the method of choice. The anterolateral thigh flap can be a good alternative, especially when free flaps are contraindicated, but sensitivity is markedly inferior in these flaps.

Lensing reconstruction from a patchwork of polarization maps

International Nuclear Information System (INIS)

Namikawa, Toshiya; Nagata, Ryo

2014-01-01

The lensing signals involved in CMB polarization maps have already been measured with ground-based experiments such as SPTpol and POLARBEAR, and would become important as a probe of cosmological and astrophysical issues in the near future. Sizes of polarization maps from ground-based experiments are, however, limited by contamination of long wavelength modes of observational noise. To further extract the lensing signals, we explore feasibility of measuring lensing signals from a collection of small sky maps each of which is observed separately by a ground-based large telescope, i.e., lensing reconstruction from a patchwork map of large sky coverage organized from small sky patches. We show that, although the B-mode power spectrum obtained from the patchwork map is biased due to baseline uncertainty, bias on the lensing potential would be negligible if the B-mode on scales larger than the blowup scale of 1/f noise is removed in the lensing reconstruction. As examples of cosmological applications, we also show 1) the cross-correlations between the reconstructed lensing potential and full-sky temperature/polarization maps from satellite missions such as PLANCK and LiteBIRD, and 2) the use of the reconstructed potential for delensing B-mode polarization of LiteBIRD observation

FACTORS AFFECTING ROAD TRAFFIC NOISE ANNOYANCE AMONG WHITE-COLLAR EMPLOYEES WORKING IN TEHRAN

Directory of Open Access Journals (Sweden)

*1I. Alimohammadi, 2P. Nassiri, 3M. Azkhosh, 4M. Hoseini

2010-01-01

Full Text Available The effect of personal and attitudinal factors, noise level, hearing status and psychological traits on traffic-related noise annoyance among white-collar employees working in Tehran has been carefully analyzed. This survey has been conducted by interviewing 495 citizens working in non-manufacturing industries in Tehran, using questionnaires, Weinstein noise sensitivity scale, Beck’s depression, Buss and perry’s aggression, Zung’s anxiety, job satisfaction and Eysenc’s personality inventory. These citizens were office workers or store employees. Noise annoyance was determined both by numerical-based questionnaire criterion and by verbal index. Personal information, attitudinal factors and hearing conditions were determined using a general questionnaire. The amount of workplace noise the participants were exposed to was directly measured at their workplaces. It was revealed that among personal factors, age (p=0.030, marital status (p=0.004, residential period (p=0.001 and wealth (p=0.04 were related to noise annoyance. Attitudinal factors including sensitivity to noise (p=0.001, individual’s opinion on the need to control the noise (p=0.000 and individuals’ assessment of the amount of the workplace ambient noise (p= 0.000 were found to have relationship with noise annoyance. No meaningful relationship was seen between the equivalent noise level (p=0.879 and statistical noise level of L90 (p=0.909. The present study revealed that among all effective factors involved in noise annoyance, attitudinal factors had the most significant role in this regard.

Evaluation of reconstruction techniques in regional cerebral blood flow SPECT using trade-off plots: a Monte Carlo study.

Science.gov (United States)

Olsson, Anna; Arlig, Asa; Carlsson, Gudrun Alm; Gustafsson, Agnetha

2007-09-01

The image quality of single photon emission computed tomography (SPECT) depends on the reconstruction algorithm used. The purpose of the present study was to evaluate parameters in ordered subset expectation maximization (OSEM) and to compare systematically with filtered back-projection (FBP) for reconstruction of regional cerebral blood flow (rCBF) SPECT, incorporating attenuation and scatter correction. The evaluation was based on the trade-off between contrast recovery and statistical noise using different sizes of subsets, number of iterations and filter parameters. Monte Carlo simulated SPECT studies of a digital human brain phantom were used. The contrast recovery was calculated as measured contrast divided by true contrast. Statistical noise in the reconstructed images was calculated as the coefficient of variation in pixel values. A constant contrast level was reached above 195 equivalent maximum likelihood expectation maximization iterations. The choice of subset size was not crucial as long as there were > or = 2 projections per subset. The OSEM reconstruction was found to give 5-14% higher contrast recovery than FBP for all clinically relevant noise levels in rCBF SPECT. The Butterworth filter, power 6, achieved the highest stable contrast recovery level at all clinically relevant noise levels. The cut-off frequency should be chosen according to the noise level accepted in the image. Trade-off plots are shown to be a practical way of deciding the number of iterations and subset size for the OSEM reconstruction and can be used for other examination types in nuclear medicine.

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

Science.gov (United States)

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

2014-03-01

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

Choice of reconstructed tissue properties affects interpretation of lung EIT images.

Science.gov (United States)

Grychtol, Bartłomiej; Adler, Andy

2014-06-01

Electrical impedance tomography (EIT) estimates an image of change in electrical properties within a body from stimulations and measurements at surface electrodes. There is significant interest in EIT as a tool to monitor and guide ventilation therapy in mechanically ventilated patients. In lung EIT, the EIT inverse problem is commonly linearized and only changes in electrical properties are reconstructed. Early algorithms reconstructed changes in resistivity, while most recent work using the finite element method reconstructs conductivity. Recently, we demonstrated that EIT images of ventilation can be misleading if the electrical contrasts within the thorax are not taken into account during the image reconstruction process. In this paper, we explore the effect of the choice of the reconstructed electrical properties (resistivity or conductivity) on the resulting EIT images. We show in simulation and experimental data that EIT images reconstructed with the same algorithm but with different parametrizations lead to large and clinically significant differences in the resulting images, which persist even after attempts to eliminate the impact of the parameter choice by recovering volume changes from the EIT images. Since there is no consensus among the most popular reconstruction algorithms and devices regarding the parametrization, this finding has implications for potential clinical use of EIT. We propose a program of research to develop reconstruction techniques that account for both the relationship between air volume and electrical properties of the lung and artefacts introduced by the linearization.

