Spatiotemporal matrix image formation for programmable ultrasound scanners

Science.gov (United States)

Berthon, Beatrice; Morichau-Beauchant, Pierre; Porée, Jonathan; Garofalakis, Anikitos; Tavitian, Bertrand; Tanter, Mickael; Provost, Jean

2018-02-01

As programmable ultrasound scanners become more common in research laboratories, it is increasingly important to develop robust software-based image formation algorithms that can be obtained in a straightforward fashion for different types of probes and sequences with a small risk of error during implementation. In this work, we argue that as the computational power keeps increasing, it is becoming practical to directly implement an approximation to the matrix operator linking reflector point targets to the corresponding radiofrequency signals via thoroughly validated and widely available simulations software. Once such a spatiotemporal forward-problem matrix is constructed, standard and thus highly optimized inversion procedures can be leveraged to achieve very high quality images in real time. Specifically, we show that spatiotemporal matrix image formation produces images of similar or enhanced quality when compared against standard delay-and-sum approaches in phantoms and in vivo, and show that this approach can be used to form images even when using non-conventional probe designs for which adapted image formation algorithms are not readily available.

Satisfactory visualization rates of standard cardiac views at 18 to 22 weeks' gestation using spatiotemporal image correlation.

Science.gov (United States)

Cohen, Leeber; Mangers, Kristie; Grobman, William A; Platt, Lawrence D

2009-12-01

The purpose of this study was to determine the frequency with which 3 standard screening views of the fetal heart (4-chamber, left ventricular outflow tract [LVOT], and right ventricular outflow tract [RVOT]) can be obtained satisfactorily with the spatiotemporal image correlation (STIC) technique. A prospective study of 111 patients undergoing anatomic surveys at 18 to 22 weeks was performed. Two ultrasound machines with fetal cardiac settings were used. The best volume set that could be obtained from each patient during a 45-minute examination was graded by 2 sonologists with regard to whether the 4-chamber, LVOT, and RVOT images were satisfactory for screening. All 3 views were judged satisfactory for screening in most patients: 1 sonologist graded the views as satisfactory in 70% of the patients, whereas the other found the views to be satisfactory in 83%. The position of the placenta did not alter the probability of achieving a satisfactory view, but a fetus in the spine anterior position was associated with a significantly lower probability that the views were regarded as satisfactory for screening (odds ratio, 0.28; 95% confidence interval, 0.09-0.70; P < .05). This study suggests that STIC may assist with screening for cardiac anomalies at 18 to 22 weeks' gestation.

A Novel Image Encryption Algorithm Based on DNA Encoding and Spatiotemporal Chaos

Directory of Open Access Journals (Sweden)

Chunyan Song

2015-10-01

Full Text Available DNA computing based image encryption is a new, promising field. In this paper, we propose a novel image encryption scheme based on DNA encoding and spatiotemporal chaos. In particular, after the plain image is primarily diffused with the bitwise Exclusive-OR operation, the DNA mapping rule is introduced to encode the diffused image. In order to enhance the encryption, the spatiotemporal chaotic system is used to confuse the rows and columns of the DNA encoded image. The experiments demonstrate that the proposed encryption algorithm is of high key sensitivity and large key space, and it can resist brute-force attack, entropy attack, differential attack, chosen-plaintext attack, known-plaintext attack and statistical attack.

Synchronization of spatiotemporal chaotic systems and application to secure communication of digital image

International Nuclear Information System (INIS)

Wang Xing-Yuan; Zhang Na; Ren Xiao-Li; Zhang Yong-Lei

2011-01-01

Coupled map lattices (CMLs) are taken as examples to study the synchronization of spatiotemporal chaotic systems. In this paper, we use the nonlinear coupled method to implement the synchronization of two coupled map lattices. Through the appropriate separation of the linear term from the nonlinear term of the spatiotemporal chaotic system, we set the nonlinear term as the coupling function and then we can achieve the synchronization of two coupled map lattices. After that, we implement the secure communication of digital image using this synchronization method. Then, the discrete characteristics of the nonlinear coupling spatiotemporal chaos are applied to the discrete pixel of the digital image. After the synchronization of both the communication parties, the receiver can decrypt the original image. Numerical simulations show the effectiveness and the feasibility of the proposed program. (general)

Spatio-Temporal Encoding in Medical Ultrasound Imaging

DEFF Research Database (Denmark)

Gran, Fredrik

2005-01-01

In this dissertation two methods for spatio-temporal encoding in medical ultrasound imaging are investigated. The first technique is based on a frequency division approach. Here, the available spectrum of the transducer is divided into a set of narrow bands. A waveform is designed for each band...... the signal to noise ratio and simultaneously the penetration depth so that the medical doctor can image deeper lying structures. The method is tested both experimentally and in simulation and has also evaluated for the purpose of blood flow estimation. The work presented is based on four papers which...

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

International Nuclear Information System (INIS)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-01-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins. (paper)

Tracking molecular dynamics without tracking: image correlation of photo-activation microscopy

Science.gov (United States)

Pandžić, Elvis; Rossy, Jérémie; Gaus, Katharina

2015-03-01

Measuring protein dynamics in the plasma membrane can provide insights into the mechanisms of receptor signaling and other cellular functions. To quantify protein dynamics on the single molecule level over the entire cell surface, sophisticated approaches such as single particle tracking (SPT), photo-activation localization microscopy (PALM) and fluctuation-based analysis have been developed. However, analyzing molecular dynamics of fluorescent particles with intermittent excitation and low signal-to-noise ratio present at high densities has remained a challenge. We overcame this problem by applying spatio-temporal image correlation spectroscopy (STICS) analysis to photo-activated (PA) microscopy time series. In order to determine under which imaging conditions this approach is valid, we simulated PA images of diffusing particles in a homogeneous environment and varied photo-activation, reversible blinking and irreversible photo-bleaching rates. Further, we simulated data with high particle densities that populated mobile objects (such as adhesions and vesicles) that often interfere with STICS and fluctuation-based analysis. We demonstrated in experimental measurements that the diffusion coefficient of the epidermal growth factor receptor (EGFR) fused to PAGFP in live COS-7 cells can be determined in the plasma membrane and revealed differences in the time-dependent diffusion maps between wild-type and mutant Lck in activated T cells. In summary, we have developed a new analysis approach for live cell photo-activation microscopy data based on image correlation spectroscopy to quantify the spatio-temporal dynamics of single proteins.

Prenatal Diagnosis of Fetal Interrupted Aortic Arch Type A by Two-Dimensional Echocardiography and Four-Dimensional Echocardiography with B-Flow Imaging and Spatiotemporal Image Correlation.

Science.gov (United States)

Zhang, Dongyu; Zhang, Ying; Ren, Weidong; Sun, Feifei; Guo, Yajun; Sun, Wei; Wang, Yu; Huang, Liping; Cai, Ailu

2016-01-01

Fetal interrupted aortic arch (IAA) is a rare cardiac anomaly and its prenatal diagnosis is challenging. The purpose of our report is to evaluate the use of two-dimensional echocardiography (2DE) and 4D echocardiography with B-flow imaging and spatiotemporal image correlation (4D BF-STIC) in detecting IAA type A (IAA-A). Twenty-three cases of confirmed IAA-A identified by fetal echocardiography were involved in the study. The fetal echocardiography image data were reviewed to analyze the ratio of right ventricle to left ventricle (RV/LV) diameter, the ratio of main pulmonary artery to ascending aorta (MPA/AAO) diameter, and the correlation of RV/LV diameter ratio and size of ventricular septal defect (VSD). 4D BF-STIC was performed in 21 fetuses using the sagittal view (4D BF-STIC-sagittal) and the four-chamber view (4D BF-STIC-4CV) as initial planes of view. An additional 183 normal fetuses were also included in our study. RV/LV and MPA/AAO ratios were calculated and compared with that of IAA-A fetuses. Fetal 2DE, 4D BF-STIC-sagittal, and 4D BF-STIC-4CV were used to visualize the aortic arch and its associated neck vessels. Six subgroups were evaluated according to gestational age. Fetal 2DE, 4D BF-STIC-sagittal, and 4D BF-STIC-4CV made the correct prenatal diagnosis of IAA-A in 19/23 (82.6%), 14/21 (66.7%), and 19/21 (90.5%) of patients, respectively. A significantly enlarged MPA combined with symmetric ventricles was found in the IAA-A fetuses, while the size of the VSD was negatively correlated with RV/LV ratio. 4D BF-STIC-sagittal and 4D BF-STIC-4CV were better than traditional 2D ultrasound in detecting the aortic arch and neck vessels between 17 and 28 gestational weeks and 29 to 40 gestational weeks in normal fetuses. It is demonstrated that IAA-A could be diagnosed by traditional fetal echocardiography, while 4D technique could better display the anatomic structure and the spatial relationships of the great arteries. Use of volume reconstruction may

a Comparative Analysis of Spatiotemporal Data Fusion Models for Landsat and Modis Data

Science.gov (United States)

Hazaymeh, K.; Almagbile, A.

2018-04-01

In this study, three documented spatiotemporal data fusion models were applied to Landsat-7 and MODIS surface reflectance, and NDVI. The algorithms included the spatial and temporal adaptive reflectance fusion model (STARFM), sparse representation based on a spatiotemporal reflectance fusion model (SPSTFM), and spatiotemporal image-fusion model (STI-FM). The objectives of this study were to (i) compare the performance of these three fusion models using a one Landsat-MODIS spectral reflectance image pairs using time-series datasets from the Coleambally irrigation area in Australia, and (ii) quantitatively evaluate the accuracy of the synthetic images generated from each fusion model using statistical measurements. Results showed that the three fusion models predicted the synthetic Landsat-7 image with adequate agreements. The STI-FM produced more accurate reconstructions of both Landsat-7 spectral bands and NDVI. Furthermore, it produced surface reflectance images having the highest correlation with the actual Landsat-7 images. This study indicated that STI-FM would be more suitable for spatiotemporal data fusion applications such as vegetation monitoring, drought monitoring, and evapotranspiration.

Fetal cardiac stroke volume determination by four-dimensional ultrasound with spatio-temporal image correlation compared with two-dimensional and Doppler ultrasonography.

Science.gov (United States)

Rizzo, Giuseppe; Capponi, Alessandra; Cavicchioni, Ottavia; Vendola, Marianne; Arduini, Domenico

2007-12-01

To assess the agreement of stroke volume (SV) measured with two-dimensional (2D) ultrasonography with Doppler capability (vs) four-dimensional (4D) with spatiotemporal image correlation (STIC) in normal and growth restricted fetuses. 2D Doppler and 4D STIC were used to measure SV of 40 normal fetuses at 20 to 22 and 28 to 32 weeks, and 16 growth-restricted fetuses at 26 to 34 weeks of gestation. Intraclass correlation was used to evaluate the agreement between left and right SV obtained by the two techniques, and proportionate Bland-Altman plots constructed. The time necessary to obtain SV was analyzed. The intraclass correlation coefficient between 2D Doppler and 4D STIC measurements for the left ventricle were 0.977 and 0.980 for the right ventricle. The proportionate limits of agreement between the two methods were 18.7 to 23.9% for the left ventricle and - 20.9 to 21.7% for the right ventricle. The time necessary to measure SV was significantly shorter with 4D STIC (3.1 (vs) 7.9 min p < 0.0001) than with 2D Doppler. There is a good agreement between SV measured either by 2D Doppler or by 4D STIC. The 4D STIC represents a simple and rapid technique to estimate fetal SV and promises to become the method of choice. Copyright (c) 2007 John Wiley & Sons, Ltd.

Travel Cost Inference from Sparse, Spatio-Temporally Correlated Time Series Using Markov Models

DEFF Research Database (Denmark)

Yang, Bin; Guo, Chenjuan; Jensen, Christian S.

2013-01-01

of such time series offers insight into the underlying system and enables prediction of system behavior. While the techniques presented in the paper apply more generally, we consider the case of transportation systems and aim to predict travel cost from GPS tracking data from probe vehicles. Specifically, each...... road segment has an associated travel-cost time series, which is derived from GPS data. We use spatio-temporal hidden Markov models (STHMM) to model correlations among different traffic time series. We provide algorithms that are able to learn the parameters of an STHMM while contending...... with the sparsity, spatio-temporal correlation, and heterogeneity of the time series. Using the resulting STHMM, near future travel costs in the transportation network, e.g., travel time or greenhouse gas emissions, can be inferred, enabling a variety of routing services, e.g., eco-routing. Empirical studies...

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs.

Science.gov (United States)

Gu, Qing; Wang, Ke; Li, Jiadan; Ma, Ligang; Deng, Jinsong; Zheng, Kefeng; Zhang, Xiaobin; Sheng, Li

2015-10-20

It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006-2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS) technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes). According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

Spatio-Temporal Trends and Identification of Correlated Variables with Water Quality for Drinking-Water Reservoirs

Directory of Open Access Journals (Sweden)

Qing Gu

2015-10-01

Full Text Available It is widely accepted that characterizing the spatio-temporal trends of water quality parameters and identifying correlated variables with water quality are indispensable for the management and protection of water resources. In this study, cluster analysis was used to classify 56 typical drinking water reservoirs in Zhejiang Province into three groups representing different water quality levels, using data of four water quality parameters for the period 2006–2010. Then, the spatio-temporal trends in water quality were analyzed, assisted by geographic information systems (GIS technology and statistical analysis. The results indicated that the water quality showed a trend of degradation from southwest to northeast, and the overall water quality level was exacerbated during the study period. Correlation analysis was used to evaluate the relationships between water quality parameters and ten independent variables grouped into four categories (land use, socio-economic factors, geographical features, and reservoir attributes. According to the correlation coefficients, land use and socio-economic indicators were identified as the most significant factors related to reservoir water quality. The results offer insights into the spatio-temporal variations of water quality parameters and factors impacting the water quality of drinking water reservoirs in Zhejiang Province, and they could assist managers in making effective strategies to better protect water resources.

Spatio-temporal prediction of daily temperatures using time-series of MODIS LST images

Science.gov (United States)

Hengl, Tomislav; Heuvelink, Gerard B. M.; Perčec Tadić, Melita; Pebesma, Edzer J.

2012-01-01

A computational framework to generate daily temperature maps using time-series of publicly available MODIS MOD11A2 product Land Surface Temperature (LST) images (1 km resolution; 8-day composites) is illustrated using temperature measurements from the national network of meteorological stations (159) in Croatia. The input data set contains 57,282 ground measurements of daily temperature for the year 2008. Temperature was modeled as a function of latitude, longitude, distance from the sea, elevation, time, insolation, and the MODIS LST images. The original rasters were first converted to principal components to reduce noise and filter missing pixels in the LST images. The residual were next analyzed for spatio-temporal auto-correlation; sum-metric separable variograms were fitted to account for zonal and geometric space-time anisotropy. The final predictions were generated for time-slices of a 3D space-time cube, constructed in the R environment for statistical computing. The results show that the space-time regression model can explain a significant part of the variation in station-data (84%). MODIS LST 8-day (cloud-free) images are unbiased estimator of the daily temperature, but with relatively low precision (±4.1°C); however their added value is that they systematically improve detection of local changes in land surface temperature due to local meteorological conditions and/or active heat sources (urban areas, land cover classes). The results of 10-fold cross-validation show that use of spatio-temporal regression-kriging and incorporation of time-series of remote sensing images leads to significantly more accurate maps of temperature than if plain spatial techniques were used. The average (global) accuracy of mapping temperature was ±2.4°C. The regression-kriging explained 91% of variability in daily temperatures, compared to 44% for ordinary kriging. Further software advancement—interactive space-time variogram exploration and automated retrieval

Cryptanalysis on an image block encryption algorithm based on spatiotemporal chaos

International Nuclear Information System (INIS)

Wang Xing-Yuan; He Guo-Xiang

2012-01-01

An image block encryption scheme based on spatiotemporal chaos has been proposed recently. In this paper, we analyse the security weakness of the proposal. The main problem of the original scheme is that the generated keystream remains unchanged for encrypting every image. Based on the flaws, we demonstrate a chosen plaintext attack for revealing the equivalent keys with only 6 pairs of plaintext/ciphertext used. Finally, experimental results show the validity of our attack. (general)

Probabilistic M/EEG source imaging from sparse spatio-temporal event structure

DEFF Research Database (Denmark)

Stahlhut, Carsten; Attias, Hagai T.; Wipf, David

While MEG and EEG source imaging methods have to tackle a severely ill-posed problem their success can be stated as their ability to constrain the solutions using appropriate priors. In this paper we propose a hierarchical Bayesian model facilitating spatio-temporal patterns through the use of bo...

Spatio-temporal diffusion of dynamic PET images

International Nuclear Information System (INIS)

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

2011-01-01

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

Comparison of two methods for calculating the mean vascularization index of ovarian stroma on the basis of spatio-temporal image correlation high-definition flow technology.

Science.gov (United States)

Kudla, Marek J; Kandzia, Tomasz; Alcázar, Juan Luis

2013-11-01

The aim of our study was to determine the agreement between two different methods for calculating the mean vascularization index (VI) of ovarian stroma using spatio-temporal image correlation-high definition flow (STIC-HDF) technology. Stored 4-D STIC-HDF volume data for ovaries of 34 premenopausal women were assessed retrospectively. We calculated the mean VI from the VI values derived for each 3-D volume within the STIC sequence. Then, the examiner subjectively selected the two volumes with the highest and lowest color signals, respectively. We averaged these two values. Agreement between VI measurements was estimated by calculating intra-class correlation coefficients. The intra-class correlation coefficient for the VI was 0.999 (95% confidence interval: 0.999-1.000). The mean time needed to calculate the mean VI using the entire 4-D STIC sequence was significantly longer than the mean time needed to calculate the average value from the volumes with the highest and lowest color signals determined by the operator (p < 0001). We conclude that there is significant agreement between the two methods. Calculating the average VI from the highest and lowest values is less time consuming than calculating the mean VI from the complete STIC sequence. Copyright © 2013 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

4D cone beam CT via spatiotemporal tensor framelet

International Nuclear Information System (INIS)

Gao, Hao; Li, Ruijiang; Xing, Lei; Lin, Yuting

2012-01-01

Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

4D cone beam CT via spatiotemporal tensor framelet

Energy Technology Data Exchange (ETDEWEB)

Gao, Hao, E-mail: hao.gao@emory.edu [Departments of Mathematics and Computer Science, and Radiology and Imaging Sciences, Emory University, Atlanta, Georgia 30322 (United States); Li, Ruijiang; Xing, Lei [Department of Radiation Oncology, Stanford University, Stanford, California 94305 (United States); Lin, Yuting [Department of Radiological Sciences, University of California, Irvine, California 92697 (United States)

2012-11-15

Purpose: On-board 4D cone beam CT (4DCBCT) offers respiratory phase-resolved volumetric imaging, and improves the accuracy of target localization in image guided radiation therapy. However, the clinical utility of this technique has been greatly impeded by its degraded image quality, prolonged imaging time, and increased imaging dose. The purpose of this letter is to develop a novel iterative 4DCBCT reconstruction method for improved image quality, increased imaging speed, and reduced imaging dose. Methods: The essence of this work is to introduce the spatiotemporal tensor framelet (STF), a high-dimensional tensor generalization of the 1D framelet for 4DCBCT, to effectively take into account of highly correlated and redundant features of the patient anatomy during respiration, in a multilevel fashion with multibasis sparsifying transform. The STF-based algorithm is implemented on a GPU platform for improved computational efficiency. To evaluate the method, 4DCBCT full-fan scans were acquired within 30 s, with a gantry rotation of 200°; STF is also compared with a state-of-art reconstruction method via spatiotemporal total variation regularization. Results: Both the simulation and experimental results demonstrate that STF-based reconstruction achieved superior image quality. The reconstruction of 20 respiratory phases took less than 10 min on an NVIDIA Tesla C2070 GPU card. The STF codes are available at https://sites.google.com/site/spatiotemporaltensorframelet . Conclusions: By effectively utilizing the spatiotemporal coherence of the patient anatomy among different respiratory phases in a multilevel fashion with multibasis sparsifying transform, the proposed STF method potentially enables fast and low-dose 4DCBCT with improved image quality.

Assessment of Spatiotemporal Fusion Algorithms for Planet and Worldview Images.

Science.gov (United States)

Kwan, Chiman; Zhu, Xiaolin; Gao, Feng; Chou, Bryan; Perez, Daniel; Li, Jiang; Shen, Yuzhong; Koperski, Krzysztof; Marchisio, Giovanni

2018-03-31

Although Worldview-2 (WV) images (non-pansharpened) have 2-m resolution, the re-visit times for the same areas may be seven days or more. In contrast, Planet images are collected using small satellites that can cover the whole Earth almost daily. However, the resolution of Planet images is 3.125 m. It would be ideal to fuse these two satellites images to generate high spatial resolution (2 m) and high temporal resolution (1 or 2 days) images for applications such as damage assessment, border monitoring, etc. that require quick decisions. In this paper, we evaluate three approaches to fusing Worldview (WV) and Planet images. These approaches are known as Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM), Flexible Spatiotemporal Data Fusion (FSDAF), and Hybrid Color Mapping (HCM), which have been applied to the fusion of MODIS and Landsat images in recent years. Experimental results using actual Planet and Worldview images demonstrated that the three aforementioned approaches have comparable performance and can all generate high quality prediction images.

Imaging collagen type I fibrillogenesis with high spatiotemporal resolution

International Nuclear Information System (INIS)

Stamov, Dimitar R; Stock, Erik; Franz, Clemens M; Jähnke, Torsten; Haschke, Heiko

2015-01-01

Fibrillar collagens, such as collagen type I, belong to the most abundant extracellular matrix proteins and they have received much attention over the last five decades due to their large interactome, complex hierarchical structure and high mechanical stability. Nevertheless, the collagen self-assembly process is still incompletely understood. Determining the real-time kinetics of collagen type I formation is therefore pivotal for better understanding of collagen type I structure and function, but visualising the dynamic self-assembly process of collagen I on the molecular scale requires imaging techniques offering high spatiotemporal resolution. Fast and high-speed scanning atomic force microscopes (AFM) provide the means to study such processes on the timescale of seconds under near-physiological conditions. In this study we have applied fast AFM tip scanning to study the assembly kinetics of fibrillar collagen type I nanomatrices with a temporal resolution reaching eight seconds for a frame size of 500 nm. By modifying the buffer composition and pH value, the kinetics of collagen fibrillogenesis can be adjusted for optimal analysis by fast AFM scanning. We furthermore show that amplitude-modulation imaging can be successfully applied to extract additional structural information from collagen samples even at high scan rates. Fast AFM scanning with controlled amplitude modulation therefore provides a versatile platform for studying dynamic collagen self-assembly processes at high resolution. - Highlights: • Continuous non-invasive time-lapse investigation of collagen I fibrillogenesis in situ. • Imaging of collagen I self-assembly with high spatiotemporal resolution. • Application of setpoint modulation to study the hierarchical structure of collagen I. • Observing real-time formation of the D-banding pattern in collagen I

Imaging collagen type I fibrillogenesis with high spatiotemporal resolution

Energy Technology Data Exchange (ETDEWEB)

Stamov, Dimitar R, E-mail: stamov@jpk.com [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany); Stock, Erik [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany); Franz, Clemens M [DFG-Center for Functional Nanostructures (CFN), Karlsruhe Institute of Technology (KIT), Wolfgang-Gaede-Strasse 1a, 76131 Karlsruhe (Germany); Jähnke, Torsten; Haschke, Heiko [JPK Instruments AG, Bouchéstrasse 12, 12435 Berlin (Germany)

2015-02-15

Fibrillar collagens, such as collagen type I, belong to the most abundant extracellular matrix proteins and they have received much attention over the last five decades due to their large interactome, complex hierarchical structure and high mechanical stability. Nevertheless, the collagen self-assembly process is still incompletely understood. Determining the real-time kinetics of collagen type I formation is therefore pivotal for better understanding of collagen type I structure and function, but visualising the dynamic self-assembly process of collagen I on the molecular scale requires imaging techniques offering high spatiotemporal resolution. Fast and high-speed scanning atomic force microscopes (AFM) provide the means to study such processes on the timescale of seconds under near-physiological conditions. In this study we have applied fast AFM tip scanning to study the assembly kinetics of fibrillar collagen type I nanomatrices with a temporal resolution reaching eight seconds for a frame size of 500 nm. By modifying the buffer composition and pH value, the kinetics of collagen fibrillogenesis can be adjusted for optimal analysis by fast AFM scanning. We furthermore show that amplitude-modulation imaging can be successfully applied to extract additional structural information from collagen samples even at high scan rates. Fast AFM scanning with controlled amplitude modulation therefore provides a versatile platform for studying dynamic collagen self-assembly processes at high resolution. - Highlights: • Continuous non-invasive time-lapse investigation of collagen I fibrillogenesis in situ. • Imaging of collagen I self-assembly with high spatiotemporal resolution. • Application of setpoint modulation to study the hierarchical structure of collagen I. • Observing real-time formation of the D-banding pattern in collagen I.

Spatio-temporal correlations in the Manna model in one, three and five dimensions

Science.gov (United States)

Willis, Gary; Pruessner, Gunnar

2018-02-01

Although the paradigm of criticality is centered around spatial correlations and their anomalous scaling, not many studies of self-organized criticality (SOC) focus on spatial correlations. Often, integrated observables, such as avalanche size and duration, are used, not least as to avoid complications due to the unavoidable lack of translational invariance. The present work is a survey of spatio-temporal correlation functions in the Manna Model of SOC, measured numerically in detail in d = 1,3 and 5 dimensions and compared to theoretical results, in particular relating them to “integrated” observables such as avalanche size and duration scaling, that measure them indirectly. Contrary to the notion held by some of SOC models organizing into a critical state by re-arranging their spatial structure avalanche by avalanche, which may be expected to result in large, nontrivial, system-spanning spatial correlations in the quiescent state (between avalanches), correlations of inactive particles in the quiescent state have a small amplitude that does not and cannot increase with the system size, although they display (noisy) power law scaling over a range linear in the system size. Self-organization, however, does take place as the (one-point) density of inactive particles organizes into a particular profile that is asymptotically independent of the driving location, also demonstrated analytically in one dimension. Activity and its correlations, on the other hand, display nontrivial long-ranged spatio-temporal scaling with exponents that can be related to established results, in particular avalanche size and duration exponents. The correlation length and amplitude are set by the system size (confirmed analytically for some observables), as expected in systems displaying finite size scaling. In one dimension, we find some surprising inconsistencies of the dynamical exponent. A (spatially extended) mean field theory (MFT) is recovered, with some corrections, in five

Spatio-Temporal Series Remote Sensing Image Prediction Based on Multi-Dictionary Bayesian Fusion

Directory of Open Access Journals (Sweden)

Chu He

2017-11-01

Full Text Available Contradictions in spatial resolution and temporal coverage emerge from earth observation remote sensing images due to limitations in technology and cost. Therefore, how to combine remote sensing images with low spatial yet high temporal resolution as well as those with high spatial yet low temporal resolution to construct images with both high spatial resolution and high temporal coverage has become an important problem called spatio-temporal fusion problem in both research and practice. A Multi-Dictionary Bayesian Spatio-Temporal Reflectance Fusion Model (MDBFM has been proposed in this paper. First, multiple dictionaries from regions of different classes are trained. Second, a Bayesian framework is constructed to solve the dictionary selection problem. A pixel-dictionary likehood function and a dictionary-dictionary prior function are constructed under the Bayesian framework. Third, remote sensing images before and after the middle moment are combined to predict images at the middle moment. Diverse shapes and textures information is learned from different landscapes in multi-dictionary learning to help dictionaries capture the distinctions between regions. The Bayesian framework makes full use of the priori information while the input image is classified. The experiments with one simulated dataset and two satellite datasets validate that the MDBFM is highly effective in both subjective and objective evaluation indexes. The results of MDBFM show more precise details and have a higher similarity with real images when dealing with both type changes and phenology changes.

Spatial Specificity in Spatiotemporal Encoding and Fourier Imaging

Science.gov (United States)

Goerke, Ute

2015-01-01

Purpose Ultrafast imaging techniques based on spatiotemporal-encoding (SPEN), such as RASER (rapid acquisition with sequential excitation and refocusing), is a promising new class of sequences since they are largely insensitive to magnetic field variations which cause signal loss and geometric distortion in EPI. So far, attempts to theoretically describe the point-spread-function (PSF) for the original SPEN-imaging techniques have yielded limited success. To fill this gap a novel definition for an apparent PSF is proposed. Theory Spatial resolution in SPEN-imaging is determined by the spatial phase dispersion imprinted on the acquired signal by a frequency-swept excitation or refocusing pulse. The resulting signal attenuation increases with larger distance from the vertex of the quadratic phase profile. Methods Bloch simulations and experiments were performed to validate theoretical derivations. Results The apparent PSF quantifies the fractional contribution of magnetization to a voxel’s signal as a function of distance to the voxel. In contrast, the conventional PSF represents the signal intensity at various locations. Conclusion The definition of the conventional PSF fails for SPEN-imaging since only the phase of isochromats, but not the amplitude of the signal varies. The concept of the apparent PSF is shown to be generalizable to conventional Fourier- imaging techniques. PMID:26712657

Spatiotemporal Analysis of RGB-D-T Facial Images for Multimodal Pain Level Recognition

DEFF Research Database (Denmark)

Irani, Ramin; Nasrollahi, Kamal; Oliu Simon, Marc

2015-01-01

facial images for pain detection and pain intensity level recognition. For this purpose, we extract energies released by facial pixels using a spatiotemporal filter. Experiments on a group of 12 elderly people applying the multimodal approach show that the proposed method successfully detects pain...

Spatiotemporal Fusion of Remote Sensing Images with Structural Sparsity and Semi-Coupled Dictionary Learning

Directory of Open Access Journals (Sweden)

Jingbo Wei

2016-12-01

Full Text Available Fusion of remote sensing images with different spatial and temporal resolutions is highly needed by diverse earth observation applications. A small number of spatiotemporal fusion methods using sparse representation appear to be more promising than traditional linear mixture methods in reflecting abruptly changing terrestrial content. However, one of the main difficulties is that the results of sparse representation have reduced expressional accuracy; this is due in part to insufficient prior knowledge. For remote sensing images, the cluster and joint structural sparsity of the sparse coefficients could be employed as a priori knowledge. In this paper, a new optimization model is constructed with the semi-coupled dictionary learning and structural sparsity to predict the unknown high-resolution image from known images. Specifically, the intra-block correlation and cluster-structured sparsity are considered for single-channel reconstruction, and the inter-band similarity of joint-structured sparsity is considered for multichannel reconstruction, and both are implemented with block sparse Bayesian learning. The detailed optimization steps are given iteratively. In the experimental procedure, the red, green, and near-infrared bands of Landsat-7 and Moderate Resolution Imaging Spectrometer (MODIS satellites are put to fusion with root mean square errors to check the prediction accuracy. It can be concluded from the experiment that the proposed methods can produce higher quality than state-of-the-art methods.

Efficient image or video encryption based on spatiotemporal chaos system

International Nuclear Information System (INIS)

Lian Shiguo

2009-01-01

In this paper, an efficient image/video encryption scheme is constructed based on spatiotemporal chaos system. The chaotic lattices are used to generate pseudorandom sequences and then encrypt image blocks one by one. By iterating chaotic maps for certain times, the generated pseudorandom sequences obtain high initial-value sensitivity and good randomness. The pseudorandom-bits in each lattice are used to encrypt the Direct Current coefficient (DC) and the signs of the Alternating Current coefficients (ACs). Theoretical analysis and experimental results show that the scheme has good cryptographic security and perceptual security, and it does not affect the compression efficiency apparently. These properties make the scheme a suitable choice for practical applications.

Correlated diffusion imaging

International Nuclear Information System (INIS)

Wong, Alexander; Glaister, Jeffrey; Cameron, Andrew; Haider, Masoom

2013-01-01

Prostate cancer is one of the leading causes of cancer death in the male population. Fortunately, the prognosis is excellent if detected at an early stage. Hence, the detection and localization of prostate cancer is crucial for diagnosis, as well as treatment via targeted focal therapy. New imaging techniques can potentially be invaluable tools for improving prostate cancer detection and localization. In this study, we introduce a new form of diffusion magnetic resonance imaging called correlated diffusion imaging, where the tissue being imaged is characterized by the joint correlation of diffusion signal attenuation across multiple gradient pulse strengths and timings. By taking into account signal attenuation at different water diffusion motion sensitivities, correlated diffusion imaging can provide improved delineation between cancerous tissue and healthy tissue when compared to existing diffusion imaging modalities. Quantitative evaluation using receiver operating characteristic (ROC) curve analysis, tissue class separability analysis, and visual assessment by an expert radiologist were performed to study correlated diffusion imaging for the task of prostate cancer diagnosis. These results are compared with that obtained using T2-weighted imaging and standard diffusion imaging (via the apparent diffusion coefficient (ADC)). Experimental results suggest that correlated diffusion imaging provide improved delineation between healthy and cancerous tissue and may have potential as a diagnostic tool for cancer detection and localization in the prostate gland. A new form of diffusion magnetic resonance imaging called correlated diffusion imaging (CDI) was developed for the purpose of aiding radiologists in cancer detection and localization in the prostate gland. Preliminary results show CDI shows considerable promise as a diagnostic aid for radiologists in the detection and localization of prostate cancer

Spatio-temporal correlations in models of collective motion ruled by different dynamical laws.

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Cavagna, Andrea; Conti, Daniele; Giardina, Irene; Grigera, Tomas S; Melillo, Stefania; Viale, Massimiliano

2016-11-15

Information transfer is an essential factor in determining the robustness of biological systems with distributed control. The most direct way to study the mechanisms ruling information transfer is to experimentally observe the propagation across the system of a signal triggered by some perturbation. However, this method may be inefficient for experiments in the field, as the possibilities to perturb the system are limited and empirical observations must rely on natural events. An alternative approach is to use spatio-temporal correlations to probe the information transfer mechanism directly from the spontaneous fluctuations of the system, without the need to have an actual propagating signal on record. Here we test this method on models of collective behaviour in their deeply ordered phase by using ground truth data provided by numerical simulations in three dimensions. We compare two models characterized by very different dynamical equations and information transfer mechanisms: the classic Vicsek model, describing an overdamped noninertial dynamics and the inertial spin model, characterized by an underdamped inertial dynamics. By using dynamic finite-size scaling, we show that spatio-temporal correlations are able to distinguish unambiguously the diffusive information transfer mechanism of the Vicsek model from the linear mechanism of the inertial spin model.

Resolving Fast, Confined Diffusion in Bacteria with Image Correlation Spectroscopy.

Science.gov (United States)

Rowland, David J; Tuson, Hannah H; Biteen, Julie S

2016-05-24

By following single fluorescent molecules in a microscope, single-particle tracking (SPT) can measure diffusion and binding on the nanometer and millisecond scales. Still, although SPT can at its limits characterize the fastest biomolecules as they interact with subcellular environments, this measurement may require advanced illumination techniques such as stroboscopic illumination. Here, we address the challenge of measuring fast subcellular motion by instead analyzing single-molecule data with spatiotemporal image correlation spectroscopy (STICS) with a focus on measurements of confined motion. Our SPT and STICS analysis of simulations of the fast diffusion of confined molecules shows that image blur affects both STICS and SPT, and we find biased diffusion rate measurements for STICS analysis in the limits of fast diffusion and tight confinement due to fitting STICS correlation functions to a Gaussian approximation. However, we determine that with STICS, it is possible to correctly interpret the motion that blurs single-molecule images without advanced illumination techniques or fast cameras. In particular, we present a method to overcome the bias due to image blur by properly estimating the width of the correlation function by directly calculating the correlation function variance instead of using the typical Gaussian fitting procedure. Our simulation results are validated by applying the STICS method to experimental measurements of fast, confined motion: we measure the diffusion of cytosolic mMaple3 in living Escherichia coli cells at 25 frames/s under continuous illumination to illustrate the utility of STICS in an experimental parameter regime for which in-frame motion prevents SPT and tight confinement of fast diffusion precludes stroboscopic illumination. Overall, our application of STICS to freely diffusing cytosolic protein in small cells extends the utility of single-molecule experiments to the regime of fast confined diffusion without requiring advanced

A graph-based approach to detect spatiotemporal dynamics in satellite image time series

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Guttler, Fabio; Ienco, Dino; Nin, Jordi; Teisseire, Maguelonne; Poncelet, Pascal

2017-08-01

Enhancing the frequency of satellite acquisitions represents a key issue for Earth Observation community nowadays. Repeated observations are crucial for monitoring purposes, particularly when intra-annual process should be taken into account. Time series of images constitute a valuable source of information in these cases. The goal of this paper is to propose a new methodological framework to automatically detect and extract spatiotemporal information from satellite image time series (SITS). Existing methods dealing with such kind of data are usually classification-oriented and cannot provide information about evolutions and temporal behaviors. In this paper we propose a graph-based strategy that combines object-based image analysis (OBIA) with data mining techniques. Image objects computed at each individual timestamp are connected across the time series and generates a set of evolution graphs. Each evolution graph is associated to a particular area within the study site and stores information about its temporal evolution. Such information can be deeply explored at the evolution graph scale or used to compare the graphs and supply a general picture at the study site scale. We validated our framework on two study sites located in the South of France and involving different types of natural, semi-natural and agricultural areas. The results obtained from a Landsat SITS support the quality of the methodological approach and illustrate how the framework can be employed to extract and characterize spatiotemporal dynamics.

A novel image block cryptosystem based on a spatiotemporal chaotic system and a chaotic neural network

International Nuclear Information System (INIS)

Wang Xing-Yuan; Bao Xue-Mei

2013-01-01

In this paper, we propose a novel block cryptographic scheme based on a spatiotemporal chaotic system and a chaotic neural network (CNN). The employed CNN comprises a 4-neuron layer called a chaotic neuron layer (CNL), where the spatiotemporal chaotic system participates in generating its weight matrix and other parameters. The spatiotemporal chaotic system used in our scheme is the typical coupled map lattice (CML), which can be easily implemented in parallel by hardware. A 160-bit-long binary sequence is used to generate the initial conditions of the CML. The decryption process is symmetric relative to the encryption process. Theoretical analysis and experimental results prove that the block cryptosystem is secure and practical, and suitable for image encryption. (general)

Intracellular dynamics and fate of polystyrene nanoparticles in A549 Lung epithelial cells monitored by image (cross-) correlation spectroscopy and single particle tracking.

Science.gov (United States)

Deville, Sarah; Penjweini, Rozhin; Smisdom, Nick; Notelaers, Kristof; Nelissen, Inge; Hooyberghs, Jef; Ameloot, Marcel

2015-10-01

Novel insights in nanoparticle (NP) uptake routes of cells, their intracellular trafficking and subcellular targeting can be obtained through the investigation of their temporal and spatial behavior. In this work, we present the application of image (cross-) correlation spectroscopy (IC(C)S) and single particle tracking (SPT) to monitor the intracellular dynamics of polystyrene (PS) NPs in the human lung carcinoma A549 cell line. The ensemble kinetic behavior of NPs inside the cell was characterized by temporal and spatiotemporal image correlation spectroscopy (TICS and STICS). Moreover, a more direct interpretation of the diffusion and flow detected in the NP motion was obtained by SPT by monitoring individual NPs. Both techniques demonstrate that the PS NP transport in A549 cells is mainly dependent on microtubule-assisted transport. By applying spatiotemporal image cross-correlation spectroscopy (STICCS), the correlated motions of NPs with the early endosomes, late endosomes and lysosomes are identified. PS NPs were equally distributed among the endolysosomal compartment during the time interval of the experiments. The cotransport of the NPs with the lysosomes is significantly larger compared to the other cell organelles. In the present study we show that the complementarity of ICS-based techniques and SPT enables a consistent elaborate model of the complex behavior of NPs inside biological systems. Copyright © 2015 Elsevier B.V. All rights reserved.

Edge-based correlation image registration for multispectral imaging

Science.gov (United States)

Nandy, Prabal [Albuquerque, NM

2009-11-17

Registration information for images of a common target obtained from a plurality of different spectral bands can be obtained by combining edge detection and phase correlation. The images are edge-filtered, and pairs of the edge-filtered images are then phase correlated to produce phase correlation images. The registration information can be determined based on these phase correlation images.

Urban Link Travel Time Prediction Based on a Gradient Boosting Method Considering Spatiotemporal Correlations

Directory of Open Access Journals (Sweden)

Faming Zhang

2016-11-01

Full Text Available The prediction of travel times is challenging because of the sparseness of real-time traffic data and the intrinsic uncertainty of travel on congested urban road networks. We propose a new gradient–boosted regression tree method to accurately predict travel times. This model accounts for spatiotemporal correlations extracted from historical and real-time traffic data for adjacent and target links. This method can deliver high prediction accuracy by combining simple regression trees with poor performance. It corrects the error found in existing models for improved prediction accuracy. Our spatiotemporal gradient–boosted regression tree model was verified in experiments. The training data were obtained from big data reflecting historic traffic conditions collected by probe vehicles in Wuhan from January to May 2014. Real-time data were extracted from 11 weeks of GPS records collected in Wuhan from 5 May 2014 to 20 July 2014. Based on these data, we predicted link travel time for the period from 21 July 2014 to 25 July 2014. Experiments showed that our proposed spatiotemporal gradient–boosted regression tree model obtained better results than gradient boosting, random forest, or autoregressive integrated moving average approaches. Furthermore, these results indicate the advantages of our model for urban link travel time prediction.