Choice of reconstructed tissue properties affects interpretation of lung EIT images

International Nuclear Information System (INIS)

Grychtol, Bartłomiej; Adler, Andy

2014-01-01

Electrical impedance tomography (EIT) estimates an image of change in electrical properties within a body from stimulations and measurements at surface electrodes. There is significant interest in EIT as a tool to monitor and guide ventilation therapy in mechanically ventilated patients. In lung EIT, the EIT inverse problem is commonly linearized and only changes in electrical properties are reconstructed. Early algorithms reconstructed changes in resistivity, while most recent work using the finite element method reconstructs conductivity. Recently, we demonstrated that EIT images of ventilation can be misleading if the electrical contrasts within the thorax are not taken into account during the image reconstruction process. In this paper, we explore the effect of the choice of the reconstructed electrical properties (resistivity or conductivity) on the resulting EIT images. We show in simulation and experimental data that EIT images reconstructed with the same algorithm but with different parametrizations lead to large and clinically significant differences in the resulting images, which persist even after attempts to eliminate the impact of the parameter choice by recovering volume changes from the EIT images. Since there is no consensus among the most popular reconstruction algorithms and devices regarding the parametrization, this finding has implications for potential clinical use of EIT. We propose a program of research to develop reconstruction techniques that account for both the relationship between air volume and electrical properties of the lung and artefacts introduced by the linearization. (paper)

Interplay of Gene Expression Noise and Ultrasensitive Dynamics Affects Bacterial Operon Organization

Science.gov (United States)

Ray, J. Christian J; Igoshin, Oleg A.

2012-01-01

Bacterial chromosomes are organized into polycistronic cotranscribed operons, but the evolutionary pressures maintaining them are unclear. We hypothesized that operons alter gene expression noise characteristics, resulting in selection for or against maintaining operons depending on network architecture. Mathematical models for 6 functional classes of network modules showed that three classes exhibited decreased noise and 3 exhibited increased noise with same-operon cotranscription of interacting proteins. Noise reduction was often associated with a decreased chance of reaching an ultrasensitive threshold. Stochastic simulations of the lac operon demonstrated that the predicted effects of transcriptional coupling hold for a complex network module. We employed bioinformatic analysis to find overrepresentation of noise-minimizing operon organization compared with randomized controls. Among constitutively expressed physically interacting protein pairs, higher coupling frequencies appeared at lower expression levels, where noise effects are expected to be dominant. Our results thereby suggest an important role for gene expression noise, in many cases interacting with an ultrasensitive switch, in maintaining or selecting for operons in bacterial chromosomes. PMID:22956903

Qualitative and quantitative improvements of PET reconstruction on GPU architecture

International Nuclear Information System (INIS)

Autret, Awen

2016-01-01

In positron emission tomography, reconstructed images suffer from a high noise level and a low resolution. Iterative reconstruction processes require an estimation of the system response (scanner and patient) and the quality of the images depends on the accuracy of this estimate. Accurate and fast to compute models already exists for the attenuation, scattering, random coincidences and dead times. Thus, this thesis focuses on modeling the system components associated with the detector response and the positron range. A new multi-GPU parallelization of the reconstruction based on a cutting of the volume is also proposed to speed up the reconstruction exploiting the computing power of such architectures. The proposed detector response model is based on a multi-ray approach that includes all the detector effects as the geometry and the scattering in the crystals. An evaluation study based on data obtained through Mote Carlo simulation (MCS) showed this model provides reconstructed images with a better contrast to noise ratio and resolution compared with those of the methods from the state of the art. The proposed positron range model is based on a simplified MCS, integrated into the forward projector during the reconstruction. A GPU implementation of this method allows running MCS three order of magnitude faster than the same simulation on GATE, while providing similar results. An evaluation study shows this model integrated in the reconstruction gives images with better contrast recovery and resolution while avoiding artifacts. (author)

Near-source noise suppression of AMT by compressive sensing and mathematical morphology filtering

Science.gov (United States)

Li, Guang; Xiao, Xiao; Tang, Jing-Tian; Li, Jin; Zhu, Hui-Jie; Zhou, Cong; Yan, Fa-Bao

2017-12-01

In deep mineral exploration, the acquisition of audio magnetotelluric (AMT) data is severely affected by ambient noise near the observation sites; This near-field noise restricts investigation depths. Mathematical morphological filtering (MMF) proved effective in suppressing large-scale strong and variably shaped noise, typically low-frequency noise, but can not deal with pulse noise of AMT data. We combine compressive sensing and MMF. First, we use MMF to suppress the large-scale strong ambient noise; second, we use the improved orthogonal match pursuit (IOMP) algorithm to remove the residual pulse noise. To remove the noise and protect the useful AMT signal, a redundant dictionary that matches with spikes and is insensitive to the useful signal is designed. Synthetic and field data from the Luzong field suggest that the proposed method suppresses the near-source noise and preserves the signal well; thus, better results are obtained that improve the output of either MMF or IOMP.

Accuracy of dynamical-decoupling-based spectroscopy of Gaussian noise

Science.gov (United States)

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.

Axially symmetric reconstruction of plasma emission and absorption coefficients

International Nuclear Information System (INIS)

Yang Lixin; Jia Hui; Yang Jiankun; Li Xiujian; Chen Shaorong; Liu Xishun

2013-01-01

A layered structure imaging model is developed in order to reconstruct emission coefficients and absorption coefficients simultaneously, in laser fusion core plasma diagnostics. A novel axially symmetric reconstruction method that utilizes the LM (Levenberg-Marquardt) nonlinear least squares minimization algorithm is proposed based on the layered structure. Numerical simulation results demonstrate that the proposed method is sufficiently accurate to reconstruct emission coefficients and absorption coefficients, and when the standard deviation of noise is 0.01, the errors of emission coefficients and absorption coefficients are 0.17, 0.22, respectively. Furthermore, this method could perform much better on reconstruction effect compared with traditional inverse Abel transform algorithms. (authors)

TH-A-18C-07: Noise Suppression in Material Decomposition for Dual-Energy CT

International Nuclear Information System (INIS)

Dong, X; Petrongolo, M; Wang, T; Zhu, L

2014-01-01

Purpose: A general problem of dual-energy CT (DECT) is that the decomposition is sensitive to noise in the two sets of dual-energy projection data, resulting in severely degraded qualities of decomposed images. We have previously proposed an iterative denoising method for DECT. Using a linear decomposition function, the method does not gain the full benefits of DECT on beam-hardening correction. In this work, we expand the framework of our iterative method to include non-linear decomposition models for noise suppression in DECT. Methods: We first obtain decomposed projections, which are free of beam-hardening artifacts, using a lookup table pre-measured on a calibration phantom. First-pass material images with high noise are reconstructed from the decomposed projections using standard filter-backprojection reconstruction. Noise on the decomposed images is then suppressed by an iterative method, which is formulated in the form of least-square estimation with smoothness regularization. Based on the design principles of a best linear unbiased estimator, we include the inverse of the estimated variance-covariance matrix of the decomposed images as the penalty weight in the least-square term. Analytical formulae are derived to compute the variance-covariance matrix from the measured decomposition lookup table. Results: We have evaluated the proposed method via phantom studies. Using non-linear decomposition, our method effectively suppresses the streaking artifacts of beam-hardening and obtains more uniform images than our previous approach based on a linear model. The proposed method reduces the average noise standard deviation of two basis materials by one order of magnitude without sacrificing the spatial resolution. Conclusion: We propose a general framework of iterative denoising for material decomposition of DECT. Preliminary phantom studies have shown the proposed method improves the image uniformity and reduces noise level without resolution loss. In the future

GRACE star camera noise

Science.gov (United States)

Harvey, Nate

2016-08-01

Extending results from previous work by Bandikova et al. (2012) and Inacio et al. (2015), this paper analyzes Gravity Recovery and Climate Experiment (GRACE) star camera attitude measurement noise by processing inter-camera quaternions from 2003 to 2015. We describe a correction to star camera data, which will eliminate a several-arcsec twice-per-rev error with daily modulation, currently visible in the auto-covariance function of the inter-camera quaternion, from future GRACE Level-1B product releases. We also present evidence supporting the argument that thermal conditions/settings affect long-term inter-camera attitude biases by at least tens-of-arcsecs, and that several-to-tens-of-arcsecs per-rev star camera errors depend largely on field-of-view.

Sparse regularization for EIT reconstruction incorporating structural information derived from medical imaging.

Science.gov (United States)

Gong, Bo; Schullcke, Benjamin; Krueger-Ziolek, Sabine; Mueller-Lisse, Ullrich; Moeller, Knut

2016-06-01

Electrical impedance tomography (EIT) reconstructs the conductivity distribution of a domain using electrical data on its boundary. This is an ill-posed inverse problem usually solved on a finite element mesh. For this article, a special regularization method incorporating structural information of the targeted domain is proposed and evaluated. Structural information was obtained either from computed tomography images or from preliminary EIT reconstructions by a modified k-means clustering. The proposed regularization method integrates this structural information into the reconstruction as a soft constraint preferring sparsity in group level. A first evaluation with Monte Carlo simulations indicated that the proposed solver is more robust to noise and the resulting images show fewer artifacts. This finding is supported by real data analysis. The structure based regularization has the potential to balance structural a priori information with data driven reconstruction. It is robust to noise, reduces artifacts and produces images that reflect anatomy and are thus easier to interpret for physicians.

Underwater noise modelling for environmental impact assessment

Energy Technology Data Exchange (ETDEWEB)

Farcas, Adrian [Centre for Environment, Fisheries and Aquaculture Science (Cefas), Pakefield Road, Lowestoft, NR33 0HT (United Kingdom); Thompson, Paul M. [Lighthouse Field Station, Institute of Biological and Environmental Sciences, University of Aberdeen, Cromarty IV11 8YL (United Kingdom); Merchant, Nathan D., E-mail: nathan.merchant@cefas.co.uk [Centre for Environment, Fisheries and Aquaculture Science (Cefas), Pakefield Road, Lowestoft, NR33 0HT (United Kingdom)

2016-02-15

Assessment of underwater noise is increasingly required by regulators of development projects in marine and freshwater habitats, and noise pollution can be a constraining factor in the consenting process. Noise levels arising from the proposed activity are modelled and the potential impact on species of interest within the affected area is then evaluated. Although there is considerable uncertainty in the relationship between noise levels and impacts on aquatic species, the science underlying noise modelling is well understood. Nevertheless, many environmental impact assessments (EIAs) do not reflect best practice, and stakeholders and decision makers in the EIA process are often unfamiliar with the concepts and terminology that are integral to interpreting noise exposure predictions. In this paper, we review the process of underwater noise modelling and explore the factors affecting predictions of noise exposure. Finally, we illustrate the consequences of errors and uncertainties in noise modelling, and discuss future research needs to reduce uncertainty in noise assessments.

Underwater noise modelling for environmental impact assessment

International Nuclear Information System (INIS)

Farcas, Adrian; Thompson, Paul M.; Merchant, Nathan D.

2016-01-01

Assessment of underwater noise is increasingly required by regulators of development projects in marine and freshwater habitats, and noise pollution can be a constraining factor in the consenting process. Noise levels arising from the proposed activity are modelled and the potential impact on species of interest within the affected area is then evaluated. Although there is considerable uncertainty in the relationship between noise levels and impacts on aquatic species, the science underlying noise modelling is well understood. Nevertheless, many environmental impact assessments (EIAs) do not reflect best practice, and stakeholders and decision makers in the EIA process are often unfamiliar with the concepts and terminology that are integral to interpreting noise exposure predictions. In this paper, we review the process of underwater noise modelling and explore the factors affecting predictions of noise exposure. Finally, we illustrate the consequences of errors and uncertainties in noise modelling, and discuss future research needs to reduce uncertainty in noise assessments.

Orbital Reconstruction: Patient-Specific Orbital Floor Reconstruction Using a Mirroring Technique and a Customized Titanium Mesh.

Science.gov (United States)

Tarsitano, Achille; Badiali, Giovanni; Pizzigallo, Angelo; Marchetti, Claudio

2016-10-01

Enophthalmos is a severe complication of primary reconstruction of orbital floor fractures. The goal of secondary reconstruction procedures is to restore symmetrical globe positions to recover function and aesthetics. The authors propose a new method of orbital floor reconstruction using a mirroring technique and a customized titanium mesh, printed using a direct metal laser-sintering method. This reconstructive protocol involves 4 steps: mirroring of the healthy orbit at the affected site, virtual design of a patient-specific orbital floor mesh, CAM procedures for direct laser-sintering of the customized titanium mesh, and surgical insertion of the device. Using a computed tomography data set, the normal, uninjured side of the craniofacial skeleton was reflected onto the contralateral injured side, and a reconstructive orbital floor mesh was designed virtually on the mirrored orbital bone surface. The solid-to-layer files of the mesh were then manufactured using direct metal laser sintering, which resolves the shaping and bending biases inherent in the indirect method. An intraoperative navigation system ensured accuracy of the entire procedure. Clinical outcomes were assessed using 3dMD photogrammetry and computed tomography data in 7 treated patients. The technique described here appears to be a viable method to correct complex orbital floor defects needing delayed reconstruction. This study represents the first step in the development of a wider experimental protocol for orbital floor reconstruction using computer-assisted design-computer-assisted manufacturing technology.

Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction

Energy Technology Data Exchange (ETDEWEB)

Koc, Gonca; Courtier, Jesse L.; Phelps, Andrew; Marcovici, Peter A.; MacKenzie, John D. [UCSF Benioff Children' s Hospital, Department of Radiology and Biomedical Imaging, San Francisco, CA (United States)

2014-07-15

Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo trademark), a technique developed to improve image quality and reduce noise. To evaluate Veo trademark as an improved method when compared to adaptive statistical iterative reconstruction (ASIR trademark) for the depiction of small vessels on pediatric CT. Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo trademark and ASIR trademark algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests. Readers stated a preference for Veo trademark over ASIR trademark images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo trademark vs. ASIR trademark reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo trademark and ASIR trademark images. Veo trademark consistently showed more of the vessel anatomy: longer vessel length and more branching vessels. When compared to the more established adaptive statistical iterative reconstruction algorithm, model

Self-adapting denoising, alignment and reconstruction in electron tomography in materials science

Energy Technology Data Exchange (ETDEWEB)

Printemps, Tony, E-mail: tony.printemps@cea.fr [Université Grenoble Alpes, F-38000 Grenoble (France); CEA, LETI, MINATEC Campus, F-38054 Grenoble (France); Mula, Guido [Dipartimento di Fisica, Università di Cagliari, Cittadella Universitaria, S.P. 8km 0.700, 09042 Monserrato (Italy); Sette, Daniele; Bleuet, Pierre; Delaye, Vincent; Bernier, Nicolas; Grenier, Adeline; Audoit, Guillaume; Gambacorti, Narciso; Hervé, Lionel [Université Grenoble Alpes, F-38000 Grenoble (France); CEA, LETI, MINATEC Campus, F-38054 Grenoble (France)

2016-01-15

An automatic procedure for electron tomography is presented. This procedure is adapted for specimens that can be fashioned into a needle-shaped sample and has been evaluated on inorganic samples. It consists of self-adapting denoising, automatic and accurate alignment including detection and correction of tilt axis, and 3D reconstruction. We propose the exploitation of a large amount of information of an electron tomography acquisition to achieve robust and automatic mixed Poisson–Gaussian noise parameter estimation and denoising using undecimated wavelet transforms. The alignment is made by mixing three techniques, namely (i) cross-correlations between neighboring projections, (ii) common line algorithm to get a precise shift correction in the direction of the tilt axis and (iii) intermediate reconstructions to precisely determine the tilt axis and shift correction in the direction perpendicular to that axis. Mixing alignment techniques turns out to be very efficient and fast. Significant improvements are highlighted in both simulations and real data reconstructions of porous silicon in high angle annular dark field mode and agglomerated silver nanoparticles in incoherent bright field mode. 3D reconstructions obtained with minimal user-intervention present fewer artefacts and less noise, which permits easier and more reliable segmentation and quantitative analysis. After careful sample preparation and data acquisition, the denoising procedure, alignment and reconstruction can be achieved within an hour for a 3D volume of about a hundred million voxels, which is a step toward a more routine use of electron tomography. - Highlights: • Goal: perform a reliable and user-independent 3D electron tomography reconstruction. • Proposed method: self-adapting denoising and alignment prior to 3D reconstruction. • Noise estimation and denoising are performed using wavelet transform. • Tilt axis determination is done automatically as well as projection alignment. �

Computed tomography depiction of small pediatric vessels with model-based iterative reconstruction

International Nuclear Information System (INIS)

Koc, Gonca; Courtier, Jesse L.; Phelps, Andrew; Marcovici, Peter A.; MacKenzie, John D.

2014-01-01

Computed tomography (CT) is extremely important in characterizing blood vessel anatomy and vascular lesions in children. Recent advances in CT reconstruction technology hold promise for improved image quality and also reductions in radiation dose. This report evaluates potential improvements in image quality for the depiction of small pediatric vessels with model-based iterative reconstruction (Veo trademark), a technique developed to improve image quality and reduce noise. To evaluate Veo trademark as an improved method when compared to adaptive statistical iterative reconstruction (ASIR trademark) for the depiction of small vessels on pediatric CT. Seventeen patients (mean age: 3.4 years, range: 2 days to 10.0 years; 6 girls, 11 boys) underwent contrast-enhanced CT examinations of the chest and abdomen in this HIPAA compliant and institutional review board approved study. Raw data were reconstructed into separate image datasets using Veo trademark and ASIR trademark algorithms (GE Medical Systems, Milwaukee, WI). Four blinded radiologists subjectively evaluated image quality. The pulmonary, hepatic, splenic and renal arteries were evaluated for the length and number of branches depicted. Datasets were compared with parametric and non-parametric statistical tests. Readers stated a preference for Veo trademark over ASIR trademark images when subjectively evaluating image quality criteria for vessel definition, image noise and resolution of small anatomical structures. The mean image noise in the aorta and fat was significantly less for Veo trademark vs. ASIR trademark reconstructed images. Quantitative measurements of mean vessel lengths and number of branches vessels delineated were significantly different for Veo trademark and ASIR trademark images. Veo trademark consistently showed more of the vessel anatomy: longer vessel length and more branching vessels. When compared to the more established adaptive statistical iterative reconstruction algorithm, model

Reconstruction of the solid transport of the river Tiber by a stochastic model

International Nuclear Information System (INIS)

Grimaldi, S.; Magnaldi, S.; Margaritora, G.

1999-01-01

The chronological series of cumulative suspended solids transport observed at Ripetta station in river Tiber (Rome, Italy) is reconstructed on the base of the correlation with the chronological series of liquid discharge, using a TFN (Transfer Function Noise) stochastic model with SARIMA noise. The results are compared with those similar reconstructions based on linear correlation that can be found in literature. Finally, the importance of floods intensity and frequency decrease observed after 1950 at Ripetta station is shown as not negligible aggravation for the decrease solid transport in river Tiber [it

Orthotropic conductivity reconstruction with virtual-resistive network and Faraday's law

KAUST Repository

Lee, Min-Gi

2015-06-01

We obtain the existence and the uniqueness at the same time in the reconstruction of orthotropic conductivity in two-space dimensions by using two sets of internal current densities and boundary conductivity. The curl-free equation of Faraday\\'s law is taken instead of the elliptic equation in a divergence form that is typically used in electrical impedance tomography. A reconstruction method based on layered bricks-type virtual-resistive network is developed to reconstruct orthotropic conductivity with up to 40% multiplicative noise.

The SRT reconstruction algorithm for semiquantification in PET imaging

Energy Technology Data Exchange (ETDEWEB)

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

2015-10-15

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

The SRT reconstruction algorithm for semiquantification in PET imaging

International Nuclear Information System (INIS)

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

2015-01-01

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

Feature reconstruction of LFP signals based on PLSR in the neural information decoding study.