SPATIOTEMPORAL CONTRAST SENSITIVITY OF EARLY VISION

NARCIS (Netherlands)

Hateren, J.H. van

Based on the spatial and temporal statistics of natural images, a theory is developed that specifies spatiotemporal filters that maximize the flow of information through noisy channels of limited dynamic range. Sensitivities resulting from these spatiotemporal filters are very similar to the human

Spatio-temporal imaging of the hemoglobin in the compressed breast with diffuse optical tomography

Science.gov (United States)

Boverman, Gregory; Fang, Qianqian; Carp, Stefan A.; Miller, Eric L.; Brooks, Dana H.; Selb, Juliette; Moore, Richard H.; Kopans, Daniel B.; Boas, David A.

2007-07-01

We develop algorithms for imaging the time-varying optical absorption within the breast given diffuse optical tomographic data collected over a time span that is long compared to the dynamics of the medium. Multispectral measurements allow for the determination of the time-varying total hemoglobin concentration and of oxygen saturation. To facilitate the image reconstruction, we decompose the hemodynamics in time into a linear combination of spatio-temporal basis functions, the coefficients of which are estimated using all of the data simultaneously, making use of a Newton-based nonlinear optimization algorithm. The solution of the extremely large least-squares problem which arises in computing the Newton update is obtained iteratively using the LSQR algorithm. A Laplacian spatial regularization operator is applied, and, in addition, we make use of temporal regularization which tends to encourage similarity between the images of the spatio-temporal coefficients. Results are shown for an extensive simulation, in which we are able to image and quantify localized changes in both total hemoglobin concentration and oxygen saturation. Finally, a breast compression study has been performed for a normal breast cancer screening subject, using an instrument which allows for highly accurate co-registration of multispectral diffuse optical measurements with an x-ray tomosynthesis image of the breast. We are able to quantify the global return of blood to the breast following compression, and, in addition, localized changes are observed which correspond to the glandular region of the breast.

Spatiotemporal processing of gated cardiac SPECT images using deformable mesh modeling

International Nuclear Information System (INIS)

Brankov, Jovan G.; Yang Yongyi; Wernick, Miles N.

2005-01-01

In this paper we present a spatiotemporal processing approach, based on deformable mesh modeling, for noise reduction in gated cardiac single-photon emission computed tomography images. Because of the partial volume effect (PVE), clinical cardiac-gated perfusion images exhibit a phenomenon known as brightening--the myocardium appears to become brighter as the heart wall thickens. Although brightening is an artifact, it serves as an important diagnostic feature for assessment of wall thickening in clinical practice. Our proposed processing algorithm aims to preserve this important diagnostic feature while reducing the noise level in the images. The proposed algorithm is based on the use of a deformable mesh for modeling the cardiac motion in a gated cardiac sequence, based on which the images are processed by smoothing along space-time trajectories of object points while taking into account the PVE. Our experiments demonstrate that the proposed algorithm can yield significantly more-accurate results than several existing methods

Spatio-temporal encoding using narrow-band linear frequency modulated signals in synthetic aperture ultrasound imaging

DEFF Research Database (Denmark)

Gran, Fredrik; Jensen, Jørgen Arendt

2005-01-01

In this paper a method for spatio-temporal encoding is presented for synthetic transmit aperture ultrasound imaging (STA). The purpose is to excite several transmitters at the same time in order to transmit more acoustic energy in every single transmission. When increasing the transmitted acousti...

Débito cardíaco e fração de ejeção fetal por meio do spatio-temporal image correlation (STIC: comparação entre fetos masculinos e femininos Fetal cardiac output and ejection fraction by spatio-temporal image correlation (STIC: comparison between male and female fetuses

Directory of Open Access Journals (Sweden)

Christiane Simioni

2012-06-01

Full Text Available OBJETIVO: Comparar do débito cardíaco (DC e a fração de ejeção (FE do coração de fetos masculinos e femininos obtidos por meio da ultrassonografia tridimensional, utilizando o spatio-temporal image correlation (STIC. MÉTODOS: Realizou-se um estudo de corte transversal com 216 fetos normais, entre 20 a 34 semanas de gestação, sendo 108 masculinos e 108 femininos. Os volumes ventriculares no final da sístole e diástole foram obtidos por meio do STIC, sendo as avaliações volumétricas realizadas pelo virtual organ computer-aided analysis (VOCAL com rotação de 30º. Para o cálculo do DC utilizou-se a fórmula: DC= volume sistólico/frequência cardíaca fetal, enquanto que para a FE utilizou-se a fórmula: FE= volume sistólico/volume diastólico final. O DC (combinado, feminino e masculino e a FE (masculina e feminina foram comparadas utilizando-se o teste t não pareado e ANCOVA. Foram criados gráficos de dispersão com os percentis 5, 50 e 95. RESULTADOS: A média do DC combinado, DC direito, DC esquerdo, FE direita e FE esquerda, para feminino e masculino, foram 240,07 mL/min; 122,67 mL/min; 123,40 mL/min; 72,84%; 67,22%; 270,56 mL/min; 139,22 mL/min; 131,34 mL/min; 70,73% e 64,76%, respectivamente; sem diferença estatística (P> 0,05. CONCLUSÕES: O DC e a FE fetal obtidos por meio da ultrassonografia tridimensional (STIC não apresentaram diferença significativa em relação ao gênero.OBJECTIVE: To compare the cardiac output (CO and ejection fraction (EF of the heart of male and female fetuses obtained by 3D-ultrasonography using spatio-temporal image correlation (STIC. METHODS: We conducted a cross-sectional study with 216 normal fetuses, between 20 and 34 weeks of gestation, 108 male and 108 female. Ventricular volumes at the end of systole and diastole were obtained by STIC, and the volumetric assessments performed by the virtual organ computer-aided analysis (VOCAL rotated 30º. To calculate the DC used the formula

Fully refocused multi-shot spatiotemporally encoded MRI: robust imaging in the presence of metallic implants.

Science.gov (United States)

Ben-Eliezer, Noam; Solomon, Eddy; Harel, Elad; Nevo, Nava; Frydman, Lucio

2012-12-01

An approach has been recently introduced for acquiring arbitrary 2D NMR spectra or images in a single scan, based on the use of frequency-swept RF pulses for the sequential excitation and acquisition of the spins response. This spatiotemporal-encoding (SPEN) approach enables a unique, voxel-by-voxel refocusing of all frequency shifts in the sample, for all instants throughout the data acquisition. The present study investigates the use of this full-refocusing aspect of SPEN-based imaging in the multi-shot MRI of objects, subject to sizable field inhomogeneities that complicate conventional imaging approaches. 2D MRI experiments were performed at 7 T on phantoms and on mice in vivo, focusing on imaging in proximity to metallic objects. Fully refocused SPEN-based spin echo imaging sequences were implemented, using both Cartesian and back-projection trajectories, and compared with k-space encoded spin echo imaging schemes collected on identical samples under equal bandwidths and acquisition timing conditions. In all cases assayed, the fully refocused spatiotemporally encoded experiments evidenced a ca. 50 % reduction in signal dephasing in the proximity of the metal, as compared to analogous results stemming from the k-space encoded spin echo counterparts. The results in this study suggest that SPEN-based acquisition schemes carry the potential to overcome strong field inhomogeneities, of the kind that currently preclude high-field, high-resolution tissue characterizations in the neighborhood of metallic implants.

Spatio-temporal change detection from multidimensional arrays: Detecting deforestation from MODIS time series

Science.gov (United States)

Lu, Meng; Pebesma, Edzer; Sanchez, Alber; Verbesselt, Jan

2016-07-01

Growing availability of long-term satellite imagery enables change modeling with advanced spatio-temporal statistical methods. Multidimensional arrays naturally match the structure of spatio-temporal satellite data and can provide a clean modeling process for complex spatio-temporal analysis over large datasets. Our study case illustrates the detection of breakpoints in MODIS imagery time series for land cover change in the Brazilian Amazon using the BFAST (Breaks For Additive Season and Trend) change detection framework. BFAST includes an Empirical Fluctuation Process (EFP) to alarm the change and a change point time locating process. We extend the EFP to account for the spatial autocorrelation between spatial neighbors and assess the effects of spatial correlation when applying BFAST on satellite image time series. In addition, we evaluate how sensitive EFP is to the assumption that its time series residuals are temporally uncorrelated, by modeling it as an autoregressive process. We use arrays as a unified data structure for the modeling process, R to execute the analysis, and an array database management system to scale computation. Our results point to BFAST as a robust approach against mild temporal and spatial correlation, to the use of arrays to ease the modeling process of spatio-temporal change, and towards communicable and scalable analysis.

Self-calibrated correlation imaging with k-space variant correlation functions.

Science.gov (United States)

Li, Yu; Edalati, Masoud; Du, Xingfu; Wang, Hui; Cao, Jie J

2018-03-01

Correlation imaging is a previously developed high-speed MRI framework that converts parallel imaging reconstruction into the estimate of correlation functions. The presented work aims to demonstrate this framework can provide a speed gain over parallel imaging by estimating k-space variant correlation functions. Because of Fourier encoding with gradients, outer k-space data contain higher spatial-frequency image components arising primarily from tissue boundaries. As a result of tissue-boundary sparsity in the human anatomy, neighboring k-space data correlation varies from the central to the outer k-space. By estimating k-space variant correlation functions with an iterative self-calibration method, correlation imaging can benefit from neighboring k-space data correlation associated with both coil sensitivity encoding and tissue-boundary sparsity, thereby providing a speed gain over parallel imaging that relies only on coil sensitivity encoding. This new approach is investigated in brain imaging and free-breathing neonatal cardiac imaging. Correlation imaging performs better than existing parallel imaging techniques in simulated brain imaging acceleration experiments. The higher speed enables real-time data acquisition for neonatal cardiac imaging in which physiological motion is fast and non-periodic. With k-space variant correlation functions, correlation imaging gives a higher speed than parallel imaging and offers the potential to image physiological motion in real-time. Magn Reson Med 79:1483-1494, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Effective and efficient analysis of spatio-temporal data

Science.gov (United States)

Zhang, Zhongnan

Spatio-temporal data mining, i.e., mining knowledge from large amount of spatio-temporal data, is a highly demanding field because huge amounts of spatio-temporal data have been collected in various applications, ranging from remote sensing, to geographical information systems (GIS), computer cartography, environmental assessment and planning, etc. The collection data far exceeded human's ability to analyze which make it crucial to develop analysis tools. Recent studies on data mining have extended to the scope of data mining from relational and transactional datasets to spatial and temporal datasets. Among the various forms of spatio-temporal data, remote sensing images play an important role, due to the growing wide-spreading of outer space satellites. In this dissertation, we proposed two approaches to analyze the remote sensing data. The first one is about applying association rules mining onto images processing. Each image was divided into a number of image blocks. We built a spatial relationship for these blocks during the dividing process. This made a large number of images into a spatio-temporal dataset since each image was shot in time-series. The second one implemented co-occurrence patterns discovery from these images. The generated patterns represent subsets of spatial features that are located together in space and time. A weather analysis is composed of individual analysis of several meteorological variables. These variables include temperature, pressure, dew point, wind, clouds, visibility and so on. Local-scale models provide detailed analysis and forecasts of meteorological phenomena ranging from a few kilometers to about 100 kilometers in size. When some of above meteorological variables have some special change tendency, some kind of severe weather will happen in most cases. Using the discovery of association rules, we found that some special meteorological variables' changing has tight relation with some severe weather situation that will happen

Spatio-temporal analysis of blood perfusion by imaging photoplethysmography

Science.gov (United States)

Zaunseder, Sebastian; Trumpp, Alexander; Ernst, Hannes; Förster, Michael; Malberg, Hagen

2018-02-01

Imaging photoplethysmography (iPPG) has attracted much attention over the last years. The vast majority of works focuses on methods to reliably extract the heart rate from videos. Only a few works addressed iPPGs ability to exploit spatio-temporal perfusion pattern to derive further diagnostic statements. This work directs at the spatio-temporal analysis of blood perfusion from videos. We present a novel algorithm that bases on the two-dimensional representation of the blood pulsation (perfusion map). The basic idea behind the proposed algorithm consists of a pairwise estimation of time delays between photoplethysmographic signals of spatially separated regions. The probabilistic approach yields a parameter denoted as perfusion speed. We compare the perfusion speed versus two parameters, which assess the strength of blood pulsation (perfusion strength and signal to noise ratio). Preliminary results using video data with different physiological stimuli (cold pressure test, cold face test) show that all measures are influenced by those stimuli (some of them with statistical certainty). The perfusion speed turned out to be more sensitive than the other measures in some cases. However, our results also show that the intraindividual stability and interindividual comparability of all used measures remain critical points. This work proves the general feasibility of employing the perfusion speed as novel iPPG quantity. Future studies will address open points like the handling of ballistocardiographic effects and will try to deepen the understanding of the predominant physiological mechanisms and their relation to the algorithmic performance.

Simultaneous spatio-temporal focusing for tissue manipulation

Directory of Open Access Journals (Sweden)

Squier J.

2013-11-01

Full Text Available Simultaneous spatiotemporal focusing (SSTF is applied to lens tissue and compared directly with standard femtosecond micromachining of the tissue at the same numerical aperture. Third harmonic generation imaging is used for spatio-temporal characterization of the processing conditions obtained with both a standard and SSTF focus.

The use of spatio-temporal correlation to forecast critical transitions

Science.gov (United States)

Karssenberg, Derek; Bierkens, Marc F. P.

2010-05-01

Complex dynamical systems may have critical thresholds at which the system shifts abruptly from one state to another. Such critical transitions have been observed in systems ranging from the human body system to financial markets and the Earth system. Forecasting the timing of critical transitions before they are reached is of paramount importance because critical transitions are associated with a large shift in dynamical regime of the system under consideration. However, it is hard to forecast critical transitions, because the state of the system shows relatively little change before the threshold is reached. Recently, it was shown that increased spatio-temporal autocorrelation and variance can serve as alternative early warning signal for critical transitions. However, thus far these second order statistics have not been used for forecasting in a data assimilation framework. Here we show that the use of spatio-temporal autocorrelation and variance in the state of the system reduces the uncertainty in the predicted timing of critical transitions compared to classical approaches that use the value of the system state only. This is shown by assimilating observed spatio-temporal autocorrelation and variance into a dynamical system model using a Particle Filter. We adapt a well-studied distributed model of a logistically growing resource with a fixed grazing rate. The model describes the transition from an underexploited system with high resource biomass to overexploitation as grazing pressure crosses the critical threshold, which is a fold bifurcation. To represent limited prior information, we use a large variance in the prior probability distributions of model parameters and the system driver (grazing rate). First, we show that the rate of increase in spatio-temporal autocorrelation and variance prior to reaching the critical threshold is relatively consistent across the uncertainty range of the driver and parameter values used. This indicates that an increase in

Intracellular localization and dynamics of Hypericin loaded PLLA nanocarriers by image correlation spectroscopy.

Science.gov (United States)

Penjweini, Rozhin; Deville, Sarah; D'Olieslaeger, Lien; Berden, Mandy; Ameloot, Marcel; Ethirajan, Anitha

2015-11-28

The study of cell-nanoparticle interactions is an important aspect for understanding drug delivery using nanocarriers. In this regard, advances in fluorescence based microscopy are useful for the investigation of temporal and spatial behavior of nanoparticles (NPs) within the intracellular environment. In this work, we focus on the delivery of the naturally-occurring hydrophobic photosensitizer Hypericin in human lung carcinoma A549 cells by using biodegradable poly L-lactic acid NPs. For the first time, Hypericin containing NPs are prepared by combining the miniemulsion technique with the solvent evaporation method. This approach yields an efficient loading of the NPs with Hypericin and allows for additional cargo molecules. To monitor the release of Hypercin from the NPs, an additional fluorescent lipophilic dye Coumarin-6 is incorporated in the NPs. Temporal and spatiotemporal image correlation spectroscopy is used to determine the fate of the NPs carrying the potential cargo. Both directed and non-directed motions are detected. By using image cross-correlation spectroscopy and specific fluorescent labeling of endosomes, lysosomes and mitochondria, the dynamics of the cargo loaded NPs in association with the organelles is studied. Copyright © 2015 Elsevier B.V. All rights reserved.

The spatiotemporal pattern of Src activation at lipid rafts revealed by diffusion-corrected FRET imaging.

Directory of Open Access Journals (Sweden)

Shaoying Lu

2008-07-01

Full Text Available Genetically encoded biosensors based on fluorescence resonance energy transfer (FRET have been widely applied to visualize the molecular activity in live cells with high spatiotemporal resolution. However, the rapid diffusion of biosensor proteins hinders a precise reconstruction of the actual molecular activation map. Based on fluorescence recovery after photobleaching (FRAP experiments, we have developed a finite element (FE method to analyze, simulate, and subtract the diffusion effect of mobile biosensors. This method has been applied to analyze the mobility of Src FRET biosensors engineered to reside at different subcompartments in live cells. The results indicate that the Src biosensor located in the cytoplasm moves 4-8 folds faster (0.93+/-0.06 microm(2/sec than those anchored on different compartments in plasma membrane (at lipid raft: 0.11+/-0.01 microm(2/sec and outside: 0.18+/-0.02 microm(2/sec. The mobility of biosensor at lipid rafts is slower than that outside of lipid rafts and is dominated by two-dimensional diffusion. When this diffusion effect was subtracted from the FRET ratio images, high Src activity at lipid rafts was observed at clustered regions proximal to the cell periphery, which remained relatively stationary upon epidermal growth factor (EGF stimulation. This result suggests that EGF induced a Src activation at lipid rafts with well-coordinated spatiotemporal patterns. Our FE-based method also provides an integrated platform of image analysis for studying molecular mobility and reconstructing the spatiotemporal activation maps of signaling molecules in live cells.

Second-order analysis of structured inhomogeneous spatio-temporal point processes

DEFF Research Database (Denmark)

Møller, Jesper; Ghorbani, Mohammad

Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for first general inhomogeneous spatio-temporal point processes and second inhomogeneous spatio-temporal Cox processes. Assuming...... spatio-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates e.g. to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio......-temporal Gaussian process. Another concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data (the UK 2001 epidemic foot and mouth disease data)....

Aspects of second-order analysis of structured inhomogeneous spatio-temporal processes

DEFF Research Database (Denmark)

Møller, Jesper; Ghorbani, Mohammad

2012-01-01

Statistical methodology for spatio-temporal point processes is in its infancy. We consider second-order analysis based on pair correlation functions and K-functions for general inhomogeneous spatio-temporal point processes and for inhomogeneous spatio-temporal Cox processes. Assuming spatio......-temporal separability of the intensity function, we clarify different meanings of second-order spatio-temporal separability. One is second-order spatio-temporal independence and relates to log-Gaussian Cox processes with an additive covariance structure of the underlying spatio-temporal Gaussian process. Another...... concerns shot-noise Cox processes with a separable spatio-temporal covariance density. We propose diagnostic procedures for checking hypotheses of second-order spatio-temporal separability, which we apply on simulated and real data....

Transport and accumulation of PVP-Hypericin in cancer and normal cells characterized by image correlation spectroscopy techniques.

Science.gov (United States)

Penjweini, Rozhin; Smisdom, Nick; Deville, Sarah; Ameloot, Marcel

2014-05-01

PVP-Hypericin (PVP: polyvinylpyrrolidone) is a potent anti-cancer photosensitizer for photodynamic diagnosis (PDD) and therapy (PDT). However, cellular targets and mechanisms involved in the cancer-selectivity of the photosensitizer are not yet fully understood. This paper gives new insights into the differential transport and localization of PVP-Hypericin in cancer and normal cells which are essential to unravel the mechanisms of action and cancer-selectivity. Temporal (TICS) and spatiotemporal (STICS) image correlation spectroscopy are used for the assessment of PVP-Hypericin diffusion and/or velocity in the case of concerted flow in human cervical epithelial HeLa and human lung carcinoma A549 cells, as well as in human primary dendritic cells (DC) and human peripheral blood mononuclear cells (PBMC). Spatiotemporal image cross-correlation spectroscopy (STICCS) based on organelle specific fluorescent labeling is employed to study the accumulation of the photosensitizer in nucleus, mitochondria, early-endosomes and lysosomes of the cells and to assess the dynamics of co-migrating molecules. Whereas STICS and TICS did not show a remarkable difference between the dynamics of PVP-Hypericin in HeLa, A549 and DC cells, a significantly different diffusion rate of the photosensitizer was measured in PBMC. STICCS detected a stationary accumulation of PVP-Hypericin within the nucleus, mitochondria, early endosomes and lysosomes of HeLa and A549 cells. However, significant flow due to the directed motion of the organelles was detected. In contrast, no accumulation in the nucleus and mitochondria of DC and PBMC could be monitored. Copyright © 2014 Elsevier B.V. All rights reserved.

Registration of angiographic image on real-time fluoroscopic image for image-guided percutaneous coronary intervention.

Science.gov (United States)

Kim, Dongkue; Park, Sangsoo; Jeong, Myung Ho; Ryu, Jeha

2018-02-01

In percutaneous coronary intervention (PCI), cardiologists must study two different X-ray image sources: a fluoroscopic image and an angiogram. Manipulating a guidewire while alternately monitoring the two separate images on separate screens requires a deep understanding of the anatomy of coronary vessels and substantial training. We propose 2D/2D spatiotemporal image registration of the two images in a single image in order to provide cardiologists with enhanced visual guidance in PCI. The proposed 2D/2D spatiotemporal registration method uses a cross-correlation of two ECG series in each image to temporally synchronize two separate images and register an angiographic image onto the fluoroscopic image. A guidewire centerline is then extracted from the fluoroscopic image in real time, and the alignment of the centerline with vessel outlines of the chosen angiographic image is optimized using the iterative closest point algorithm for spatial registration. A proof-of-concept evaluation with a phantom coronary vessel model with engineering students showed an error reduction rate greater than 74% on wrong insertion to nontarget branches compared to the non-registration method and more than 47% reduction in the task completion time in performing guidewire manipulation for very difficult tasks. Evaluation with a small number of experienced doctors shows a potentially significant reduction in both task completion time and error rate for difficult tasks. The total registration time with real procedure X-ray (angiographic and fluoroscopic) images takes [Formula: see text] 60 ms, which is within the fluoroscopic image acquisition rate of 15 Hz. By providing cardiologists with better visual guidance in PCI, the proposed spatiotemporal image registration method is shown to be useful in advancing the guidewire to the coronary vessel branches, especially those difficult to insert into.

Geometrical optics in correlated imaging systems

International Nuclear Information System (INIS)

Cao Dezhong; Xiong Jun; Wang Kaige

2005-01-01

We discuss the geometrical optics of correlated imaging for two kinds of spatial correlations corresponding, respectively, to a classical thermal light source and a quantum two-photon entangled source. Due to the different features in the second-order spatial correlation, the two sources obey different imaging equations. The quantum entangled source behaves as a mirror, whereas the classical thermal source looks like a phase-conjugate mirror in the correlated imaging

Image scale measurement with correlation filters in a volume holographic optical correlator

Science.gov (United States)

Zheng, Tianxiang; Cao, Liangcai; He, Qingsheng; Jin, Guofan

2013-08-01

A search engine containing various target images or different part of a large scene area is of great use for many applications, including object detection, biometric recognition, and image registration. The input image captured in realtime is compared with all the template images in the search engine. A volume holographic correlator is one type of these search engines. It performs thousands of comparisons among the images at a super high speed, with the correlation task accomplishing mainly in optics. However, the inputted target image always contains scale variation to the filtering template images. At the time, the correlation values cannot properly reflect the similarity of the images. It is essential to estimate and eliminate the scale variation of the inputted target image. There are three domains for performing the scale measurement, as spatial, spectral and time domains. Most methods dealing with the scale factor are based on the spatial or the spectral domains. In this paper, a method with the time domain is proposed to measure the scale factor of the input image. It is called a time-sequential scaled method. The method utilizes the relationship between the scale variation and the correlation value of two images. It sends a few artificially scaled input images to compare with the template images. The correlation value increases and decreases with the increasing of the scale factor at the intervals of 0.8~1 and 1~1.2, respectively. The original scale of the input image can be measured by estimating the largest correlation value through correlating the artificially scaled input image with the template images. The measurement range for the scale can be 0.8~4.8. Scale factor beyond 1.2 is measured by scaling the input image at the factor of 1/2, 1/3 and 1/4, correlating the artificially scaled input image with the template images, and estimating the new corresponding scale factor inside 0.8~1.2.

A flexible spatiotemporal method for fusing satellite images with different resolutions

Science.gov (United States)

Xiaolin Zhu; Eileen H. Helmer; Feng Gao; Desheng Liu; Jin Chen; Michael A. Lefsky

2016-01-01

Studies of land surface dynamics in heterogeneous landscapes often require remote sensing datawith high acquisition frequency and high spatial resolution. However, no single sensor meets this requirement. This study presents a new spatiotemporal data fusion method, the Flexible Spatiotemporal DAta Fusion (FSDAF) method, to generate synthesized frequent high spatial...

Monitoring the Spatiotemporal Activities of miRNAs in Small Animal Models Using Molecular Imaging Modalities

Directory of Open Access Journals (Sweden)

Patrick Baril

2015-03-01

Full Text Available MicroRNAs (miRNAs are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

Monitoring the spatiotemporal activities of miRNAs in small animal models using molecular imaging modalities.

Science.gov (United States)

Baril, Patrick; Ezzine, Safia; Pichon, Chantal

2015-03-04

MicroRNAs (miRNAs) are a class of small non-coding RNAs that regulate gene expression by binding mRNA targets via sequence complementary inducing translational repression and/or mRNA degradation. A current challenge in the field of miRNA biology is to understand the functionality of miRNAs under physiopathological conditions. Recent evidence indicates that miRNA expression is more complex than simple regulation at the transcriptional level. MiRNAs undergo complex post-transcriptional regulations such miRNA processing, editing, accumulation and re-cycling within P-bodies. They are dynamically regulated and have a well-orchestrated spatiotemporal localization pattern. Real-time and spatio-temporal analyses of miRNA expression are difficult to evaluate and often underestimated. Therefore, important information connecting miRNA expression and function can be lost. Conventional miRNA profiling methods such as Northern blot, real-time PCR, microarray, in situ hybridization and deep sequencing continue to contribute to our knowledge of miRNA biology. However, these methods can seldom shed light on the spatiotemporal organization and function of miRNAs in real-time. Non-invasive molecular imaging methods have the potential to address these issues and are thus attracting increasing attention. This paper reviews the state-of-the-art of methods used to detect miRNAs and discusses their contribution in the emerging field of miRNA biology and therapy.

A Spatiotemporal Multi-View-Based Learning Method for Short-Term Traffic Forecasting

Directory of Open Access Journals (Sweden)

Shifen Cheng

2018-06-01

Full Text Available Short-term traffic forecasting plays an important part in intelligent transportation systems. Spatiotemporal k-nearest neighbor models (ST-KNNs have been widely adopted for short-term traffic forecasting in which spatiotemporal matrices are constructed to describe traffic conditions. The performance of the models is closely related to the spatial dependencies, the temporal dependencies, and the interaction of spatiotemporal dependencies. However, these models use distance functions and correlation coefficients to identify spatial neighbors and measure the temporal interaction by only considering the temporal closeness of traffic, which result in existing ST-KNNs that cannot fully reflect the essential features of road traffic. This study proposes an improved spatiotemporal k-nearest neighbor model for short-term traffic forecasting by utilizing a multi-view learning algorithm named MVL-STKNN that fully considers the spatiotemporal dependencies of traffic data. First, the spatial neighbors for each road segment are automatically determined using cross-correlation under different temporal dependencies. Three spatiotemporal views are built on the constructed spatiotemporal closeness, periodic, and trend matrices to represent spatially heterogeneous traffic states. Second, a spatiotemporal weighting matrix is introduced into the ST-KNN model to recognize similar traffic patterns in the three spatiotemporal views. Finally, the results of traffic pattern recognition under these three spatiotemporal views are aggregated by using a neural network algorithm to describe the interaction of spatiotemporal dependencies. Extensive experiments were conducted using real vehicular-speed datasets collected on city roads and expressways. In comparison with baseline methods, the results show that the MVL-STKNN model greatly improves short-term traffic forecasting by lowering the mean absolute percentage error between 28.24% and 46.86% for the city road dataset and

A framework for noise-power spectrum analysis of multidimensional images

International Nuclear Information System (INIS)

Siewerdsen, J.H.; Cunningham, I.A.; Jaffray, D.A.

2002-01-01

A methodological framework for experimental analysis of the noise-power spectrum (NPS) of multidimensional images is presented that employs well-known properties of the n-dimensional (nD) Fourier transform. The approach is generalized to n dimensions, reducing to familiar cases for n=1 (e.g., time series) and n=2 (e.g., projection radiography) and demonstrated experimentally for two cases in which n=3 (viz., using an active matrix flat-panel imager for x-ray fluoroscopy and cone-beam CT to form three-dimensional (3D) images in spatiotemporal and volumetric domains, respectively). The relationship between fully nD NPS analysis and various techniques for analyzing a 'central slice' of the NPS is formulated in a manner that is directly applicable to measured nD data, highlights the effects of correlation, and renders issues of NPS normalization transparent. The spatiotemporal NPS of fluoroscopic images is analyzed under varying conditions of temporal correlation (image lag) to investigate the degree to which the NPS is reduced by such correlation. For first-frame image lag of ∼5-8 %, the NPS is reduced by ∼20% compared to the lag-free case. A simple model is presented that results in an approximate rule of thumb for computing the effect of image lag on NPS under conditions of spatiotemporal separability. The volumetric NPS of cone-beam CT images is analyzed under varying conditions of spatial correlation, controlled by adjustment of the reconstruction filter. The volumetric NPS is found to be highly asymmetric, exhibiting a ramp characteristic in transverse planes (typical of filtered back-projection) and a band-limited characteristic in the longitudinal direction (resulting from low-pass characteristics of the imager). Such asymmetry could have implications regarding the detectability of structures visualized in transverse versus sagittal or coronal planes. In all cases, appreciation of the full dimensionality of the image data is essential to obtaining

Mechanical shape correlation : a novel integrated digital image correlation approach

NARCIS (Netherlands)

Kleinendorst, S.M.; Hoefnagels, J.P.M.; Geers, M.G.D.; Lamberti, L.; Lin, M.-T.; Furlong, C.; Sciammarella, C.

2018-01-01

Mechanical Shape Correlation (MSC) is a novel integrated digital image correlation technique, used to determine the optimal set of constitutive parameters to describe the experimentally observed mechanical behavior of a test specimen, based on digital images taken during the experiment. In contrast

Ghost imaging with third-order correlated thermal light

International Nuclear Information System (INIS)

Ou, L-H; Kuang, L-M

2007-01-01

In this paper, we propose a ghost imaging scheme with third-order correlated thermal light. We show that it is possible to produce the spatial information of an object at two different places in a nonlocal fashion by means of a third-order correlated imaging process with a third-order correlated thermal source and third-order correlation measurement. Concretely, we propose a protocol to create two ghost images at two different places from one object. This protocol involves two optical configurations. We derive the Gaussian thin lens equations and plot the geometrical optics of the ghost imaging processes for the two configurations. It is indicated that third-order correlated ghost imaging with thermal light exhibits richer correlated imaging effects than second-order correlated ghost imaging with thermal light

Correlative intravital imaging of cGMP signals and vasodilation in mice

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Martin eThunemann

2014-10-01

Full Text Available Cyclic guanosine monophosphate (cGMP is an important signaling molecule and drug target in the cardiovascular system. It is well known that stimulation of the vascular nitric oxide (NO-cGMP pathway results in vasodilation. However, the spatiotemporal dynamics of cGMP signals themselves and the cGMP concentrations within specific cardiovascular cell types in health, disease, and during pharmacotherapy with cGMP-elevating drugs are largely unknown. To facilitate the analysis of cGMP signaling in vivo, we have generated transgenic mice that express fluorescence resonance energy transfer (FRET-based cGMP sensor proteins. Here, we describe two models of intravital FRET/cGMP imaging in the vasculature of cGMP sensor mice: (1 epifluorescence-based ratio imaging in resistance-type vessels of the cremaster muscle and (2 ratio imaging by multiphoton microscopy within the walls of subcutaneous blood vessels accessed through a dorsal skinfold chamber. Both methods allow simultaneous monitoring of NO-induced cGMP transients and vasodilation in living mice. Detailed protocols of all steps necessary to perform and evaluate intravital imaging experiments of the vasculature of anesthetized mice including surgery, imaging, and data evaluation are provided. An image segmentation approach is described to estimate FRET/cGMP changes within moving structures such as the vessel wall during vasodilation. The methods presented herein should be useful to visualize cGMP or other biochemical signals that are detectable with FRET-based biosensors, such as cyclic adenosine monophosphate or Ca2+, and to correlate them with respective vascular responses. With further refinement and combination of transgenic mouse models and intravital imaging technologies, we envision an exciting future, in which we are able to ‘watch’ biochemistry, (patho physiology, and pharmacotherapy in the context of a living mammalian organism.

Spatiotemporal distribution of algal and nutrient, and their correlations based on long-term monitoring data in Lake Taihu, China

Science.gov (United States)

Acharya, K.; Li, Y.; Stone, M.; Yu, Z.; Young, M.; Shafer, D. S.; Zhu, J.; Warwick, J. J.

2009-12-01

Eutrophication in Lake Taihu - China’s third largest freshwater lake - has led to deterioration of water quality and caused more frequent cyanobacteria blooms at many lake locations in recent years. Eutrophication is thought to be fueled by increased nutrient loading, a consequence of rapid population and economic growth in the region. To understand the spatiotemporal distribution of algal blooms, a database was developed that includes long-term meteorological, hydrological, water quality, and socioeconomic data from the Lake Taihu watershed. The data were collected through various field observations, and augmented with information from local and provincial agencies, and universities. Based on the data, spatiotemporal distributions of, and correlations between, chlorophyll-a (Chl-a), total phosphorus (TP), total nitrogen (TN) and water temperature (WT) were analyzed. Results revealed a high degree of correlation between TP and Chl-a concentrations during warm seasons, with high concentrations of both substances present in the northern and northwest portions of the lake. During winter months, Chl-a concentrations were more strongly correlated with WT. Spatial trends in TP and TN concentrations corresponded to observed nutrient fluxes from adjoining rivers in densely populated areas, demonstrating the influence of watershed pollutant loads on lake water quality. Among important questions to be answered is whether wind-driven resuspension of existing nutrients in sediments in this shallow (cyanobacteria blooms to begin. This study identifies other questions, data gaps, and research needs, and provides a foundation for improving lake management strategies.

An implicit spatiotemporal shape model for human activity localization and recognition

NARCIS (Netherlands)

Oikonomopoulos, A.; Patras, I.; Pantic, Maja

2009-01-01

In this paper we address the problem of localisation and recognition of human activities in unsegmented image sequences. The main contribution of the proposed method is the use of an implicit representation of the spatiotemporal shape of the activity which relies on the spatiotemporal localization

Prenatal diagnosis of congenital heart disease using four-dimensional spatio-temporal image correlation (STIC) telemedicine via an Internet link: a pilot study.

Science.gov (United States)

Viñals, F; Mandujano, L; Vargas, G; Giuliano, A

2005-01-01

To assess whether the spatio-temporal image correlation (STIC) acquisition technique can be taught to a general obstetrician by e-mail; whether STIC volume datasets can be transmitted over the Internet; and whether STIC volume datasets analyzed offline at a remote setting can be used to confirm or exclude major cardiac defects (TELE-STIC). This was a prospective study involving 50 pregnant women with gestational ages ranging between 20 and 36 weeks. These patients were selected by two general obstetricians (operators) working in geographically remote areas of Chile. Although both obstetricians were users of equipment capable of four-dimensional (4D) ultrasound with STIC, they lacked skill in the performance of fetal cardiac examination. A dedicated web disk was created to upload the acquired volume datasets using an Internet broadband connection. Offline analysis was performed by a single investigator experienced in fetal echocardiography (the administrator). A telemedicine link via the Internet was possible in all cases. Seventy-seven volume datasets were sent to the web server. A complete cardiac examination according to set criteria was achieved by the administrator in 86% of the cases scanned by one operator and 95% of the cases scanned by the other operator. Three patients had cardiac defects confirmed postnatally, two fetuses had extracardiac anomalies and one fetus had a suspected cardiac defect unconfirmed by second-opinion TELE-STIC. There were two isolated major congenital heart defects. Both patients were given advice by e-mail and teleconference using a web camera about the likely outcome and benefits of scheduling in utero transport to a tertiary care center. STIC volumes can be obtained by operators inexperienced in fetal echocardiography, transmitted via the Internet, and their analysis enables recognition of most of the structures and views necessary to assess fetal cardiac anatomy. The preliminary use of TELE-STIC allowed us to demonstrate that

Quaternionic Spatiotemporal Filtering for Dense Motion Field Estimation in Ultrasound Imaging

Directory of Open Access Journals (Sweden)

Marion Adrien

2010-01-01

Full Text Available Abstract Blood motion estimation provides fundamental clinical information to prevent and detect pathologies such as cancer. Ultrasound imaging associated with Doppler methods is often used for blood flow evaluation. However, Doppler methods suffer from shortcomings such as limited spatial resolution and the inability to estimate lateral motion. Numerous methods such as block matching and decorrelation-based techniques have been proposed to overcome these limitations. In this paper, we propose an original method to estimate dense fields of vector velocity from ultrasound image sequences. Our proposal is based on a spatiotemporal approach and considers 2D+t data as a 3D volume. Orientation of the texture within this volume is related to velocity. Thus, we designed a bank of 3D quaternionic filters to estimate local orientation and then calculate local velocities. The method was applied to a large set of experimental and simulated flow sequences with low motion ( 1 mm/s within small vessels ( 1 mm. Evaluation was conducted with several quantitative criteria such as the normalized mean error or the estimated mean velocity. The results obtained show the good behaviour of our method, characterizing the flows studied.

Reliability-guided digital image correlation for image deformation measurement

International Nuclear Information System (INIS)

Pan Bing

2009-01-01

A universally applicable reliability-guided digital image correlation (DIC) method is proposed for reliable image deformation measurement. The zero-mean normalized cross correlation (ZNCC) coefficient is used to identify the reliability of the point computed. The correlation calculation begins with a seed point and is then guided by the ZNCC coefficient. That means the neighbors of the point with the highest ZNCC coefficient in a queue for computed points will be processed first. Thus the calculation path is always along the most reliable direction, and possible error propagation of the conventional DIC method can be avoided. The proposed novel DIC method is universally applicable to the images with shadows, discontinuous areas, and deformation discontinuity. Two image pairs were used to evaluate the performance of the proposed technique, and the successful results clearly demonstrate its robustness and effectiveness

Finite element formulation for a digital image correlation method

International Nuclear Information System (INIS)

Sun Yaofeng; Pang, John H. L.; Wong, Chee Khuen; Su Fei

2005-01-01

A finite element formulation for a digital image correlation method is presented that will determine directly the complete, two-dimensional displacement field during the image correlation process on digital images. The entire interested image area is discretized into finite elements that are involved in the common image correlation process by use of our algorithms. This image correlation method with finite element formulation has an advantage over subset-based image correlation methods because it satisfies the requirements of displacement continuity and derivative continuity among elements on images. Numerical studies and a real experiment are used to verify the proposed formulation. Results have shown that the image correlation with the finite element formulation is computationally efficient, accurate, and robust

Image correlation method for DNA sequence alignment.

Science.gov (United States)

Curilem Saldías, Millaray; Villarroel Sassarini, Felipe; Muñoz Poblete, Carlos; Vargas Vásquez, Asticio; Maureira Butler, Iván

2012-01-01

The complexity of searches and the volume of genomic data make sequence alignment one of bioinformatics most active research areas. New alignment approaches have incorporated digital signal processing techniques. Among these, correlation methods are highly sensitive. This paper proposes a novel sequence alignment method based on 2-dimensional images, where each nucleic acid base is represented as a fixed gray intensity pixel. Query and known database sequences are coded to their pixel representation and sequence alignment is handled as object recognition in a scene problem. Query and database become object and scene, respectively. An image correlation process is carried out in order to search for the best match between them. Given that this procedure can be implemented in an optical correlator, the correlation could eventually be accomplished at light speed. This paper shows an initial research stage where results were "digitally" obtained by simulating an optical correlation of DNA sequences represented as images. A total of 303 queries (variable lengths from 50 to 4500 base pairs) and 100 scenes represented by 100 x 100 images each (in total, one million base pair database) were considered for the image correlation analysis. The results showed that correlations reached very high sensitivity (99.01%), specificity (98.99%) and outperformed BLAST when mutation numbers increased. However, digital correlation processes were hundred times slower than BLAST. We are currently starting an initiative to evaluate the correlation speed process of a real experimental optical correlator. By doing this, we expect to fully exploit optical correlation light properties. As the optical correlator works jointly with the computer, digital algorithms should also be optimized. The results presented in this paper are encouraging and support the study of image correlation methods on sequence alignment.

Analysis of Correlation Tendency between Wind and Solar from Various Spatio-temporal Perspectives

Science.gov (United States)

Wang, X.; Weihua, X.; Mei, Y.