Science.gov (United States)

Yonghui Dong; Zhigang Shang; Mengmeng Li; Xinyu Liu; Hong Wan

2017-07-01

To solve the problems of Signal-to-Noise Ratio (SNR) and multicollinearity when the Local Field Potential (LFP) signals is used for the decoding of animal motion intention, a feature reconstruction of LFP signals based on partial least squares regression (PLSR) in the neural information decoding study is proposed in this paper. Firstly, the feature information of LFP coding band is extracted based on wavelet transform. Then the PLSR model is constructed by the extracted LFP coding features. According to the multicollinearity characteristics among the coding features, several latent variables which contribute greatly to the steering behavior are obtained, and the new LFP coding features are reconstructed. Finally, the K-Nearest Neighbor (KNN) method is used to classify the reconstructed coding features to verify the decoding performance. The results show that the proposed method can achieve the highest accuracy compared to the other three methods and the decoding effect of the proposed method is robust.

Environmental noise and noise modelling-some aspects in Malaysian development

International Nuclear Information System (INIS)

Leong, Mohd Salman; Mohd Shafiek bin Hj Yaacob

1994-01-01

Environmental noise is of growing concern in Malaysia with the increasing awareness of the need for an environmental quality consistent with improved quality of life. While noise is one of the several elements in an Environmental Impact Assessment report, the degree of emphasis in the assessment is not as thorough as other aspects in the EIA study. The measurements, prediction (if at all any), and evaluation tended to be superficial. The paper presents a summary of correct noise descriptors and annoyance assessment parameters appropriate for the evaluation of environmental noise. The paper further highlights current inadequacies in the Environmental Quality Act for noise pollution, and annoyance assessment. Some examples of local noise pollution are presented. A discussion on environmental noise modelling is presented. Examples illustrating environmental noise modelling for a mining operation and a power station are given. It is the authors' recommendation that environmental noise modelling be made mandatory in all EIA studies such that a more definitive assessment could be realised

Efficient L1 regularization-based reconstruction for fluorescent molecular tomography using restarted nonlinear conjugate gradient.

Science.gov (United States)

Shi, Junwei; Zhang, Bin; Liu, Fei; Luo, Jianwen; Bai, Jing

2013-09-15

For the ill-posed fluorescent molecular tomography (FMT) inverse problem, the L1 regularization can protect the high-frequency information like edges while effectively reduce the image noise. However, the state-of-the-art L1 regularization-based algorithms for FMT reconstruction are expensive in memory, especially for large-scale problems. An efficient L1 regularization-based reconstruction algorithm based on nonlinear conjugate gradient with restarted strategy is proposed to increase the computational speed with low memory consumption. The reconstruction results from phantom experiments demonstrate that the proposed algorithm can obtain high spatial resolution and high signal-to-noise ratio, as well as high localization accuracy for fluorescence targets.

Evaluation of noise pollution in oil extracting region of Lavan and the effect of noise enclosure on noise abatement

Directory of Open Access Journals (Sweden)

F. Golbabaei

2007-09-01

Full Text Available Background and aims   Overexposure to industrial noise pollution induce hearing loss workers. Occupational hearing loss may cause interference whit oral communication, so it may  increase the risk of occupational accidents in workplace as well as affects whit social activities.  This study was conducted on Lavan Island, are of oil extracting regions in the south of Iran. The  object of this study was to evaluate noise pollution and determining the effect of noise enclosure  on noise abatement.   Methods   The noise sources were recognized and noise pressure level was measured by CEL- 440. Noise dose of the exposed workers in high level noise area were measured by CEL 272.   Results   Major noise sources were gas turbines, diesel generators, compressors, fans and gas containing pips, noise contour map revealers that noise level were higher than the recommended national exposure limit. The results of workers noise dose show that their noise exposure were  higher than the recommended value, (p<0.001. Finally, by using the results of noise frequency  analysis of different noise sources, the noise pressure level of each sources was determined in   terms of enclosing them.   Conclusion   By enclosing the noise sources, noise pressure levels can be lowered douse to  acceptable levels but limitation of applying enclosure should be regarded.  

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

Hospital organizational factors affect the use of immediate breast reconstruction after mastectomy for breast cancer in the Netherlands

NARCIS (Netherlands)

Schreuder, K.; van Bommel, A.C.M.; de Ligt, K. M.; Maduro, John H.; Vrancken Peeters, M.T.F.D.; Mureau, Marc A.M.; Siesling, S.

2017-01-01

Objectives Significant hospital variation in the use of immediate breast reconstruction (IBR) after mastectomy exists in the Netherlands. Aims of this study were to identify hospital organizational factors affecting the use of IBR after mastectomy for ductal carcinoma in situ (DCIS) or invasive

Immersive virtual reality and environmental noise assessment: An innovative audio–visual approach

International Nuclear Information System (INIS)

Ruotolo, Francesco; Maffei, Luigi; Di Gabriele, Maria; Iachini, Tina; Masullo, Massimiliano; Ruggiero, Gennaro; Senese, Vincenzo Paolo

2013-01-01

Several international studies have shown that traffic noise has a negative impact on people's health and that people's annoyance does not depend only on noise energetic levels, but rather on multi-perceptual factors. The combination of virtual reality technology and audio rendering techniques allow us to experiment a new approach for environmental noise assessment that can help to investigate in advance the potential negative effects of noise associated with a specific project and that in turn can help designers to make educated decisions. In the present study, the audio–visual impact of a new motorway project on people has been assessed by means of immersive virtual reality technology. In particular, participants were exposed to 3D reconstructions of an actual landscape without the projected motorway (ante operam condition), and of the same landscape with the projected motorway (post operam condition). Furthermore, individuals' reactions to noise were assessed by means of objective cognitive measures (short term verbal memory and executive functions) and subjective evaluations (noise and visual annoyance). Overall, the results showed that the introduction of a projected motorway in the environment can have immediate detrimental effects of people's well-being depending on the distance from the noise source. In particular, noise due to the new infrastructure seems to exert a negative influence on short term verbal memory and to increase both visual and noise annoyance. The theoretical and practical implications of these findings are discussed. -- Highlights: ► Impact of traffic noise on people's well-being depends on multi-perceptual factors. ► A multisensory virtual reality technology is used to simulate a projected motorway. ► Effects on short-term memory and auditory and visual subjective annoyance were found. ► The closer the distance from the motorway the stronger was the effect. ► Multisensory virtual reality methodologies can be used to study

Noise propagation in x-ray phase-contrast imaging and computed tomography

International Nuclear Information System (INIS)

Nesterets, Yakov I; Gureyev, Timur E

2014-01-01

Three phase-retrieval algorithms, based on the transport-of-intensity equation and on the contrast transfer function for propagation-based imaging, and on the linearized geometrical optics approximation for analyser-based imaging, are investigated. The algorithms are compared in terms of their effect on propagation of noise from projection images to the corresponding phase-retrieved images and further to the computed tomography (CT) images/slices of a monomorphous object reconstructed using filtered backprojection algorithm. The comparison is carried out in terms of an integral noise characteristic, the variance, as well as in terms of a simple figure-of-merit, i.e. signal-to-noise ratio per unit dose. A gain factor is introduced that quantitatively characterizes the effect of phase retrieval on the variance of noise in the reconstructed projection images and in the axial slices of the object. Simple analytical expressions are derived for the gain factor and the signal-to-noise ratio, which indicate that the application of phase-retrieval algorithms can increase these parameters by up to two orders of magnitude compared to raw projection images and conventional CT, thus allowing significant improvement in the image quality and/or reduction of the x-ray dose delivered to the patient. (paper)

Ultralow dose computed tomography attenuation correction for pediatric PET CT using adaptive statistical iterative reconstruction

International Nuclear Information System (INIS)

Brady, Samuel L.; Shulkin, Barry L.