2017-12-01

Analysis of correlation between wind resources and solar resources could explore their complementary features, enhance the utilization efficiency of renewable energy and further alleviate the carbon emission issues caused by the fossil energy. In this paper, we discuss the correlation between wind and solar from various spatio-temporal perspectives (from east to west, in terms of plain, plateau, hill, and mountain, from hourly to daily, ten days and monthly) with observed data and modeled data from NOAA (National Oceanic and Atmospheric Administration) and NERL (National Renewable Energy Laboratory). With investigation of wind speed time series and solar radiation time series (period: 10 years, resolution: 1h) of 72 stations located in various landform and distributed dispersedly in USA, the results show that the correlation coefficient, Kendall's rank correlation coefficient, changes negative to positive value from east coast to west coast of USA, and this phenomena become more obvious when the time scale of resolution increases from daily to ten days and monthly. Furthermore, considering the differences of landforms which influence the local meteorology the Kendall coefficients of diverse topographies are compared and it is found that the coefficients descend from mountain to hill, plateau and plain. However, no such evident tendencies could be found in daily scale. According to this research, it is proposed that the complementary feature of wind resources and solar resources in the east or in the mountain area of USA is conspicuous. Subsequent study would try to further verify this analysis by investigating the operation status of wind power station and solar power station.

Quantum Image Encryption Algorithm Based on Image Correlation Decomposition

Science.gov (United States)

Hua, Tianxiang; Chen, Jiamin; Pei, Dongju; Zhang, Wenquan; Zhou, Nanrun

2015-02-01

A novel quantum gray-level image encryption and decryption algorithm based on image correlation decomposition is proposed. The correlation among image pixels is established by utilizing the superposition and measurement principle of quantum states. And a whole quantum image is divided into a series of sub-images. These sub-images are stored into a complete binary tree array constructed previously and then randomly performed by one of the operations of quantum random-phase gate, quantum revolving gate and Hadamard transform. The encrypted image can be obtained by superimposing the resulting sub-images with the superposition principle of quantum states. For the encryption algorithm, the keys are the parameters of random phase gate, rotation angle, binary sequence and orthonormal basis states. The security and the computational complexity of the proposed algorithm are analyzed. The proposed encryption algorithm can resist brute force attack due to its very large key space and has lower computational complexity than its classical counterparts.

Spatiotemporal alignment of in utero BOLD-MRI series.

Science.gov (United States)

Turk, Esra Abaci; Luo, Jie; Gagoski, Borjan; Pascau, Javier; Bibbo, Carolina; Robinson, Julian N; Grant, P Ellen; Adalsteinsson, Elfar; Golland, Polina; Malpica, Norberto

2017-08-01

To present a method for spatiotemporal alignment of in-utero magnetic resonance imaging (MRI) time series acquired during maternal hyperoxia for enabling improved quantitative tracking of blood oxygen level-dependent (BOLD) signal changes that characterize oxygen transport through the placenta to fetal organs. The proposed pipeline for spatiotemporal alignment of images acquired with a single-shot gradient echo echo-planar imaging includes 1) signal nonuniformity correction, 2) intravolume motion correction based on nonrigid registration, 3) correction of motion and nonrigid deformations across volumes, and 4) detection of the outlier volumes to be discarded from subsequent analysis. BOLD MRI time series collected from 10 pregnant women during 3T scans were analyzed using this pipeline. To assess pipeline performance, signal fluctuations between consecutive timepoints were examined. In addition, volume overlap and distance between manual region of interest (ROI) delineations in a subset of frames and the delineations obtained through propagation of the ROIs from the reference frame were used to quantify alignment accuracy. A previously demonstrated rigid registration approach was used for comparison. The proposed pipeline improved anatomical alignment of placenta and fetal organs over the state-of-the-art rigid motion correction methods. In particular, unexpected temporal signal fluctuations during the first normoxia period were significantly decreased (P quantitative studies of placental function by improving spatiotemporal alignment across placenta and fetal organs. 1 Technical Efficacy: Stage 1 J. MAGN. RESON. IMAGING 2017;46:403-412. © 2017 International Society for Magnetic Resonance in Medicine.

How about a Bayesian M/EEG imaging method correcting for incomplete spatio-temporal priors

DEFF Research Database (Denmark)

Stahlhut, Carsten; Attias, Hagai T.; Sekihara, Kensuke

2013-01-01

previous spatio-temporal inverse M/EEG models, the proposed model benefits of consisting of two source terms, namely, a spatio-temporal pattern term limiting the source configuration to a spatio-temporal subspace and a source correcting term to pick up source activity not covered by the spatio......-temporal prior belief. We have tested the model on both artificial data and real EEG data in order to demonstrate the efficacy of the model. The model was tested at different SNRs (-10.0,-5.2, -3.0, -1.0, 0, 0.8, 3.0 dB) using white noise. At all SNRs the sAquavit performs best in AUC measure, e.g. at SNR=0d...

Correlated statistical uncertainties in coded-aperture imaging

International Nuclear Information System (INIS)

Fleenor, Matthew C.; Blackston, Matthew A.; Ziock, Klaus P.

2015-01-01

In nuclear security applications, coded-aperture imagers can provide a wealth of information regarding the attributes of both the radioactive and nonradioactive components of the objects being imaged. However, for optimum benefit to the community, spatial attributes need to be determined in a quantitative and statistically meaningful manner. To address a deficiency of quantifiable errors in coded-aperture imaging, we present uncertainty matrices containing covariance terms between image pixels for MURA mask patterns. We calculated these correlated uncertainties as functions of variation in mask rank, mask pattern over-sampling, and whether or not anti-mask data are included. Utilizing simulated point source data, we found that correlations arose when two or more image pixels were summed. Furthermore, we found that the presence of correlations was heightened by the process of over-sampling, while correlations were suppressed by the inclusion of anti-mask data and with increased mask rank. As an application of this result, we explored how statistics-based alarming is impacted in a radiological search scenario

Image processing by use of the digital cross-correlator

International Nuclear Information System (INIS)

Katou, Yoshinori

1982-01-01

We manufactured for trial an instrument which achieved the image processing using digital correlators. A digital correlator perform 64-bit parallel correlation at 20 MH. The output of a digital correlator is a 7-bit word representing. An A-D converter is used to quantize it a precision of six bits. The resulting 6-bit word is fed to six correlators, wired in parallel. The image processing achieved in 12 bits, whose digital outputs converted an analog signal by a D-A converter. This instrument is named the digital cross-correlator. The method which was used in the image processing system calculated the convolution with the digital correlator. It makes various digital filters. In the experiment with the image processing video signals from TV camera were used. The digital image processing time was approximately 5 μs. The contrast was enhanced and smoothed. The digital cross-correlator has the image processing of 16 sorts, and was produced inexpensively. (author)

DIfferential Subsampling with Cartesian Ordering (DISCO): a high spatio-temporal resolution Dixon imaging sequence for multiphasic contrast enhanced abdominal imaging.

Science.gov (United States)

Saranathan, Manojkumar; Rettmann, Dan W; Hargreaves, Brian A; Clarke, Sharon E; Vasanawala, Shreyas S

2012-06-01

To develop and evaluate a multiphasic contrast-enhanced MRI method called DIfferential Sub-sampling with Cartesian Ordering (DISCO) for abdominal imaging. A three-dimensional, variable density pseudo-random k-space segmentation scheme was developed and combined with a Dixon-based fat-water separation algorithm to generate high temporal resolution images with robust fat suppression and without compromise in spatial resolution or coverage. With institutional review board approval and informed consent, 11 consecutive patients referred for abdominal MRI at 3 Tesla (T) were imaged with both DISCO and a routine clinical three-dimensional SPGR-Dixon (LAVA FLEX) sequence. All images were graded by two radiologists using quality of fat suppression, severity of artifacts, and overall image quality as scoring criteria. For assessment of arterial phase capture efficiency, the number of temporal phases with angiographic phase and hepatic arterial phase was recorded. There were no significant differences in quality of fat suppression, artifact severity or overall image quality between DISCO and LAVA FLEX images (P > 0.05, Wilcoxon signed rank test). The angiographic and arterial phases were captured in all 11 patients scanned using the DISCO acquisition (mean number of phases were two and three, respectively). DISCO effectively captures the fast dynamics of abdominal pathology such as hyperenhancing hepatic lesions with a high spatio-temporal resolution. Typically, 1.1 × 1.5 × 3 mm spatial resolution over 60 slices was achieved with a temporal resolution of 4-5 s. Copyright © 2012 Wiley Periodicals, Inc.

Imaging in scattering media using correlation image sensors and sparse convolutional coding

KAUST Repository

Heide, Felix; Xiao, Lei; Kolb, Andreas; Hullin, Matthias B.; Heidrich, Wolfgang

2014-01-01

Correlation image sensors have recently become popular low-cost devices for time-of-flight, or range cameras. They usually operate under the assumption of a single light path contributing to each pixel. We show that a more thorough analysis of the sensor data from correlation sensors can be used can be used to analyze the light transport in much more complex environments, including applications for imaging through scattering and turbid media. The key of our method is a new convolutional sparse coding approach for recovering transient (light-in-flight) images from correlation image sensors. This approach is enabled by an analysis of sparsity in complex transient images, and the derivation of a new physically-motivated model for transient images with drastically improved sparsity.

Imaging in scattering media using correlation image sensors and sparse convolutional coding

KAUST Repository

Heide, Felix

2014-10-17

Correlation image sensors have recently become popular low-cost devices for time-of-flight, or range cameras. They usually operate under the assumption of a single light path contributing to each pixel. We show that a more thorough analysis of the sensor data from correlation sensors can be used can be used to analyze the light transport in much more complex environments, including applications for imaging through scattering and turbid media. The key of our method is a new convolutional sparse coding approach for recovering transient (light-in-flight) images from correlation image sensors. This approach is enabled by an analysis of sparsity in complex transient images, and the derivation of a new physically-motivated model for transient images with drastically improved sparsity.

Rainfall spatiotemporal variability relation to wetlands hydroperiods

Science.gov (United States)

Serrano-Hidalgo, Carmen; Guardiola-Albert, Carolina; Fernandez-Naranjo, Nuria

2017-04-01

Doñana natural space (Southwestern Spain) is one of the largest protected wetlands in Europe. The wide marshes present in this natural space have such ecological value that this wetland has been declared a Ramsar reserve in 1982. Apart from the extensive marsh, there are also small lagoons and seasonally flooded areas which are likewise essential to maintain a wide variety of valuable habitats. Hydroperiod, the length of time each point remains flooded along an annual cycle, is a critical ecological parameter that shapes aquatic plants and animals distribution and determines available habitat for many of the living organisms in the marshes. Recently, there have been published two different works estimating the hydroperiod of Doñana lagoons with Landsat Time Series images (Cifuentes et al., 2015; Díaz-Delgado et al., 2016). In both works the flooding cycle hydroperiod in Doñana marshes reveals a flooding regime mainly driven by rainfall, evapotranspiration, topography and local hydrological management actions. The correlation found between rainfall and hydroperiod is studied differently in both works. While in one the rainfall is taken from one raingauge (Cifuentes et al., 2015), the one performed by Díaz-Delgado (2016) uses annual rainfall maps interpolated with the inverse of the distance method. The rainfall spatiotemporal variability in this area can be highly significant; however the amount of this importance has not been quantified at the moment. In the present work the geostatistical tool known as spatiotemporal variogram is used to study the rainfall spatiotemporal variability. The spacetime package implemented in R (Pebesma, 2012) facilities its computation from a high rainfall data base of more than 100 raingauges from 1950 to 2016. With the aid of these variograms the rainfall spatiotemporal variability is quantified. The principal aim of the present work is the study of the relation between the rainfall spatiotemporal variability and the

Bioinspired nanocomplex for spatiotemporal imaging of sequential mRNA expression in differentiating neural stem cells.

Science.gov (United States)

Wang, Zhe; Zhang, Ruili; Wang, Zhongliang; Wang, He-Fang; Wang, Yu; Zhao, Jun; Wang, Fu; Li, Weitao; Niu, Gang; Kiesewetter, Dale O; Chen, Xiaoyuan

2014-12-23

Messenger RNA plays a pivotal role in regulating cellular activities. The expression dynamics of specific mRNA contains substantial information on the intracellular milieu. Unlike the imaging of stationary mRNAs, real-time intracellular imaging of the dynamics of mRNA expression is of great value for investigating mRNA biology and exploring specific cellular cascades. In addition to advanced imaging methods, timely extracellular stimulation is another key factor in regulating the mRNA expression repertoire. The integration of effective stimulation and imaging into a single robust system would significantly improve stimulation efficiency and imaging accuracy, producing fewer unwanted artifacts. In this study, we developed a multifunctional nanocomplex to enable self-activating and spatiotemporal imaging of the dynamics of mRNA sequential expression during the neural stem cell differentiation process. This nanocomplex showed improved enzymatic stability, fast recognition kinetics, and high specificity. With a mechanism regulated by endogenous cell machinery, this nanocomplex realized the successive stimulating motif release and the dynamic imaging of chronological mRNA expression during neural stem cell differentiation without the use of transgenetic manipulation. The dynamic imaging montage of mRNA expression ultimately facilitated genetic heterogeneity analysis. In vivo lateral ventricle injection of this nanocomplex enabled endogenous neural stem cell activation and labeling at their specific differentiation stages. This nanocomplex is highly amenable as an alternative tool to explore the dynamics of intricate mRNA activities in various physiological and pathological conditions.

Neurocysticercosis: Correlative pathomorphology and MR imaging

International Nuclear Information System (INIS)

Lotz, J.; Hewlett, R.; Alheit, B.; Tygerberg Hospital, Stellenbosch; Bowen, R.

1988-01-01

CT and MR images of 32 patients with neurocysticercosis were correlated with pathomorphology. Gross morphological features of cystic larvae, complex arachnoid cysts, granulomatous abscesses, basal meningitis and mineralised nodules correlated closely with the images obtained, especially on MR, where resolution permitted visualisation of larval protoscolices. Our material indicates three forms of the natural history of neurocysticercosis related chiefly to anatomic location, and provides details of the evolution of large, complex arachnoid cysts. (orig.)

Neurocysticercosis: Correlative pathomorphology and MR imaging

Energy Technology Data Exchange (ETDEWEB)

Lotz, J.; Hewlett, R.; Alheit, B.; Bowen, R.

1988-02-01

CT and MR images of 32 patients with neurocysticercosis were correlated with pathomorphology. Gross morphological features of cystic larvae, complex arachnoid cysts, granulomatous abscesses, basal meningitis and mineralised nodules correlated closely with the images obtained, especially on MR, where resolution permitted visualisation of larval protoscolices. Our material indicates three forms of the natural history of neurocysticercosis related chiefly to anatomic location, and provides details of the evolution of large, complex arachnoid cysts.

Partial Fourier techniques in single-shot cross-term spatiotemporal encoded MRI.

Science.gov (United States)

Zhang, Zhiyong; Frydman, Lucio

2018-03-01

Cross-term spatiotemporal encoding (xSPEN) is a single-shot approach with exceptional immunity to field heterogeneities, the images of which faithfully deliver 2D spatial distributions without requiring a priori information or using postacquisition corrections. xSPEN, however, suffers from signal-to-noise ratio penalties due to its non-Fourier nature and due to diffusion losses-especially when seeking high resolution. This study explores partial Fourier transform approaches that, acting along either the readout or the spatiotemporally encoded dimensions, reduce these penalties. xSPEN uses an orthogonal (e.g., z) gradient to read, in direct space, the low-bandwidth (e.g., y) dimension. This substantially changes the nature of partial Fourier acquisitions vis-à-vis conventional imaging counterparts. A suitable theoretical analysis is derived to implement these procedures, along either the spatiotemporally or readout axes. Partial Fourier single-shot xSPEN images were recorded on preclinical and human scanners. Owing to their reduction in the experiments' acquisition times, this approach provided substantial sensitivity gains vis-à-vis previous implementations for a given targeted in-plane resolution. The physical origins of these gains are explained. Partial Fourier approaches, particularly when implemented along the low-bandwidth spatiotemporal dimension, provide several-fold sensitivity advantages at minimal costs to the execution and processing of the single-shot experiments. Magn Reson Med 79:1506-1514, 2018. © 2017 International Society for Magnetic Resonance in Medicine. © 2017 International Society for Magnetic Resonance in Medicine.

Spatiotemporal Correlations between Water Footprint and Agricultural Inputs: A Case Study of Maize Production in Northeast China

Directory of Open Access Journals (Sweden)

Peili Duan

2015-07-01

Full Text Available To effectively manage water resources in agricultural production, it is necessary to understand the spatiotemporal variation of the water footprint (WF and the influences of agricultural inputs. Employing spatial autocorrelation analysis and a geographically weighted regression (GWR model, we explored the spatial variations of the WF and their relationships with agricultural inputs from 1998 to 2012 in Northeast China. The results indicated that: (1 the spatial distribution of WFs for the 36 major maize production prefectures was heterogeneous in Northeast China; (2 a cluster of high WFs was found in southeast Liaoning Province, while a cluster of low WFs was found in central Jilin Province, and (3 spatial and temporal differentiation in the correlations between the WF of maize production and agricultural inputs existed according to the GWR model. These correlations increased over time. Our results suggested that localized strategies for reducing the WF should be formulated based on specific relationships between the WF and agricultural inputs.

Spatiotemporal closure of fractional laser-ablated channels imaged by optical coherence tomography and reflectance confocal microscopy

DEFF Research Database (Denmark)

Banzhaf, Christina A.; Wind, Bas S.; Mogensen, Mette

2016-01-01

Background and Objective Optical coherence tomography (OCT) and reflectance confocal microscopy (RCM) offer high-resolution optical imaging of the skin, which may provide benefit in the context of laser-assisted drug delivery. We aimed to characterize postoperative healing of ablative fractional...... laser (AFXL)-induced channels and dynamics in their spatiotemporal closure using in vivo OCT and RCM techniques. Study design/Materials and Methods The inner forearm of healthy subjects (n = 6) was exposed to 10,600 nm fractional CO2 laser using 5 and 25% densities, 120 μm beam diameter, 5, 15, and 25 m......J/microbeam. Treatment sites were scanned with OCT to evaluate closure of AFXL-channels and RCM to evaluate subsequent re-epithelialization. Results OCT and RCM identified laser channels in epidermis and upper dermis as black, ablated tissue defects surrounded by characteristic hyper-and hyporeflective zones. OCT imaged...

Hidden neuronal correlations in cultured networks

International Nuclear Information System (INIS)

Segev, Ronen; Baruchi, Itay; Hulata, Eyal; Ben-Jacob, Eshel

2004-01-01

Utilization of a clustering algorithm on neuronal spatiotemporal correlation matrices recorded during a spontaneous activity of in vitro networks revealed the existence of hidden correlations: the sequence of synchronized bursting events (SBEs) is composed of statistically distinguishable subgroups each with its own distinct pattern of interneuron spatiotemporal correlations. These findings hint that each of the SBE subgroups can serve as a template for coding, storage, and retrieval of a specific information

Estimating the state of large spatio-temporally chaotic systems

International Nuclear Information System (INIS)

Ott, E.; Hunt, B.R.; Szunyogh, I.; Zimin, A.V.; Kostelich, E.J.; Corazza, M.; Kalnay, E.; Patil, D.J.; Yorke, J.A.

2004-01-01

We consider the estimation of the state of a large spatio-temporally chaotic system from noisy observations and knowledge of a system model. Standard state estimation techniques using the Kalman filter approach are not computationally feasible for systems with very many effective degrees of freedom. We present and test a new technique (called a Local Ensemble Kalman Filter), generally applicable to large spatio-temporally chaotic systems for which correlations between system variables evaluated at different points become small at large separation between the points

Extracting flat-field images from scene-based image sequences using phase correlation

Energy Technology Data Exchange (ETDEWEB)

Caron, James N., E-mail: Caron@RSImd.com [Research Support Instruments, 4325-B Forbes Boulevard, Lanham, Maryland 20706 (United States); Montes, Marcos J. [Naval Research Laboratory, Code 7231, 4555 Overlook Avenue, SW, Washington, DC 20375 (United States); Obermark, Jerome L. [Naval Research Laboratory, Code 8231, 4555 Overlook Avenue, SW, Washington, DC 20375 (United States)

2016-06-15

Flat-field image processing is an essential step in producing high-quality and radiometrically calibrated images. Flat-fielding corrects for variations in the gain of focal plane array electronics and unequal illumination from the system optics. Typically, a flat-field image is captured by imaging a radiometrically uniform surface. The flat-field image is normalized and removed from the images. There are circumstances, such as with remote sensing, where a flat-field image cannot be acquired in this manner. For these cases, we developed a phase-correlation method that allows the extraction of an effective flat-field image from a sequence of scene-based displaced images. The method uses sub-pixel phase correlation image registration to align the sequence to estimate the static scene. The scene is removed from sequence producing a sequence of misaligned flat-field images. An average flat-field image is derived from the realigned flat-field sequence.

Artificial neural network does better spatiotemporal compressive sampling

Science.gov (United States)

Lee, Soo-Young; Hsu, Charles; Szu, Harold

2012-06-01

Spatiotemporal sparseness is generated naturally by human visual system based on artificial neural network modeling of associative memory. Sparseness means nothing more and nothing less than the compressive sensing achieves merely the information concentration. To concentrate the information, one uses the spatial correlation or spatial FFT or DWT or the best of all adaptive wavelet transform (cf. NUS, Shen Shawei). However, higher dimensional spatiotemporal information concentration, the mathematics can not do as flexible as a living human sensory system. The reason is obviously for survival reasons. The rest of the story is given in the paper.

Spatiotemporal complexity in coupled map lattices

International Nuclear Information System (INIS)

Kaneko, Kunihiko

1986-01-01

Some spatiotemporal patterns of couple map lattices are presented. The chaotic kink-like motions are shown for the phase motion of the coupled circle lattices. An extension of the couple map lattice approach to Hamiltonian dynamics is briefly reported. An attempt to characterize the high-dimensional attractor by the extension of the correlation dimension is discussed. (author)

Spatio-Temporal Rule Mining

DEFF Research Database (Denmark)

Gidofalvi, Gyozo; Pedersen, Torben Bach

2005-01-01

Recent advances in communication and information technology, such as the increasing accuracy of GPS technology and the miniaturization of wireless communication devices pave the road for Location-Based Services (LBS). To achieve high quality for such services, spatio-temporal data mining techniques...... are needed. In this paper, we describe experiences with spatio-temporal rule mining in a Danish data mining company. First, a number of real world spatio-temporal data sets are described, leading to a taxonomy of spatio-temporal data. Second, the paper describes a general methodology that transforms...... the spatio-temporal rule mining task to the traditional market basket analysis task and applies it to the described data sets, enabling traditional association rule mining methods to discover spatio-temporal rules for LBS. Finally, unique issues in spatio-temporal rule mining are identified and discussed....

Advancing of Land Surface Temperature Retrieval Using Extreme Learning Machine and Spatio-Temporal Adaptive Data Fusion Algorithm

Directory of Open Access Journals (Sweden)

Yang Bai

2015-04-01

Full Text Available As a critical variable to characterize the biophysical processes in ecological environment, and as a key indicator in the surface energy balance, evapotranspiration and urban heat islands, Land Surface Temperature (LST retrieved from Thermal Infra-Red (TIR images at both high temporal and spatial resolution is in urgent need. However, due to the limitations of the existing satellite sensors, there is no earth observation which can obtain TIR at detailed spatial- and temporal-resolution simultaneously. Thus, several attempts of image fusion by blending the TIR data from high temporal resolution sensor with data from high spatial resolution sensor have been studied. This paper presents a novel data fusion method by integrating image fusion and spatio-temporal fusion techniques, for deriving LST datasets at 30 m spatial resolution from daily MODIS image and Landsat ETM+ images. The Landsat ETM+ TIR data were firstly enhanced based on extreme learning machine (ELM algorithm using neural network regression model, from 60 m to 30 m resolution. Then, the MODIS LST and enhanced Landsat ETM+ TIR data were fused by Spatio-temporal Adaptive Data Fusion Algorithm for Temperature mapping (SADFAT in order to derive high resolution synthetic data. The synthetic images were evaluated for both testing and simulated satellite images. The average difference (AD and absolute average difference (AAD are smaller than 1.7 K, where the correlation coefficient (CC and root-mean-square error (RMSE are 0.755 and 1.824, respectively, showing that the proposed method enhances the spatial resolution of the predicted LST images and preserves the spectral information at the same time.

An image correlation procedure for digitally reconstructed radiographs and electronic portal images

International Nuclear Information System (INIS)

Dong, Lei; Boyer, Arthur L.

1995-01-01

Purpose: To study a procedure that uses megavoltage digitally reconstructed radiographs (DRRs) calculated from patient's three-dimensional (3D) computed tomography (CT) data as a reference image for correlation with on-line electronic portal images (EPIs) to detect patient setup errors. Methods and Materials: Megavoltage DRRs were generated by ray tracing through a modified volumetric CT data set in which CT numbers were converted into linear attenuation coefficients for the therapeutic beam energy. The DRR transmission image was transformed to the grayscale window of the EPI by a histogram-matching technique. An alternative approach was to calibrate the transmission DRR using a measured response curve of the electronic portal imaging device (EPID). This forces the calculated transmission fluence values to be distributed in the same range as that of the EPID image. A cross-correlation technique was used to determine the degree of alignment of the patient anatomy found in the EPID image relative to the reference DRR. Results: Phantom studies demonstrated that the correlation procedure had a standard deviation of 0.5 mm and 0.5 deg. in aligning translational shifts and in-plane rotations. Systematic errors were found between a reference DRR and a reference EPID image. The automated grayscale image-correlation process was completed within 3 s on a workstation computer or 12 s on a PC. Conclusion: The alignment procedure allows the direct comparison of a patient's treatment portal designed with a 3D planning computer with a patient's on-line portal image acquired at the treatment unit. The image registration process is automated to the extent that it requires minimal user intervention, and it is fast and accurate enough for on-line clinical applications

Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography.

Science.gov (United States)

Zhang, Tao; Yousaf, Ufra; Hsiao, Albert; Cheng, Joseph Y; Alley, Marcus T; Lustig, Michael; Pauly, John M; Vasanawala, Shreyas S

2015-10-01

Pediatric contrast-enhanced MR angiography is often limited by respiration, other patient motion and compromised spatiotemporal resolution. To determine the reliability of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography method for depicting abdominal arterial anatomy in young children. With IRB approval and informed consent, we retrospectively identified 27 consecutive children (16 males and 11 females; mean age: 3.8 years, range: 14 days to 8.4 years) referred for contrast-enhanced MR angiography at our institution, who had undergone free-breathing spatiotemporally accelerated time-resolved contrast-enhanced MR angiography studies. A radio-frequency-spoiled gradient echo sequence with Cartesian variable density k-space sampling and radial view ordering, intrinsic motion navigation and intermittent fat suppression was developed. Images were reconstructed with soft-gated parallel imaging locally low-rank method to achieve both motion correction and high spatiotemporal resolution. Quality of delineation of 13 abdominal arteries in the reconstructed images was assessed independently by two radiologists on a five-point scale. Ninety-five percent confidence intervals of the proportion of diagnostically adequate cases were calculated. Interobserver agreements were also analyzed. Eleven out of 13 arteries achieved acceptable image quality (mean score range: 3.9-5.0) for both readers. Fair to substantial interobserver agreement was reached on nine arteries. Free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography frequently yields diagnostic image quality for most abdominal arteries in young children.

Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography

Energy Technology Data Exchange (ETDEWEB)

Zhang, Tao; Cheng, Joseph Y. [Stanford University, Department of Radiology, Stanford, CA (United States); Stanford University, Department of Electrical Engineering, Stanford, CA (United States); Yousaf, Ufra; Alley, Marcus T.; Vasanawala, Shreyas S. [Stanford University, Department of Radiology, Stanford, CA (United States); Hsiao, Albert [University of California, San Diego, Department of Radiology, San Diego, CA (United States); Lustig, Michael [Stanford University, Department of Electrical Engineering, Stanford, CA (United States); University of California, Berkeley, Department of Electrical Engineering and Computer Sciences, Berkeley, CA (United States); Pauly, John M. [Stanford University, Department of Electrical Engineering, Stanford, CA (United States)

2015-10-15

Pediatric contrast-enhanced MR angiography is often limited by respiration, other patient motion and compromised spatiotemporal resolution. To determine the reliability of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography method for depicting abdominal arterial anatomy in young children. With IRB approval and informed consent, we retrospectively identified 27 consecutive children (16 males and 11 females; mean age: 3.8 years, range: 14 days to 8.4 years) referred for contrast-enhanced MR angiography at our institution, who had undergone free-breathing spatiotemporally accelerated time-resolved contrast-enhanced MR angiography studies. A radio-frequency-spoiled gradient echo sequence with Cartesian variable density k-space sampling and radial view ordering, intrinsic motion navigation and intermittent fat suppression was developed. Images were reconstructed with soft-gated parallel imaging locally low-rank method to achieve both motion correction and high spatiotemporal resolution. Quality of delineation of 13 abdominal arteries in the reconstructed images was assessed independently by two radiologists on a five-point scale. Ninety-five percent confidence intervals of the proportion of diagnostically adequate cases were calculated. Interobserver agreements were also analyzed. Eleven out of 13 arteries achieved acceptable image quality (mean score range: 3.9-5.0) for both readers. Fair to substantial interobserver agreement was reached on nine arteries. Free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography frequently yields diagnostic image quality for most abdominal arteries in young children. (orig.)

Clinical performance of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced pediatric abdominal MR angiography

International Nuclear Information System (INIS)

Zhang, Tao; Cheng, Joseph Y.; Yousaf, Ufra; Alley, Marcus T.; Vasanawala, Shreyas S.; Hsiao, Albert; Lustig, Michael; Pauly, John M.

2015-01-01

Pediatric contrast-enhanced MR angiography is often limited by respiration, other patient motion and compromised spatiotemporal resolution. To determine the reliability of a free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography method for depicting abdominal arterial anatomy in young children. With IRB approval and informed consent, we retrospectively identified 27 consecutive children (16 males and 11 females; mean age: 3.8 years, range: 14 days to 8.4 years) referred for contrast-enhanced MR angiography at our institution, who had undergone free-breathing spatiotemporally accelerated time-resolved contrast-enhanced MR angiography studies. A radio-frequency-spoiled gradient echo sequence with Cartesian variable density k-space sampling and radial view ordering, intrinsic motion navigation and intermittent fat suppression was developed. Images were reconstructed with soft-gated parallel imaging locally low-rank method to achieve both motion correction and high spatiotemporal resolution. Quality of delineation of 13 abdominal arteries in the reconstructed images was assessed independently by two radiologists on a five-point scale. Ninety-five percent confidence intervals of the proportion of diagnostically adequate cases were calculated. Interobserver agreements were also analyzed. Eleven out of 13 arteries achieved acceptable image quality (mean score range: 3.9-5.0) for both readers. Fair to substantial interobserver agreement was reached on nine arteries. Free-breathing spatiotemporally accelerated 3-D time-resolved contrast-enhanced MR angiography frequently yields diagnostic image quality for most abdominal arteries in young children. (orig.)

Image sequence analysis using spatio-temporal texture

International Nuclear Information System (INIS)

Sengupta, S.K.; Clark, G.A.; Barnes, F.L.; Schaich, P.C.

1994-01-01

The authors have developed and coded an algorithm for motion pattern classification based on spatio-temporal texture. The algorithm has been implemented and tested for the detection of wakes in simulated data with a relatively low signal-to-noise ratio (0.7 dB). Using a open-quote hold one out close-quote method, a detection probability of 100% with a 0% false alarm rate has been achieved on the limited number of samples (47 in each category) tested. The actual detection can be displayed in the form of a movie that can effectively show the submarine tracks based on the detected wake locations

Ghost imaging with atoms

Science.gov (United States)

Khakimov, R. I.; Henson, B. M.; Shin, D. K.; Hodgman, S. S.; Dall, R. G.; Baldwin, K. G. H.; Truscott, A. G.

2016-12-01

Ghost imaging is a counter-intuitive phenomenon—first realized in quantum optics—that enables the image of a two-dimensional object (mask) to be reconstructed using the spatio-temporal properties of a beam of particles with which it never interacts. Typically, two beams of correlated photons are used: one passes through the mask to a single-pixel (bucket) detector while the spatial profile of the other is measured by a high-resolution (multi-pixel) detector. The second beam never interacts with the mask. Neither detector can reconstruct the mask independently, but temporal cross-correlation between the two beams can be used to recover a ‘ghost’ image. Here we report the realization of ghost imaging using massive particles instead of photons. In our experiment, the two beams are formed by correlated pairs of ultracold, metastable helium atoms, which originate from s-wave scattering of two colliding Bose-Einstein condensates. We use higher-order Kapitza-Dirac scattering to generate a large number of correlated atom pairs, enabling the creation of a clear ghost image with submillimetre resolution. Future extensions of our technique could lead to the realization of ghost interference, and enable tests of Einstein-Podolsky-Rosen entanglement and Bell’s inequalities with atoms.

Skeletal MR imaging: Correlation with skeletal scintigraphy

International Nuclear Information System (INIS)

Colletti, P.M.; Raval, J.K.; Ford, P.V.; Benson, R.C.; Kerr, R.M.; Boswell, W.D.; Siegel, M.E.; Ralls, P.W.

1987-01-01

Skeletal MR images bone marrow while skeletal scintigraphy uses bone metabolism to demonstrate abnormalities. The purpose of this paper is to correlate these MR and scintigraphic findings. T1 and T2 MR images at 0.5 T were correlated with planar bone scintigraphy (RN) using Tc-99m MDP in 56 patients. Of 23 cases with suspected spinal metastases, 19 were positive by MR imaging, 16 by RN. Individual lesions were shown better by MR imaging in five and by RN in two. These two cases had scoliosis, a potential difficulty with MR imaging. In 14 cases of suspected avascular necrosis (AVN), MR imaging was positive in 13 while RN was positive in ten. One negative case by RN had bilateral AVN by MR imaging. Four skull lesions shown easily by RN were seen only in retrospect on MR images. MR imaging is advantageous in evaluating bones with predominant marrow such as vertebrae or the femoral head, while RN is superior in areas primarily composed of cortical bone such as the skull

A Mixed Land Cover Spatio-temporal Data Model Based on Object-oriented and Snapshot

Directory of Open Access Journals (Sweden)

LI Yinchao

2016-07-01

Full Text Available Spatio-temporal data model (STDM is one of the hot topics in the domains of spatio-temporal database and data analysis. There is a common view that a universal STDM is always of high complexity due to the various situation of spatio-temporal data. In this article, a mixed STDM is proposed based on object-oriented and snapshot models for modelling and analyzing landcover change (LCC. This model uses the object-oriented STDM to describe the spatio-temporal processes of land cover patches and organize their spatial and attributive properties. In the meantime, it uses the snapshot STDM to present the spatio-temporal distribution of LCC on the whole via snapshot images. The two types of models are spatially and temporally combined into a mixed version. In addition to presenting the spatio-temporal events themselves, this model could express the transformation events between different classes of spatio-temporal objects. It can be used to create database for historical data of LCC, do spatio-temporal statistics, simulation and data mining with the data. In this article, the LCC data in Heilongjiang province is used for case study to validate spatio-temporal data management and analysis abilities of mixed STDM, including creating database, spatio-temporal query, global evolution analysis and patches spatio-temporal process expression.

Digital Correlation based on Wavelet Transform for Image Detection

International Nuclear Information System (INIS)

Barba, L; Vargas, L; Torres, C; Mattos, L

2011-01-01

In this work is presented a method for the optimization of digital correlators to improve the characteristic detection on images using wavelet transform as well as subband filtering. It is proposed an approach of wavelet-based image contrast enhancement in order to increase the performance of digital correlators. The multiresolution representation is employed to improve the high frequency content of images taken into account the input contrast measured for the original image. The energy of correlation peaks and discrimination level of several objects are improved with this technique. To demonstrate the potentiality in extracting characteristics using the wavelet transform, small objects inside reference images are detected successfully.

Pilomatricomas in children: imaging characteristics with pathologic correlation

International Nuclear Information System (INIS)

Lim, Hyun Wook; Im, Soo Ah; Lim, Gye-Yeon; Park, Hyun Jin; Lee, Heejeong; Sung, Mi Sook; Kang, Bong Joo; Kim, Jee Young

2007-01-01

Although pilomatricoma commonly occurs in children, there is still a poor understanding of the imaging characteristics of pilomatricoma and lack of agreement regarding its imaging findings and histopathologic features. To characterize the radiologic appearance of pilomatricomas on US, CT, and MR and to correlate the imaging findings with histopathologic features. The imaging findings of 47 pilomatricomas on US (n = 17), CT (n = 31), and MR (n = 5) were retrospectively evaluated. Pathologic specimens of all cases were reviewed and compared with imaging findings. All lesions were well-circumscribed, subcutaneous nodules with partial attachment to the overlying skin. On US, the lesions were mostly hyperechoic with posterior acoustic shadowing and hypoechoic rim. On CT, they appeared as enhancing soft-tissue masses with varying amounts of calcification. MR findings were internal reticulations and patchy areas on T2-weighted images and contrast-enhanced T1-weighted images, corresponding to edematous stroma on pathology. Peritumoral inflammatory changes and connective capsule on pathology were well correlated with imaging findings. Pilomatricoma should be considered when US or CT shows a well-defined hyperechoic or calcific nodule in subcutaneous fat attached to the skin in children. MR images may be helpful in diagnosis. Pathologic findings are well correlated with imaging findings. (orig.)

Estimating repetitive spatiotemporal patterns from resting-state brain activity data.

Science.gov (United States)

Takeda, Yusuke; Hiroe, Nobuo; Yamashita, Okito; Sato, Masa-Aki

2016-06-01

Repetitive spatiotemporal patterns in spontaneous brain activities have been widely examined in non-human studies. These studies have reported that such patterns reflect past experiences embedded in neural circuits. In human magnetoencephalography (MEG) and electroencephalography (EEG) studies, however, spatiotemporal patterns in resting-state brain activities have not been extensively examined. This is because estimating spatiotemporal patterns from resting-state MEG/EEG data is difficult due to their unknown onsets. Here, we propose a method to estimate repetitive spatiotemporal patterns from resting-state brain activity data, including MEG/EEG. Without the information of onsets, the proposed method can estimate several spatiotemporal patterns, even if they are overlapping. We verified the performance of the method by detailed simulation tests. Furthermore, we examined whether the proposed method could estimate the visual evoked magnetic fields (VEFs) without using stimulus onset information. The proposed method successfully detected the stimulus onsets and estimated the VEFs, implying the applicability of this method to real MEG data. The proposed method was applied to resting-state functional magnetic resonance imaging (fMRI) data and MEG data. The results revealed informative spatiotemporal patterns representing consecutive brain activities that dynamically change with time. Using this method, it is possible to reveal discrete events spontaneously occurring in our brains, such as memory retrieval. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Self-adaptive isogeometric global digital image correlation and digital height correlation

NARCIS (Netherlands)

Hoefnagels, J. P M; Kleinendorst, S. M.; Ruybalid, A. P.; Verhoosel, C. V.; Geers, M. G D; Yoshida, S.; Lamberti, L.; Sciammarella, C.

2017-01-01

This work explores the full potential of isogeometric shape functions for global digital image correlation. To this end, a novel DIC and DHC (digital height correlation) methodology have been developed based on adaptive refinement of isogeometric shape functions. Non-Uniform Rational B-Spline

Spatial correlation genetic algorithm for fractal image compression

International Nuclear Information System (INIS)

Wu, M.-S.; Teng, W.-C.; Jeng, J.-H.; Hsieh, J.-G.

2006-01-01

Fractal image compression explores the self-similarity property of a natural image and utilizes the partitioned iterated function system (PIFS) to encode it. This technique is of great interest both in theory and application. However, it is time-consuming in the encoding process and such drawback renders it impractical for real time applications. The time is mainly spent on the search for the best-match block in a large domain pool. In this paper, a spatial correlation genetic algorithm (SC-GA) is proposed to speed up the encoder. There are two stages for the SC-GA method. The first stage makes use of spatial correlations in images for both the domain pool and the range pool to exploit local optima. The second stage is operated on the whole image to explore more adequate similarities if the local optima are not satisfied. With the aid of spatial correlation in images, the encoding time is 1.5 times faster than that of traditional genetic algorithm method, while the quality of the retrieved image is almost the same. Moreover, about half of the matched blocks come from the correlated space, so fewer bits are required to represent the fractal transform and therefore the compression ratio is also improved

Spatiotemporal Data Mining: A Computational Perspective

Directory of Open Access Journals (Sweden)

Shashi Shekhar

2015-10-01

Full Text Available Explosive growth in geospatial and temporal data as well as the emergence of new technologies emphasize the need for automated discovery of spatiotemporal knowledge. Spatiotemporal data mining studies the process of discovering interesting and previously unknown, but potentially useful patterns from large spatiotemporal databases. It has broad application domains including ecology and environmental management, public safety, transportation, earth science, epidemiology, and climatology. The complexity of spatiotemporal data and intrinsic relationships limits the usefulness of conventional data science techniques for extracting spatiotemporal patterns. In this survey, we review recent computational techniques and tools in spatiotemporal data mining, focusing on several major pattern families: spatiotemporal outlier, spatiotemporal coupling and tele-coupling, spatiotemporal prediction, spatiotemporal partitioning and summarization, spatiotemporal hotspots, and change detection. Compared with other surveys in the literature, this paper emphasizes the statistical foundations of spatiotemporal data mining and provides comprehensive coverage of computational approaches for various pattern families. ISPRS Int. J. Geo-Inf. 2015, 4 2307 We also list popular software tools for spatiotemporal data analysis. The survey concludes with a look at future research needs.

Joint level-set and spatio-temporal motion detection for cell segmentation.