2015-01-01

Purpose: To develop ultralow 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 ultralow doses (10–35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) 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 (SUV bw ) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. Results: CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUV bw , background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3–0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. Conclusions: Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake

Ultralow dose computed tomography attenuation correction for pediatric PET CT using adaptive statistical iterative reconstruction

Energy Technology Data Exchange (ETDEWEB)

Brady, Samuel L., E-mail: samuel.brady@stjude.org [Division of Diagnostic Imaging, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105 (United States); Shulkin, Barry L. [Nuclear Medicine and Department of Radiological Sciences, St. Jude Children’s Research Hospital, Memphis, Tennessee 38105 (United States)

2015-02-15

Purpose: To develop ultralow 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 ultralow doses (10–35 mA s). CT quantitation: noise, low-contrast resolution, and CT numbers for 11 tissue substitutes were analyzed in-phantom. CT quantitation was analyzed to a reduction of 90% volume computed tomography dose index (0.39/3.64; mGy) 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 (SUV{sub bw}) of various diameter targets (range 8–37 mm), background uniformity, and spatial resolution. Radiation dose and CTAC noise magnitude were compared for 140 patient examinations (76 post-ASiR implementation) to determine relative dose reduction and noise control. Results: CT numbers were constant to within 10% from the nondose reduced CTAC image for 90% dose reduction. No change in SUV{sub bw}, background percent uniformity, or spatial resolution for PET images reconstructed with CTAC protocols was found down to 90% dose reduction. Patient population effective dose analysis demonstrated relative CTAC dose reductions between 62% and 86% (3.2/8.3–0.9/6.2). Noise magnitude in dose-reduced patient images increased but was not statistically different from predose-reduced patient images. Conclusions: Using ASiR allowed for aggressive reduction in CT dose with no change in PET reconstructed images while maintaining sufficient image quality for colocalization of hybrid CT anatomy and PET radioisotope uptake.

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.

Head-to-head comparison of adaptive statistical and model-based iterative reconstruction algorithms for submillisievert coronary CT angiography.

Science.gov (United States)

Benz, Dominik C; Fuchs, Tobias A; Gräni, Christoph; Studer Bruengger, Annina A; Clerc, Olivier F; Mikulicic, Fran; Messerli, Michael; Stehli, Julia; Possner, Mathias; Pazhenkottil, Aju P; Gaemperli, Oliver; Kaufmann, Philipp A; Buechel, Ronny R

2018-02-01

Iterative reconstruction (IR) algorithms allow for a significant reduction in radiation dose of coronary computed tomography angiography (CCTA). We performed a head-to-head comparison of adaptive statistical IR (ASiR) and model-based IR (MBIR) algorithms to assess their impact on quantitative image parameters and diagnostic accuracy for submillisievert CCTA. CCTA datasets of 91 patients were reconstructed using filtered back projection (FBP), increasing contributions of ASiR (20, 40, 60, 80, and 100%), and MBIR. Signal and noise were measured in the aortic root to calculate signal-to-noise ratio (SNR). In a subgroup of 36 patients, diagnostic accuracy of ASiR 40%, ASiR 100%, and MBIR for diagnosis of coronary artery disease (CAD) was compared with invasive coronary angiography. Median radiation dose was 0.21 mSv for CCTA. While increasing levels of ASiR gradually reduced image noise compared with FBP (up to - 48%, P ASiR (-59% compared with ASiR 100%; P ASiR 40% and ASiR 100% resulted in substantially lower diagnostic accuracy to detect CAD as diagnosed by invasive coronary angiography compared with MBIR: sensitivity and specificity were 100 and 37%, 100 and 57%, and 100 and 74% for ASiR 40%, ASiR 100%, and MBIR, respectively. MBIR offers substantial noise reduction with increased SNR, paving the way for implementation of submillisievert CCTA protocols in clinical routine. In contrast, inferior noise reduction by ASiR negatively affects diagnostic accuracy of submillisievert CCTA for CAD detection. Published on behalf of the European Society of Cardiology. All rights reserved. © The Author 2017. For permissions, please email: journals.permissions@oup.com.

Application of iterative reconstruction in dynamic studies

International Nuclear Information System (INIS)

Meikle, S.R.

1998-01-01

Full text: The conventional approach to analysing dynamic tomographic data (SPECT or PET) is to reconstruct projections corresponding to each time interval separately and then fit a suitable tracer kinetic model to the dynamic sequence (method 1 ) . This approach assumes that the tracer distribution remains static during any given time interval and, for practical reasons, filtered back-projection (FBP) is the preferred reconstruction algorithm. However, alternative approaches exist which lend themselves to iterative algorithms, such as EM. One approach is to fit the model directly to the projection data, followed by EM reconstruction of the parameter estimates (method 2). This requires that the tracer model can be expressed as a linear function of the unknown model parameters. A third alternative is to incorporate the tracer model into the reconstruction algorithm (method 3). Such an extension was described during the early development of the EM algorithm, referred to as the EM parametric image reconstruction algorithm (EM-PIRA). We have investigated these various strategies for analysing dynamic data and their relative pros and cons. Tracer modelling was performed using a general model, referred to as spectral analysis, which makes no restriction on the number of physiological compartments and satisfies the linearity requirement of method 2. A kinetic software phantom was created and used to test the convergence and noise properties of the different approaches. In summary, method 2 is the most practical as it reduces the number of reconstructions by at least an order of magnitude and provides improved signal-to-noise ratios compared with method 1. EM-PIRA allows greater flexibility in the choice of parametric images and appears to have a regularising effect on convergence. Methods 2 and 3 are also better suited to dynamic scanning with a rotating camera, as they can potentially account for changes in tracer distribution between projections

Ambient noise adjoint tomography for a linear array in North China

Science.gov (United States)

Zhang, C.; Yao, H.; Liu, Q.; Yuan, Y. O.; Zhang, P.; Feng, J.; Fang, L.

2017-12-01

Ambient noise tomography based on dispersion data and ray theory has been widely utilized for imaging crustal structures. In order to improve the inversion accuracy, ambient noise tomography based on the 3D adjoint approach or full waveform inversion has been developed recently, however, the computational cost is tremendous. In this study we present 2D ambient noise adjoint tomography for a linear array in north China with significant computational efficiency compared to 3D ambient noise adjoint tomography. During the preprocessing, we first convert the observed data in 3D media, i.e., surface-wave empirical Green's functions (EGFs) from ambient noise cross-correlation, to the reconstructed EGFs in 2D media using a 3D/2D transformation scheme. Different from the conventional steps of measuring phase dispersion, the 2D adjoint tomography refines 2D shear wave speeds along the profile directly from the reconstructed Rayleigh wave EGFs in the period band 6-35s. With the 2D initial model extracted from the 3D model from traditional ambient noise tomography, adjoint tomography updates the model by minimizing the frequency-dependent Rayleigh wave traveltime misfits between the reconstructed EGFs and synthetic Green function (SGFs) in 2D media generated by the spectral-element method (SEM), with a preconditioned conjugate gradient method. The multitaper traveltime difference measurement is applied in four period bands during the inversion: 20-35s, 15-30s, 10-20s and 6-15s. The recovered model shows more detailed crustal structures with pronounced low velocity anomaly in the mid-lower crust beneath the junction of Taihang Mountains and Yin-Yan Mountains compared with the initial model. This low velocity structure may imply the possible intense crust-mantle interactions, probably associated with the magmatic underplating during the Mesozoic to Cenozoic evolution of the region. To our knowledge, it's first time that ambient noise adjoint tomography is implemented in 2D media

Similarity-regulation of OS-EM for accelerated SPECT reconstruction

Science.gov (United States)

Vaissier, P. E. B.; Beekman, F. J.; Goorden, M. C.

2016-06-01

Ordered subsets expectation maximization (OS-EM) is widely used to accelerate image reconstruction in single photon emission computed tomography (SPECT). Speedup of OS-EM over maximum likelihood expectation maximization (ML-EM) is close to the number of subsets used. Although a high number of subsets can shorten reconstruction times significantly, it can also cause severe image artifacts such as improper erasure of reconstructed activity if projections contain few counts. We recently showed that such artifacts can be prevented by using a count-regulated OS-EM (CR-OS-EM) algorithm which automatically adapts the number of subsets for each voxel based on the estimated number of counts that the voxel contributed to the projections. While CR-OS-EM reached high speed-up over ML-EM in high-activity regions of images, speed in low-activity regions could still be very slow. In this work we propose similarity-regulated OS-EM (SR-OS-EM) as a much faster alternative to CR-OS-EM. SR-OS-EM also automatically and locally adapts the number of subsets, but it uses a different criterion for subset regulation: the number of subsets that is used for updating an individual voxel depends on how similar the reconstruction algorithm would update the estimated activity in that voxel with different subsets. Reconstructions of an image quality phantom and in vivo scans show that SR-OS-EM retains all of the favorable properties of CR-OS-EM, while reconstruction speed can be up to an order of magnitude higher in low-activity regions. Moreover our results suggest that SR-OS-EM can be operated with identical reconstruction parameters (including the number of iterations) for a wide range of count levels, which can be an additional advantage from a user perspective since users would only have to post-filter an image to present it at an appropriate noise level.

Interior noise analysis of a construction equipment cabin based on airborne and structure-borne noise predictions

Energy Technology Data Exchange (ETDEWEB)

Kim, Sung Hee; Hong, Suk Yoon [Seoul National University, Seoul (Korea, Republic of); Song, Jee Hun [Chonnam National University, Gwangju (Korea, Republic of); Joo, Won Ho [Hyundai Heavy Industries Co. Ltd, Ulsan (Korea, Republic of)

2012-04-15

Noise from construction equipment affects not only surrounding residents, but also the operators of the machines. Noise that affects drivers must be evaluated during the preliminary design stage. This paper suggests an interior noise analysis procedure for construction equipment cabins. The analysis procedure, which can be used in the preliminary design stage, was investigated for airborne and structure borne noise. The total interior noise of a cabin was predicted from the airborne noise analysis and structure-borne noise analysis. The analysis procedure consists of four steps: modeling, vibration analysis, acoustic analysis and total interior noise analysis. A mesh model of a cabin for numerical analysis was made at the modeling step. At the vibration analysis step, the mesh model was verified and modal analysis and frequency response analysis are performed. At the acoustic analysis step, the vibration results from the vibration analysis step were used as initial values for radiated noise analysis and noise reduction analysis. Finally, the total cabin interior noise was predicted using the acoustic results from the acoustic analysis step. Each step was applied to a cabin of a middle-sized excavator and verified by comparison with measured data. The cabin interior noise of a middle-sized wheel loader and a large-sized forklift were predicted using the analysis procedure of the four steps and were compared with measured data. The interior noise analysis procedure of construction equipment cabins is expected to be used during the preliminary design stage.

Interior noise analysis of a construction equipment cabin based on airborne and structure-borne noise predictions

International Nuclear Information System (INIS)

Kim, Sung Hee; Hong, Suk Yoon; Song, Jee Hun; Joo, Won Ho

2012-01-01

Noise from construction equipment affects not only surrounding residents, but also the operators of the machines. Noise that affects drivers must be evaluated during the preliminary design stage. This paper suggests an interior noise analysis procedure for construction equipment cabins. The analysis procedure, which can be used in the preliminary design stage, was investigated for airborne and structure borne noise. The total interior noise of a cabin was predicted from the airborne noise analysis and structure-borne noise analysis. The analysis procedure consists of four steps: modeling, vibration analysis, acoustic analysis and total interior noise analysis. A mesh model of a cabin for numerical analysis was made at the modeling step. At the vibration analysis step, the mesh model was verified and modal analysis and frequency response analysis are performed. At the acoustic analysis step, the vibration results from the vibration analysis step were used as initial values for radiated noise analysis and noise reduction analysis. Finally, the total cabin interior noise was predicted using the acoustic results from the acoustic analysis step. Each step was applied to a cabin of a middle-sized excavator and verified by comparison with measured data. The cabin interior noise of a middle-sized wheel loader and a large-sized forklift were predicted using the analysis procedure of the four steps and were compared with measured data. The interior noise analysis procedure of construction equipment cabins is expected to be used during the preliminary design stage

Speckle reduction in digital holography with resampling ring masks

Science.gov (United States)

Zhang, Wenhui; Cao, Liangcai; Jin, Guofan

2018-01-01

One-shot digital holographic imaging has the advantages of high stability and low temporal cost. However, the reconstruction is affected by the speckle noise. Resampling ring-mask method in spectrum domain is proposed for speckle reduction. The useful spectrum of one hologram is divided into several sub-spectra by ring masks. In the reconstruction, angular spectrum transform is applied to guarantee the calculation accuracy which has no approximation. N reconstructed amplitude images are calculated from the corresponding sub-spectra. Thanks to speckle's random distribution, superimposing these N uncorrelated amplitude images would lead to a final reconstructed image with lower speckle noise. Normalized relative standard deviation values of the reconstructed image are used to evaluate the reduction of speckle. Effect of the method on the spatial resolution of the reconstructed image is also quantitatively evaluated. Experimental and simulation results prove the feasibility and effectiveness of the proposed method.