Science.gov (United States)

Boukari, Fatima; Makrogiannis, Sokratis

2016-08-10

Cell segmentation is a critical step for quantification and monitoring of cell cycle progression, cell migration, and growth control to investigate cellular immune response, embryonic development, tumorigenesis, and drug effects on live cells in time-lapse microscopy images. In this study, we propose a joint spatio-temporal diffusion and region-based level-set optimization approach for moving cell segmentation. Moving regions are initially detected in each set of three consecutive sequence images by numerically solving a system of coupled spatio-temporal partial differential equations. In order to standardize intensities of each frame, we apply a histogram transformation approach to match the pixel intensities of each processed frame with an intensity distribution model learned from all frames of the sequence during the training stage. After the spatio-temporal diffusion stage is completed, we compute the edge map by nonparametric density estimation using Parzen kernels. This process is followed by watershed-based segmentation and moving cell detection. We use this result as an initial level-set function to evolve the cell boundaries, refine the delineation, and optimize the final segmentation result. We applied this method to several datasets of fluorescence microscopy images with varying levels of difficulty with respect to cell density, resolution, contrast, and signal-to-noise ratio. We compared the results with those produced by Chan and Vese segmentation, a temporally linked level-set technique, and nonlinear diffusion-based segmentation. We validated all segmentation techniques against reference masks provided by the international Cell Tracking Challenge consortium. The proposed approach delineated cells with an average Dice similarity coefficient of 89 % over a variety of simulated and real fluorescent image sequences. It yielded average improvements of 11 % in segmentation accuracy compared to both strictly spatial and temporally linked Chan

Intensity correlation imaging with sunlight-like source

Science.gov (United States)

Wang, Wentao; Tang, Zhiguo; Zheng, Huaibin; Chen, Hui; Yuan, Yuan; Liu, Jinbin; Liu, Yanyan; Xu, Zhuo

2018-05-01

We show a method of intensity correlation imaging of targets illuminated by a sunlight-like source both theoretically and experimentally. With a Faraday anomalous dispersion optical filter (FADOF), we have modulated the coherence time of a thermal source up to 0.167 ns. And we carried out measurements of temporal and spatial correlations, respectively, with an intensity interferometer setup. By skillfully using the even Fourier fitting on the very sparse sampling data, the images of targets are successfully reconstructed from the low signal-noise-ratio(SNR) interference pattern by applying an iterative phase retrieval algorithm. The resulting imaging quality is as well as the one obtained by the theoretical fitting. The realization of such a case will bring this technique closer to geostationary satellite imaging illuminated by sunlight.

Quantum correlated imaging is a promising new technique in medical imaging

Institute of Scientific and Technical Information of China (English)

Nan Zhang; Zhaohua Yang

2017-01-01

Cardio-cerebral vascular diseases are common and frequently occurring serious diseases that threaten humans. In recent years, Digital Subtraction Angiography (DSA) has played a vital role in the diagnosis and treatment of cardio-cerebral vascular diseases. However, DSA is not able to visualize intravascular structures in real time, and it is especially difficult to evaluate each layer of the vascular wall and the composition of atherosclerotic plaques with DSA. Quantum correlated imaging is a new technique that can be used to perform real-time online imaging of intravascular flow, vascular wall structure, and atherosclerotic plaque composition. Quantum correlated imaging is a promising new technique that will soon be used in the diagnosis and treatment of cardio-cerebral vascular diseases.

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

Science.gov (United States)

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

2018-02-07

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

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

Science.gov (United States)

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

2018-01-01

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

Spatiotemporal dynamics of a digital phase-locked loop based coupled map lattice system

Energy Technology Data Exchange (ETDEWEB)

Banerjee, Tanmoy, E-mail: tbanerjee@phys.buruniv.ac.in; Paul, Bishwajit; Sarkar, B. C. [Department of Physics, University of Burdwan, Burdwan, West Bengal 713 104 (India)

2014-03-15

We explore the spatiotemporal dynamics of a coupled map lattice (CML) system, which is realized with a one dimensional array of locally coupled digital phase-locked loops (DPLLs). DPLL is a nonlinear feedback-controlled system widely used as an important building block of electronic communication systems. We derive the phase-error equation of the spatially extended system of coupled DPLLs, which resembles a form of the equation of a CML system. We carry out stability analysis for the synchronized homogeneous solutions using the circulant matrix formalism. It is shown through extensive numerical simulations that with the variation of nonlinearity parameter and coupling strength the system shows transitions among several generic features of spatiotemporal dynamics, viz., synchronized fixed point solution, frozen random pattern, pattern selection, spatiotemporal intermittency, and fully developed spatiotemporal chaos. We quantify the spatiotemporal dynamics using quantitative measures like average quadratic deviation and spatial correlation function. We emphasize that instead of using an idealized model of CML, which is usually employed to observe the spatiotemporal behaviors, we consider a real world physical system and establish the existence of spatiotemporal chaos and other patterns in this system. We also discuss the importance of the present study in engineering application like removal of clock-skew in parallel processors.

Spatiotemporal Change Detection Using Landsat Imagery: the Case Study of Karacabey Flooded Forest, Bursa, Turkey

Science.gov (United States)

Akay, A. E.; Gencal, B.; Taş, İ.

2017-11-01

This short paper aims to detect spatiotemporal detection of land use/land cover change within Karacabey Flooded Forest region. Change detection analysis applied to Landsat 5 TM images representing July 2000 and a Landsat 8 OLI representing June 2017. Various image processing tools were implemented using ERDAS 9.2, ArcGIS 10.4.1, and ENVI programs to conduct spatiotemporal change detection over these two images such as band selection, corrections, subset, classification, recoding, accuracy assessment, and change detection analysis. Image classification revealed that there are five significant land use/land cover types, including forest, flooded forest, swamp, water, and other lands (i.e. agriculture, sand, roads, settlement, and open areas). The results indicated that there was increase in flooded forest, water, and other lands, while the cover of forest and swamp decreased.

INCREMENTAL PRINCIPAL COMPONENT ANALYSIS BASED OUTLIER DETECTION METHODS FOR SPATIOTEMPORAL DATA STREAMS

Directory of Open Access Journals (Sweden)

A. Bhushan

2015-07-01

Full Text Available In this paper, we address outliers in spatiotemporal data streams obtained from sensors placed across geographically distributed locations. Outliers may appear in such sensor data due to various reasons such as instrumental error and environmental change. Real-time detection of these outliers is essential to prevent propagation of errors in subsequent analyses and results. Incremental Principal Component Analysis (IPCA is one possible approach for detecting outliers in such type of spatiotemporal data streams. IPCA has been widely used in many real-time applications such as credit card fraud detection, pattern recognition, and image analysis. However, the suitability of applying IPCA for outlier detection in spatiotemporal data streams is unknown and needs to be investigated. To fill this research gap, this paper contributes by presenting two new IPCA-based outlier detection methods and performing a comparative analysis with the existing IPCA-based outlier detection methods to assess their suitability for spatiotemporal sensor data streams.

Spatiotemporal fusion of multiple-satellite aerosol optical depth (AOD) products using Bayesian maximum entropy method

Science.gov (United States)

Tang, Qingxin; Bo, Yanchen; Zhu, Yuxin

2016-04-01

Merging multisensor aerosol optical depth (AOD) products is an effective way to produce more spatiotemporally complete and accurate AOD products. A spatiotemporal statistical data fusion framework based on a Bayesian maximum entropy (BME) method was developed for merging satellite AOD products in East Asia. The advantages of the presented merging framework are that it not only utilizes the spatiotemporal autocorrelations but also explicitly incorporates the uncertainties of the AOD products being merged. The satellite AOD products used for merging are the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Level-2 AOD products (MOD04_L2) and the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) Deep Blue Level 2 AOD products (SWDB_L2). The results show that the average completeness of the merged AOD data is 95.2%,which is significantly superior to the completeness of MOD04_L2 (22.9%) and SWDB_L2 (20.2%). By comparing the merged AOD to the Aerosol Robotic Network AOD records, the results show that the correlation coefficient (0.75), root-mean-square error (0.29), and mean bias (0.068) of the merged AOD are close to those (the correlation coefficient (0.82), root-mean-square error (0.19), and mean bias (0.059)) of the MODIS AOD. In the regions where both MODIS and SeaWiFS have valid observations, the accuracy of the merged AOD is higher than those of MODIS and SeaWiFS AODs. Even in regions where both MODIS and SeaWiFS AODs are missing, the accuracy of the merged AOD is also close to the accuracy of the regions where both MODIS and SeaWiFS have valid observations.

Characterization of dynamic changes of current source localization based on spatiotemporal fMRI constrained EEG source imaging

Science.gov (United States)

Nguyen, Thinh; Potter, Thomas; Grossman, Robert; Zhang, Yingchun

2018-06-01

Objective. Neuroimaging has been employed as a promising approach to advance our understanding of brain networks in both basic and clinical neuroscience. Electroencephalography (EEG) and functional magnetic resonance imaging (fMRI) represent two neuroimaging modalities with complementary features; EEG has high temporal resolution and low spatial resolution while fMRI has high spatial resolution and low temporal resolution. Multimodal EEG inverse methods have attempted to capitalize on these properties but have been subjected to localization error. The dynamic brain transition network (DBTN) approach, a spatiotemporal fMRI constrained EEG source imaging method, has recently been developed to address these issues by solving the EEG inverse problem in a Bayesian framework, utilizing fMRI priors in a spatial and temporal variant manner. This paper presents a computer simulation study to provide a detailed characterization of the spatial and temporal accuracy of the DBTN method. Approach. Synthetic EEG data were generated in a series of computer simulations, designed to represent realistic and complex brain activity at superficial and deep sources with highly dynamical activity time-courses. The source reconstruction performance of the DBTN method was tested against the fMRI-constrained minimum norm estimates algorithm (fMRIMNE). The performances of the two inverse methods were evaluated both in terms of spatial and temporal accuracy. Main results. In comparison with the commonly used fMRIMNE method, results showed that the DBTN method produces results with increased spatial and temporal accuracy. The DBTN method also demonstrated the capability to reduce crosstalk in the reconstructed cortical time-course(s) induced by neighboring regions, mitigate depth bias and improve overall localization accuracy. Significance. The improved spatiotemporal accuracy of the reconstruction allows for an improved characterization of complex neural activity. This improvement can be

Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

DEFF Research Database (Denmark)

Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

2017-01-01

Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...... gauges in the model area. The spatiotemporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatiotemporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying on precipitation output...

Ultrasonic Detection Using Correlation Images (Preprint)

National Research Council Canada - National Science Library

Cepel, Raini; Ho, K. C; Rinker, Brett A; Palmer, Donald D; Neal, Steven P

2006-01-01

.... In this paper, we describe an amplitude independent approach for imaging and detection based on the similarity of adjacent signals, quantified by the correlation coefficient calculated between A-scans...

Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

KAUST Repository

Sun, Ying; Genton, Marc G.

2011-01-01

This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio

Oscillations, complex spatiotemporal behavior, and information transport in networks of excitatory and inhibitory neurons

International Nuclear Information System (INIS)

Destexhe, A.

1994-01-01

Various types of spatiotemporal behavior are described for two-dimensional networks of excitatory and inhibitory neurons with time delayed interactions. It is described how the network behaves as several structural parameters are varied, such as the number of neurons, the connectivity, and the values of synaptic weights. A transition from spatially uniform oscillations to spatiotemporal chaos via intermittentlike behavior is observed. The properties of spatiotemporally chaotic solutions are investigated by evaluating the largest positive Lyapunov exponent and the loss of correlation with distance. Finally, properties of information transport are evaluated during uniform oscillations and spatiotemporal chaos. It is shown that the diffusion coefficient increases significantly in the spatiotemporal phase similar to the increase of transport coefficients at the onset of fluid turbulence. It is proposed that such a property should be seen in other media, such as chemical turbulence or networks of oscillators. The possibility of measuring information transport from appropriate experiments is also discussed

Monitoring Local Changes in Granite Rock Under Biaxial Test: A Spatiotemporal Imaging Application With Diffuse Waves

Science.gov (United States)

Xie, Fan; Ren, Yaqiong; Zhou, Yongsheng; Larose, Eric; Baillet, Laurent

2018-03-01

Diffuse acoustic or seismic waves are highly sensitive to detect changes of mechanical properties in heterogeneous geological materials. In particular, thanks to acoustoelasticity, we can quantify stress changes by tracking acoustic or seismic relative velocity changes in the material at test. In this paper, we report on a small-scale laboratory application of an innovative time-lapse tomography technique named Locadiff to image spatiotemporal mechanical changes on a granite sample under biaxial loading, using diffuse waves at ultrasonic frequencies (300 kHz to 900 kHz). We demonstrate the ability of the method to image reversible stress evolution and deformation process, together with the development of reversible and irreversible localized microdamage in the specimen at an early stage. Using full-field infrared thermography, we visualize stress-induced temperature changes and validate stress images obtained from diffuse ultrasound. We demonstrate that the inversion with a good resolution can be achieved with only a limited number of receivers distributed around a single source, all located at the free surface of the specimen. This small-scale experiment is a proof of concept for frictional earthquake-like failure (e.g., stick-slip) research at laboratory scale as well as large-scale seismic applications, potentially including active fault monitoring.

Novel Super-Resolution Approach to Time-Resolved Volumetric 4-Dimensional Magnetic Resonance Imaging With High Spatiotemporal Resolution for Multi-Breathing Cycle Motion Assessment

International Nuclear Information System (INIS)

Li, Guang; Wei, Jie; Kadbi, Mo; Moody, Jason; Sun, August; Zhang, Shirong; Markova, Svetlana; Zakian, Kristen; Hunt, Margie; Deasy, Joseph O.

2017-01-01

Purpose: To develop and evaluate a super-resolution approach to reconstruct time-resolved 4-dimensional magnetic resonance imaging (TR-4DMRI) with a high spatiotemporal resolution for multi-breathing cycle motion assessment. Methods and Materials: A super-resolution approach was developed to combine fast 3-dimensional (3D) cine MRI with low resolution during free breathing (FB) and high-resolution 3D static MRI during breath hold (BH) using deformable image registration. A T1-weighted, turbo field echo sequence, coronal 3D cine acquisition, partial Fourier approximation, and SENSitivity Encoding parallel acceleration were used. The same MRI pulse sequence, field of view, and acceleration techniques were applied in both FB and BH acquisitions; the intensity-based Demons deformable image registration method was used. Under an institutional review board–approved protocol, 7 volunteers were studied with 3D cine FB scan (voxel size: 5 × 5 × 5 mm"3) at 2 Hz for 40 seconds and a 3D static BH scan (2 × 2 × 2 mm"3). To examine the image fidelity of 3D cine and super-resolution TR-4DMRI, a mobile gel phantom with multi-internal targets was scanned at 3 speeds and compared with the 3D static image. Image similarity among 3D cine, 4DMRI, and 3D static was evaluated visually using difference image and quantitatively using voxel intensity correlation and Dice index (phantom only). Multi-breathing-cycle waveforms were extracted and compared in both phantom and volunteer images using the 3D cine as the references. Results: Mild imaging artifacts were found in the 3D cine and TR-4DMRI of the mobile gel phantom with a Dice index of >0.95. Among 7 volunteers, the super-resolution TR-4DMRI yielded high voxel-intensity correlation (0.92 ± 0.05) and low voxel-intensity difference (<0.05). The detected motion differences between TR-4DMRI and 3D cine were −0.2 ± 0.5 mm (phantom) and −0.2 ± 1.9 mm (diaphragms). Conclusion: Super-resolution TR-4DMRI has been

Novel Super-Resolution Approach to Time-Resolved Volumetric 4-Dimensional Magnetic Resonance Imaging With High Spatiotemporal Resolution for Multi-Breathing Cycle Motion Assessment

Energy Technology Data Exchange (ETDEWEB)

Li, Guang, E-mail: lig2@mskcc.org [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York (United States); Wei, Jie [Department of Computer Science, City College of New York, New York, New York (United States); Kadbi, Mo [Philips Healthcare, MR Therapy Cleveland, Ohio (United States); Moody, Jason; Sun, August; Zhang, Shirong; Markova, Svetlana; Zakian, Kristen; Hunt, Margie; Deasy, Joseph O. [Department of Medical Physics, Memorial Sloan Kettering Cancer Center, New York, New York (United States)

2017-06-01

Purpose: To develop and evaluate a super-resolution approach to reconstruct time-resolved 4-dimensional magnetic resonance imaging (TR-4DMRI) with a high spatiotemporal resolution for multi-breathing cycle motion assessment. Methods and Materials: A super-resolution approach was developed to combine fast 3-dimensional (3D) cine MRI with low resolution during free breathing (FB) and high-resolution 3D static MRI during breath hold (BH) using deformable image registration. A T1-weighted, turbo field echo sequence, coronal 3D cine acquisition, partial Fourier approximation, and SENSitivity Encoding parallel acceleration were used. The same MRI pulse sequence, field of view, and acceleration techniques were applied in both FB and BH acquisitions; the intensity-based Demons deformable image registration method was used. Under an institutional review board–approved protocol, 7 volunteers were studied with 3D cine FB scan (voxel size: 5 × 5 × 5 mm{sup 3}) at 2 Hz for 40 seconds and a 3D static BH scan (2 × 2 × 2 mm{sup 3}). To examine the image fidelity of 3D cine and super-resolution TR-4DMRI, a mobile gel phantom with multi-internal targets was scanned at 3 speeds and compared with the 3D static image. Image similarity among 3D cine, 4DMRI, and 3D static was evaluated visually using difference image and quantitatively using voxel intensity correlation and Dice index (phantom only). Multi-breathing-cycle waveforms were extracted and compared in both phantom and volunteer images using the 3D cine as the references. Results: Mild imaging artifacts were found in the 3D cine and TR-4DMRI of the mobile gel phantom with a Dice index of >0.95. Among 7 volunteers, the super-resolution TR-4DMRI yielded high voxel-intensity correlation (0.92 ± 0.05) and low voxel-intensity difference (<0.05). The detected motion differences between TR-4DMRI and 3D cine were −0.2 ± 0.5 mm (phantom) and −0.2 ± 1.9 mm (diaphragms). Conclusion: Super-resolution TR-4

MR imaging of symptomatic osteochondromas with pathological correlation

International Nuclear Information System (INIS)

Mehta, M.; Knapp, T.; White, L.M.; Wunder, J.S.; Bell, R.S.

1998-01-01

Objective. To demonstrate the value of MR imaging in the diagnosis and differentiation of the various symptomatic complications of osteochondromas, providing pathological correlation with emphasis on the usefulness of MR imaging as a single imaging modality in these patients. Design. We retrospectively reviewed all MR examinations of clinically symptomatic osteochondromas (30 patients) performed at our institution between March 1990 and October 1997. Patients. Thirty patients had clinically symptomatic osteochondromas during the study period. Twenty patients were male and 10 were female. There were five cases of multiple osteochondromatosis. Pathological correlation was available in 24 patients. Results and conclusion. Symptomatic complications included fracture (7%), osseous deformity limiting range of motion (23%), vascular injury (7%), neurological compromise (10%), bursa formation (27%) and malignant transformation (27%). MR imaging was able to diagnose or suggest the etiology for the clinical symptomatology in all cases, demonstrating that it is an ideal imaging modality in the diagnostic evaluation of symptomatic complications of osteochondromas and often avoids the need for further imaging. (orig.)

Electrical Resistance Tomography for Visualization of Moving Objects Using a Spatiotemporal Total Variation Regularization Algorithm

Directory of Open Access Journals (Sweden)

Bo Chen

2018-05-01

Full Text Available Electrical resistance tomography (ERT has been considered as a data collection and image reconstruction method in many multi-phase flow application areas due to its advantages of high speed, low cost and being non-invasive. In order to improve the quality of the reconstructed images, the Total Variation algorithm attracts abundant attention due to its ability to solve large piecewise and discontinuous conductivity distributions. In industrial processing tomography (IPT, techniques such as ERT have been used to extract important flow measurement information. For a moving object inside a pipe, a velocity profile can be calculated from the cross correlation between signals generated from ERT sensors. Many previous studies have used two sets of 2D ERT measurements based on pixel-pixel cross correlation, which requires two ERT systems. In this paper, a method for carrying out flow velocity measurement using a single ERT system is proposed. A novel spatiotemporal total variation regularization approach is utilised to exploit sparsity both in space and time in 4D, and a voxel-voxel cross correlation method is adopted for measurement of flow profile. Result shows that the velocity profile can be calculated with a single ERT system and that the volume fraction and movement can be monitored using the proposed method. Both semi-dynamic experimental and static simulation studies verify the suitability of the proposed method. For in plane velocity profile, a 3D image based on temporal 2D images produces velocity profile with accuracy of less than 1% error and a 4D image for 3D velocity profiling shows an error of 4%.

Spatiotemporal Characteristics for the Depth from Luminance Contrast

Directory of Open Access Journals (Sweden)

Kazuya Matsubara

2011-05-01

Full Text Available Images with higher luminance contrast tend to be perceived closer in depth. To investigate a spatiotemporal characteristic of this effect, we evaluated subjective depth of a test stimulus with various spatial and temporal frequencies. For the purpose, the depth of a reference stimulus was matched to that of the test stimulus by changing the binocular disparity. The results showed that the test stimulus was perceived closer with higher luminance contrast for all conditions. Contrast efficiency was obtained from the contrast that provided the subjective depth for each spatiotemporal frequency. The shape of the contrast efficiency function was spatially low-pass and temporally band-pass. This characteristic is different from the one measure for a detection task. This suggests that only subset of contrast signals are used for depth from contrast.

Imaging the spatio-temporal dynamics of supragranular activity in the rat somatosensory cortex in response to stimulation of the paws.

Directory of Open Access Journals (Sweden)

M L Morales-Botello

Full Text Available We employed voltage-sensitive dye (VSD imaging to investigate the spatio-temporal dynamics of the responses of the supragranular somatosensory cortex to stimulation of the four paws in urethane-anesthetized rats. We obtained the following main results. (1 Stimulation of the contralateral forepaw evoked VSD responses with greater amplitude and smaller latency than stimulation of the contralateral hindpaw, and ipsilateral VSD responses had a lower amplitude and greater latency than contralateral responses. (2 While the contralateral stimulation initially activated only one focus, the ipsilateral stimulation initially activated two foci: one focus was typically medial to the focus activated by contralateral stimulation and was stereotaxically localized in the motor cortex; the other focus was typically posterior to the focus activated by contralateral stimulation and was stereotaxically localized in the somatosensory cortex. (3 Forepaw and hindpaw somatosensory stimuli activated large areas of the sensorimotor cortex, well beyond the forepaw and hindpaw somatosensory areas of classical somatotopic maps, and forepaw stimuli activated larger cortical areas with greater activation velocity than hindpaw stimuli. (4 Stimulation of the forepaw and hindpaw evoked different cortical activation dynamics: forepaw responses displayed a clear medial directionality, whereas hindpaw responses were much more uniform in all directions. In conclusion, this work offers a complete spatio-temporal map of the supragranular VSD cortical activation in response to stimulation of the paws, showing important somatotopic differences between contralateral and ipsilateral maps as well as differences in the spatio-temporal activation dynamics in response to forepaw and hindpaw stimuli.

Theoretical scheme of thermal-light many-ghost imaging by Nth-order intensity correlation

International Nuclear Information System (INIS)

Liu Yingchuan; Kuang Leman

2011-01-01

In this paper, we propose a theoretical scheme of many-ghost imaging in terms of Nth-order correlated thermal light. We obtain the Gaussian thin lens equations in the many-ghost imaging protocol. We show that it is possible to produce N-1 ghost images of an object at different places in a nonlocal fashion by means of a higher order correlated imaging process with an Nth-order correlated thermal source and correlation measurements. We investigate the visibility of the ghost images in the scheme and obtain the upper bounds of the visibility for the Nth-order correlated thermal-light ghost imaging. It is found that the visibility of the ghost images can be dramatically enhanced when the order of correlation becomes larger. It is pointed out that the many-ghost imaging phenomenon is an observable physical effect induced by higher order coherence or higher order correlations of optical fields.

Data on spatiotemporal urban sprawl of Dire Dawa City, Eastern Ethiopia.

Science.gov (United States)

Taffa, Chaltu; Mekonen, Teferi; Mulugeta, Messay; Tesfaye, Bechaye

2017-06-01

The data presented in this paper shows the spatiotemporal expansion of Dire Dawa City (eastern Ethiopia) and the ensuing land use land cover changes in its peri-urban areas between 1985 and 2015. The data were generated from satellite images of Thematic Mapper (TM), Enhanced Thematic Mapper-Plus (ETM+) and OLI (Operational Land Image) with path/raw value of 166/053 by using Arc GIS 10.1 software. The precision of the images was verified by geolocation data collected from ground control points by using Geographic Positioning System (GPS) receiver. Four LULC classes (built up area, vegetation, barren land and farmland) with their respective spatiotemporal dimensions were clearly identified in the analysis. Built up area had shown an overall annual increment of 15.8% (82 ha per year) from 517 ha in 1985 to 2976 ha in 2015. Expansion took place in all directions but it was more pronounced along the main road towards other nearby towns, recently established business/service areas and the Industrial Park. Barren land, farmland and vegetation areas showed speedy decline over the years.

Spatiotemporal Data Organization and Application Research

Science.gov (United States)

Tan, C.; Yan, S.

2017-09-01

Organization and management of spatiotemporal data is a key support technology for intelligence in all fields of the smart city. The construction of a smart city cannot be realized without spatiotemporal data. Oriented to support intelligent applications this paper proposes an organizational model for spatiotemporal data, and details the construction of a spatiotemporal big data calculation, analysis, and service framework for highly efficient management and intelligent application of spatiotemporal data for the entire data life cycle.

A generic, time-resolved, integrated digital image correlation, identification approach

NARCIS (Netherlands)

Hoefnagels, J.P.M.; Neggers, J.; Blaysat, Benoît; Hild, François; Geers, M.G.D.; Jin, H.; Sciammarella, C.; Yoshida, S.; Lamberti, L.

2015-01-01

A generic one-step Integrated Digital Image Correlation (I-DIC) inverse parameter identification approach is introduced that enables direct identification of constitutive model parameters by intimately integrating a Finite Elements Method (FEM) with Digital Image Correlation (DIC), directly

Spatiotemporal PET Imaging of Dynamic Metabolic Changes After Therapeutic Approaches of Induced Pluripotent Stem Cells, Neuronal Stem Cells, and a Chinese Patent Medicine in Stroke.

Science.gov (United States)

Zhang, Hong; Song, Fahuan; Xu, Caiyun; Liu, Hao; Wang, Zefeng; Li, Jinhui; Wu, Shuang; YehuaShen; Chen, Yao; Zhu, Yunqi; Du, Ruili; Tian, Mei

2015-11-01

This study aimed to use spatiotemporal PET imaging to investigate the dynamic metabolic changes after a combined therapeutic approach of induced pluripotent stem cells (iPSCs), neuronal stem cells (NSCs), and Chinese patent medicine in a rat model of cerebral ischemia-reperfusion injury. Cerebral ischemia was established by the middle cerebral artery occlusion approach. Thirty-six male rats were randomly assigned to 1 of the 6 groups: control phosphate-buffered saline (PBS), Chinese patent medicine (Qing-kai-ling [QKL]), induced pluripotent stem cells (iPSCs), combination of iPSCs and QKL, neuronal stem cells (NSCs), and combination of NSCs and QKL. Serial (18)F-FDG small-animal PET imaging and neurofunctional tests were performed weekly. Autoradiographic imaging and immunohistochemical and immunofluorescent analyses were performed at 4 wk after stem cell transplantation. Compared with the PBS control group, significantly higher (18)F-FDG accumulations in the ipsilateral cerebral infarction were observed in 5 treatment groups from weeks 1-4. Interestingly, the most intensive (18)F-FDG accumulation was found in the NSCs + QKL group at week 1 but in the iPSCs + QKL group at week 4. The neurofunctional scores in the 5 treatment groups were significantly higher than that of the PBS group from week 3 to 4. In addition, there was a significant correlation between the PET imaging findings and neurofunctional recovery (P PET imaging with (18)F-FDG demonstrated dynamic metabolic and functional recovery after iPSCs or NSCs combined with QKL in a rat model of cerebral ischemia-reperfusion injury. iPSCs or NSCs combined with Chinese medicine QKL seemed to be a better therapeutic approach than these stem cells used individually. © 2015 by the Society of Nuclear Medicine and Molecular Imaging, Inc.

Correlation of early-phase 18F-florbetapir (AV-45/Amyvid) PET images to FDG images: preliminary studies

International Nuclear Information System (INIS)

Hsiao, Ing-Tsung; Hsieh, Chia-Ju; Wey, Shiaw-Pyng; Lin, Kun-Ju; Huang, Chin-Chang; Hsu, Wen-Chun; Yen, Tzu-Chen; Kung, Mei-Ping

2012-01-01

18 F-Florbetapir (AV-45/Amyvid) is a novel positron emission tomography (PET) tracer for imaging plaque pathology in Alzheimer's disease (AD), while PET images of fluorodeoxyglucose (FDG) for cerebral glucose metabolism can provide complementary information to amyloid plaque images for diagnosis of AD. The goal of this preliminary study was to investigate the perfusion-like property of relative cerebral blood flow estimates (R 1 ) and summed early-phase AV-45 images [perfusion AV-45 (pAV-45)] and optimize the early time frame for pAV-45. Dynamic AV-45 PET scans (0-180 min) were performed in seven subjects. pAV-45, late-phase AV-45, and FDG images were spatially normalized to the Montreal Neurological Institute template aided by individual MRI images, and the corresponding standardized uptake value ratio (SUVR) was computed. The R 1 images were derived from a simplified reference tissue model. Correlations between regional and voxelwise R 1 and the corresponding FDG images were calculated. An optimization of time frames of pAV-45 was conducted in terms of correlation to FDG images. The optimal early time frame was validated in a separate cohort. The regional distribution in the R 1 images correlated well (R = 0.91) to that of the FDG within subjects. Consistently high correlation was noted across a long range of time frames. The maximal correlation of pAV-45 to FDG SUVR of R = 0.95 was observed at the time frame of 1-6 min, while the peak correlation of R = 0.99 happened at 0-2 min between pAV-45 and R 1 . A similar result was achieved in the validation cohort. Preliminary results showed that the distribution patterns of R 1 and pAV-45 images are highly correlated with normalized FDG images, and the initial 5-min early time frame of 1-6 min is potentially useful in providing complementary FDG-like information to the amyloid plaque density by late-phase AV-45 images. (orig.)

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System.

Science.gov (United States)

Xiong, Lian; Yang, Liu; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-14

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay.

Spatiotemporal norepinephrine mapping using a high-density CMOS microelectrode array.

Science.gov (United States)

Wydallis, John B; Feeny, Rachel M; Wilson, William; Kern, Tucker; Chen, Tom; Tobet, Stuart; Reynolds, Melissa M; Henry, Charles S

2015-10-21

A high-density amperometric electrode array containing 8192 individually addressable platinum working electrodes with an integrated potentiostat fabricated using Complementary Metal Oxide Semiconductor (CMOS) processes is reported. The array was designed to enable electrochemical imaging of chemical gradients with high spatiotemporal resolution. Electrodes are arranged over a 2 mm × 2 mm surface area into 64 subarrays consisting of 128 individual Pt working electrodes as well as Pt pseudo-reference and auxiliary electrodes. Amperometric measurements of norepinephrine in tissue culture media were used to demonstrate the ability of the array to measure concentration gradients in complex media. Poly(dimethylsiloxane) microfluidics were incorporated to control the chemical concentrations in time and space, and the electrochemical response at each electrode was monitored to generate electrochemical heat maps, demonstrating the array's imaging capabilities. A temporal resolution of 10 ms can be achieved by simultaneously monitoring a single subarray of 128 electrodes. The entire 2 mm × 2 mm area can be electrochemically imaged in 64 seconds by cycling through all subarrays at a rate of 1 Hz per subarray. Monitoring diffusional transport of norepinephrine is used to demonstrate the spatiotemporal resolution capabilities of the system.

Improved kinect-based spatiotemporal and kinematic treadmill gait assessment.

Science.gov (United States)

Eltoukhy, Moataz; Oh, Jeonghoon; Kuenze, Christopher; Signorile, Joseph

2017-01-01

A cost-effective, clinician friendly gait assessment tool that can automatically track patients' anatomical landmarks can provide practitioners with important information that is useful in prescribing rehabilitative and preventive therapies. This study investigated the validity and reliability of the Microsoft Kinect v2 as a potential inexpensive gait analysis tool. Ten healthy subjects walked on a treadmill at 1.3 and 1.6m·s -1 , as spatiotemporal parameters and kinematics were extracted concurrently using the Kinect and three-dimensional motion analysis. Spatiotemporal measures included step length and width, step and stride times, vertical and mediolateral pelvis motion, and foot swing velocity. Kinematic outcomes included hip, knee, and ankle joint angles in the sagittal plane. The absolute agreement and relative consistency between the two systems were assessed using interclass correlations coefficients (ICC2,1), while reproducibility between systems was established using Lin's Concordance Correlation Coefficient (rc). Comparison of ensemble curves and associated 90% confidence intervals (CI90) of the hip, knee, and ankle joint angles were performed to investigate if the Kinect sensor could consistently and accurately assess lower extremity joint motion throughout the gait cycle. Results showed that the Kinect v2 sensor has the potential to be an effective clinical assessment tool for sagittal plane knee and hip joint kinematics, as well as some spatiotemporal temporal variables including pelvis displacement and step characteristics during the gait cycle. Copyright © 2016 Elsevier B.V. All rights reserved.

A hybrid correlation analysis with application to imaging genetics

Science.gov (United States)

Hu, Wenxing; Fang, Jian; Calhoun, Vince D.; Wang, Yu-Ping

2018-03-01

Investigating the association between brain regions and genes continues to be a challenging topic in imaging genetics. Current brain region of interest (ROI)-gene association studies normally reduce data dimension by averaging the value of voxels in each ROI. This averaging may lead to a loss of information due to the existence of functional sub-regions. Pearson correlation is widely used for association analysis. However, it only detects linear correlation whereas nonlinear correlation may exist among ROIs. In this work, we introduced distance correlation to ROI-gene association analysis, which can detect both linear and nonlinear correlations and overcome the limitation of averaging operations by taking advantage of the information at each voxel. Nevertheless, distance correlation usually has a much lower value than Pearson correlation. To address this problem, we proposed a hybrid correlation analysis approach, by applying canonical correlation analysis (CCA) to the distance covariance matrix instead of directly computing distance correlation. Incorporating CCA into distance correlation approach may be more suitable for complex disease study because it can detect highly associated pairs of ROI and gene groups, and may improve the distance correlation level and statistical power. In addition, we developed a novel nonlinear CCA, called distance kernel CCA, which seeks the optimal combination of features with the most significant dependence. This approach was applied to imaging genetic data from the Philadelphia Neurodevelopmental Cohort (PNC). Experiments showed that our hybrid approach produced more consistent results than conventional CCA across resampling and both the correlation and statistical significance were increased compared to distance correlation analysis. Further gene enrichment analysis and region of interest (ROI) analysis confirmed the associations of the identified genes with brain ROIs. Therefore, our approach provides a powerful tool for finding

Speckle pattern processing by digital image correlation

Directory of Open Access Journals (Sweden)

Gubarev Fedor

2016-01-01

Full Text Available Testing the method of speckle pattern processing based on the digital image correlation is carried out in the current work. Three the most widely used formulas of the correlation coefficient are tested. To determine the accuracy of the speckle pattern processing, test speckle patterns with known displacement are used. The optimal size of a speckle pattern template used for determination of correlation and corresponding the speckle pattern displacement is also considered in the work.

Adjusted functional boxplots for spatio-temporal data visualization and outlier detection

KAUST Repository

Sun, Ying

2011-10-24

This article proposes a simulation-based method to adjust functional boxplots for correlations when visualizing functional and spatio-temporal data, as well as detecting outliers. We start by investigating the relationship between the spatio-temporal dependence and the 1.5 times the 50% central region empirical outlier detection rule. Then, we propose to simulate observations without outliers on the basis of a robust estimator of the covariance function of the data. We select the constant factor in the functional boxplot to control the probability of correctly detecting no outliers. Finally, we apply the selected factor to the functional boxplot of the original data. As applications, the factor selection procedure and the adjusted functional boxplots are demonstrated on sea surface temperatures, spatio-temporal precipitation and general circulation model (GCM) data. The outlier detection performance is also compared before and after the factor adjustment. © 2011 John Wiley & Sons, Ltd.

Wavelet-space correlation imaging for high-speed MRI without motion monitoring or data segmentation.

Science.gov (United States)

Li, Yu; Wang, Hui; Tkach, Jean; Roach, David; Woods, Jason; Dumoulin, Charles

2015-12-01

This study aims to (i) develop a new high-speed MRI approach by implementing correlation imaging in wavelet-space, and (ii) demonstrate the ability of wavelet-space correlation imaging to image human anatomy with involuntary or physiological motion. Correlation imaging is a high-speed MRI framework in which image reconstruction relies on quantification of data correlation. The presented work integrates correlation imaging with a wavelet transform technique developed originally in the field of signal and image processing. This provides a new high-speed MRI approach to motion-free data collection without motion monitoring or data segmentation. The new approach, called "wavelet-space correlation imaging", is investigated in brain imaging with involuntary motion and chest imaging with free-breathing. Wavelet-space correlation imaging can exceed the speed limit of conventional parallel imaging methods. Using this approach with high acceleration factors (6 for brain MRI, 16 for cardiac MRI, and 8 for lung MRI), motion-free images can be generated in static brain MRI with involuntary motion and nonsegmented dynamic cardiac/lung MRI with free-breathing. Wavelet-space correlation imaging enables high-speed MRI in the presence of involuntary motion or physiological dynamics without motion monitoring or data segmentation. © 2014 Wiley Periodicals, Inc.

Diagnosing cysts with correlation coefficient images from 2-dimensional freehand elastography.

Science.gov (United States)

Booi, Rebecca C; Carson, Paul L; O'Donnell, Matthew; Richards, Michael S; Rubin, Jonathan M

2007-09-01

We compared the diagnostic potential of using correlation coefficient images versus elastograms from 2-dimensional (2D) freehand elastography to characterize breast cysts. In this preliminary study, which was approved by the Institutional Review Board and compliant with the Health Insurance Portability and Accountability Act, we imaged 4 consecutive human subjects (4 cysts, 1 biopsy-verified benign breast parenchyma) with freehand 2D elastography. Data were processed offline with conventional 2D phase-sensitive speckle-tracking algorithms. The correlation coefficient in the cyst and surrounding tissue was calculated, and appearances of the cysts in the correlation coefficient images and elastograms were compared. The correlation coefficient in the cysts was considerably lower (14%-37%) than in the surrounding tissue because of the lack of sufficient speckle in the cysts, as well as the prominence of random noise, reverberations, and clutter, which decorrelated quickly. Thus, the cysts were visible in all correlation coefficient images. In contrast, the elastograms associated with these cysts each had different elastographic patterns. The solid mass in this study did not have the same high decorrelation rate as the cysts, having a correlation coefficient only 2.1% lower than that of surrounding tissue. Correlation coefficient images may produce a more direct, reliable, and consistent method for characterizing cysts than elastograms.

Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

KAUST Repository

Xie, Le

2014-01-01

We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

Prenatal Visualization of the Pulmonary and Aortic Valves and Leaflets Is Feasible Using 4-Dimensional Sonography

NARCIS (Netherlands)

Adriaanse, B.M.; Uittenbogaard, L.B.; Tromp, C.H.; Heymans, M.W.; Vugt, J.M.G. van; Haak, M.C.

2016-01-01

OBJECTIVES: The purpose of this study was to determine whether the morphologic characteristics and area of the semilunar valves in healthy fetuses and fetuses with cardiac defects can be visualized by using spatiotemporal image correlation (STIC). METHODS: Spatiotemporal image correlation volumes

Replication Strategy for Spatiotemporal Data Based on Distributed Caching System

Science.gov (United States)

Xiong, Lian; Tao, Yang; Xu, Juan; Zhao, Lun

2018-01-01

The replica strategy in distributed cache can effectively reduce user access delay and improve system performance. However, developing a replica strategy suitable for varied application scenarios is still quite challenging, owing to differences in user access behavior and preferences. In this paper, a replication strategy for spatiotemporal data (RSSD) based on a distributed caching system is proposed. By taking advantage of the spatiotemporal locality and correlation of user access, RSSD mines high popularity and associated files from historical user access information, and then generates replicas and selects appropriate cache node for placement. Experimental results show that the RSSD algorithm is simple and efficient, and succeeds in significantly reducing user access delay. PMID:29342897

Correlation of early-phase {sup 18}F-florbetapir (AV-45/Amyvid) PET images to FDG images: preliminary studies

Energy Technology Data Exchange (ETDEWEB)

Hsiao, Ing-Tsung; Hsieh, Chia-Ju; Wey, Shiaw-Pyng; Lin, Kun-Ju [Chang Gung Memorial Hospital, Department of Nuclear Medicine and Molecular Imaging Center, Taipei (China); Chang Gung University, Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, Taipei (China); Huang, Chin-Chang; Hsu, Wen-Chun [Chang Gung Memorial Hospital, Department of Neurology, Taipei (China); Yen, Tzu-Chen [Chang Gung Memorial Hospital, Department of Nuclear Medicine and Molecular Imaging Center, Taipei (China); Kung, Mei-Ping [Chang Gung Memorial Hospital, Department of Nuclear Medicine and Molecular Imaging Center, Taipei (China); Chang Gung University, Healthy Aging Research Center and Department of Medical Imaging and Radiological Sciences, Taipei (China); University of Pennsylvania, Department of Radiology, Philadelphia, PA (United States)

2012-04-15

{sup 18}F-Florbetapir (AV-45/Amyvid) is a novel positron emission tomography (PET) tracer for imaging plaque pathology in Alzheimer's disease (AD), while PET images of fluorodeoxyglucose (FDG) for cerebral glucose metabolism can provide complementary information to amyloid plaque images for diagnosis of AD. The goal of this preliminary study was to investigate the perfusion-like property of relative cerebral blood flow estimates (R{sub 1}) and summed early-phase AV-45 images [perfusion AV-45 (pAV-45)] and optimize the early time frame for pAV-45. Dynamic AV-45 PET scans (0-180 min) were performed in seven subjects. pAV-45, late-phase AV-45, and FDG images were spatially normalized to the Montreal Neurological Institute template aided by individual MRI images, and the corresponding standardized uptake value ratio (SUVR) was computed. The R{sub 1} images were derived from a simplified reference tissue model. Correlations between regional and voxelwise R{sub 1} and the corresponding FDG images were calculated. An optimization of time frames of pAV-45 was conducted in terms of correlation to FDG images. The optimal early time frame was validated in a separate cohort. The regional distribution in the R{sub 1} images correlated well (R = 0.91) to that of the FDG within subjects. Consistently high correlation was noted across a long range of time frames. The maximal correlation of pAV-45 to FDG SUVR of R = 0.95 was observed at the time frame of 1-6 min, while the peak correlation of R = 0.99 happened at 0-2 min between pAV-45 and R{sub 1}. A similar result was achieved in the validation cohort. Preliminary results showed that the distribution patterns of R{sub 1} and pAV-45 images are highly correlated with normalized FDG images, and the initial 5-min early time frame of 1-6 min is potentially useful in providing complementary FDG-like information to the amyloid plaque density by late-phase AV-45 images. (orig.)

Robust Small Target Co-Detection from Airborne Infrared Image Sequences.

Science.gov (United States)

Gao, Jingli; Wen, Chenglin; Liu, Meiqin

2017-09-29

In this paper, a novel infrared target co-detection model combining the self-correlation features of backgrounds and the commonality features of targets in the spatio-temporal domain is proposed to detect small targets in a sequence of infrared images with complex backgrounds. Firstly, a dense target extraction model based on nonlinear weights is proposed, which can better suppress background of images and enhance small targets than weights of singular values. Secondly, a sparse target extraction model based on entry-wise weighted robust principal component analysis is proposed. The entry-wise weight adaptively incorporates structural prior in terms of local weighted entropy, thus, it can extract real targets accurately and suppress background clutters efficiently. Finally, the commonality of targets in the spatio-temporal domain are used to construct target refinement model for false alarms suppression and target confirmation. Since real targets could appear in both of the dense and sparse reconstruction maps of a single frame, and form trajectories after tracklet association of consecutive frames, the location correlation of the dense and sparse reconstruction maps for a single frame and tracklet association of the location correlation maps for successive frames have strong ability to discriminate between small targets and background clutters. Experimental results demonstrate that the proposed small target co-detection method can not only suppress background clutters effectively, but also detect targets accurately even if with target-like interference.

In Situ Correlated Molecular Imaging of Chemically Communicating Microbial Communities

Energy Technology Data Exchange (ETDEWEB)

Bohn, Paul W. [Univ. of Notre Dame, IN (United States); Shrout, J. D. [Univ. of Notre Dame, IN (United States); Sweedler, J. V. [Univ. of Illinois, Urbana-Champaign, IL (United States); Farrand, S. [Univ. of Illinois, Urbana-Champaign, IL (United States)

2016-01-25

This document constitutes the final technical report for DE-SC0006642, In Situ Correlated Molecular Imaging of Chemically Communicating Microbial Communities, a project carried out collaboratively by investigators at Notre Dame and UIUC. The work carried out under DOE support in this project produced advances in two areas: development of new highly sophisticated correlated imaging approaches and the application of these new tools to the growth and differentiation of microbial communities under a variety of environmental conditions. A significant effort involved the creation of technical enhancements and sampling approaches to allow us to advance heterocorrelated mass spectrometry imaging (MSI) and correlated Raman microscopy (CRM) from bacterial cultures and biofilms. We then exploited these measurement advances in heterocorrelated MS/CRM imaging to determine relationship of signaling molecules and excreted signaling molecules produced by P. aeruginosa to conditions relevant to the rhizosphere. In particular, we: (1) developed a laboratory testbed mimic for the rhizosphere to enable microbial growth on slides under controlled conditions; (2) integrated specific measurements of (a) rhamnolipids, (b) quinolone/quinolones, and (c) phenazines specific to P. aeruginosa; and (3) utilized the imaging tools to probe how messenger secretion, quorum sensing and swarming behavior are correlated with behavior.

Self-Organization of Spatio-Temporal Hierarchy via Learning of Dynamic Visual Image Patterns on Action Sequences.

Science.gov (United States)

Jung, Minju; Hwang, Jungsik; Tani, Jun

2015-01-01

It is well known that the visual cortex efficiently processes high-dimensional spatial information by using a hierarchical structure. Recently, computational models that were inspired by the spatial hierarchy of the visual cortex have shown remarkable performance in image recognition. Up to now, however, most biological and computational modeling studies have mainly focused on the spatial domain and do not discuss temporal domain processing of the visual cortex. Several studies on the visual cortex and other brain areas associated with motor control support that the brain also uses its hierarchical structure as a processing mechanism for temporal information. Based on the success of previous computational models using spatial hierarchy and temporal hierarchy observed in the brain, the current report introduces a novel neural network model for the recognition of dynamic visual image patterns based solely on the learning of exemplars. This model is characterized by the application of both spatial and temporal constraints on local neural activities, resulting in the self-organization of a spatio-temporal hierarchy necessary for the recognition of complex dynamic visual image patterns. The evaluation with the Weizmann dataset in recognition of a set of prototypical human movement patterns showed that the proposed model is significantly robust in recognizing dynamically occluded visual patterns compared to other baseline models. Furthermore, an evaluation test for the recognition of concatenated sequences of those prototypical movement patterns indicated that the model is endowed with a remarkable capability for the contextual recognition of long-range dynamic visual image patterns.

Spatio-Temporal Saliency Perception via Hypercomplex Frequency Spectral Contrast

Directory of Open Access Journals (Sweden)

Zhiqiang Tian

2013-03-01

Full Text Available Salient object perception is the process of sensing the salient information from the spatio-temporal visual scenes, which is a rapid pre-attention mechanism for the target location in a visual smart sensor. In recent decades, many successful models of visual saliency perception have been proposed to simulate the pre-attention behavior. Since most of the methods usually need some ad hoc parameters or high-cost preprocessing, they are difficult to rapidly detect salient object or be implemented by computing parallelism in a smart sensor. In this paper, we propose a novel spatio-temporal saliency perception method based on spatio-temporal hypercomplex spectral contrast (HSC. Firstly, the proposed HSC algorithm represent the features in the HSV (hue, saturation and value color space and features of motion by a hypercomplex number. Secondly, the spatio-temporal salient objects are efficiently detected by hypercomplex Fourier spectral contrast in parallel. Finally, our saliency perception model also incorporates with the non-uniform sampling, which is a common phenomenon of human vision that directs visual attention to the logarithmic center of the image/video in natural scenes. The experimental results on the public saliency perception datasets demonstrate the effectiveness of the proposed approach compared to eleven state-of-the-art approaches. In addition, we extend the proposed model to moving object extraction in dynamic scenes, and the proposed algorithm is superior to the traditional algorithms.

Fluorescence decay time imaging using an imaging photon detector with a radio frequency photon correlation system

Science.gov (United States)

Morgan, Christopher G.; Mitchell, A. C.; Murray, J. G.

1990-05-01

An imaging photon detector has been modified to incorporate fast timing electronics coupled to a custom built photon correlator interfaced to a RISC computer. Using excitation with intensity- muodulated light, fluorescence images can be readily obtained where contrast is determined by the decay time of emission, rather than by intensity. This technology is readily extended to multifrequency phase/demodulation fluorescence imaging or to differential polarised phase fluorometry. The potential use of the correlator for confocal imaging with a laser scanner is also briefly discussed.

Data on spatiotemporal urban sprawl of Dire Dawa City, Eastern Ethiopia

Directory of Open Access Journals (Sweden)

Chaltu Taffa

2017-06-01

Full Text Available The data presented in this paper shows the spatiotemporal expansion of Dire Dawa City (eastern Ethiopia and the ensuing land use land cover changes in its peri-urban areas between 1985 and 2015. The data were generated from satellite images of Thematic Mapper (TM, Enhanced Thematic Mapper-Plus (ETM+ and OLI (Operational Land Image with path/raw value of 166/053 by using Arc GIS 10.1 software. The precision of the images was verified by geolocation data collected from ground control points by using Geographic Positioning System (GPS receiver. Four LULC classes (built up area, vegetation, barren land and farmland with their respective spatiotemporal dimensions were clearly identified in the analysis. Built up area had shown an overall annual increment of 15.8% (82 ha per year from 517 ha in 1985 to 2976 ha in 2015. Expansion took place in all directions but it was more pronounced along the main road towards other nearby towns, recently established business/service areas and the Industrial Park. Barren land, farmland and vegetation areas showed speedy decline over the years.

Bayesian spatio-temporal analysis and geospatial risk factors of human monocytic ehrlichiosis.

Directory of Open Access Journals (Sweden)

Ram K Raghavan

Full Text Available Variations in spatio-temporal patterns of Human Monocytic Ehrlichiosis (HME infection in the state of Kansas, USA were examined and the relationship between HME relative risk and various environmental, climatic and socio-economic variables were evaluated. HME data used in the study was reported to the Kansas Department of Health and Environment between years 2005-2012, and geospatial variables representing the physical environment [National Land cover/Land use, NASA Moderate Resolution Imaging Spectroradiometer (MODIS], climate [NASA MODIS, Prediction of Worldwide Renewable Energy (POWER], and socio-economic conditions (US Census Bureau were derived from publicly available sources. Following univariate screening of candidate variables using logistic regressions, two Bayesian hierarchical models were fit; a partial spatio-temporal model with random effects and a spatio-temporal interaction term, and a second model that included additional covariate terms. The best fitting model revealed that spatio-temporal autocorrelation in Kansas increased steadily from 2005-2012, and identified poverty status, relative humidity, and an interactive factor, 'diurnal temperature range x mixed forest area' as significant county-level risk factors for HME. The identification of significant spatio-temporal pattern and new risk factors are important in the context of HME prevention, for future research in the areas of ecology and evolution of HME, and as well as climate change impacts on tick-borne diseases.

A novel spatiotemporal muscle activity imaging approach based on the Extended Kalman Filter.

Science.gov (United States)

Wang, Jing; Zhang, Yingchun; Zhu, Xiangjun; Zhou, Ping; Liu, Chenguang; Rymer, William Z

2012-01-01

A novel spatiotemporal muscle activity imaging (sMAI) approach has been developed using the Extended Kalman Filter (EKF) to reconstruct internal muscle activities from non-invasive multi-channel surface electromyogram (sEMG) recordings. A distributed bioelectric dipole source model is employed to describe the internal muscle activity space, and a linear relationship between the muscle activity space and the sEMG measurement space is then established. The EKF is employed to recursively solve the ill-posed inverse problem in the sMAI approach, in which the weighted minimum norm (WMN) method is utilized to calculate the initial state and a new nonlinear method is developed based on the propagating features of muscle activities to predict the recursive state. A series of computer simulations was conducted to test the performance of the proposed sMAI approach. Results show that the localization error rapidly decreases over 35% and the overlap ratio rapidly increases over 45% compared to the results achieved using the WMN method only. The present promising results demonstrate the feasibility of utilizing the proposed EKF-based sMAI approach to accurately reconstruct internal muscle activities from non-invasive sEMG recordings.

Fourier-transform ghost imaging with pure far-field correlated thermal light

International Nuclear Information System (INIS)

Liu Honglin; Shen Xia; Han Shensheng; Zhu Daming

2007-01-01

Pure far-field correlated thermal light beams are created with phase grating, and Fourier-transform ghost imaging depending only on the far-field correlation is demonstrated experimentally. Theoretical analysis and the results of experimental investigation of this pure far-field correlated thermal light are presented. Applications which may be exploited with this imaging scheme are discussed

Spatiotemporal Modeling of Community Risk

Science.gov (United States)

2016-03-01

Ertugay, and Sebnem Duzgun, “Exploratory and Inferential Methods for Spatio-Temporal Analysis of Residential Fire Clustering in Urban Areas,” Fire ...response in communities.”26 In “Exploratory and Inferential Methods for Spatio-temporal Analysis of Residential Fire Clustering in Urban Areas,” Ceyhan...of fire resources spread across the community. Spatiotemporal modeling shows that actualized risk is dynamic and relatively patterned. Though

SU-D-202-02: Quantitative Imaging: Correlation Between Image Feature Analysis and the Accuracy of Manually Drawn Contours On PET Images

Energy Technology Data Exchange (ETDEWEB)

Lamichhane, N; Johnson, P; Chinea, F; Patel, V; Yang, F [University of Miami, Miami, FL (United States)

2016-06-15

Purpose: To evaluate the correlation between image features and the accuracy of manually drawn target contours on synthetic PET images Methods: A digital PET phantom was used in combination with Monte Carlo simulation to create a set of 26 simulated PET images featuring a variety of tumor shapes and activity heterogeneity. These tumor volumes were used as a gold standard in comparisons with manual contours delineated by 10 radiation oncologist on the simulated PET images. Metrics used to evaluate segmentation accuracy included the dice coefficient, false positive dice, false negative dice, symmetric mean absolute surface distance, and absolute volumetric difference. Image features extracted from the simulated tumors consisted of volume, shape complexity, mean curvature, and intensity contrast along with five texture features derived from the gray-level neighborhood difference matrices including contrast, coarseness, busyness, strength, and complexity. Correlation between these features and contouring accuracy were examined. Results: Contour accuracy was reasonably well correlated with a variety of image features. Dice coefficient ranged from 0.7 to 0.90 and was correlated closely with contrast (r=0.43, p=0.02) and complexity (r=0.5, p<0.001). False negative dice ranged from 0.10 to 0.50 and was correlated closely with contrast (r=0.68, p<0.001) and complexity (r=0.66, p<0.001). Absolute volumetric difference ranged from 0.0002 to 0.67 and was correlated closely with coarseness (r=0.46, p=0.02) and complexity (r=0.49, p=0.008). Symmetric mean absolute difference ranged from 0.02 to 1 and was correlated closely with mean curvature (r=0.57, p=0.02) and contrast (r=0.6, p=0.001). Conclusion: The long term goal of this study is to assess whether contouring variability can be reduced by providing feedback to the practitioner based on image feature analysis. The results are encouraging and will be used to develop a statistical model which will enable a prediction of

A Bayesian spatio-temporal geostatistical model with an auxiliary lattice for large datasets

KAUST Repository

Xu, Ganggang

2015-01-01

When spatio-temporal datasets are large, the computational burden can lead to failures in the implementation of traditional geostatistical tools. In this paper, we propose a computationally efficient Bayesian hierarchical spatio-temporal model in which the spatial dependence is approximated by a Gaussian Markov random field (GMRF) while the temporal correlation is described using a vector autoregressive model. By introducing an auxiliary lattice on the spatial region of interest, the proposed method is not only able to handle irregularly spaced observations in the spatial domain, but it is also able to bypass the missing data problem in a spatio-temporal process. Because the computational complexity of the proposed Markov chain Monte Carlo algorithm is of the order O(n) with n the total number of observations in space and time, our method can be used to handle very large spatio-temporal datasets with reasonable CPU times. The performance of the proposed model is illustrated using simulation studies and a dataset of precipitation data from the coterminous United States.

Spatiotemporal chaos from bursting dynamics

International Nuclear Information System (INIS)

Berenstein, Igal; De Decker, Yannick

2015-01-01

In this paper, we study the emergence of spatiotemporal chaos from mixed-mode oscillations, by using an extended Oregonator model. We show that bursting dynamics consisting of fast/slow mixed mode oscillations along a single attractor can lead to spatiotemporal chaotic dynamics, although the spatially homogeneous solution is itself non-chaotic. This behavior is observed far from the Hopf bifurcation and takes the form of a spatiotemporal intermittency where the system locally alternates between the fast and the slow phases of the mixed mode oscillations. We expect this form of spatiotemporal chaos to be generic for models in which one or several slow variables are coupled to activator-inhibitor type of oscillators

Optimum slicing of radical prostatectomy specimens for correlation between histopathology and medical images

International Nuclear Information System (INIS)

Chen, Li Hong; Ng, Wan Sing; Ho, Henry; Yuen, John; Cheng, Chris; Lazaro, Richie; Thng, Choon Hua

2010-01-01

There is a need for methods which enable precise correlation of histologic sections with in vivo prostate images. Such methods would allow direct comparison between imaging features and functional or histopathological heterogeneity of tumors. Correlation would be particularly useful for validating the accuracy of imaging modalities, developing imaging techniques, assessing image-guided therapy, etc. An optimum prostate slicing method for accurate correlation between the histopathological and medical imaging planes in terms of section angle, thickness and level was sought. Literature review (51 references from 1986-2009 were cited) was done on the various sectioning apparatus or techniques used to slice the prostate specimen for accurate correlation between histopathological data and medical imaging. Technology evaluation was performed with review and discussion of various methods used to section other organs and their possible applications for sectioning prostatectomy specimens. No consensus has been achieved on how the prostate should be dissected to achieve a good correlation. Various customized sectioning instruments and techniques working with different mechanism are used in different research institutes to improve the correlation. Some of the methods have convincingly shown significant potential for improving image-specimen correlation. However, the semisolid consistent property of prostate tissue and the lack of identifiable landmarks remain challenges to be overcome, especially for fresh prostate sectioning and microtomy without external fiducials. A standardized optimum protocol to dissect prostatectomy specimens is needed for the validation of medical imaging modalities by histologic correlation. These standards can enhance disease management by improving the comparability between different modalities. (orig.)

Elimination of spiral waves and spatiotemporal chaos by the pulse with a specific spatiotemporal configuration

International Nuclear Information System (INIS)

Yuan Guoyong; Yang Shiping; Wang Guangrui; Chen Shigang

2008-01-01

Spiral waves and spatiotemporal chaos are sometimes harmful and should be controlled. In this paper spiral waves and spatiotemporal chaos are successfully eliminated by the pulse with a very specific spatiotemporal configuration. The excited position D of spiral waves or spatiotemporal chaos is first recorded at an arbitrary time (t 0 ). When the system at the domain D enters a recovering state, the external pulse is injected into the domain. If the intensity and the working time of the pulse are appropriate, spiral waves and spatiotemporal chaos can finally be eliminated because counter-directional waves can be generated by the pulse. There are two advantages in the method. One is that the tip can be quickly eliminated together with the body of spiral wave, and the other is that the injected pulse may be weak and the duration can be very short so that the original system is nearly not affected, which is important for practical applications

Study of morphological changes in scattering and optically anisotropic medium through correlation images

Science.gov (United States)

Jain, Neha; Shukla, Prashant; Singh, Jai

2018-05-01

Correlation images are very useful in determining the morphological changes. We have investigated the correlation image analysis on depolarization and retardance matrices of polystyrene and gelatine samples respectively. We observed that that correlation images have a potential to show a significant variation with change in the concentration of samples (polystyrene and gelatine). For polystyrene microspheres the correlation value decreases with increasing scattering coefficient. In gelatine samples the correlation also decreases with sample concentration. This variation in correlation for retardance shows the change in a birefringence property of gelatine solution.

ESIPT-Based Photoactivatable Fluorescent Probe for Ratiometric Spatiotemporal Bioimaging

Directory of Open Access Journals (Sweden)

Xiaohong Zhou

2016-10-01

Full Text Available Photoactivatable fluorophores have become an important technique for the high spatiotemporal resolution of biological imaging. Here, we developed a novel photoactivatable probe (PHBT, which is based on 2-(2-hydroxyphenylbenzothiazole (HBT, a small organic fluorophore known for its classic luminescence mechanism through excited-state intramolecular proton transfer (ESIPT with the keto form and the enol form. After photocleavage, PHBT released a ratiometric fluorophore HBT, which showed dual emission bands with more than 73-fold fluorescence enhancement at 512 nm in buffer and more than 69-fold enhancement at 452 nm in bovine serum. The probe displayed a high ratiometric imaging resolution and is believed to have a wide application in biological imaging.

Tensor-based spatiotemporal saliency detection

Science.gov (United States)

Dou, Hao; Li, Bin; Deng, Qianqian; Zhang, LiRui; Pan, Zhihong; Tian, Jinwen

2018-03-01

This paper proposes an effective tensor-based spatiotemporal saliency computation model for saliency detection in videos. First, we construct the tensor representation of video frames. Then, the spatiotemporal saliency can be directly computed by the tensor distance between different tensors, which can preserve the complete temporal and spatial structure information of object in the spatiotemporal domain. Experimental results demonstrate that our method can achieve encouraging performance in comparison with the state-of-the-art methods.

Correlation of the clinical and physical image quality in chest radiography for average adults with a computed radiography imaging system.

Science.gov (United States)

Moore, C S; Wood, T J; Beavis, A W; Saunderson, J R

2013-07-01

The purpose of this study was to examine the correlation between the quality of visually graded patient (clinical) chest images and a quantitative assessment of chest phantom (physical) images acquired with a computed radiography (CR) imaging system. The results of a previously published study, in which four experienced image evaluators graded computer-simulated postero-anterior chest images using a visual grading analysis scoring (VGAS) scheme, were used for the clinical image quality measurement. Contrast-to-noise ratio (CNR) and effective dose efficiency (eDE) were used as physical image quality metrics measured in a uniform chest phantom. Although optimal values of these physical metrics for chest radiography were not derived in this work, their correlation with VGAS in images acquired without an antiscatter grid across the diagnostic range of X-ray tube voltages was determined using Pearson's correlation coefficient. Clinical and physical image quality metrics increased with decreasing tube voltage. Statistically significant correlations between VGAS and CNR (R=0.87, pchest CR images acquired without an antiscatter grid. A statistically significant correlation has been found between the clinical and physical image quality in CR chest imaging. The results support the value of using CNR and eDE in the evaluation of quality in clinical thorax radiography.

Evaluation of high resolution spatio-temporal precipitation extremes from a stochastic weather generator

DEFF Research Database (Denmark)

Sørup, Hjalte Jomo Danielsen; Christensen, O. B.; Arnbjerg-Nielsen, Karsten

gauges in the model area. The spatio-temporal performance of the model with respect to precipitation extremes is evaluated in the points of a 2x2 km regular grid covering the full model area. The model satisfactorily reproduces the extreme behaviour of the observed precipitation with respect to event...... intensity levels and unconditional spatial correlation when evaluated using an event based ranking approach at point scale and an advanced spatio-temporal coupling of extreme events. Prospectively the model can be used as a tool to evaluate the impact of climate change without relying onprecipitation output......Spatio-temporal rainfall is modelled for the North-Eastern part of Zealand (Denmark) using the Spatio-Temporal Neyman-Scott Rectangular Pulses model as implemented in the RainSim software. Hourly precipitation series for fitting the model are obtained from a dense network of tipping bucket rain...

Ghost imaging based on Pearson correlation coefficients

International Nuclear Information System (INIS)

Yu Wen-Kai; Yao Xu-Ri; Liu Xue-Feng; Li Long-Zhen; Zhai Guang-Jie

2015-01-01

Correspondence imaging is a new modality of ghost imaging, which can retrieve a positive/negative image by simple conditional averaging of the reference frames that correspond to relatively large/small values of the total intensity measured at the bucket detector. Here we propose and experimentally demonstrate a more rigorous and general approach in which a ghost image is retrieved by calculating a Pearson correlation coefficient between the bucket detector intensity and the brightness at a given pixel of the reference frames, and at the next pixel, and so on. Furthermore, we theoretically provide a statistical interpretation of these two imaging phenomena, and explain how the error depends on the sample size and what kind of distribution the error obeys. According to our analysis, the image signal-to-noise ratio can be greatly improved and the sampling number reduced by means of our new method. (paper)

Smartphone based scalable reverse engineering by digital image correlation

Science.gov (United States)

Vidvans, Amey; Basu, Saurabh

2018-03-01

There is a need for scalable open source 3D reconstruction systems for reverse engineering. This is because most commercially available reconstruction systems are capital and resource intensive. To address this, a novel reconstruction technique is proposed. The technique involves digital image correlation based characterization of surface speeds followed by normalization with respect to angular speed during rigid body rotational motion of the specimen. Proof of concept of the same is demonstrated and validated using simulation and empirical characterization. Towards this, smart-phone imaging and inexpensive off the shelf components along with those fabricated additively using poly-lactic acid polymer with a standard 3D printer are used. Some sources of error in this reconstruction methodology are discussed. It is seen that high curvatures on the surface suppress accuracy of reconstruction. Reasons behind this are delineated in the nature of the correlation function. Theoretically achievable resolution during smart-phone based 3D reconstruction by digital image correlation is derived.

Spatiotemporal Features of the Three-Dimensional Architectural Landscape in Qingdao, China.

Science.gov (United States)

Zhang, Peifeng

2015-01-01

The evolution and development of the three-dimensional (3D) architectural landscape is the basis of proper urban planning, eco-environment construction and the improvement of environmental quality. This paper presents the spatiotemporal characteristics of the 3D architectural landscape of the Shinan and Shibei districts in Qingdao, China, based on buildings' 3D information extracted from Quickbird images from 2003 to 2012, supported by Barista, landscape metrics and GIS. The results demonstrated that: (1) Shinan and Shibei districts expanded vertically and urban land use intensity increased noticeably from year to year. (2) Significant differences in the 3D architectural landscape existed among the western, central and eastern regions, and among the 26 sub-districts over the study period. The differentiation was consistent with the diverse development history, function and planning of the two districts. Finally, we found that population correlates positively with the variation in the 3D architectural landscape. This research provides an important reference for related studies, urban planning and eco-city construction.

Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic 'gold' standard.

Science.gov (United States)

Wang, Xian-Hong; Zhou, Xiao-Nong; Vounatsou, Penelope; Chen, Zhao; Utzinger, Jürg; Yang, Kun; Steinmann, Peter; Wu, Xiao-Hua

2008-06-11

Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA), from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People's Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the 'true' prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken into consideration when making risk prediction at small scales.

Spatiotemporal Fusion of Multisource Remote Sensing Data: Literature Survey, Taxonomy, Principles, Applications, and Future Directions

Directory of Open Access Journals (Sweden)

Xiaolin Zhu

2018-03-01

Full Text Available Satellite time series with high spatial resolution is critical for monitoring land surface dynamics in heterogeneous landscapes. Although remote sensing technologies have experienced rapid development in recent years, data acquired from a single satellite sensor are often unable to satisfy our demand. As a result, integrated use of data from different sensors has become increasingly popular in the past decade. Many spatiotemporal data fusion methods have been developed to produce synthesized images with both high spatial and temporal resolutions from two types of satellite images, frequent coarse-resolution images, and sparse fine-resolution images. These methods were designed based on different principles and strategies, and therefore show different strengths and limitations. This diversity brings difficulties for users to choose an appropriate method for their specific applications and data sets. To this end, this review paper investigates literature on current spatiotemporal data fusion methods, categorizes existing methods, discusses the principal laws underlying these methods, summarizes their potential applications, and proposes possible directions for future studies in this field.

Exploring the brain on multiple scales with correlative two-photon and light sheet microscopy

Science.gov (United States)

Silvestri, Ludovico; Allegra Mascaro, Anna Letizia; Costantini, Irene; Sacconi, Leonardo; Pavone, Francesco S.

2014-02-01

One of the unique features of the brain is that its activity cannot be framed in a single spatio-temporal scale, but rather spans many orders of magnitude both in space and time. A single imaging technique can reveal only a small part of this complex machinery. To obtain a more comprehensive view of brain functionality, complementary approaches should be combined into a correlative framework. Here, we describe a method to integrate data from in vivo two-photon fluorescence imaging and ex vivo light sheet microscopy, taking advantage of blood vessels as reference chart. We show how the apical dendritic arbor of a single cortical pyramidal neuron imaged in living thy1-GFP-M mice can be found in the large-scale brain reconstruction obtained with light sheet microscopy. Starting from the apical portion, the whole pyramidal neuron can then be segmented. The correlative approach presented here allows contextualizing within a three-dimensional anatomic framework the neurons whose dynamics have been observed with high detail in vivo.

OPTICAL correlation identification technology applied in underwater laser imaging target identification

Science.gov (United States)

Yao, Guang-tao; Zhang, Xiao-hui; Ge, Wei-long

2012-01-01

The underwater laser imaging detection is an effective method of detecting short distance target underwater as an important complement of sonar detection. With the development of underwater laser imaging technology and underwater vehicle technology, the underwater automatic target identification has gotten more and more attention, and is a research difficulty in the area of underwater optical imaging information processing. Today, underwater automatic target identification based on optical imaging is usually realized with the method of digital circuit software programming. The algorithm realization and control of this method is very flexible. However, the optical imaging information is 2D image even 3D image, the amount of imaging processing information is abundant, so the electronic hardware with pure digital algorithm will need long identification time and is hard to meet the demands of real-time identification. If adopt computer parallel processing, the identification speed can be improved, but it will increase complexity, size and power consumption. This paper attempts to apply optical correlation identification technology to realize underwater automatic target identification. The optics correlation identification technology utilizes the Fourier transform characteristic of Fourier lens which can accomplish Fourier transform of image information in the level of nanosecond, and optical space interconnection calculation has the features of parallel, high speed, large capacity and high resolution, combines the flexibility of calculation and control of digital circuit method to realize optoelectronic hybrid identification mode. We reduce theoretical formulation of correlation identification and analyze the principle of optical correlation identification, and write MATLAB simulation program. We adopt single frame image obtained in underwater range gating laser imaging to identify, and through identifying and locating the different positions of target, we can improve

Cross Correlation versus Normalized Mutual Information on Image Registration

Science.gov (United States)

Tan, Bin; Tilton, James C.; Lin, Guoqing

2016-01-01

This is the first study to quantitatively assess and compare cross correlation and normalized mutual information methods used to register images in subpixel scale. The study shows that the normalized mutual information method is less sensitive to unaligned edges due to the spectral response differences than is cross correlation. This characteristic makes the normalized image resolution a better candidate for band to band registration. Improved band-to-band registration in the data from satellite-borne instruments will result in improved retrievals of key science measurements such as cloud properties, vegetation, snow and fire.

Correlation Filters for Detection of Cellular Nuclei in Histopathology Images.

Science.gov (United States)

Ahmad, Asif; Asif, Amina; Rajpoot, Nasir; Arif, Muhammad; Minhas, Fayyaz Ul Amir Afsar

2017-11-21

Nuclei detection in histology images is an essential part of computer aided diagnosis of cancers and tumors. It is a challenging task due to diverse and complicated structures of cells. In this work, we present an automated technique for detection of cellular nuclei in hematoxylin and eosin stained histopathology images. Our proposed approach is based on kernelized correlation filters. Correlation filters have been widely used in object detection and tracking applications but their strength has not been explored in the medical imaging domain up till now. Our experimental results show that the proposed scheme gives state of the art accuracy and can learn complex nuclear morphologies. Like deep learning approaches, the proposed filters do not require engineering of image features as they can operate directly on histopathology images without significant preprocessing. However, unlike deep learning methods, the large-margin correlation filters developed in this work are interpretable, computationally efficient and do not require specialized or expensive computing hardware. A cloud based webserver of the proposed method and its python implementation can be accessed at the following URL: http://faculty.pieas.edu.pk/fayyaz/software.html#corehist .

Automated Spatio-Temporal Analysis of Remotely Sensed Imagery for Water Resources Management

Science.gov (United States)

Bahr, Thomas

2016-04-01

a common video format. • Plotting the time series of water surface area in square kilometers. The automated spatio-temporal analysis introduced here can be embedded in virtually any existing geospatial workflow for operational applications. Three integration options were implemented in this case study: • Integration within any ArcGIS environment whether deployed on the desktop, in the cloud, or online. Execution uses a customized ArcGIS script tool. A Python script file retrieves the parameters from the user interface and runs the precompiled IDL code. That IDL code is used to interface between the Python script and the relevant ENVITasks. • Publishing the spatio-temporal analysis tasks as services via the ENVI Services Engine (ESE). ESE is a cloud-based image analysis solution to publish and deploy advanced ENVI image and data analytics to existing enterprise infrastructures. For this purpose the entire IDL code can be capsuled in a single ENVITask. • Integration in an existing geospatial workflow using the Python-to-IDL Bridge. This mechanism allows calling IDL code within Python on a user-defined platform. The results of this case study verify the drastic decrease of the amount of surface water in the AOI, indicative of the major drought that is pervasive throughout California. Accordingly, the time series analysis was correlated successfully with the daily reservoir elevations of the Don Pedro reservoir (station DNP, operated by CDEC).

Spatiotemporal Stability of Cu-ATSM and FLT Positron Emission Tomography Distributions During Radiation Therapy

Energy Technology Data Exchange (ETDEWEB)

Bradshaw, Tyler J.; Yip, Stephen; Jallow, Ngoneh [Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin (United States); Forrest, Lisa J. [Department of Surgical Sciences, School of Veterinary Medicine, University of Wisconsin, Madison, Wisconsin (United States); Jeraj, Robert, E-mail: rjeraj@wisc.edu [Department of Medical Physics, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin (United States); Department of Human Oncology, School of Medicine and Public Health, University of Wisconsin, Madison, Wisconsin (United States)

2014-06-01

Purpose: In dose painting, in which functional imaging is used to define biological targets for radiation therapy dose escalation, changes in spatial distributions of biological properties during treatment can compromise the quality of therapy. The goal of this study was to assess the spatiotemporal stability of 2 potential dose painting targets—hypoxia and proliferation—in canine tumors during radiation therapy. Methods and Materials: Twenty-two canine patients with sinonasal tumors (14 carcinoma and 8 sarcoma) were imaged before hypofractionated radiation therapy with copper(II)-diacetyl-bis(N4-methylthiosemicarbazone) (Cu-ATSM) positron emission tomography/computed tomography (PET/CT) for hypoxia and 3′-deoxy-3′-{sup 18}F-fluorothymidine (FLT) PET/CT for proliferation. The FLT scans were repeated after 2 fractions and the Cu-ATSM scans after 3 fractions. Midtreatment PET/CT images were deformably registered to pretreatment PET/CT images. Voxel-based Spearman correlation coefficients quantified the spatial stability of Cu-ATSM and FLT uptake distributions between pretreatment and midtreatment scans. Paired t tests determined significant differences between the patients' respective Cu-ATSM and FLT correlations coefficients. Standardized uptake value measures were also compared between pretreatment and midtreatment scans by use of paired t tests. Results: Spatial distributions of Cu-ATSM and FLT uptake were stable through midtreatment for both sarcomas and carcinomas: the population mean ± standard deviation in Spearman correlation coefficient was 0.88 ± 0.07 for Cu-ATSM and 0.79 ± 0.13 for FLT. The patients' Cu-ATSM correlation coefficients were significantly higher than their respective FLT correlation coefficients (P=.001). Changes in Cu-ATSM SUV measures from pretreatment to midtreatment were histology dependent: carcinomas experienced significant decreases in Cu-ATSM uptake (P<.05), whereas sarcomas did not (P>.20). Both histologies

Mapping Daily Evapotranspiration based on Spatiotemporal Fusion of ASTER and MODIS Images over Irrigated Agricultural Areas in the Heihe River Basin, Northwest China

Science.gov (United States)

Huang, C.; LI, Y.

2017-12-01

Continuous monitoring of daily evapotranspiration (ET) is crucial for allocating and managing water resources in irrigated agricultural areas in arid regions. In this study, continuous daily ET at a 90-m spatial resolution was estimated using the Surface Energy Balance System (SEBS) by fusing Moderate Resolution Imaging Spectroradiometer (MODIS) images with high temporal resolution and Advanced Space-borne Thermal Emission Reflectance Radiometer (ASTER) images with high spatial resolution. The spatiotemporal characteristics of these sensors were obtained using the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM). The performance of this approach was validated over a heterogeneous oasis-desert region covered by cropland, residential, woodland, water, Gobi desert, sandy desert, desert steppe, and wetland areas using in situ observations from automatic meteorological systems (AMS) and eddy covariance (EC) systems in the middle reaches of the Heihe River Basin in Northwest China. The error introduced during the data fusion process based on STARFM is within an acceptable range for predicted LST at a 90-m spatial resolution. The surface energy fluxes estimated using SEBS based on predicted remotely sensed data that combined the spatiotemporal characteristics of MODIS and ASTER agree well with the surface energy fluxes observed using EC systems for all land cover types, especially for vegetated area with MAP values range from 9% to 15%, which are less than the uncertainty (18%) of the observed in this study area. Time series of daily ET modelled from SEBS were compared to that modelled from PT-JPL (one of Satellite-based Priestley-Taylor ET model) and observations from EC systems. SEBS performed generally better than PT-JPL for vegetated area, especially irrigated cropland with bias, RMSE, and MAP values of 0.29 mm/d, 0.75 mm/d, 13% at maize site, -0.33 mm/d, 0.81 mm/d, and 14% at vegetable sites.

Photon-number correlation for quantum enhanced imaging and sensing

Science.gov (United States)

Meda, A.; Losero, E.; Samantaray, N.; Scafirimuto, F.; Pradyumna, S.; Avella, A.; Ruo-Berchera, I.; Genovese, M.

2017-09-01

In this review we present the potentialities and the achievements of the use of non-classical photon-number correlations in twin-beam states for many applications, ranging from imaging to metrology. Photon-number correlations in the quantum regime are easily produced and are rather robust against unavoidable experimental losses, and noise in some cases, if compared to the entanglement, where losing one photon can completely compromise the state and its exploitable advantages. Here, we will focus on quantum enhanced protocols in which only phase-insensitive intensity measurements (photon-number counting) are performed, which allow probing the transmission/absorption properties of a system, leading, for example, to innovative target detection schemes in a strong background. In this framework, one of the advantages is that the sources experimentally available emit a wide number of pair-wise correlated modes, which can be intercepted and exploited separately, for example by many pixels of a camera, providing a parallelism, essential in several applications, such as wide-field sub-shot-noise imaging and quantum enhanced ghost imaging. Finally, non-classical correlation enables new possibilities in quantum radiometry, e.g. the possibility of absolute calibration of a spatial resolving detector from the on-off single-photon regime to the linear regime in the same setup.

Soil Moisture Retrieval and Spatiotemporal Pattern Analysis Using Sentinel-1 Data of Dahra, Senegal

Directory of Open Access Journals (Sweden)

Zhiqu Liu

2017-11-01

Full Text Available The spatiotemporal pattern of soil moisture is of great significance for the understanding of the water exchange between the land surface and the atmosphere. The two-satellite constellation of the Sentinel-1 mission provides C-band synthetic aperture radar (SAR observations with high spatial and temporal resolutions, which are suitable for soil moisture monitoring. In this paper, we aim to assess the capability of pattern analysis based on the soil moisture retrieved from Sentinel-1 time-series data of Dahra in Senegal. The look-up table (LUT method is used in the retrieval with the backscattering coefficients that are simulated by the advanced integrated equation Model (AIEM for the soil layer and the Michigan microwave canopy scattering (MIMICS model for the vegetation layer. The temporal trend of Sentinel-1A soil moisture is evaluated by the ground measurements from the site at Dahra, with an unbiased root-mean-squared deviation (ubRMSD of 0.053 m3/m3, a mean average deviation (MAD of 0.034 m3/m3, and an R value of 0.62. The spatial variation is also compared with the existing microwave products at a coarse scale, which confirms the reliability of the Sentinel-1A soil moisture. The spatiotemporal patterns are analyzed by empirical orthogonal functions (EOF, and the geophysical factors that are affecting soil moisture are discussed. The first four EOFs of soil moisture explain 77.2% of the variance in total and the primary EOF explains 66.2%, which shows the dominant pattern at the study site. Soil texture and the normalized difference vegetation index are more closely correlated with the primary pattern than the topography and temperature in the study area. The investigation confirms the potential for soil moisture retrieval and spatiotemporal pattern analysis using Sentinel-1 images.