Split-Bregman-based sparse-view CT reconstruction

Energy Technology Data Exchange (ETDEWEB)

Vandeghinste, Bert; Vandenberghe, Stefaan [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Goossens, Bart; Pizurica, Aleksandra; Philips, Wilfried [Ghent Univ. (Belgium). Image Processing and Interpretation Research Group (IPI); Beenhouwer, Jan de [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Wilrijk (Belgium). The Vision Lab; Staelens, Steven [Ghent Univ. (Belgium). Medical Image and Signal Processing (MEDISIP); Antwerp Univ., Edegem (Belgium). Molecular Imaging Centre Antwerp

2011-07-01

Total variation minimization has been extensively researched for image denoising and sparse view reconstruction. These methods show superior denoising performance for simple images with little texture, but result in texture information loss when applied to more complex images. It could thus be beneficial to use other regularizers within medical imaging. We propose a general regularization method, based on a split-Bregman approach. We show results for this framework combined with a total variation denoising operator, in comparison to ASD-POCS. We show that sparse-view reconstruction and noise regularization is possible. This general method will allow us to investigate other regularizers in the context of regularized CT reconstruction, and decrease the acquisition times in {mu}CT. (orig.)

Reconstruction of sound source signal by analytical passive TR in the environment with airflow

Science.gov (United States)

Wei, Long; Li, Min; Yang, Debin; Niu, Feng; Zeng, Wu

2017-03-01

In the acoustic design of air vehicles, the time-domain signals of noise sources on the surface of air vehicles can serve as data support to reveal the noise source generation mechanism, analyze acoustic fatigue, and take measures for noise insulation and reduction. To rapidly reconstruct the time-domain sound source signals in an environment with flow, a method combining the analytical passive time reversal mirror (AP-TR) with a shear flow correction is proposed. In this method, the negative influence of flow on sound wave propagation is suppressed by the shear flow correction, obtaining the corrected acoustic propagation time delay and path. Those corrected time delay and path together with the microphone array signals are then submitted to the AP-TR, reconstructing more accurate sound source signals in the environment with airflow. As an analytical method, AP-TR offers a supplementary way in 3D space to reconstruct the signal of sound source in the environment with airflow instead of the numerical TR. Experiments on the reconstruction of the sound source signals of a pair of loud speakers are conducted in an anechoic wind tunnel with subsonic airflow to validate the effectiveness and priorities of the proposed method. Moreover the comparison by theorem and experiment result between the AP-TR and the time-domain beamforming in reconstructing the sound source signal is also discussed.

Noise in the Sea and Its Impacts on Marine Organisms

Science.gov (United States)

Peng, Chao; Zhao, Xinguo; Liu, Guangxu

2015-01-01

With the growing utilization and exploration of the ocean, anthropogenic noise increases significantly and gives rise to a new kind of pollution: noise pollution. In this review, the source and the characteristics of noise in the sea, the significance of sound to marine organisms, and the impacts of noise on marine organisms are summarized. In general, the studies about the impact of noise on marine organisms are mainly on adult fish and mammals, which account for more than 50% and 20% of all the cases reported. Studies showed that anthropogenic noise can cause auditory masking, leading to cochlear damage, changes in individual and social behavior, altered metabolisms, hampered population recruitment, and can subsequently affect the health and service functions of marine ecosystems. However, since different sampling methodologies and unstandarized measurements were used and the effects of noise on marine organisms are dependent on the characteristics of the species and noise investigated, it is difficult to compare the reported results. Moreover, the scarcity of studies carried out with other species and with larval or juvenile individuals severely constrains the present understanding of noise pollution. In addition, further studies are needed to reveal in detail the causes for the detected impacts. PMID:26437424

Noise-aware dictionary-learning-based sparse representation framework for detection and removal of single and combined noises from ECG signal.

Science.gov (United States)

Satija, Udit; Ramkumar, Barathram; Sabarimalai Manikandan, M

2017-02-01

Automatic electrocardiogram (ECG) signal enhancement has become a crucial pre-processing step in most ECG signal analysis applications. In this Letter, the authors propose an automated noise-aware dictionary learning-based generalised ECG signal enhancement framework which can automatically learn the dictionaries based on the ECG noise type for effective representation of ECG signal and noises, and can reduce the computational load of sparse representation-based ECG enhancement system. The proposed framework consists of noise detection and identification, noise-aware dictionary learning, sparse signal decomposition and reconstruction. The noise detection and identification is performed based on the moving average filter, first-order difference, and temporal features such as number of turning points, maximum absolute amplitude, zerocrossings, and autocorrelation features. The representation dictionary is learned based on the type of noise identified in the previous stage. The proposed framework is evaluated using noise-free and noisy ECG signals. Results demonstrate that the proposed method can significantly reduce computational load as compared with conventional dictionary learning-based ECG denoising approaches. Further, comparative results show that the method outperforms existing methods in automatically removing noises such as baseline wanders, power-line interference, muscle artefacts and their combinations without distorting the morphological content of local waves of ECG signal.

A multiresolution approach to iterative reconstruction algorithms in X-ray computed tomography.

Science.gov (United States)

De Witte, Yoni; Vlassenbroeck, Jelle; Van Hoorebeke, Luc

2010-09-01

In computed tomography, the application of iterative reconstruction methods in practical situations is impeded by their high computational demands. Especially in high resolution X-ray computed tomography, where reconstruction volumes contain a high number of volume elements (several giga voxels), this computational burden prevents their actual breakthrough. Besides the large amount of calculations, iterative algorithms require the entire volume to be kept in memory during reconstruction, which quickly becomes cumbersome for large data sets. To overcome this obstacle, we present a novel multiresolution reconstruction, which greatly reduces the required amount of memory without significantly affecting the reconstructed image quality. It is shown that, combined with an efficient implementation on a graphical processing unit, the multiresolution approach enables the application of iterative algorithms in the reconstruction of large volumes at an acceptable speed using only limited resources.

Noise removal in multichannel image data by a parametric maximum noise fraction estimator