Patient positioning method based on binary image correlation between two edge images for proton-beam radiation therapy

International Nuclear Information System (INIS)

Sawada, Akira; Yoda, Kiyoshi; Numano, Masumi; Futami, Yasuyuki; Yamashita, Haruo; Murayama, Shigeyuki; Tsugami, Hironobu

2005-01-01

A new technique based on normalized binary image correlation between two edge images has been proposed for positioning proton-beam radiotherapy patients. A Canny edge detector was used to extract two edge images from a reference x-ray image and a test x-ray image of a patient before positioning. While translating and rotating the edged test image, the absolute value of the normalized binary image correlation between the two edge images is iteratively maximized. Each time before rotation, dilation is applied to the edged test image to avoid a steep reduction of the image correlation. To evaluate robustness of the proposed method, a simulation has been carried out using 240 simulated edged head front-view images extracted from a reference image by varying parameters of the Canny algorithm with a given range of rotation angles and translation amounts in x and y directions. It was shown that resulting registration errors have an accuracy of one pixel in x and y directions and zero degrees in rotation, even when the number of edge pixels significantly differs between the edged reference image and the edged simulation image. Subsequently, positioning experiments using several sets of head, lung, and hip data have been performed. We have observed that the differences of translation and rotation between manual positioning and the proposed method were within one pixel in translation and one degree in rotation. From the results of the validation study, it can be concluded that a significant reduction in workload for the physicians and technicians can be achieved with this method

Learning statistical correlation for fast prostate registration in image-guided radiotherapy

International Nuclear Information System (INIS)

Shi Yonghong; Liao Shu; Shen Dinggang

2011-01-01

Purpose: In adaptive radiation therapy of prostate cancer, fast and accurate registration between the planning image and treatment images of the patient is of essential importance. With the authors' recently developed deformable surface model, prostate boundaries in each treatment image can be rapidly segmented and their correspondences (or relative deformations) to the prostate boundaries in the planning image are also established automatically. However, the dense correspondences on the nonboundary regions, which are important especially for transforming the treatment plan designed in the planning image space to each treatment image space, are remained unresolved. This paper presents a novel approach to learn the statistical correlation between deformations of prostate boundary and nonboundary regions, for rapidly estimating deformations of the nonboundary regions when given the deformations of the prostate boundary at a new treatment image. Methods: The main contributions of the proposed method lie in the following aspects. First, the statistical deformation correlation will be learned from both current patient and other training patients, and further updated adaptively during the radiotherapy. Specifically, in the initial treatment stage when the number of treatment images collected from the current patient is small, the statistical deformation correlation is mainly learned from other training patients. As more treatment images are collected from the current patient, the patient-specific information will play a more important role in learning patient-specific statistical deformation correlation to effectively reflect prostate deformation of the current patient during the treatment. Eventually, only the patient-specific statistical deformation correlation is used to estimate dense correspondences when a sufficient number of treatment images have been acquired from the current patient. Second, the statistical deformation correlation will be learned by using a

Low-dose 4D cone-beam CT via joint spatiotemporal regularization of tensor framelet and nonlocal total variation

Science.gov (United States)

Han, Hao; Gao, Hao; Xing, Lei

2017-08-01

Excessive radiation exposure is still a major concern in 4D cone-beam computed tomography (4D-CBCT) due to its prolonged scanning duration. Radiation dose can be effectively reduced by either under-sampling the x-ray projections or reducing the x-ray flux. However, 4D-CBCT reconstruction under such low-dose protocols is prone to image artifacts and noise. In this work, we propose a novel joint regularization-based iterative reconstruction method for low-dose 4D-CBCT. To tackle the under-sampling problem, we employ spatiotemporal tensor framelet (STF) regularization to take advantage of the spatiotemporal coherence of the patient anatomy in 4D images. To simultaneously suppress the image noise caused by photon starvation, we also incorporate spatiotemporal nonlocal total variation (SNTV) regularization to make use of the nonlocal self-recursiveness of anatomical structures in the spatial and temporal domains. Under the joint STF-SNTV regularization, the proposed iterative reconstruction approach is evaluated first using two digital phantoms and then using physical experiment data in the low-dose context of both under-sampled and noisy projections. Compared with existing approaches via either STF or SNTV regularization alone, the presented hybrid approach achieves improved image quality, and is particularly effective for the reconstruction of low-dose 4D-CBCT data that are not only sparse but noisy.

METHODS OF DISTANCE MEASUREMENT’S ACCURACY INCREASING BASED ON THE CORRELATION ANALYSIS OF STEREO IMAGES

Directory of Open Access Journals (Sweden)

V. L. Kozlov

2018-01-01

Full Text Available To solve the problem of increasing the accuracy of restoring a three-dimensional picture of space using two-dimensional digital images, it is necessary to use new effective techniques and algorithms for processing and correlation analysis of digital images. Actively developed tools that allow you to reduce the time costs for processing stereo images, improve the quality of the depth maps construction and automate their construction. The aim of the work is to investigate the possibilities of using various techniques for processing digital images to improve the measurements accuracy of the rangefinder based on the correlation analysis of the stereo image. The results of studies of the influence of color channel mixing techniques on the distance measurements accuracy for various functions realizing correlation processing of images are presented. Studies on the analysis of the possibility of using integral representation of images to reduce the time cost in constructing a depth map areproposed. The results of studies of the possibility of using images prefiltration before correlation processing when distance measuring by stereo imaging areproposed.It is obtained that using of uniform mixing of channels leads to minimization of the total number of measurement errors, and using of brightness extraction according to the sRGB standard leads to an increase of errors number for all of the considered correlation processing techniques. Integral representation of the image makes it possible to accelerate the correlation processing, but this method is useful for depth map calculating in images no more than 0.5 megapixels. Using of image filtration before correlation processing can provide, depending on the filter parameters, either an increasing of the correlation function value, which is useful for analyzing noisy images, or compression of the correlation function.

Simulating Optical Correlation on a Digital Image Processing

Science.gov (United States)

Denning, Bryan

1998-04-01

Optical Correlation is a useful tool for recognizing objects in video scenes. In this paper, we explore the characteristics of a composite filter known as the equal correlation peak synthetic discriminant function (ECP SDF). Although the ECP SDF is commonly used in coherent optical correlation systems, the authors simulated the operation of a correlator using an EPIX frame grabber/image processor board to complete this work. Issues pertaining to simulating correlation using an EPIX board will be discussed. Additionally, the ability of the ECP SDF to detect objects that have been subjected to inplane rotation and small scale changes will be addressed by correlating filters against true-class objects placed randomly within a scene. To test the robustness of the filters, the results of correlating the filter against false-class objects that closely resemble the true class will also be presented.

Monitoring and identification of spatiotemporal landscape changes in multiple remote sensing images by using a stratified conditional Latin hypercube sampling approach and geostatistical simulation.

Science.gov (United States)

Lin, Yu-Pin; Chu, Hone-Jay; Huang, Yu-Long; Tang, Chia-Hsi; Rouhani, Shahrokh

2011-06-01

This study develops a stratified conditional Latin hypercube sampling (scLHS) approach for multiple, remotely sensed, normalized difference vegetation index (NDVI) images. The objective is to sample, monitor, and delineate spatiotemporal landscape changes, including spatial heterogeneity and variability, in a given area. The scLHS approach, which is based on the variance quadtree technique (VQT) and the conditional Latin hypercube sampling (cLHS) method, selects samples in order to delineate landscape changes from multiple NDVI images. The images are then mapped for calibration and validation by using sequential Gaussian simulation (SGS) with the scLHS selected samples. Spatial statistical results indicate that in terms of their statistical distribution, spatial distribution, and spatial variation, the statistics and variograms of the scLHS samples resemble those of multiple NDVI images more closely than those of cLHS and VQT samples. Moreover, the accuracy of simulated NDVI images based on SGS with scLHS samples is significantly better than that of simulated NDVI images based on SGS with cLHS samples and VQT samples, respectively. However, the proposed approach efficiently monitors the spatial characteristics of landscape changes, including the statistics, spatial variability, and heterogeneity of NDVI images. In addition, SGS with the scLHS samples effectively reproduces spatial patterns and landscape changes in multiple NDVI images.

Bayesian spatio-temporal modeling of Schistosoma japonicum prevalence data in the absence of a diagnostic 'gold' standard.

Directory of Open Access Journals (Sweden)

Xian-Hong Wang

Full Text Available BACKGROUND: Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. METHODOLOGY/PRINCIPAL FINDINGS: We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA, from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People's Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the 'true' prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. CONCLUSION/SIGNIFICANCE: Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken

Spatiotemporal optical solitons

International Nuclear Information System (INIS)

Malomed, Boris A; Mihalache, Dumitru; Wise, Frank; Torner, Lluis

2005-01-01

In the course of the past several years, a new level of understanding has been achieved about conditions for the existence, stability, and generation of spatiotemporal optical solitons, which are nondiffracting and nondispersing wavepackets propagating in nonlinear optical media. Experimentally, effectively two-dimensional (2D) spatiotemporal solitons that overcome diffraction in one transverse spatial dimension have been created in quadratic nonlinear media. With regard to the theory, fundamentally new features of light pulses that self-trap in one or two transverse spatial dimensions and do not spread out in time, when propagating in various optical media, were thoroughly investigated in models with various nonlinearities. Stable vorticity-carrying spatiotemporal solitons have been predicted too, in media with competing nonlinearities (quadratic-cubic or cubic-quintic). This article offers an up-to-date survey of experimental and theoretical results in this field. Both achievements and outstanding difficulties are reviewed, and open problems are highlighted. Also briefly described are recent predictions for stable 2D and 3D solitons in Bose-Einstein condensates supported by full or low-dimensional optical lattices. (review article)

Spatio-Temporal Data Exchange Standards

DEFF Research Database (Denmark)

Jensen, Christian Søndergaard; Schmidt, Albrecht

2003-01-01

We believe that research that concerns aspects of spatio-temporal data management may benefit from taking into account the various standards for spatio-temporal data formats. For example, this may contribute to rendering prototype software “open” and more readily useful. This paper thus identifies...... and briefly surveys standardization in relation to primarily the exchange and integration of spatio-temporal data. An overview of several data exchange languages is offered, along with reviews their potential for facilitating the collection of test data and the leveraging of prototypes. The standards, most...... of which are XML-based, lend themselves to the integration of prototypes into middleware architectures, e.g., as Web services....

Spatio-Temporal Video Segmentation with Shape Growth or Shrinkage Constraint

Science.gov (United States)

Tarabalka, Yuliya; Charpiat, Guillaume; Brucker, Ludovic; Menze, Bjoern H.

2014-01-01

We propose a new method for joint segmentation of monotonously growing or shrinking shapes in a time sequence of noisy images. The task of segmenting the image time series is expressed as an optimization problem using the spatio-temporal graph of pixels, in which we are able to impose the constraint of shape growth or of shrinkage by introducing monodirectional infinite links connecting pixels at the same spatial locations in successive image frames. The globally optimal solution is computed with a graph cut. The performance of the proposed method is validated on three applications: segmentation of melting sea ice floes and of growing burned areas from time series of 2D satellite images, and segmentation of a growing brain tumor from sequences of 3D medical scans. In the latter application, we impose an additional intersequences inclusion constraint by adding directed infinite links between pixels of dependent image structures.

Enhanced spatio-temporal alignment of plantar pressure image sequences using B-splines.

Science.gov (United States)

Oliveira, Francisco P M; Tavares, João Manuel R S

2013-03-01

This article presents an enhanced methodology to align plantar pressure image sequences simultaneously in time and space. The temporal alignment of the sequences is accomplished using B-splines in the time modeling, and the spatial alignment can be attained using several geometric transformation models. The methodology was tested on a dataset of 156 real plantar pressure image sequences (3 sequences for each foot of the 26 subjects) that was acquired using a common commercial plate during barefoot walking. In the alignment of image sequences that were synthetically deformed both in time and space, an outstanding accuracy was achieved with the cubic B-splines. This accuracy was significantly better (p align real image sequences with unknown transformation involved, the alignment based on cubic B-splines also achieved superior results than our previous methodology (p alignment on the dynamic center of pressure (COP) displacement was also assessed by computing the intraclass correlation coefficients (ICC) before and after the temporal alignment of the three image sequence trials of each foot of the associated subject at six time instants. The results showed that, generally, the ICCs related to the medio-lateral COP displacement were greater when the sequences were temporally aligned than the ICCs of the original sequences. Based on the experimental findings, one can conclude that the cubic B-splines are a remarkable solution for the temporal alignment of plantar pressure image sequences. These findings also show that the temporal alignment can increase the consistency of the COP displacement on related acquired plantar pressure image sequences.

Spatiotemporal throughfall patterns beneath an urban tree row

Science.gov (United States)

Bogeholz, P.; Van Stan, J. T., II; Hildebrandt, A.; Friesen, J.; Dibble, M.; Norman, Z.

2016-12-01

Much recent research has focused on throughfall patterns in natural forests as they can influence the heterogeneity of surface ecohydrological and biogeochemical processes. However, to the knowledge of the authors, no work has assessed how urban forest structures affect the spatiotemporal variability of throughfall water flux. Urbanization greatly alters not only a significant portion of the land surface, but canopy structure, with the most typical urban forest configuration being landscaped tree rows along streets, swales, parking lot medians, etc. This study examines throughfall spatiotemporal patterns for a landscaped tree row of Pinus elliottii (Engelm., slash pine) on Georgia Southern University's campus (southeastern, USA) using 150 individual observations per storm. Throughfall correlation lengths beneath this tree row were similar to, but appeared to be more stable across storm size than, observations in past studies on natural forests. Individual tree overlap and the planting interval also may more strongly drive throughfall patterns in tree rows. Meteorological influences beyond storm magnitude (intensity, intermittency, wind conditions, and atmospheric moisture demand) are also examined.

Correlation and image compression for limited-bandwidth CCD.

Energy Technology Data Exchange (ETDEWEB)

Thompson, Douglas G.

2005-07-01

As radars move to Unmanned Aerial Vehicles with limited-bandwidth data downlinks, the amount of data stored and transmitted with each image becomes more significant. This document gives the results of a study to determine the effect of lossy compression in the image magnitude and phase on Coherent Change Detection (CCD). We examine 44 lossy compression types, plus lossless zlib compression, and test each compression method with over 600 CCD image pairs. We also derive theoretical predictions for the correlation for most of these compression schemes, which compare favorably with the experimental results. We recommend image transmission formats for limited-bandwidth programs having various requirements for CCD, including programs which cannot allow performance degradation and those which have stricter bandwidth requirements at the expense of CCD performance.

Correlation of sequential MR imaging of the injured spinal cord with prognosis

International Nuclear Information System (INIS)

Takahashi, Mutsumasa; Izunaga, Hiroshi; Sato, Ryuichiro; Shinzato, Jintetsu; Korogi, Yukunori; Yamashita, Yasuyuki; Sakae, Terumi

1993-01-01

Forty-nine patients with acute spinal cord injuries were studied sequentially with MR imaging by using 0.5 Tesla superconductive units, and sequential MR changes were correlated with the prognosis of the patients. MR images were obtained within one week of the injury and then every two to six months when possible. The Frankel classification of neurologic function was correlated with MR findings. The most frequently observed types of signal intensity patterns on MR imaging were type 0 (isointensity on both T 1 - and T 2 -weighted images) and type I (isointensity on T 1 - and hyperintensity on T 2 -weighted images). In subsequent subacute and chronic stages, type II (hypointensity on T 1 and hyperintensity on T 2 ) was most frequently observed. The evolution of type 0 was to types I and II, whereas type I usually turned into type II or remained as type I. Type III (hyperintensity on T 1 and hyper-, iso- or hypointensity on T 2 images) patients were few in number. There was a good correlation between MR imaging patterns and neurologic recovery for initial and subsequent MR patterns, in that type 0 showed good recovery, whereas types I and II revealed good improvement or no recovery. In addition, the extent of the high signal intensity area on initial as well as on subsequent T 2 -weighted images was proportionally correlated to neurologic recovery. The degree of cord compression was also important for predicting recovery of neurologic function. Findings of MR imaging of acutely injured spinal cord suggested the prognosis of spinal cord injury, especially when sequential studies were obtained. (author)

Gastrointestinal stromal tumours: Correlation of modified NIH risk stratification with diffusion-weighted MR imaging as an imaging biomarker

International Nuclear Information System (INIS)

Kang, Tae Wook; Kim, Seong Hyun; Jang, Kyung Mi; Choi, Dongil; Ha, Sang Yun; Kim, Kyoung-Mee; Kang, Won Ki; Kim, Min Ji

2015-01-01

Highlights: • Except size and necrosis, conventional MR findings of GISTs were not significantly different according to the modified NIH criteria. • The ADC values of GISTs were negatively correlated with the modified NIH criteria. • The ADC value can be helpful for the determination of intermediate or high-risk GISTs. - Abstract: Purpose: To evaluate the correlation of risk grade of gastrointestinal stromal tumours (GISTs) based on modified National Institutes of Health (NIH) criteria with conventional magnetic resonance (MR) imaging and diffusion-weighted (DW) imaging. Methods: We included 22 patients with histopathologically proven GISTs in the stomach or small bowel who underwent pre-operative gadoxetic acid-enhanced MR imaging and DW imaging. We retrospectively assessed correlations between morphologic findings, qualitative (signal intensity, consensus from two observers) and quantitative (degree of dynamic enhancement using signal intensity of tumour/muscle ratio and apparent diffusion coefficient [ADC]) values, and the modified NIH criteria for risk stratification. Spearman partial correlation analysis was used to control for tumour size as a confounding factor. The optimal cut-off level of ADC values for intermediate or high risk GISTs was analyzed using a receiver operating characteristic analysis. Results: Except tumour size and necrosis, conventional MR imaging findings, including the degree of dynamic enhancement, were not significantly different according to the modified NIH criteria (p > 0.05). Tumour ADC values were negatively correlated with the modified NIH criteria, before and after adjustment of tumour size (ρ = −0.754; p < 0.001 and ρ = −0.513; p = 0.017, respectively). The optimal cut-off value for the determination of intermediate or high-risk GISTs was 1.279 × 10 −3 mm 2 /s (100% sensitivity, 69.2% specificity, 81.8% accuracy). Conclusion: Except tumour size and necrosis, conventional MR imaging findings did not correlate with

Gastrointestinal stromal tumours: Correlation of modified NIH risk stratification with diffusion-weighted MR imaging as an imaging biomarker

Energy Technology Data Exchange (ETDEWEB)

Kang, Tae Wook [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kim, Seong Hyun, E-mail: kshyun@skku.edu [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Jang, Kyung Mi; Choi, Dongil [Department of Radiology and Center for Imaging Science, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Ha, Sang Yun; Kim, Kyoung-Mee [Department of Pathology, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kang, Won Ki [Division of Oncology, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul 135-710 (Korea, Republic of); Kim, Min Ji [Biostatics Unit, Samsung Biomedical Research Institute, Samsung Medical Center, Seoul 135-710 (Korea, Republic of)

2015-01-15

Highlights: • Except size and necrosis, conventional MR findings of GISTs were not significantly different according to the modified NIH criteria. • The ADC values of GISTs were negatively correlated with the modified NIH criteria. • The ADC value can be helpful for the determination of intermediate or high-risk GISTs. - Abstract: Purpose: To evaluate the correlation of risk grade of gastrointestinal stromal tumours (GISTs) based on modified National Institutes of Health (NIH) criteria with conventional magnetic resonance (MR) imaging and diffusion-weighted (DW) imaging. Methods: We included 22 patients with histopathologically proven GISTs in the stomach or small bowel who underwent pre-operative gadoxetic acid-enhanced MR imaging and DW imaging. We retrospectively assessed correlations between morphologic findings, qualitative (signal intensity, consensus from two observers) and quantitative (degree of dynamic enhancement using signal intensity of tumour/muscle ratio and apparent diffusion coefficient [ADC]) values, and the modified NIH criteria for risk stratification. Spearman partial correlation analysis was used to control for tumour size as a confounding factor. The optimal cut-off level of ADC values for intermediate or high risk GISTs was analyzed using a receiver operating characteristic analysis. Results: Except tumour size and necrosis, conventional MR imaging findings, including the degree of dynamic enhancement, were not significantly different according to the modified NIH criteria (p > 0.05). Tumour ADC values were negatively correlated with the modified NIH criteria, before and after adjustment of tumour size (ρ = −0.754; p < 0.001 and ρ = −0.513; p = 0.017, respectively). The optimal cut-off value for the determination of intermediate or high-risk GISTs was 1.279 × 10{sup −3} mm{sup 2}/s (100% sensitivity, 69.2% specificity, 81.8% accuracy). Conclusion: Except tumour size and necrosis, conventional MR imaging findings did not

Imaging the square of the correlated two-electron wave function of a hydrogen molecule.

Science.gov (United States)

Waitz, M; Bello, R Y; Metz, D; Lower, J; Trinter, F; Schober, C; Keiling, M; Lenz, U; Pitzer, M; Mertens, K; Martins, M; Viefhaus, J; Klumpp, S; Weber, T; Schmidt, L Ph H; Williams, J B; Schöffler, M S; Serov, V V; Kheifets, A S; Argenti, L; Palacios, A; Martín, F; Jahnke, T; Dörner, R

2017-12-22

The toolbox for imaging molecules is well-equipped today. Some techniques visualize the geometrical structure, others the electron density or electron orbitals. Molecules are many-body systems for which the correlation between the constituents is decisive and the spatial and the momentum distribution of one electron depends on those of the other electrons and the nuclei. Such correlations have escaped direct observation by imaging techniques so far. Here, we implement an imaging scheme which visualizes correlations between electrons by coincident detection of the reaction fragments after high energy photofragmentation. With this technique, we examine the H 2 two-electron wave function in which electron-electron correlation beyond the mean-field level is prominent. We visualize the dependence of the wave function on the internuclear distance. High energy photoelectrons are shown to be a powerful tool for molecular imaging. Our study paves the way for future time resolved correlation imaging at FELs and laser based X-ray sources.

Spatiotemporal Features of the Three-Dimensional Architectural Landscape in Qingdao, China.

Directory of Open Access Journals (Sweden)

Peifeng Zhang

Full Text Available The evolution and development of the three-dimensional (3D architectural landscape is the basis of proper urban planning, eco-environment construction and the improvement of environmental quality. This paper presents the spatiotemporal characteristics of the 3D architectural landscape of the Shinan and Shibei districts in Qingdao, China, based on buildings' 3D information extracted from Quickbird images from 2003 to 2012, supported by Barista, landscape metrics and GIS. The results demonstrated that: (1 Shinan and Shibei districts expanded vertically and urban land use intensity increased noticeably from year to year. (2 Significant differences in the 3D architectural landscape existed among the western, central and eastern regions, and among the 26 sub-districts over the study period. The differentiation was consistent with the diverse development history, function and planning of the two districts. Finally, we found that population correlates positively with the variation in the 3D architectural landscape. This research provides an important reference for related studies, urban planning and eco-city construction.

Referential processing: reciprocity and correlates of naming and imaging.

Science.gov (United States)

Paivio, A; Clark, J M; Digdon, N; Bons, T

1989-03-01

To shed light on the referential processes that underlie mental translation between representations of objects and words, we studied the reciprocity and determinants of naming and imaging reaction times (RT). Ninety-six subjects pressed a key when they had covertly named 248 pictures or imaged to their names. Mean naming and imagery RTs for each item were correlated with one another, and with properties of names, images, and their interconnections suggested by prior research and dual coding theory. Imagery RTs correlated .56 (df = 246) with manual naming RTs and .58 with voicekey naming RTs from prior studies. A factor analysis of the RTs and of 31 item characteristics revealed 7 dimensions. Imagery and naming RTs loaded on a common referential factor that included variables related to both directions of processing (e.g., missing names and missing images). Naming RTs also loaded on a nonverbal-to-verbal factor that included such variables as number of different names, whereas imagery RTs loaded on a verbal-to-nonverbal factor that included such variables as rated consistency of imagery. The other factors were verbal familiarity, verbal complexity, nonverbal familiarity, and nonverbal complexity. The findings confirm the reciprocity of imaging and naming, and their relation to constructs associated with distinct phases of referential processing.

Coalescence measurements for evolving foams monitored by real-time projection imaging

International Nuclear Information System (INIS)

Myagotin, A; Helfen, L; Baumbach, T

2009-01-01

Real-time radiographic projection imaging together with novel spatio-temporal image analysis is presented to be a powerful technique for the quantitative analysis of coalescence processes accompanying the generation and temporal evolution of foams and emulsions. Coalescence events can be identified as discontinuities in a spatio-temporal image representing a sequence of projection images. Detection, identification of intensity and localization of the discontinuities exploit a violation criterion of the Fourier shift theorem and are based on recursive spatio-temporal image partitioning. The proposed method is suited for automated measurements of discontinuity rates (i.e., discontinuity intensity per unit time), so that large series of radiographs can be analyzed without user intervention. The application potential is demonstrated by the quantification of coalescence during the formation and decay of metal foams monitored by real-time x-ray radiography

Mechanical assessment of bovine pericardium using Müeller matrix imaging, enhanced backscattering and digital image correlation analysis.

Science.gov (United States)

Cuando-Espitia, Natanael; Sánchez-Arévalo, Francisco; Hernández-Cordero, Juan

2015-08-01

Mechanical characterization of tissue is an important but complex task. We demonstrate the simultaneous use of Mueller matrix imaging (MMI), enhanced backscattering (EBS) and digital image correlation (DIC) in a bovine pericardium (BP) tensile test. The interest in BP relies on its wide use as valve replacement and biological patch. We show that the mean free path (MFP), obtained through EBS measurements, can be used as an indicator of the anisotropy of the fiber ensemble. Our results further show a good correlation between retardance images and displacement vector fields, which are intrinsically related with the fiber interaction within the tissue.

From fast fluorescence imaging to molecular diffusion law on live cell membranes in a commercial microscope.

Science.gov (United States)

Di Rienzo, Carmine; Gratton, Enrico; Beltram, Fabio; Cardarelli, Francesco

2014-10-09

It has become increasingly evident that the spatial distribution and the motion of membrane components like lipids and proteins are key factors in the regulation of many cellular functions. However, due to the fast dynamics and the tiny structures involved, a very high spatio-temporal resolution is required to catch the real behavior of molecules. Here we present the experimental protocol for studying the dynamics of fluorescently-labeled plasma-membrane proteins and lipids in live cells with high spatiotemporal resolution. Notably, this approach doesn't need to track each molecule, but it calculates population behavior using all molecules in a given region of the membrane. The starting point is a fast imaging of a given region on the membrane. Afterwards, a complete spatio-temporal autocorrelation function is calculated correlating acquired images at increasing time delays, for example each 2, 3, n repetitions. It is possible to demonstrate that the width of the peak of the spatial autocorrelation function increases at increasing time delay as a function of particle movement due to diffusion. Therefore, fitting of the series of autocorrelation functions enables to extract the actual protein mean square displacement from imaging (iMSD), here presented in the form of apparent diffusivity vs average displacement. This yields a quantitative view of the average dynamics of single molecules with nanometer accuracy. By using a GFP-tagged variant of the Transferrin Receptor (TfR) and an ATTO488 labeled 1-palmitoyl-2-hydroxy-sn-glycero-3-phosphoethanolamine (PPE) it is possible to observe the spatiotemporal regulation of protein and lipid diffusion on µm-sized membrane regions in the micro-to-milli-second time range.

Adaptive Microwave Staring Correlated Imaging for Targets Appearing in Discrete Clusters.

Science.gov (United States)

Tian, Chao; Jiang, Zheng; Chen, Weidong; Wang, Dongjin

2017-10-21

Microwave staring correlated imaging (MSCI) can achieve ultra-high resolution in real aperture staring radar imaging using the correlated imaging process (CIP) under all-weather and all-day circumstances. The CIP must combine the received echo signal with the temporal-spatial stochastic radiation field. However, a precondition of the CIP is that the continuous imaging region must be discretized to a fine grid, and the measurement matrix should be accurately computed, which makes the imaging process highly complex when the MSCI system observes a wide area. This paper proposes an adaptive imaging approach for the targets in discrete clusters to reduce the complexity of the CIP. The approach is divided into two main stages. First, as discrete clustered targets are distributed in different range strips in the imaging region, the transmitters of the MSCI emit narrow-pulse waveforms to separate the echoes of the targets in different strips in the time domain; using spectral entropy, a modified method robust against noise is put forward to detect the echoes of the discrete clustered targets, based on which the strips with targets can be adaptively located. Second, in a strip with targets, the matched filter reconstruction algorithm is used to locate the regions with targets, and only the regions of interest are discretized to a fine grid; sparse recovery is used, and the band exclusion is used to maintain the non-correlation of the dictionary. Simulation results are presented to demonstrate that the proposed approach can accurately and adaptively locate the regions with targets and obtain high-quality reconstructed images.

A dense camera network for cropland (CropInsight) - developing high spatiotemporal resolution crop Leaf Area Index (LAI) maps through network images and novel satellite data

Science.gov (United States)

Kimm, H.; Guan, K.; Luo, Y.; Peng, J.; Mascaro, J.; Peng, B.

2017-12-01

Monitoring crop growth conditions is of primary interest to crop yield forecasting, food production assessment, and risk management of individual farmers and agribusiness. Despite its importance, there are limited access to field level crop growth/condition information in the public domain. This scarcity of ground truth data also hampers the use of satellite remote sensing for crop monitoring due to the lack of validation. Here, we introduce a new camera network (CropInsight) to monitor crop phenology, growth, and conditions that are designed for the US Corn Belt landscape. Specifically, this network currently includes 40 sites (20 corn and 20 soybean fields) across southern half of the Champaign County, IL ( 800 km2). Its wide distribution and automatic operation enable the network to capture spatiotemporal variations of crop growth condition continuously at the regional scale. At each site, low-maintenance, and high-resolution RGB digital cameras are set up having a downward view from 4.5 m height to take continuous images. In this study, we will use these images and novel satellite data to construct daily LAI map of the Champaign County at 30 m spatial resolution. First, we will estimate LAI from the camera images and evaluate it using the LAI data collected from LAI-2200 (LI-COR, Lincoln, NE). Second, we will develop relationships between the camera-based LAI estimation and vegetation indices derived from a newly developed MODIS-Landsat fusion product (daily, 30 m resolution, RGB + NIR + SWIR bands) and the Planet Lab's high-resolution satellite data (daily, 5 meter, RGB). Finally, we will scale up the above relationships to generate high spatiotemporal resolution crop LAI map for the whole Champaign County. The proposed work has potentials to expand to other agro-ecosystems and to the broader US Corn Belt.

Validation of a raw data-based synchronization signal (kymogram) for phase-correlated cardiac image reconstruction

International Nuclear Information System (INIS)

Ertel, Dirk; Kachelriess, Marc; Kalender, Willi A.; Pflederer, Tobias; Achenbach, Stephan; Steffen, Peter

2008-01-01

Phase-correlated reconstruction is commonly used in computed tomography (CT)-based cardiac imaging. Alternatively to the commonly used ECG, the raw data-based kymogram function can be used as a synchronization signal. We used raw data of 100 consecutive patient exams to compare the performance of kymogram function to the ECG signal. For objective validation the correlation of the ECG and the kymogram was assessed. Additionally, we performed a double-blinded comparison of ECG-based and kymogram-based phase-correlated images. The two synchronization signals showed good correlation indicated by a mean difference in the detected heart rate of negligible 0.2 bpm. The mean image quality score was 2.0 points for kymogram-correlated images and 2.3 points for ECG-correlated images, respectively (3: best; 0: worst). The kymogram and the ECG provided images adequate for diagnosis for 93 and 97 patients, respectively. For 50% of the datasets the kymogram provided an equivalent or even higher image quality compared with the ECG signal. We conclude that an acceptable image quality can be assured in most cases by the kymogram. Improvements of image quality by the kymogram function were observed in a noticeable number of cases. The kymogram can serve as a backup solution when an ECG is not available or lacking in quality. (orig.)

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging.

Science.gov (United States)

Xu, Xiao Quan; Choi, Young Jun; Sung, Yu Sub; Yoon, Ra Gyoung; Jang, Seung Won; Park, Ji Eun; Heo, Young Jin; Baek, Jung Hwan; Lee, Jeong Hyun

2016-01-01

To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D(*)), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D(*) and model-free parameters from the DCE-MRI (wash-in, Tmax, Emax, initial AUC60, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis. No correlation was found between f or D(*) and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D(*) (p > 0.05, respectively). Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.

Observations of a Cold Front at High Spatiotemporal Resolution Using an X-Band Phased Array Imaging Radar

Directory of Open Access Journals (Sweden)

Andrew Mahre

2017-02-01

Full Text Available While the vertical structure of cold fronts has been studied using various methods, previous research has shown that traditional methods of observing meteorological phenomena (such as pencil-beam radars in PPI/volumetric mode are not well-suited for resolving small-scale cold front phenomena, due to relatively low spatiotemporal resolution. Additionally, non-simultaneous elevation sampling within a vertical cross-section can lead to errors in analysis, as differential vertical advection cannot be distinguished from temporal evolution. In this study, a cold front from 19 September 2015 is analyzed using the Atmospheric Imaging Radar (AIR. The AIR transmits a 20-degree fan beam in elevation, and digital beamforming is used on receive to generate simultaneous receive beams. This mobile, X-band, phased-array radar offers temporal sampling on the order of 1 s (while in RHI mode, range sampling of 30 m (37.5 m native resolution, and continuous, arbitrarily oversampled data in the vertical dimension. Here, 0.5-degree sampling is used in elevation (1-degree native resolution. This study is the first in which a cold front has been studied via imaging radar. The ability of the AIR to obtain simultaneous RHIs at high temporal sampling rates without mechanical steering allows for analysis of features such as Kelvin-Helmholtz instabilities and feeder flow.

Integrated global digital image correlation for interface delamination characterization

KAUST Repository

Hoefnagels, Johan P.M.

2013-07-23

Interfacial delamination is a key reliability challenge in composites and micro-electronic systems due to (high-density) integration of dissimilar materials. Predictive finite element models are used to minimize delamination failures during design, but require accurate interface models to capture (irreversible) crack initiation and propagation behavior observed in experiments. Therefore, an Integrated Global Digital Image Correlation (I-GDIC) strategy is developed for accurate determination of mechanical interface behavior from in-situ delamination experiments. Recently, a novel miniature delamination setup was presented that enables in-situ microscopic characterization of interface delamination while sensitively measuring global load-displacement curves for all mode mixities. Nevertheless, extraction of detailed mechanical interface behavior from measured images is challenging, because deformations are tiny and measurement noise large. Therefore, an advanced I-GDIC methodology is developed which correlates the image patterns by only deforming the images using kinematically-admissible \\'eigenmodes\\' that correspond to the few parameters controlling the interface tractions in an analytic description of the crack tip deformation field, thereby greatly enhancing accuracy and robustness. This method is validated on virtual delamination experiments, simulated using a recently developed self-adaptive cohesive zone (CZ) finite element framework. © The Society for Experimental Mechanics, Inc. 2014.

A Tentative Application Of Morphological Filters To Time-Varying Images

Science.gov (United States)

Billard, D.; Poquillon, B.

1989-03-01

In this paper, morphological filters, which are commonly used to process either 2D or multidimensional static images, are generalized to the analysis of time-varying image sequence. The introduction of the time dimension induces then interesting prop-erties when designing such spatio-temporal morphological filters. In particular, the specification of spatio-temporal structuring ele-ments (equivalent to time-varying spatial structuring elements) can be adjusted according to the temporal variations of the image sequences to be processed : this allows to derive specific morphological transforms to perform noise filtering or moving objects discrimination on dynamic images viewed by a non-stationary sensor. First, a brief introduction to the basic principles underlying morphological filters will be given. Then, a straightforward gener-alization of these principles to time-varying images will be pro-posed. This will lead us to define spatio-temporal opening and closing and to introduce some of their possible applications to process dynamic images. At last, preliminary results obtained us-ing a natural forward looking infrared (FUR) image sequence are presented.

Estimating spatio-temporal dynamics of size-structured populations

DEFF Research Database (Denmark)

Kristensen, Kasper; Thygesen, Uffe Høgsbro; Andersen, Ken Haste

2014-01-01

with simple stock dynamics, to estimate simultaneously how size distributions and spatial distributions develop in time. We demonstrate the method for a cod population sampled by trawl surveys. Particular attention is paid to correlation between size classes within each trawl haul due to clustering...... of individuals with similar size. The model estimates growth, mortality and reproduction, after which any aspect of size-structure, spatio-temporal population dynamics, as well as the sampling process can be probed. This is illustrated by two applications: 1) tracking the spatial movements of a single cohort...

Spatio-Temporal Multiway Data Decomposition Using Principal Tensor Analysis on k-Modes: The R Package PTAk

Directory of Open Access Journals (Sweden)

Didier G. Leibovici

2010-10-01

Full Text Available The purpose of this paper is to describe the R package {PTAk and how the spatio-temporal context can be taken into account in the analyses. Essentially PTAk( is a multiway multidimensional method to decompose a multi-entries data-array, seen mathematically as a tensor of any order. This PTAk-modes method proposes a way of generalizing SVD (singular value decomposition, as well as some other well known methods included in the R package, such as PARAFAC or CANDECOMP and the PCAn-modes or Tucker-n model. The example datasets cover different domains with various spatio-temporal characteristics and issues: (i~medical imaging in neuropsychology with a functional MRI (magnetic resonance imaging study, (ii~pharmaceutical research with a pharmacodynamic study with EEG (electro-encephaloegraphic data for a central nervous system (CNS drug, and (iii~geographical information system (GIS with a climatic dataset that characterizes arid and semi-arid variations. All the methods implemented in the R package PTAk also support non-identity metrics, as well as penalizations during the optimization process. As a result of these flexibilities, together with pre-processing facilities, PTAk constitutes a framework for devising extensions of multidimensional methods such ascorrespondence analysis, discriminant analysis, and multidimensional scaling, also enabling spatio-temporal constraints.

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

Directory of Open Access Journals (Sweden)

Meiyu Liang

2013-01-01

Full Text Available In order to improve the spatiotemporal resolution of the video sequences, a novel spatiotemporal super-resolution reconstruction model (STSR based on robust optical flow and Zernike moment is proposed in this paper, which integrates the spatial resolution reconstruction and temporal resolution reconstruction into a unified framework. The model does not rely on accurate estimation of subpixel motion and is robust to noise and rotation. Moreover, it can effectively overcome the problems of hole and block artifacts. First we propose an efficient robust optical flow motion estimation model based on motion details preserving, then we introduce the biweighted fusion strategy to implement the spatiotemporal motion compensation. Next, combining the self-adaptive region correlation judgment strategy, we construct a fast fuzzy registration scheme based on Zernike moment for better STSR with higher efficiency, and then the final video sequences with high spatiotemporal resolution can be obtained by fusion of the complementary and redundant information with nonlocal self-similarity between the adjacent video frames. Experimental results demonstrate that the proposed method outperforms the existing methods in terms of both subjective visual and objective quantitative evaluations.

Real time implementation of the parametric imaging correlation algorithms

Energy Technology Data Exchange (ETDEWEB)

Bogorodski, Piotr; Wolek, Tomasz; Wasielewski, Jaroslaw; Piatkowski, Adam [Medical and Nuclear Electronics Division, Institute of Radioelectronics, Warsaw University of Technology, 00-665 Warsaw, Nowowiejska 15/19 (Poland)

1999-12-31

A novel method for functional image evaluation from image set obtained in contrast aided Ultrafast Computed Tomography and Magnetic Resonance Imaging will be presented. The method converts temporal set of images of first-pass transit of injected contrast, to a single parametric image. The main difference between proposed procedure and other widely accepted methods is fast, that our method applies correlation and discrimination analysis to each concentration-time curve, instead of fitting them to the given a priori tracer kinetics model. A stress will be put on execution speed (i.e. shortening of the time required to obtain a perfusion relevant image), and easiest user interface allowing the physician to utilize the system without any technical assistance. Both execution speed and user interface should satisfy requirements in the interventional procedures. (authors)

Development of digital image correlation method to analyse crack ...

Indian Academy of Sciences (India)

samples were performed to verify the performance of the digital image correlation method. ... development cannot be measured accurately. ..... Mendelson A 1983 Plasticity: Theory and application (USA: Krieger Publishing company Malabar,.

Diffusion tensor imaging correlates with lesion volume in cerebral hemisphere infarctions

International Nuclear Information System (INIS)

Rossi, Maija E; Jason, Eeva; Marchesotti, Silvia; Dastidar, Prasun; Ollikainen, Jyrki; Soimakallio, Seppo

2010-01-01

Both a large lesion volume and abnormalities in diffusion tensor imaging are independently associated with a poor prognosis after cerebral infarctions. Therefore, we assume that they are associated. This study assessed the associations between lesion volumes and diffusion tensor imaging in patients with a right-sided cerebral infarction. The lesion volumes of 33 patients (age 65.9 ± 8.7, 26 males and 7 females) were imaged using computed tomography (CT) in the acute phase (within 3-4 hours) and magnetic resonance imaging (MRI) in the chronic phase (follow-up at 12 months, with a range of 8-27 months). The chronic-phase fractional anisotropy (FA) and mean diffusivity (MD) values were measured at the site of the infarct and selected white matter tracts. Neurological tests in both the acute and chronic phases, and DTI lateralization were assessed with the Wilcoxon signed-rank test. The effects of thrombolytic therapy (n = 10) were assessed with the Mann-Whitney U test. The correlations between the measured parameters were analysed with Spearman's rho correlation. Bonferroni post-hoc correction was used to compensate for the familywise error rate in multiple comparisons. Several MD values in the right hemisphere correlated positively and FA values negatively with the lesion volumes. These correlations included both lesion area and healthy tissue. The results of the mini-mental state examination and the National Institutes of Health Stroke Scale also correlated with the lesion volume. A larger infarct volume is associated with more pronounced tissue modifications in the chronic stage as observed with the MD and FA alterations

Regulation of Spatiotemporal Patterns by Biological Variability: General Principles and Applications to Dictyostelium discoideum.

Directory of Open Access Journals (Sweden)

Miriam Grace

2015-11-01

Full Text Available Spatiotemporal patterns often emerge from local interactions in a self-organizing fashion. In biology, the resulting patterns are also subject to the influence of the systematic differences between the system's constituents (biological variability. This regulation of spatiotemporal patterns by biological variability is the topic of our review. We discuss several examples of correlations between cell properties and the self-organized spatiotemporal patterns, together with their relevance for biology. Our guiding, illustrative example will be spiral waves of cAMP in a colony of Dictyostelium discoideum cells. Analogous processes take place in diverse situations (such as cardiac tissue, where spiral waves occur in potentially fatal ventricular fibrillation so a deeper understanding of this additional layer of self-organized pattern formation would be beneficial to a wide range of applications. One of the most striking differences between pattern-forming systems in physics or chemistry and those in biology is the potential importance of variability. In the former, system components are essentially identical with random fluctuations determining the details of the self-organization process and the resulting patterns. In biology, due to variability, the properties of potentially very few cells can have a driving influence on the resulting asymptotic collective state of the colony. Variability is one means of implementing a few-element control on the collective mode. Regulatory architectures, parameters of signaling cascades, and properties of structure formation processes can be "reverse-engineered" from observed spatiotemporal patterns, as different types of regulation and forms of interactions between the constituents can lead to markedly different correlations. The power of this biology-inspired view of pattern formation lies in building a bridge between two scales: the patterns as a collective state of a very large number of cells on the one hand

Imaging pediatric magnet ingestion with surgical-pathological correlation.

Science.gov (United States)

Otjen, Jeffrey P; Rohrmann, Charles A; Iyer, Ramesh S

2013-07-01

Foreign body ingestion is a common problem in the pediatric population and a frequent cause for emergency room visits. Magnets are common household objects that when ingested can bring about severe, possibly fatal gastrointestinal complications. Radiography is an integral component of the management of these children. Pediatric and emergency radiologists alike must be aware of imaging manifestations of magnet ingestion, as their identification drives decision-making for consulting surgeons and gastroenterologists. Radiology can thus substantially augment the clinical history and physical exam, facilitating appropriate management. This manuscript sequentially presents cases of magnet ingestion featuring imaging findings coupled with surgical and pathological correlation. Each case is presented to highlight ways in which the radiologist can make impactful contributions to diagnosis and management. Clinical overview with pitfalls of magnet ingestion imaging and an imaging decision tree will also be presented.

Imaging pediatric magnet ingestion with surgical-pathological correlation

International Nuclear Information System (INIS)

Otjen, Jeffrey P.; Iyer, Ramesh S.; Rohrmann, Charles A.

2013-01-01

Foreign body ingestion is a common problem in the pediatric population and a frequent cause for emergency room visits. Magnets are common household objects that when ingested can bring about severe, possibly fatal gastrointestinal complications. Radiography is an integral component of the management of these children. Pediatric and emergency radiologists alike must be aware of imaging manifestations of magnet ingestion, as their identification drives decision-making for consulting surgeons and gastroenterologists. Radiology can thus substantially augment the clinical history and physical exam, facilitating appropriate management. This manuscript sequentially presents cases of magnet ingestion featuring imaging findings coupled with surgical and pathological correlation. Each case is presented to highlight ways in which the radiologist can make impactful contributions to diagnosis and management. Clinical overview with pitfalls of magnet ingestion imaging and an imaging decision tree will also be presented. (orig.)

Spatio-temporal Variability of Albedo and its Impact on Glacier Melt Modelling

Science.gov (United States)

Kinnard, C.; Mendoza, C.; Abermann, J.; Petlicki, M.; MacDonell, S.; Urrutia, R.

2017-12-01

Albedo is an important variable for the surface energy balance of glaciers, yet its representation within distributed glacier mass-balance models is often greatly simplified. Here we study the spatio-temporal evolution of albedo on Glacier Universidad, central Chile (34°S, 70°W), using time-lapse terrestrial photography, and investigate its effect on the shortwave radiation balance and modelled melt rates. A 12 megapixel digital single-lens reflex camera was setup overlooking the glacier and programmed to take three daily images of the glacier during a two-year period (2012-2014). One image was chosen for each day with no cloud shading on the glacier. The RAW images were projected onto a 10m resolution digital elevation model (DEM), using the IMGRAFT software (Messerli and Grinsted, 2015). A six-parameter camera model was calibrated using a single image and a set of 17 ground control points (GCPs), yielding a georeferencing accuracy of accounting for possible camera movement over time. The reflectance values from the projected image were corrected for topographic and atmospheric influences using a parametric solar irradiation model, following a modified algorithm based on Corripio (2004), and then converted to albedo using reference albedo measurements from an on-glacier automatic weather station (AWS). The image-based albedo was found to compare well with independent albedo observations from a second AWS in the glacier accumulation area. Analysis of the albedo maps showed that the albedo is more spatially-variable than the incoming solar radiation, making albedo a more important factor of energy balance spatial variability. The incorporation of albedo maps within an enhanced temperature index melt model revealed that the spatio-temporal variability of albedo is an important factor for the calculation of glacier-wide meltwater fluxes.

Spatiotemporal Distribution of β-Amyloid in Alzheimer Disease Is the Result of Heterogeneous Regional Carrying Capacities.

Science.gov (United States)

Whittington, Alex; Sharp, David J; Gunn, Roger N

2018-05-01

β-amyloid (Aβ) accumulation in the brain is 1 of 2 pathologic hallmarks of Alzheimer disease (AD), and the spatial distribution of Aβ has been studied extensively ex vivo. Methods: We applied mathematical modeling to Aβ in vivo PET imaging data to investigate competing theories of Aβ spread in AD. Results: Our results provided evidence that Aβ accumulation starts in all brain regions simultaneously and that its spatiotemporal distribution is due to heterogeneous regional carrying capacities (regional maximum possible concentration of Aβ) for the aggregated protein rather than to longer-term spreading from seed regions. Conclusion: The in vivo spatiotemporal distribution of Aβ in AD can be mathematically modeled using a logistic growth model in which the Aβ carrying capacity is heterogeneous across the brain but the exponential growth rate and time of half maximal Aβ concentration are constant. © 2018 by the Society of Nuclear Medicine and Molecular Imaging.

X-linked adrenoleukodystrophy: correlation between Loes score and diffusion tensor imaging parameters.

Science.gov (United States)

Ono, Sergio Eiji; de Carvalho Neto, Arnolfo; Gasparetto, Emerson Leandro; Coelho, Luiz Otávio de Mattos; Escuissato, Dante Luiz; Bonfim, Carmem Maria Sales; Ribeiro, Lisandro Lima

2014-01-01

The present study was aimed at evaluating the correlation between diffusion tensor imaging parameters and Loes score as well as whether those parameters could indicate early structural alterations. Diffusion tensor imaging measurements were obtained in 30 studies of 14 patients with X-linked adrenoleukodystrophy and were correlated with Loes scores. A control group including 28 male patients was created to establish agematched diffusion tensor imaging measurements. Inter- and intraobserver statistical analyses were undertaken. Diffusion tensor imaging measurements presented strong Pearson correlation coefficients (r) of -0.86, 0.89, 0.89 and 0.84 for fractional anisotropy and mean, radial and axial diffusivities (p tensor measurements at early stage of the disease indicates that mean and radial diffusivities might be useful to predict the disease progression. Measurements of diffusion tensor parameters can be used as an adjunct to the Loes score, aiding in the monitoring of the disease and alerting for possible Loes score progression in the range of interest for therapeutic decisions.

Hemorrhage in pituitary adenoma: correlation of MR imaging with operative findings

Energy Technology Data Exchange (ETDEWEB)

Kurihara, N.; Takahashi, S.; Higano, S.; Mugikura, S.; Singh, L.N.; Furuta, S.; Tamura, H.; Ishibashi, T.; Maruoka, S.; Yamada, S. [Department of Radiology, Tohoku University School of Medicine, Sendai (Japan); Ikeda, H. [Department of Neurosurgery, Tohoku University School of Medicine, Sendai (Japan)

1998-07-01

The aim of this study was to correlate MR imaging and operative findings of hemorrhage in pituitary macroadenomas. We retrospectively reviewed MR images of 113 surgically proven pituitary adenomas. All patients were examined on a 1.5-T MR system. The intensity of intratumoral cystic cavities was correlated with operative findings. In 15 patients with pituitary apoplexy, we determined relationship between interval of MR examination after apoplectic event and MR signal intensity. In 8 patients with repeated preoperative MR examination, we evaluated sequential changes of intratumoral hemorrhage. There were 54 cavities at surgery: 52 were hemorrhagic and 2 were nonhemorrhagic. Twenty-nine of 52 hemorrhagic cysts demonstrated high/low signal (H/L) fluid-fluid levels on T2-weighted image (T2WI). In 19 of them, two components could be separately seen at operation: the supernatant high-intensity area represented xanthochromic fluid, and the dependent low-intensity area represented liquefied hematoma. The H/L fluid-fluid level was observed predominantly in hematomas on MR images obtained after longer intervals. In patients with repeated MR examination, follow-up MR imaging revealed additional hemorrhage or new formation of fluid-fluid levels. It was surprising that 12 of 14 cysts preoperatively judged as nonhemorrhagic in fact contained hemorrhagic components. The preoperative MR images are well correlated to the operative findings in hemorrhagic pituitary macroadenomas. It proved that 52 of 54 cystic cavities had hemorrhagic component. (orig.) With 8 figs., 3 tabs., 17 refs.

Hemorrhage in pituitary adenoma: correlation of MR imaging with operative findings

International Nuclear Information System (INIS)

Kurihara, N.; Takahashi, S.; Higano, S.; Mugikura, S.; Singh, L.N.; Furuta, S.; Tamura, H.; Ishibashi, T.; Maruoka, S.; Yamada, S.; Ikeda, H.

1998-01-01

The aim of this study was to correlate MR imaging and operative findings of hemorrhage in pituitary macroadenomas. We retrospectively reviewed MR images of 113 surgically proven pituitary adenomas. All patients were examined on a 1.5-T MR system. The intensity of intratumoral cystic cavities was correlated with operative findings. In 15 patients with pituitary apoplexy, we determined relationship between interval of MR examination after apoplectic event and MR signal intensity. In 8 patients with repeated preoperative MR examination, we evaluated sequential changes of intratumoral hemorrhage. There were 54 cavities at surgery: 52 were hemorrhagic and 2 were nonhemorrhagic. Twenty-nine of 52 hemorrhagic cysts demonstrated high/low signal (H/L) fluid-fluid levels on T2-weighted image (T2WI). In 19 of them, two components could be separately seen at operation: the supernatant high-intensity area represented xanthochromic fluid, and the dependent low-intensity area represented liquefied hematoma. The H/L fluid-fluid level was observed predominantly in hematomas on MR images obtained after longer intervals. In patients with repeated MR examination, follow-up MR imaging revealed additional hemorrhage or new formation of fluid-fluid levels. It was surprising that 12 of 14 cysts preoperatively judged as nonhemorrhagic in fact contained hemorrhagic components. The preoperative MR images are well correlated to the operative findings in hemorrhagic pituitary macroadenomas. It proved that 52 of 54 cystic cavities had hemorrhagic component. (orig.)

A Flexible Spatio-Temporal Model for Air Pollution with Spatial and Spatio-Temporal Covariates

OpenAIRE

Lindström, Johan; Szpiro, Adam A; Sampson, Paul D; Oron, Assaf P; Richards, Mark; Larson, Tim V; Sheppard, Lianne

2013-01-01

The development of models that provide accurate spatio-temporal predictions of ambient air pollution at small spatial scales is of great importance for the assessment of potential health effects of air pollution. Here we present a spatio-temporal framework that predicts ambient air pollution by combining data from several different monitoring networks and deterministic air pollution model(s) with geographic information system (GIS) covariates. The model presented in this paper has been implem...

Spatiotemporal bioeconomic performance of artificial shelters in a small-scale, rights-based managed Caribbean spiny lobster (Panulirus argus fishery

Directory of Open Access Journals (Sweden)

Maren Headley

2017-03-01

Full Text Available This study presents a bioeconomic analysis of artificial shelter performance in a fishery targeting a spiny lobster meta-population, with spatially allocated, individual exclusive benthic property rights for shelter introduction and harvest of species. Insights into fishers’ short-run decisions and fishing strategies are also provided. Spatiotemporal bioeconomic performance of shelters located in ten fishing areas during four seasons was compared using two-way ANOVAs and Pearson correlations. Results show that there was spatiotemporal heterogeneity in bioeconomic variables among fishing areas, with mean catch per unit effort (CPUE, kg shelter–1 ranging from 0.42 kg to 1.3 kg per trip, mean quasi-profits of variable costs per shelter harvested ranging from USD6.00 to USD19.57 per trip, and mean quasi-profits of variable costs ranging from USD338 to USD1069 per trip. Positive moderate correlations between shelter density and CPUE (kg shelter–1 km–2 were found. Bioeconomic performance of the shelters was influenced by spatiotemporal resource abundance and distribution, fishing area location in relation to the port, shelter density, heterogeneous fishing strategies and the management system. The results provide empirical information on the spatiotemporal performance of shelters and fishing strategies and can contribute to management at the local-scale of a meta-population distributed throughout the Caribbean Sea and Gulf of Mexico.

Integrated global digital image correlation for interface delamination characterization

KAUST Repository

Hoefnagels, Johan P.M.; Blaysat, Benoî t; Lubineau, Gilles; Geers, Marc G D

2013-01-01

, but require accurate interface models to capture (irreversible) crack initiation and propagation behavior observed in experiments. Therefore, an Integrated Global Digital Image Correlation (I-GDIC) strategy is developed for accurate determination of mechanical

Spatio-temporal variability of ichthyophagous bird assemblage around western Mediterranean open-sea cage fish farms.

Science.gov (United States)

Aguado-Giménez, Felipe; Eguía-Martínez, Sergio; Cerezo-Valverde, Jesús; García-García, Benjamín

2018-06-14

Ichthyophagous birds aggregate at cage fish farms attracted by caged and associated wild fish. Spatio-temporal variability of such birds was studied for a year through seasonal visual counts at eight farms in the western Mediterranean. Correlation with farm and location descriptors was assessed. Considerable spatio-temporal variability in fish-eating bird density and assemblage structure was observed among farms and seasons. Bird density increased from autumn to winter, with the great cormorant being the most abundant species, also accounting largely for differences among farms. Grey heron and little egret were also numerous at certain farms during the coldest seasons. Cattle egret was only observed at one farm. No shags were observed during winter. During spring and summer, bird density decreased markedly and only shags and little egrets were observed at only a few farms. Season and distance from farms to bird breeding/wintering grounds helped to explain some of the spatio-temporal variability. Copyright © 2018 Elsevier Ltd. All rights reserved.

Salivary gland masses. Dynamic MR imaging and pathologic correlation

International Nuclear Information System (INIS)

Park, Jinho; Inoue, Shingo; Ishizuka, Yasuhito; Shindo, Hiroaki; Kawanishi, Masayuki; Kakizaki, Dai; Abe, Kimihiko; Ebihara, Yoshiro

1997-01-01

To evaluate the efficiency of dynamic contrast-enhanced magnetic resonance imaging (MRI) for the diagnosis of salivary gland masses. We retrospectively examined 19 salivary gland masses that were pathologically diagnosed by surgical operation or biopsy. We obtained T1- and T2-weighted images on MRI, performed dynamic studies on each mass and examined the correlation between enhancement patterns and pathological findings. Four enhancement patterns were recognized on contrast-enhanced MRI: type 1 showed marked, homogeneous enhancement; type 2 slights, homogeneous enhancement; type 3 marginal enhancement; and type 4 poor enhancement of the mass. Most pleomorphic adenomas had a type 1 enhancement pattern, but two had a type 2 pattern. Pathologically, each mass enhancement pattern had different tumor cell and matrix components. Warthin's tumor generally showed the type 4 pattern. Primary malignant tumors of the salivary gland all showed the type 3 pattern, and pathological specimens showed many tumor cells along the marginal portion of the tumor. One inflammatory cyst and one Warthin's tumor also showed the type 3 pattern. Except for metastatic renal cell carcinoma, the enhancement patterns of late phase images and dynamic study images were the same. Dynamic MRI added little diagnostic information about salivary gland masses, but the contrast-enhanced MR features correlated well with the pathological findings. (author)

Spatio-temporal reconstruction of air temperature maps and their application to estimate rice growing season heat accumulation using multi-temporal MODIS data.

Science.gov (United States)

Zhang, Li-wen; Huang, Jing-feng; Guo, Rui-fang; Li, Xin-xing; Sun, Wen-bo; Wang, Xiu-zhen

2013-02-01

The accumulation of thermal time usually represents the local heat resources to drive crop growth. Maps of temperature-based agro-meteorological indices are commonly generated by the spatial interpolation of data collected from meteorological stations with coarse geographic continuity. To solve the critical problems of estimating air temperature (T(a)) and filling in missing pixels due to cloudy and low-quality images in growing degree days (GDDs) calculation from remotely sensed data, a novel spatio-temporal algorithm for T(a) estimation from Terra and Aqua moderate resolution imaging spectroradiometer (MODIS) data was proposed. This is a preliminary study to calculate heat accumulation, expressed in accumulative growing degree days (AGDDs) above 10 °C, from reconstructed T(a) based on MODIS land surface temperature (LST) data. The verification results of maximum T(a), minimum T(a), GDD, and AGDD from MODIS-derived data to meteorological calculation were all satisfied with high correlations over 0.01 significant levels. Overall, MODIS-derived AGDD was slightly underestimated with almost 10% relative error. However, the feasibility of employing AGDD anomaly maps to characterize the 2001-2010 spatio-temporal variability of heat accumulation and estimating the 2011 heat accumulation distribution using only MODIS data was finally demonstrated in the current paper. Our study may supply a novel way to calculate AGDD in heat-related study concerning crop growth monitoring, agricultural climatic regionalization, and agro-meteorological disaster detection at the regional scale.

Cell Matrix Remodeling Ability Shown by Image Spatial Correlation

Science.gov (United States)

Chiu, Chi-Li; Digman, Michelle A.; Gratton, Enrico

2013-01-01

Extracellular matrix (ECM) remodeling is a critical step of many biological and pathological processes. However, most of the studies to date lack a quantitative method to measure ECM remodeling at a scale comparable to cell size. Here, we applied image spatial correlation to collagen second harmonic generation (SHG) images to quantitatively evaluate the degree of collagen remodeling by cells. We propose a simple statistical method based on spatial correlation functions to determine the size of high collagen density area around cells. We applied our method to measure collagen remodeling by two breast cancer cell lines (MDA-MB-231 and MCF-7), which display different degrees of invasiveness, and a fibroblast cell line (NIH/3T3). We found distinct collagen compaction levels of these three cell lines by applying the spatial correlation method, indicating different collagen remodeling ability. Furthermore, we quantitatively measured the effect of Latrunculin B and Marimastat on MDA-MB-231 cell line collagen remodeling ability and showed that significant collagen compaction level decreases with these treatments. PMID:23935614

Dynamic CT perfusion imaging of the myocardium: a technical note on improvement of image quality.

Directory of Open Access Journals (Sweden)

Daniela Muenzel

Full Text Available OBJECTIVE: To improve image and diagnostic quality in dynamic CT myocardial perfusion imaging (MPI by using motion compensation and a spatio-temporal filter. METHODS: Dynamic CT MPI was performed using a 256-slice multidetector computed tomography scanner (MDCT. Data from two different patients-with and without myocardial perfusion defects-were evaluated to illustrate potential improvements for MPI (institutional review board approved. Three datasets for each patient were generated: (i original data (ii motion compensated data and (iii motion compensated data with spatio-temporal filtering performed. In addition to the visual assessment of the tomographic slices, noise and contrast-to-noise-ratio (CNR were measured for all data. Perfusion analysis was performed using time-density curves with regions-of-interest (ROI placed in normal and hypoperfused myocardium. Precision in definition of normal and hypoperfused areas was determined in corresponding coloured perfusion maps. RESULTS: The use of motion compensation followed by spatio-temporal filtering resulted in better alignment of the cardiac volumes over time leading to a more consistent perfusion quantification and improved detection of the extend of perfusion defects. Additionally image noise was reduced by 78.5%, with CNR improvements by a factor of 4.7. The average effective radiation dose estimate was 7.1±1.1 mSv. CONCLUSION: The use of motion compensation and spatio-temporal smoothing will result in improved quantification of dynamic CT MPI using a latest generation CT scanner.

Spatiotemporal monitoring of soil salinization in irrigated Tadla Plain (Morocco) using satellite spectral indices

Science.gov (United States)

El Harti, Abderrazak; Lhissou, Rachid; Chokmani, Karem; Ouzemou, Jamal-eddine; Hassouna, Mohamed; Bachaoui, El Mostafa; El Ghmari, Abderrahmene

2016-08-01

Soil salinization is major environmental issue in irrigated agricultural production. Conventional methods for salinization monitoring are time and money consuming and limited by the high spatiotemporal variability of this phenomenon. This work aims to propose a spatiotemporal monitoring method of soil salinization in the Tadla plain in central Morocco using spectral indices derived from Thematic Mapper (TM) and Operational Land Imager (OLI) data. Six Landsat TM/OLI satellite images acquired during 13 years period (2000-2013) coupled with in-situ electrical conductivity (EC) measurements were used to develop the proposed method. After radiometric and atmospheric correction of TM/OLI images, a new soil salinity index (OLI-SI) is proposed for soil EC estimation. Validation shows that this index allowed a satisfactory EC estimation in the Tadla irrigated perimeter with coefficient of determination R2 varying from 0.55 to 0.77 and a Root Mean Square Error (RMSE) ranging between 1.02 dS/m and 2.35 dS/m. The times-series of salinity maps produced over the Tadla plain using the proposed method show that salinity is decreasing in intensity and progressively increasing in spatial extent, over the 2000-2013 period. This trend resulted in a decrease in agricultural activities in the southwestern part of the perimeter, located in the hydraulic downstream.

Intravoxel incoehrent motion MR imaging in the head and neck: Correlation with dynamic contrast-enhanced MR imaging and diffusion-weighted imaging

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Xu, Xiao Quan; Choi, Young Jun; Sung, Yu Sub; Jang, Seung Won; Park, Ji Eun; Heo, Young Jin; Beak, Jung Hwan; Lee, Jeong Hyun [Dept. of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul (Korea, Republic of); Yoon, Ra Gyoung [Dept. of Radiology, Catholic Kwandong University International St. Mary' s Hospital, Catholic Kwandong University College of Medicine, Incheon (Korea, Republic of)

2016-09-15

To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D{sup *}), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D{sup *} and model-free parameters from the DCE-MRI (wash-in, T{sub max}, E{sub max}, initial AUC{sub 60}, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis. No correlation was found between f or D{sup *} and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D{sup *} (p > 0.05, respectively). Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.

Intravoxel Incoherent Motion MR Imaging in the Head and Neck: Correlation with Dynamic Contrast-Enhanced MR Imaging and Diffusion-Weighted Imaging

Energy Technology Data Exchange (ETDEWEB)

Xu, Xiao Quan [Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505 (Korea, Republic of); Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing 210029 (China); Choi, Young Jun; Sung, Yu Sub [Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505 (Korea, Republic of); Yoon, Ra Gyoung [Department of Radiology, Catholic Kwandong University International St. Mary' s Hospital, Catholic Kwandong University College of Medicine, Incheon 22711 (Korea, Republic of); Jang, Seung Won; Park, Ji Eun [Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505 (Korea, Republic of); Heo, Young Jin [Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505 (Korea, Republic of); Department of Radiology, Busan Paik Hospital, Inje University College of Medicine, Busan 47392 (Korea, Republic of); Baek, Jung Hwan; Lee, Jeong Hyun [Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul 05505 (Korea, Republic of)

2016-11-01

To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D{sup *}), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D{sup *} and model-free parameters from the DCE-MRI (wash-in, T{sub max}, E{sub max}, initial AUC{sub 60}, whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis. No correlation was found between f or D{sup *} and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D{sup *} (p > 0.05, respectively). Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck.

Intravoxel incoehrent motion MR imaging in the head and neck: Correlation with dynamic contrast-enhanced MR imaging and diffusion-weighted imaging

International Nuclear Information System (INIS)

Xu, Xiao Quan; Choi, Young Jun; Sung, Yu Sub; Jang, Seung Won; Park, Ji Eun; Heo, Young Jin; Beak, Jung Hwan; Lee, Jeong Hyun; Yoon, Ra Gyoung

2016-01-01

To investigate the correlation between perfusion- and diffusion-related parameters from intravoxel incoherent motion (IVIM) and those from dynamic contrast-enhanced MR imaging (DCE-MRI) and diffusion-weighted imaging in tumors and normal muscles of the head and neck. We retrospectively enrolled 20 consecutive patients with head and neck tumors with MR imaging performed using a 3T MR scanner. Tissue diffusivity (D), pseudo-diffusion coefficient (D * ), and perfusion fraction (f) were derived from bi-exponential fitting of IVIM data obtained with 14 different b-values in three orthogonal directions. We investigated the correlation between D, f, and D * and model-free parameters from the DCE-MRI (wash-in, T max , E max , initial AUC 60 , whole AUC) and the apparent diffusion coefficient (ADC) value in the tumor and normal masseter muscle using a whole volume-of-interest approach. Pearson's correlation test was used for statistical analysis. No correlation was found between f or D * and any of the parameters from the DCE-MRI in all patients or in patients with squamous cell carcinoma (p > 0.05). The ADC was significantly correlated with D values in the tumors (p < 0.001, r = 0.980) and muscles (p = 0.013, r = 0.542), despite its significantly higher value than D. The difference between ADC and D showed significant correlation with f values in the tumors (p = 0.017, r = 0.528) and muscles (p = 0.003, r = 0.630), but no correlation with D * (p > 0.05, respectively). Intravoxel incoherent motion shows no significant correlation with model-free perfusion parameters derived from the DCE-MRI but is feasible for the analysis of diffusivity in both tumors and normal muscles of the head and neck

Hippocampal sclerosis: correlation of MR imaging findings with surgical outcome

International Nuclear Information System (INIS)

Kim, Yoon Hee; Chang, Kee Hyun; Kim, Kyung Won; Han, Moon Hee; Park, Sung Ho; Nam, Hyun Woo; Choi, Kyu Ho; Cho, Woo Ho

2001-01-01

Atrophy and a high T2 signal of the hippocampus are known to be the principal MR imaging findings of hippocampal sclerosis. The purpose of this study was to determine whether or not individual MRI findings correlate with surgical outcome in patients with this condition. Preoperative MR imaging findings in 57 consecutive patients with pathologically-proven hippocampal sclerosis who underwent anterior temporal lobectomy and were followed-up for 24 months or more were retrospectively reviewed, and the results were compared with the postsurgical outcome (Engel classification). The MR images included routine sagittal T1-weighted and axial T2-weighted spin-echo images, and oblique coronal T1-weighted 3D gradient-echo and T2-weighted 2D fast spin-echo images obtained on either a 1.5 T or 1.0 T unit. The images were visually evaluated by two neuroradiologists blinded to the outcome; their focus was the presence or absence of atrophy and a high T2 hippocampal signal. Hippocampal atrophy was seen in 96% of cases (55/57) [100% (53/53) of the good outcome group (Engel class I and II), and 50% (2/4) of the poor outcome group (class III and IV)]. A high T2 hippocampal signal was seen in 61% of cases (35/57) [62% (33/53) of the good outcome group and 50% (2/4) of the poor outcome group]. All 35 patients with a high T2 signal had hippocampal atrophy. 'Normal' hippocampus, as revealed by MR imaging, occurred in 4% of patients (2/57), both of whom showed a poor outcome (Engel class III). The presence or absence of hippocampal atrophy correlated well with surgical outcome (p 0.05). Compared with a high T2 hippocampal signal, hippocampal atrophy is more common and correlates better with surgical outcome. For the prediction of this, it thus appears to be the more useful indicator

Application of digital-image-correlation techniques in analysing ...

Indian Academy of Sciences (India)

Basis theory of strain analysis using the digital image correlation method .... Type 304N Stainless Steel (Modulus of Elasticity = 193 MPa, Tensile Yield .... also proves the accuracy of the qualitative analyses by using the DIC ... We thank the National Science Council of Taiwan for supporting this research through grant. No.

Correlation between pennation angle and image quality of skeletal muscle fibre tractography using deterministic diffusion tensor imaging.

Science.gov (United States)

Okamoto, Yoshikazu; Okamoto, Toru; Yuka, Kujiraoka; Hirano, Yuji; Isobe, Tomonori; Minami, Manabu

2012-12-01

The aim of this study was to ascertain whether a correlation existed between muscle pennation angle and the ability to successfully perform tractography of the lower leg muscle fibres with deterministic diffusion tensor imaging (DTI) in normal volunteers. Fourteen volunteers aged 20-39 (mean 28.2 years old) were recruited. All volunteers were scanned using DTI, and six fibre tractographs were constructed from one lower leg of each volunteer, and the 'fibre density' was calculated in each of the tractographs. The pennation angle is the angle formed by the muscle fibre and the aponeurosis. The average pennation angle (AVPA) and standard deviation of the pennation angle (SDPA) were also measured for each muscle by ultrasonography in the same region as the MRI scan. For all 84 tractography images, the correlation coefficient between the fibre density and AVPA or SDPA was calculated. Fibre density and AVPA showed a moderate negative correlation (R = -0.72), and fibre density and SDPA showed a weak negative correlation (R = -0.47). With respect to comparisons within each muscle, AVPA and fibre density showed a moderate negative correlation in the gastrocnemius lateralis muscle (R = -0.57). Our data suggest that a larger, more variable pennation angle resulted in worse skeletal muscle tractography using deterministic DTI. © 2012 The Authors. Journal of Medical Imaging and Radiation Oncology © 2012 The Royal Australian and New Zealand College of Radiologists.

Brief communication: Landslide motion from cross correlation of UAV-derived morphological attributes

Science.gov (United States)

Peppa, Maria V.; Mills, Jon P.; Moore, Phil; Miller, Pauline E.; Chambers, Jonathan E.

2017-12-01

Unmanned aerial vehicles (UAVs) can provide observations of high spatio-temporal resolution to enable operational landslide monitoring. In this research, the construction of digital elevation models (DEMs) and orthomosaics from UAV imagery is achieved using structure-from-motion (SfM) photogrammetric procedures. The study examines the additional value that the morphological attribute of openness, amongst others, can provide to surface deformation analysis. Image-cross-correlation functions and DEM subtraction techniques are applied to the SfM outputs. Through the proposed integrated analysis, the automated quantification of a landslide's motion over time is demonstrated, with implications for the wider interpretation of landslide kinematics via UAV surveys.

Altered spatiotemporal characteristics of gait in older adults with chronic low back pain.

Science.gov (United States)

Hicks, Gregory E; Sions, J Megan; Coyle, Peter C; Pohlig, Ryan T

2017-06-01

Previous studies in older adults have identified that chronic low back pain (CLBP) is associated with slower gait speed. Given that slower gait speed is a predictor of greater morbidity and mortality among older adults, it is important to understand the underlying spatiotemporal characteristics of gait among older adults with CLBP. The purposes of this study were to determine (1) if there are differences in spatiotemporal parameters of gait between older adults with and without CLBP during self-selected and fast walking and (2) whether any of these gait characteristics are correlated with performance of a challenging walking task, e.g. stair negotiation. Spatiotemporal characteristics of gait were evaluated using a computerized walkway in 54 community-dwelling older adults with CLBP and 54 age- and sex-matched healthy controls. Older adults with CLBP walked slower than their pain-free peers during self-selected and fast walking. After controlling for body mass index and gait speed, step width was significantly greater in the CLBP group during the fast walking condition. Within the CLBP group, step width and double limb support time are significantly correlated with stair ascent/descent times. From a clinical perspective, these gait characteristics, which may be indicative of balance performance, may need to be addressed to improve overall gait speed, as well as stair-climbing performance. Future longitudinal studies confirming our findings are needed, as well as investigations focused on developing interventions to improve gait speed and decrease subsequent risk of mobility decline. Copyright © 2017 Elsevier B.V. All rights reserved.

Vaginal Masses: Magnetic Resonance Imaging Features with Pathologic Correlation

International Nuclear Information System (INIS)

Elsayes, K.M.; Narra, V.R.; Dillman, J.R.; Velcheti, V.; Hameed, O.; Tongdee, R.; Menias, C.O.

2007-01-01

The detection of vaginal lesions has increased with the expanding use of cross-sectional imaging. Magnetic resonance imaging (MRI) - with its high-contrast resolution and multiplanar capabilities - is often useful for characterizing vaginal masses. Vaginal masses can be classified as congenital, inflammatory, cystic (benign), and neoplastic (benign or malignant) in etiology. Recognition of the typical MR imaging features of such lesions is important because it often determines the treatment approach and may obviate surgery. Finally, vaginal MR imaging can be used to evaluate post-treatment changes related to previous surgery and radiation therapy. In this article, we will review pertinent vaginal anatomy, vaginal and pelvic MRI technique, and the MRI features of a variety of vaginal lesions with pathological correlation

Remote Sensing Image Fusion Based on the Combination Grey Absolute Correlation Degree and IHS Transform

Directory of Open Access Journals (Sweden)

Hui LIN

2014-12-01

Full Text Available An improved fusion algorithm for multi-source remote sensing images with high spatial resolution and multi-spectral capacity is proposed based on traditional IHS fusion and grey correlation analysis. Firstly, grey absolute correlation degree is used to discriminate non-edge pixels and edge pixels in high-spatial resolution images, by which the weight of intensity component is identified in order to combine it with high-spatial resolution image. Therefore, image fusion is achieved using IHS inverse transform. The proposed method is applied to ETM+ multi-spectral images and panchromatic image, and Quickbird’s multi-spectral images and panchromatic image respectively. The experiments prove that the fusion method proposed in the paper can efficiently preserve spectral information of the original multi-spectral images while enhancing spatial resolution greatly. By comparison and analysis, the proposed fusion algorithm is better than traditional IHS fusion and fusion method based on grey correlation analysis and IHS transform.

STSE: Spatio-Temporal Simulation Environment Dedicated to Biology

Directory of Open Access Journals (Sweden)

Gerber Susanne

2011-04-01

Full Text Available Abstract Background Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. Results The Spatio-Temporal Simulation Environment (STSE is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images. STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts

STSE: Spatio-Temporal Simulation Environment Dedicated to Biology.

Science.gov (United States)

Stoma, Szymon; Fröhlich, Martina; Gerber, Susanne; Klipp, Edda

2011-04-28

Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. The Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We

Correlation between the signal-to-noise ratio improvement factor (KSNR) and clinical image quality for chest imaging with a computed radiography system

International Nuclear Information System (INIS)

Moore, C S; Wood, T J; Saunderson, J R; Beavis, A W

2015-01-01

This work assessed the appropriateness of the signal-to-noise ratio improvement factor (K SNR ) as a metric for the optimisation of computed radiography (CR) of the chest. The results of a previous study in which four experienced image evaluators graded computer simulated chest images using a visual grading analysis scoring (VGAS) scheme to quantify the benefit of using an anti-scatter grid were used for the clinical image quality measurement (number of simulated patients  =  80). The K SNR was used to calculate the improvement in physical image quality measured in a physical chest phantom. K SNR correlation with VGAS was assessed as a function of chest region (lung, spine and diaphragm/retrodiaphragm), and as a function of x-ray tube voltage in a given chest region. The correlation of the latter was determined by the Pearson correlation coefficient. VGAS and K SNR image quality metrics demonstrated no correlation in the lung region but did show correlation in the spine and diaphragm/retrodiaphragmatic regions. However, there was no correlation as a function of tube voltage in any region; a Pearson correlation coefficient (R) of  −0.93 (p  =  0.015) was found for lung, a coefficient (R) of  −0.95 (p  =  0.46) was found for spine, and a coefficient (R) of  −0.85 (p  =  0.015) was found for diaphragm. All demonstrate strong negative correlations indicating conflicting results, i.e. K SNR increases with tube voltage but VGAS decreases. Medical physicists should use the K SNR metric with caution when assessing any potential improvement in clinical chest image quality when introducing an anti-scatter grid for CR imaging, especially in the lung region. This metric may also be a limited descriptor of clinical chest image quality as a function of tube voltage when a grid is used routinely. (paper)

Spatio-Temporal Data Construction

Directory of Open Access Journals (Sweden)

Hai Ha Le

2013-08-01

Full Text Available On the route to a spatio-temporal geoscience information system, an appropriate data model for geo-objects in space and time has been developed. In this model, geo-objects are represented as sequences of geometries and properties with continuous evolution in each time interval. Because geomodeling software systems usually model objects at specific time instances, we want to interpolate the geometry and properties from two models of an object with only geometrical constraints (no physical or mechanical constraints. This process is called spatio-temporal data construction or morphological interpolation of intermediate geometries. This paper is strictly related to shape morphing, shape deformation, cross-parameterization and compatible remeshing and is only concerned with geological surfaces. In this study, two main sub-solutions construct compatible meshes and find trajectories in which vertices of the mesh evolve. This research aims to find an algorithm to construct spatio-temporal data with some constraints from the geosciences, such as cutting surfaces by faulting or fracturing phenomena and evolving boundaries attached to other surfaces. Another goal of this research is the implementation of the algorithm in a software product, namely a gOcad plug-in. The four main procedures of the algorithm are cutting the surfaces, setting up constraints, partitioning and calculating the parameterizations and trajectories. The software has been tested to construct data for a salt dome and other surfaces in regard to the geological processes of faulting, deposition and erosion. The result of this research is an algorithm and software for the construction of spatio-temporal data.

Spatiotemporal Dynamics of Scrub Typhus Transmission in Mainland China, 2006-2014.

Science.gov (United States)

Wu, Yi-Cheng; Qian, Quan; Soares Magalhaes, Ricardo J; Han, Zhi-Hai; Hu, Wen-Biao; Haque, Ubydul; Weppelmann, Thomas A; Wang, Yong; Liu, Yun-Xi; Li, Xin-Lou; Sun, Hai-Long; Sun, Yan-Song; Clements, Archie C A; Li, Shen-Long; Zhang, Wen-Yi

2016-08-01

Scrub typhus is endemic in the Asia-Pacific region including China, and the number of reported cases has increased dramatically in the past decade. However, the spatial-temporal dynamics and the potential risk factors in transmission of scrub typhus in mainland China have yet to be characterized. This study aims to explore the spatiotemporal dynamics of reported scrub typhus cases in mainland China between January 2006 and December 2014, to detect the location of high risk spatiotemporal clusters of scrub typhus cases, and identify the potential risk factors affecting the re-emergence of the disease. Monthly cases of scrub typhus reported at the county level between 2006 and 2014 were obtained from the Chinese Center for Diseases Control and Prevention. Time-series analyses, spatiotemporal cluster analyses, and spatial scan statistics were used to explore the characteristics of the scrub typhus incidence. To explore the association between scrub typhus incidence and environmental variables panel Poisson regression analysis was conducted. During the time period between 2006 and 2014 a total of 54,558 scrub typhus cases were reported in mainland China, which grew exponentially. The majority of cases were reported each year between July and November, with peak incidence during October every year. The spatiotemporal dynamics of scrub typhus varied over the study period with high-risk clusters identified in southwest, southern, and middle-eastern part of China. Scrub typhus incidence was positively correlated with the percentage of shrub and meteorological variables including temperature and precipitation. The results of this study demonstrate areas in China that could be targeted with public health interventions to mitigate the growing threat of scrub typhus in the country.

CT and MR imaging findings of xanthogranulomatous cholecystitis: correlation with pathologic findings

Energy Technology Data Exchange (ETDEWEB)

Shuto, R.; Kiyosue, H.; Komatsu, E.; Matsumoto, S.; Mori, H. [Oita Medical Univ. (Japan). Dept. of Radiology; Kawano, K. [Oita Medical Univ. (Japan). Dept. of First Surgery; Kondo, Y.; Yokoyama, S. [Oita Medical Univ. (Japan). Dept. of First Pathology

2004-03-01

The aim of this study was to evaluate CT and MRI findings in xanthogranulomatous cholecystitis (XGC) and to correlate the imaging findings with various pathologic parameters. The study included 13 patients with histopathologically confirmed XGC. The CT (n=13) and MRI (n=5) obtained in these patients were evaluated retrospectively. On CT, low-attenuation areas in the wall of XGC correlated with foam and inflammatory cells or necrosis and/or abscess in XGC. Areas of iso- to slightly high signal intensity on T2-weighted images, showing slight enhancement at early phase and strong enhancement at last phase on dynamic study, corresponded with areas of abundant xanthogranulomas. Areas with very high signal intensity on T2-weighted images without enhancement corresponded with necrosis and/or abscesses. Luminal surface enhancement (LSE) of gallbladder wall represented preservation of the epithelial layer. The early-enhanced areas of the liver bed on dynamic CT and MR images corresponded with accumulation of inflammatory cells and abundant fibrosis. Our results indicate that CT and MRI findings correlate well with the histopathologic findings of XGC.

Region segmentation along image sequence

International Nuclear Information System (INIS)

Monchal, L.; Aubry, P.

1995-01-01

A method to extract regions in sequence of images is proposed. Regions are not matched from one image to the following one. The result of a region segmentation is used as an initialization to segment the following and image to track the region along the sequence. The image sequence is exploited as a spatio-temporal event. (authors). 12 refs., 8 figs

Three-dimensional facial digitization using advanced digital image correlation.

Science.gov (United States)

Nguyen, Hieu; Kieu, Hien; Wang, Zhaoyang; Le, Hanh N D

2018-03-20

Presented in this paper is an effective technique to acquire the three-dimensional (3D) digital images of the human face without the use of active lighting and artificial patterns. The technique is based on binocular stereo imaging and digital image correlation, and it includes two key steps: camera calibration and image matching. The camera calibration involves a pinhole model and a bundle-adjustment approach, and the governing equations of the 3D digitization process are described. For reliable pixel-to-pixel image matching, the skin pores and freckles or lentigines on the human face serve as the required pattern features to facilitate the process. It employs feature-matching-based initial guess, multiple subsets, iterative optimization algorithm, and reliability-guided computation path to achieve fast and accurate image matching. Experiments have been conducted to demonstrate the validity of the proposed technique. The simplicity of the approach and the affordable cost of the implementation show its practicability in scientific and engineering applications.

A digital correlator upgrade for the Arcminute MicroKelvin Imager

Science.gov (United States)

Hickish, Jack; Razavi-Ghods, Nima; Perrott, Yvette C.; Titterington, David J.; Carey, Steve H.; Scott, Paul F.; Grainge, Keith J. B.; Scaife, Anna M. M.; Alexander, Paul; Saunders, Richard D. E.; Crofts, Mike; Javid, Kamran; Rumsey, Clare; Jin, Terry Z.; Ely, John A.; Shaw, Clive; Northrop, Ian G.; Pooley, Guy; D'Alessandro, Robert; Doherty, Peter; Willatt, Greg P.

2018-04-01

The Arcminute Microkelvin Imager (AMI) telescopes located at the Mullard Radio Astronomy Observatory near Cambridge have been significantly enhanced by the implementation of a new digital correlator with 1.2 MHz spectral resolution. This system has replaced a 750-MHz resolution analogue lag-based correlator, and was designed to mitigate the effects of radio frequency interference, particularly that from geostationary satellites which are visible from the AMI site when observing at low declinations. The upgraded instrument consists of 18 ROACH2 Field Programmable Gate Array platforms used to implement a pair of real-time FX correlators - one for each of AMI's two arrays. The new system separates the down-converted RF baseband signal from each AMI receiver into two sub-bands, each of which are filtered to a width of 2.3 GHz and digitized at 5-Gsps with 8 bits of precision. These digital data streams are filtered into 2048 frequency channels and cross-correlated using FPGA hardware, with a commercial 10 Gb Ethernet switch providing high-speed data interconnect. Images formed using data from the new digital correlator show over an order of magnitude improvement in dynamic range over the previous system. The ability to observe at low declinations has also been significantly improved.

Application of digital image correlation method for analysing crack ...

Indian Academy of Sciences (India)

centrated strain by imitating the treatment of micro-cracks using the finite element ... water and moisture to penetrate the concrete leading to serious rust of the ... The correlations among various grey values of digital images are analysed for ...

Correlation between Health Perception, Body Image, and Eating Habits in High School Students

Directory of Open Access Journals (Sweden)

Abdullah Ichsan

2016-06-01

Full Text Available Background: Mental disorders, including eating disorders, mostly begin during youth. Moreover, negative body image is found to cause unhealthy eating habits in the context of several cross-cultural settings. This study aimed to examine the correlation between health perception and body image with eating habits among high school students. Methods: A structured, anonymous questionnaire was distributed to students of a private high school in Bandung, Indonesia in June-October 2014. The questionnaire included questions about health perception, body image, eating habits, body weight and height, and also other demographic parameters. The school was selected as the study object through purposive sampling, and 140 high school students (72 male and 68 female were ramdomly selected. Results: Male and female did not show considerable differences in health perceptions. Out of 13 statements, 12 statements of male respondents showed better body image than female. While in eating habits statements, female respondents seemed to maintain healthier eating habits than male respondents. No significant correlation was observed between body image and eating habits (r=-0.015, p=0.858. There was significant correlation between health perception and eating habits (r=0.374, p<0.001. Correlation between sex and eating habits was found (p=0.020, there was not significant relationship between eating habits and Body Mass Index (BMI (p=0.368. Conclusions: The negative relationship between body image and eating habits is not significant. However there was a significant positive relationship between health perception and eating habits. Furthermore, there was correlation between sex and eating habits, while the positive relationship between eating habits and BMI was still not found.

The Voronoi spatio-temporal data structure

Science.gov (United States)

Mioc, Darka

2002-04-01

Current GIS models cannot integrate the temporal dimension of spatial data easily. Indeed, current GISs do not support incremental (local) addition and deletion of spatial objects, and they can not support the temporal evolution of spatial data. Spatio-temporal facilities would be very useful in many GIS applications: harvesting and forest planning, cadastre, urban and regional planning, and emergency planning. The spatio-temporal model that can overcome these problems is based on a topological model---the Voronoi data structure. Voronoi diagrams are irregular tessellations of space, that adapt to spatial objects and therefore they are a synthesis of raster and vector spatial data models. The main advantage of the Voronoi data structure is its local and sequential map updates, which allows us to automatically record each event and performed map updates within the system. These map updates are executed through map construction commands that are composed of atomic actions (geometric algorithms for addition, deletion, and motion of spatial objects) on the dynamic Voronoi data structure. The formalization of map commands led to the development of a spatial language comprising a set of atomic operations or constructs on spatial primitives (points and lines), powerful enough to define the complex operations. This resulted in a new formal model for spatio-temporal change representation, where each update is uniquely characterized by the numbers of newly created and inactivated Voronoi regions. This is used for the extension of the model towards the hierarchical Voronoi data structure. In this model, spatio-temporal changes induced by map updates are preserved in a hierarchical data structure that combines events and corresponding changes in topology. This hierarchical Voronoi data structure has an implicit time ordering of events visible through changes in topology, and it is equivalent to an event structure that can support temporal data without precise temporal

Global correlation imaging of magnetic total field gradients

International Nuclear Information System (INIS)

Guo, Lianghui; Meng, Xiaohong; Shi, Lei

2012-01-01

Firstly we introduce the correlation imaging approach for the x-, y- and z-gradients of a magnetic total field anomaly for deriving the distribution of equivalent magnetic sources of the subsurface. In this approach, the subsurface space is divided into a regular grid, and then a correlation coefficient function is computed at each grid node, based on the cross-correlation between the x-gradient (or y-gradient or z-gradient) of the observed magnetic total field anomaly and the x-gradient (or y-gradient or z-gradient) of the theoretical magnetic total field anomaly due to a magnetic dipole. The resultant correlation coefficient is used to describe the probability of a magnetic dipole occurring at the node. We then define a global correlation coefficient function for comprehensively delineating the probability of an occurrence of a magnetic dipole, which takes, at each node, the maximum positive value of the corresponding correlation coefficient function of the three gradients. We finally test the approach both on synthetic data and real data from a metallic deposit area in the middle-lower reaches of the Yangtze River, China. (paper)

Image pre-filtering for measurement error reduction in digital image correlation

Science.gov (United States)

Zhou, Yihao; Sun, Chen; Song, Yuntao; Chen, Jubing

2015-02-01

In digital image correlation, the sub-pixel intensity interpolation causes a systematic error in the measured displacements. The error increases toward high-frequency component of the speckle pattern. In practice, a captured image is usually corrupted by additive white noise. The noise introduces additional energy in the high frequencies and therefore raises the systematic error. Meanwhile, the noise also elevates the random error which increases with the noise power. In order to reduce the systematic error and the random error of the measurements, we apply a pre-filtering to the images prior to the correlation so that the high-frequency contents are suppressed. Two spatial-domain filters (binomial and Gaussian) and two frequency-domain filters (Butterworth and Wiener) are tested on speckle images undergoing both simulated and real-world translations. By evaluating the errors of the various combinations of speckle patterns, interpolators, noise levels, and filter configurations, we come to the following conclusions. All the four filters are able to reduce the systematic error. Meanwhile, the random error can also be reduced if the signal power is mainly distributed around DC. For high-frequency speckle patterns, the low-pass filters (binomial, Gaussian and Butterworth) slightly increase the random error and Butterworth filter produces the lowest random error among them. By using Wiener filter with over-estimated noise power, the random error can be reduced but the resultant systematic error is higher than that of low-pass filters. In general, Butterworth filter is recommended for error reduction due to its flexibility of passband selection and maximal preservation of the allowed frequencies. Binomial filter enables efficient implementation and thus becomes a good option if computational cost is a critical issue. While used together with pre-filtering, B-spline interpolator produces lower systematic error than bicubic interpolator and similar level of the random

Spatiotemporal Wave Patterns: Information Dynamics

Energy Technology Data Exchange (ETDEWEB)

Mikhail Rabinovich; Lev Tsimring

2006-01-20

Pattern formation has traditionally been studied in non-equilibrium physics from the viewpoint of describing the basic structures and their interactions. While this is still an important area of research, the emphasis in the last few years has shifted towards analysis of specific properties of patterns in various complex media. For example, diverse and unexpected phenomena occur in neuro-like media that are characterized by highly non-trivial local dynamics. We carried out an active research program on analysis of spatio-temporal patterns in various physical systems (convection, oscillating fluid layer, soap film), as well as in neuro-like media, with an emphasis on informational aspects of the dynamics. Nonlinear nonequilibrium media and their discrete analogs have a unique ability to represent, memorize, and process the information contained in spatio-temporal patterns. Recent neurophysiological experiments demonstrated a certain universality of spatio-temporal representation of information by neural ensembles. Information processing is also revealed in the spatio-temporal dynamics of cellular patterns in nonequilibrium media. It is extremely important for many applications to study the informational aspects of these dynamics, including the origins and mechanisms of information generation, propagation and storage. Some of our results are: the discovery of self-organization of periodically oscillatory patterns in chaotic heterogeneous media; the analysis of the propagation of the information along a chaotic media as function of the entropy of the signal; the analysis of wave propagation in discrete non-equilibrium media with autocatalytic properties, which simulates the calcium dynamics in cellular membranes. Based on biological experiments we suggest the mechanism by which the spatial sensory information is transferred into the spatio-temporal code in the neural media. We also found a new mechanism of self-pinning in cellular structures and the related phenomenon

Pleasant/Unpleasant Filtering for Affective Image Retrieval Based on Cross-Correlation of EEG Features

Directory of Open Access Journals (Sweden)

Keranmu Xielifuguli

2014-01-01

Full Text Available People often make decisions based on sensitivity rather than rationality. In the field of biological information processing, methods are available for analyzing biological information directly based on electroencephalogram: EEG to determine the pleasant/unpleasant reactions of users. In this study, we propose a sensitivity filtering technique for discriminating preferences (pleasant/unpleasant for images using a sensitivity image filtering system based on EEG. Using a set of images retrieved by similarity retrieval, we perform the sensitivity-based pleasant/unpleasant classification of images based on the affective features extracted from images with the maximum entropy method: MEM. In the present study, the affective features comprised cross-correlation features obtained from EEGs produced when an individual observed an image. However, it is difficult to measure the EEG when a subject visualizes an unknown image. Thus, we propose a solution where a linear regression method based on canonical correlation is used to estimate the cross-correlation features from image features. Experiments were conducted to evaluate the validity of sensitivity filtering compared with image similarity retrieval methods based on image features. We found that sensitivity filtering using color correlograms was suitable for the classification of preferred images, while sensitivity filtering using local binary patterns was suitable for the classification of unpleasant images. Moreover, sensitivity filtering using local binary patterns for unpleasant images had a 90% success rate. Thus, we conclude that the proposed method is efficient for filtering unpleasant images.

Spatio-temporal alignment of pedobarographic image sequences.

Science.gov (United States)

Oliveira, Francisco P M; Sousa, Andreia; Santos, Rubim; Tavares, João Manuel R S

2011-07-01

This article presents a methodology to align plantar pressure image sequences simultaneously in time and space. The spatial position and orientation of a foot in a sequence are changed to match the foot represented in a second sequence. Simultaneously with the spatial alignment, the temporal scale of the first sequence is transformed with the aim of synchronizing the two input footsteps. Consequently, the spatial correspondence of the foot regions along the sequences as well as the temporal synchronizing is automatically attained, making the study easier and more straightforward. In terms of spatial alignment, the methodology can use one of four possible geometric transformation models: rigid, similarity, affine, or projective. In the temporal alignment, a polynomial transformation up to the 4th degree can be adopted in order to model linear and curved time behaviors. Suitable geometric and temporal transformations are found by minimizing the mean squared error (MSE) between the input sequences. The methodology was tested on a set of real image sequences acquired from a common pedobarographic device. When used in experimental cases generated by applying geometric and temporal control transformations, the methodology revealed high accuracy. In addition, the intra-subject alignment tests from real plantar pressure image sequences showed that the curved temporal models produced better MSE results (P alignment of pedobarographic image data, since previous methods can only be applied on static images.

Time-of-flight camera via a single-pixel correlation image sensor

Science.gov (United States)

Mao, Tianyi; Chen, Qian; He, Weiji; Dai, Huidong; Ye, Ling; Gu, Guohua

2018-04-01

A time-of-flight imager based on single-pixel correlation image sensors is proposed for noise-free depth map acquisition in presence of ambient light. Digital micro-mirror device and time-modulated IR-laser provide spatial and temporal illumination on the unknown object. Compressed sensing and ‘four bucket principle’ method are combined to reconstruct the depth map from a sequence of measurements at a low sampling rate. Second-order correlation transform is also introduced to reduce the noise from the detector itself and direct ambient light. Computer simulations are presented to validate the computational models and improvement of reconstructions.

Digital Image Analysis of Ultrasound B-mode images of Carotid Atherosclerotic Plaque: Correlation with Histological Examination

DEFF Research Database (Denmark)

Wilhjelm, Jens E.; Rosendal, Kim; Grønholdt, Marie-Louise Moes

1996-01-01

This paper reports on a study of how well texture features extracted from B-mode images of atherosclerotic plaque correlates with histological results obtained from the same plaque after carotid endarterectomy. The study reveals that a few second order texture features (diagonal moment, standard...... deviation and autocorrelation) provide good correlation within the training set (p = 0.04); However, the correlation found so far is not so high, that the method can be used in clinical prediction of plaque constituents....

Imaging diagnosis in relapsing polychondritis and correlation with clinical and serological data

International Nuclear Information System (INIS)

Thaiss, W.M.; Nikolaou, K.; Horger, M.; Spengler, W.; Xenitidis, T.; Henes, J.; Spira, D.

2016-01-01

We hypothesize that imaging findings from CT and MRI correlate better with clinical markers for assessment of disease activity in patients with the rare relapsing polychondritis (RPC) than with serological inflammatory markers. Retrospective database search at our institution identified 28 patients (13 females; age 49.0 years ± 15.0 SD) with RP between September 2004 and March 2014. Institutional review board approval was obtained for this retrospective data analysis. All patients had clinically proven RPC with at least two episodes of active disease. Of those, 18 patients were examined with CT- and MRI and presented all morphologic features of RPC like bronchial/laryngeal/auricular cartilage thickness, contrast enhancement, increased T2-signal intensity. Imaging data was subsequently correlated with corresponding clinical symptoms like fever, dyspnea, stridor, uveitis, pain, hearing impairment as well as with acute-phase-inflammatory parameters like C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). The clinical parameters were in good agreement with imaging findings and clinical symptoms such as tracheal wall thickening and dyspnea (r =0.65 p = 0.05), joint synovitis on MRI and a higher McAdam score (r = 0.84 p < 0.001). No correlations were found between inflammatory laboratory markers, imaging findings and clinical features. Imaging diagnosis in RPC using CT and/or MRI delivers information about the degree of disease activity that correlates better with clinical features than unspecific inflammatory laboratory markers. Additionally, clinically unapparent cartilage involvement can be assessed adding value to the clinical diagnosis and therapy planning in this rare disease. (orig.)

Imaging diagnosis in relapsing polychondritis and correlation with clinical and serological data

Energy Technology Data Exchange (ETDEWEB)

Thaiss, W.M.; Nikolaou, K.; Horger, M. [Eberhard Karls University, Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen (Germany); Spengler, W.; Xenitidis, T.; Henes, J. [Eberhard Karls University, Department of Internal Medicine II, Tuebingen (Germany); Spira, D. [Eberhard Karls University, Department of Radiology, Diagnostic and Interventional Radiology, Tuebingen (Germany); University Medical Center Heidelberg, Diagnostic and Interventional Radiology, Heidelberg (Germany)

2016-03-15

We hypothesize that imaging findings from CT and MRI correlate better with clinical markers for assessment of disease activity in patients with the rare relapsing polychondritis (RPC) than with serological inflammatory markers. Retrospective database search at our institution identified 28 patients (13 females; age 49.0 years ± 15.0 SD) with RP between September 2004 and March 2014. Institutional review board approval was obtained for this retrospective data analysis. All patients had clinically proven RPC with at least two episodes of active disease. Of those, 18 patients were examined with CT- and MRI and presented all morphologic features of RPC like bronchial/laryngeal/auricular cartilage thickness, contrast enhancement, increased T2-signal intensity. Imaging data was subsequently correlated with corresponding clinical symptoms like fever, dyspnea, stridor, uveitis, pain, hearing impairment as well as with acute-phase-inflammatory parameters like C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR). The clinical parameters were in good agreement with imaging findings and clinical symptoms such as tracheal wall thickening and dyspnea (r =0.65 p = 0.05), joint synovitis on MRI and a higher McAdam score (r = 0.84 p < 0.001). No correlations were found between inflammatory laboratory markers, imaging findings and clinical features. Imaging diagnosis in RPC using CT and/or MRI delivers information about the degree of disease activity that correlates better with clinical features than unspecific inflammatory laboratory markers. Additionally, clinically unapparent cartilage involvement can be assessed adding value to the clinical diagnosis and therapy planning in this rare disease. (orig.)

Correlation of breast image alignment using biomechanical modelling

Science.gov (United States)

Lee, Angela; Rajagopal, Vijay; Bier, Peter; Nielsen, Poul M. F.; Nash, Martyn P.

2009-02-01

Breast cancer is one of the most common causes of cancer death among women around the world. Researchers have found that a combination of imaging modalities (such as x-ray mammography, magnetic resonance, and ultrasound) leads to more effective diagnosis and management of breast cancers because each imaging modality displays different information about the breast tissues. In order to aid clinicians in interpreting the breast images from different modalities, we have developed a computational framework for generating individual-specific, 3D, finite element (FE) models of the breast. Medical images are embedded into this model, which is subsequently used to simulate the large deformations that the breasts undergo during different imaging procedures, thus warping the medical images to the deformed views of the breast in the different modalities. In this way, medical images of the breast taken in different geometric configurations (compression, gravity, etc.) can be aligned according to physically feasible transformations. In order to analyse the accuracy of the biomechanical model predictions, squared normalised cross correlation (NCC2) was used to provide both local and global comparisons of the model-warped images with clinical images of the breast subject to different gravity loaded states. The local comparison results were helpful in indicating the areas for improvement in the biomechanical model. To improve the modelling accuracy, we will need to investigate the incorporation of breast tissue heterogeneity into the model and altering the boundary conditions for the breast model. A biomechanical image registration tool of this kind will help radiologists to provide more reliable diagnosis and localisation of breast cancer.

Correlation of bone quality in radiographic images with clinical bone quality classification

Energy Technology Data Exchange (ETDEWEB)

Kim, Hyun Woo; Huh, Kyung Hoe; Kim, Jeong Hwa; Yi, Won Jin; Heo, Min Suk; Lee, Sam Sun; Choi, Soon Chul [Seoul National University, Seoul (Korea, Republic of); Park, Kwan Soo [Inje University, Seoul (Korea, Republic of)

2006-03-15

To investigate the validity of digital image processing on panoramic radiographs in estimating bone quality before endosseous dental implant installation by correlating bone quality in radiographic images with clinical bone quality classification. An experienced surgeon assessed and classified bone quality for implant sites with tactile sensation at the time of implant placement. Including fractal dimension eighteen morphologic features of trabecular pattern were examined in each anatomical sites on panoramic radiographs. Finally bone quality of 67 implant sites were evaluated in 42 patients. Pearson correlation analysis showed that three morphologic parameters had weak linear negative correlation with clinical bone quality classification showing correlation coefficients of -0.276, -0.280, and -0.289, respectively (p<0.05). And other three morphologic parameters had obvious linear negative correlation with clinical bone quality classification showing correlation coefficients of -0.346, -0.488, and -0.343 respectively (p<0.05). Fractal dimension also had a linear correlating with clinical bone quality classification with correlation coefficients -0.506 significantly (P<0.05). This study suggests that fractal and morphometric analysis using digital panoramic radiographs can be used to evaluate bone quality for implant recipient sites.

Sonocubic fine: new three-dimensional ultrasound software to the screening of congenital heart diseases

Directory of Open Access Journals (Sweden)

Edward Araujo Júnior

2014-09-01

Full Text Available Congenital heart disease is the most common fetal congenital malformations; however, the prenatal rate detection still is low. The two-dimensional echocardiography is the "gold standard" exam to screening and diagnosis of congenital heart disease during the prenatal; however, this exam is operator-depending and it is realized only in high risk pregnancies. Spatio-temporal image correlation is a three-dimensional ultrasound software that analyses the fetal heart and your connections in the multiplanar and rendering modes; however, spatio-temporal image correlation too is operator-depending and time-consuming. We presenting a new three-dimensional software named Sonocubic fine to the screening of congenital heart disease. This software applies intelligent navigation technology to spatio-temporal image correlation volume datasets to automatically generate nine fetal echocardiography standard views. Thus, this new software tends to be less operator-depending and time-consuming.

A nu-space for image correlation spectroscopy: characterization and application to measure protein transport in live cells

Science.gov (United States)

Potvin-Trottier, Laurent; Chen, Lingfeng; Horwitz, Alan Rick; Wiseman, Paul W.

2013-08-01

We introduce a new generalized theoretical framework for image correlation spectroscopy (ICS). Using this framework, we extend the ICS method in time-frequency (ν, nu) space to map molecular flow of fluorescently tagged proteins in individual living cells. Even in the presence of a dominant immobile population of fluorescent molecules, nu-space ICS (nICS) provides an unbiased velocity measurement, as well as the diffusion coefficient of the flow, without requiring filtering. We also develop and characterize a tunable frequency-filter for spatio-temporal ICS (STICS) that allows quantification of the density, the diffusion coefficient and the velocity of biased diffusion. We show that the techniques are accurate over a wide range of parameter space in computer simulation. We then characterize the retrograde flow of adhesion proteins (α6- and αLβ2-GFP integrins and mCherry-paxillin) in CHO.B2 cells plated on laminin and intercellular adhesion molecule 1 (ICAM-1) ligands respectively. STICS with a tunable frequency filter, in conjunction with nICS, measures two new transport parameters, the density and transport bias coefficient (a measure of the diffusive character of a flow/biased diffusion), showing that molecular flow in this cell system has a significant diffusive component. Our results suggest that the integrin-ligand interaction, along with the internal myosin-motor generated force, varies for different integrin-ligand pairs, consistent with previous results.

Spatiotemporal exploratory models for broad-scale survey data.

Science.gov (United States)

Fink, Daniel; Hochachka, Wesley M; Zuckerberg, Benjamin; Winkler, David W; Shaby, Ben; Munson, M Arthur; Hooker, Giles; Riedewald, Mirek; Sheldon, Daniel; Kelling, Steve

2010-12-01

The distributions of animal populations change and evolve through time. Migratory species exploit different habitats at different times of the year. Biotic and abiotic features that determine where a species lives vary due to natural and anthropogenic factors. This spatiotemporal variation needs to be accounted for in any modeling of species' distributions. In this paper we introduce a semiparametric model that provides a flexible framework for analyzing dynamic patterns of species occurrence and abundance from broad-scale survey data. The spatiotemporal exploratory model (STEM) adds essential spatiotemporal structure to existing techniques for developing species distribution models through a simple parametric structure without requiring a detailed understanding of the underlying dynamic processes. STEMs use a multi-scale strategy to differentiate between local and global-scale spatiotemporal structure. A user-specified species distribution model accounts for spatial and temporal patterning at the local level. These local patterns are then allowed to "scale up" via ensemble averaging to larger scales. This makes STEMs especially well suited for exploring distributional dynamics arising from a variety of processes. Using data from eBird, an online citizen science bird-monitoring project, we demonstrate that monthly changes in distribution of a migratory species, the Tree Swallow (Tachycineta bicolor), can be more accurately described with a STEM than a conventional bagged decision tree model in which spatiotemporal structure has not been imposed. We also demonstrate that there is no loss of model predictive power when a STEM is used to describe a spatiotemporal distribution with very little spatiotemporal variation; the distribution of a nonmigratory species, the Northern Cardinal (Cardinalis cardinalis).

Chondrosarcoma : MR imaging findings correlated with pathologic classification and grade

International Nuclear Information System (INIS)

Cho, Seong Whi; Kang, Heung Sik; Kim, Sam Soo; Lee, Sang Hyun; Cho, Jeong Yeon; Yeon, Kyung Mo

1996-01-01

To evaluate the MR imaging findings of chondrosarcomas by correlation with pathologic classification and grade. We performed MR imaging-pathologic correlation of nineteen chondrosarcomas. Conventional chondrosarcomas accounted for 15 cases (grade I:6, II:6, III:3) and the mesenchymal and dedifferentiated types each accounted for two. MR signal intensity (SI) of the tumor on T1- and T2-weighted images (T1WI and T2WI, respectively), was classified as homogeneous or heterogeneous low-, iso- or high SI, and enhancing pattern as marginal, marginal and septal, marginal and nodular, or diffuse enhancement. Eighteen cases of chondrosarcomas (95%) showed homogeneous or heterogeneous low- or iso SI on T1WI and high SI on T2WI. Low grade conventional chondrosarcomas showed marginal and septal (n=8/10) or marginal (n=2/10) enhancement on Gd-enhanced MR images. Grade III conventional chondrosarcomas showed marginal or marginal and nodular enhancement. Dedifferentiated and mesenchymal chondrosarcomas showed marginal and nodular or diffuse enhancement. Chondrosarcomas showed iso- or low SI on T1WI and high SI on T2WI. Marginal and septal enhancement was demonstrated on Gd-enhanced MR images of grade I and II conventional chondrosarcomas. If a tumor showed a marginal and nodular or diffuse enhancing pattern, this suggested it was a of high grade chondrosarcoma

Spatio-temporal networks: reachability, centrality and robustness.

Science.gov (United States)

Williams, Matthew J; Musolesi, Mirco

2016-06-01

Recent advances in spatial and temporal networks have enabled researchers to more-accurately describe many real-world systems such as urban transport networks. In this paper, we study the response of real-world spatio-temporal networks to random error and systematic attack, taking a unified view of their spatial and temporal performance. We propose a model of spatio-temporal paths in time-varying spatially embedded networks which captures the property that, as in many real-world systems, interaction between nodes is non-instantaneous and governed by the space in which they are embedded. Through numerical experiments on three real-world urban transport systems, we study the effect of node failure on a network's topological, temporal and spatial structure. We also demonstrate the broader applicability of this framework to three other classes of network. To identify weaknesses specific to the behaviour of a spatio-temporal system, we introduce centrality measures that evaluate the importance of a node as a structural bridge and its role in supporting spatio-temporally efficient flows through the network. This exposes the complex nature of fragility in a spatio-temporal system, showing that there is a variety of failure modes when a network is subject to systematic attacks.

Using Image Gradients to Improve Robustness of Digital Image Correlation to Non-uniform Illumination: Effects of Weighting and Normalization Choices

KAUST Repository

Xu, Jiangping; Moussawi, Ali; Gras, Renaud; Lubineau, Gilles

2015-01-01

Changes in the light condition affect the solution of intensity-based digital image correlation algorithms. One natural way to decrease the influence of illumination is to consider the gradients of the image rather than the image itself when

Analyzing Spatiotemporal Anomalies through Interactive Visualization

Directory of Open Access Journals (Sweden)

Tao Zhang

2014-06-01

Full Text Available As we move into the big data era, data grows not just in size, but also in complexity, containing a rich set of attributes, including location and time information, such as data from mobile devices (e.g., smart phones, natural disasters (e.g., earthquake and hurricane, epidemic spread, etc. We are motivated by the rising challenge and build a visualization tool for exploring generic spatiotemporal data, i.e., records containing time location information and numeric attribute values. Since the values often evolve over time and across geographic regions, we are particularly interested in detecting and analyzing the anomalous changes over time/space. Our analytic tool is based on geographic information system and is combined with spatiotemporal data mining algorithms, as well as various data visualization techniques, such as anomaly grids and anomaly bars superimposed on the map. We study how effective the tool may guide users to find potential anomalies through demonstrating and evaluating over publicly available spatiotemporal datasets. The tool for spatiotemporal anomaly analysis and visualization is useful in many domains, such as security investigation and monitoring, situation awareness, etc.

Unsupervised Learning of Spatiotemporal Features by Video Completion

OpenAIRE

Nallabolu, Adithya Reddy

2017-01-01

In this work, we present an unsupervised representation learning approach for learning rich spatiotemporal features from videos without the supervision from semantic labels. We propose to learn the spatiotemporal features by training a 3D convolutional neural network (CNN) using video completion as a surrogate task. Using a large collection of unlabeled videos, we train the CNN to predict the missing pixels of a spatiotemporal hole given the remaining parts of the video through minimizing per...

Correlation characteristics of optical coherence tomography images of turbid media with statistically inhomogeneous optical parameters

International Nuclear Information System (INIS)

Dolin, Lev S.; Sergeeva, Ekaterina A.; Turchin, Ilya V.

2012-01-01

Noisy structure of optical coherence tomography (OCT) images of turbid medium contains information about spatial variations of its optical parameters. We propose analytical model of statistical characteristics of OCT signal fluctuations from turbid medium with spatially inhomogeneous coefficients of absorption and backscattering. Analytically predicted correlation characteristics of OCT signal from spatially inhomogeneous medium are in good agreement with the results of correlation analysis of OCT images of different biological tissues. The proposed model can be efficiently applied for quantitative evaluation of statistical properties of absorption and backscattering fluctuations basing on correlation characteristics of OCT images.

Comparison of Spatiotemporal Fusion Models: A Review

Directory of Open Access Journals (Sweden)

Bin Chen

2015-02-01

Full Text Available Simultaneously capturing spatial and temporal dynamics is always a challenge for the remote sensing community. Spatiotemporal fusion has gained wide interest in various applications for its superiority in integrating both fine spatial resolution and frequent temporal coverage. Though many advances have been made in spatiotemporal fusion model development and applications in the past decade, a unified comparison among existing fusion models is still limited. In this research, we classify the models into three categories: transformation-based, reconstruction-based, and learning-based models. The objective of this study is to (i compare four fusion models (STARFM, ESTARFM, ISTAFM, and SPSTFM under a one Landsat-MODIS (L-M pair prediction mode and two L-M pair prediction mode using time-series datasets from the Coleambally irrigation area and Poyang Lake wetland; (ii quantitatively assess prediction accuracy considering spatiotemporal comparability, landscape heterogeneity, and model parameter selection; and (iii discuss the advantages and disadvantages of the three categories of spatiotemporal fusion models.

The correlation between lacunes and microbleeds on magnetic resonance imaging in consecutive 180 patients

International Nuclear Information System (INIS)

Tajitsu, Kenichiro; Yokoyama, Shunichi; Taguci, Yuichiro; Kusumoto, Kazuhiro

2006-01-01

Microbleeds on T2 * -weighted magnetic resonance imaging (MRI) represent a hemorrhagic type of small vessel disease. Small vessel disease causes both intracerebral hemorrhages and lacunar infarctions. We studied clinical background and MRI findings of the patients to clarify the correlation between microbleeds and lacunes. This study consisted of 180 consecutive patients who underwent brain MRI using 1.5T system in our hospital for a year. We obtained T2 * -weighted gradient-echo imaging as well as T1 and T2-weighted images. We statistically identified the factors related to the presence of microbleeds in all patients. The distribution of lacunes and microbleeds on MRI was compared to clarify the correlation of the lesions in the patients who had both lesions. The overall prevalence of microbleeds was 41.1% (74 of 180 patients). Logistic regression analysis indicated that previous stroke, leukoaraiosis and lacunes were significantly correlated with microbleeds. In the patients who have both microbleeds and lacunes, lesions are tended to locate in thalamus and basal ganglia, especially incidence of lacunes are significantly greater compared with other regions. Thirty-six of 398 lesions (9.05%) diagnosed as lacunes with T1- and T2-weighted imaging were demonstrated as microbleeds with T2 * -weighted gradient-echo imaging. Lacunes, leukoaraiosis as a hypertensive change on MRI had statistically significant correlation with the presence of microbleeds. T2 * -weighted gradient-echo imaging should be included in the imaging protocol for cerebrovascular disease, because T1- and T2-weighted imaging recognizing some of the microbleeds as lacunar infarction. (author)

Imaging of brain tumors with histological correlations. 2. ed.

Energy Technology Data Exchange (ETDEWEB)

Drevelegas, Antonios (ed.)

2011-07-01

This volume provides a deeper understanding of the diagnosis of brain tumors by correlating radiographic imaging features with the underlying pathological abnormalities. All modern imaging modalities are used to complete a diagnostic overview of brain tumors with emphasis on recent advances in diagnostic neuroradiology. High-quality illustrations depicting common and uncommon imaging characteristics of a wide range of brain tumors are presented and analysed, drawing attention to the ways in which these characteristics reflect different aspects of pathology. Important theoretical considerations are also discussed. Since the first edition, chapters have been revised and updated and new material has been added, including detailed information on the clinical application of functional MRI and diffusion tensor imaging. Radiologists and other clinicians interested in the current diagnostic approach to brain tumors will find this book to be an invaluable and enlightening clinical tool. (orig.)

Interrogating the Spatiotemporal Landscape of Neuromodulatory GPCR Signaling by Real-Time Imaging of cAMP in Intact Neurons and Circuits

Directory of Open Access Journals (Sweden)

Brian S. Muntean

2018-01-01

Full Text Available Summary: Modulation of neuronal circuits is key to information processing in the brain. The majority of neuromodulators exert their effects by activating G-protein-coupled receptors (GPCRs that control the production of second messengers directly impacting cellular physiology. How numerous GPCRs integrate neuromodulatory inputs while accommodating diversity of incoming signals is poorly understood. In this study, we develop an in vivo tool and analytical suite for analyzing GPCR responses by monitoring the dynamics of a key second messenger, cyclic AMP (cAMP, with excellent quantitative and spatiotemporal resolution in various neurons. Using this imaging approach in combination with CRISPR/Cas9 editing and optogenetics, we interrogate neuromodulatory mechanisms of defined populations of neurons in an intact mesolimbic reward circuit and describe how individual inputs generate discrete second-messenger signatures in a cell- and receptor-specific fashion. This offers a resource for studying native neuronal GPCR signaling in real time. : Muntean et al. develop an in vivo reagent to study processing of neurotransmitter GPCR signals by monitoring real-time dynamics of cAMP responses. They demonstrate application of this approach, in combination with CRISPR/Cas9 gene editing and optogenetics, to interrogate the functional organization of a striatal circuit. Keywords: cAMP, GPCR, neuromodulation, dopamine, striatum, imaging, optogenetics

OCML-based colour image encryption

International Nuclear Information System (INIS)

Rhouma, Rhouma; Meherzi, Soumaya; Belghith, Safya

2009-01-01

The chaos-based cryptographic algorithms have suggested some new ways to develop efficient image-encryption schemes. While most of these schemes are based on low-dimensional chaotic maps, it has been proposed recently to use high-dimensional chaos namely spatiotemporal chaos, which is modelled by one-way coupled-map lattices (OCML). Owing to their hyperchaotic behaviour, such systems are assumed to enhance the cryptosystem security. In this paper, we propose an OCML-based colour image encryption scheme with a stream cipher structure. We use a 192-bit-long external key to generate the initial conditions and the parameters of the OCML. We have made several tests to check the security of the proposed cryptosystem namely, statistical tests including histogram analysis, calculus of the correlation coefficients of adjacent pixels, security test against differential attack including calculus of the number of pixel change rate (NPCR) and unified average changing intensity (UACI), and entropy calculus. The cryptosystem speed is analyzed and tested as well.

Early evaluation of irradiated parotid glands with intravoxel incoherent motion MR imaging: correlation with dynamic contrast-enhanced MR imaging

International Nuclear Information System (INIS)

Zhou, Nan; Chu, Chen; Dou, Xin; Li, Ming; Liu, Song; Zhu, Lijing; Liu, Baorui; Guo, Tingting; Chen, Weibo; He, Jian; Yan, Jing; Zhou, Zhengyang; Yang, Xiaofeng; Liu, Tian

2016-01-01

Radiation-induced parotid damage is one of the most common complications in patients with nasopharyngeal carcinoma (NPC) undergoing radiotherapy (RT). Intravoxel incoherent motion (IVIM) magnetic resonance (MR) imaging has been reported for evaluating irradiated parotid damage. However, the changes of IVIM perfusion-related parameters in irradiated parotid glands have not been confirmed by conventional perfusion measurements obtained from dynamic contrast-enhanced (DCE) MR imaging. The purposes of this study were to monitor radiation-induced parotid damage using IVIM and DCE MR imaging and to investigate the correlations between changes of these MR parameters. Eighteen NPC patients underwent bilateral parotid T1-weighted, IVIM and DCE MR imaging pre-RT (2 weeks before RT) and post-RT (4 weeks after RT). Parotid volume; IVIM MR parameters, including apparent diffusion coefficient (ADC), pure diffusion coefficient (D), pseudo-diffusion coefficient (D*), and perfusion fraction (f); and DCE MR parameters, including maximum relative enhancement (MRE), time to peak (TTP), Wash in Rate, and the degree of xerostomia were recorded. Correlations of parotid MR parameters with mean radiation dose, atrophy rate and xerostomia degree, as well as the relationships between IVIM and DCE MR parameters, were investigated. From pre-RT to post-RT, all of the IVIM and DCE MR parameters increased significantly (p < 0.001 for ADC, D, f, MRE, Wash in Rate; p = 0.024 for D*; p = 0.037 for TTP). Change rates of ADC, f and MRE were negatively correlated with atrophy rate significantly (all p < 0.05). Significant correlations were observed between the change rates of D* and MRE (r = 0.371, p = 0.026) and between the change rates of D* and TTP (r = 0.396, p = 0.017). The intra- and interobserver reproducibility of IVIM and DCE MR parameters was good to excellent (intraclass correlation coefficient, 0.633–0.983). Early radiation-induced changes of parotid glands could be evaluated by IVIM and

Exploiting sparsity of interconnections in spatio-temporal wind speed forecasting using Wavelet Transform

International Nuclear Information System (INIS)

Tascikaraoglu, Akin; Sanandaji, Borhan M.; Poolla, Kameshwar; Varaiya, Pravin

2016-01-01

Highlights: • We propose a spatio-temporal approach for wind speed forecasting. • The method is based on a combination of Wavelet decomposition and structured-sparse recovery. • Our analyses confirm that low-dimensional structures govern the interactions between stations. • Our method particularly shows improvements for profiles with high ramps. • We examine our approach on real data and illustrate its superiority over a set of benchmark models. - Abstract: Integration of renewable energy resources into the power grid is essential in achieving the envisioned sustainable energy future. Stochasticity and intermittency characteristics of renewable energies, however, present challenges for integrating these resources into the existing grid in a large scale. Reliable renewable energy integration is facilitated by accurate wind forecasts. In this paper, we propose a novel wind speed forecasting method which first utilizes Wavelet Transform (WT) for decomposition of the wind speed data into more stationary components and then uses a spatio-temporal model on each sub-series for incorporating both temporal and spatial information. The proposed spatio-temporal forecasting approach on each sub-series is based on the assumption that there usually exists an intrinsic low-dimensional structure between time series data in a collection of meteorological stations. Our approach is inspired by Compressive Sensing (CS) and structured-sparse recovery algorithms. Based on detailed case studies, we show that the proposed approach based on exploiting the sparsity of correlations between a large set of meteorological stations and decomposing time series for higher-accuracy forecasts considerably improve the short-term forecasts compared to the temporal and spatio-temporal benchmark methods.

MR imaging of the hip in avascular necrosis: Radiologic-pathologic correlation

International Nuclear Information System (INIS)

Kang, H.S.; Lee, S.H.; Lee, Y.S.; Cho, Z.H.; Han, M.C.; Kim, C.W.

1987-01-01

MR imaging is the most sensitive modality for diagnosing avascular necrosis (AVN), but there is no established explanation for the change of signal intensity of the osteonecrotic segment. Ten surgically removed femoral heads with AVN underwent MR imaging at 2.0 T. A combination of high gradient strength (0.1 m T/cm) and small radio frequency coil (8 cm in diameter) was used to obtain images with effective thickness of 2.0 mm and pixel dimensions as small as 200 μm. MR images were correlated with high-resolution CT and histologic findings. This paper illustrates how MR images the histologic findings of AVN

Image denoising by exploring external and internal correlations.

Science.gov (United States)

Yue, Huanjing; Sun, Xiaoyan; Yang, Jingyu; Wu, Feng

2015-06-01

Single image denoising suffers from limited data collection within a noisy image. In this paper, we propose a novel image denoising scheme, which explores both internal and external correlations with the help of web images. For each noisy patch, we build internal and external data cubes by finding similar patches from the noisy and web images, respectively. We then propose reducing noise by a two-stage strategy using different filtering approaches. In the first stage, since the noisy patch may lead to inaccurate patch selection, we propose a graph based optimization method to improve patch matching accuracy in external denoising. The internal denoising is frequency truncation on internal cubes. By combining the internal and external denoising patches, we obtain a preliminary denoising result. In the second stage, we propose reducing noise by filtering of external and internal cubes, respectively, on transform domain. In this stage, the preliminary denoising result not only enhances the patch matching accuracy but also provides reliable estimates of filtering parameters. The final denoising image is obtained by fusing the external and internal filtering results. Experimental results show that our method constantly outperforms state-of-the-art denoising schemes in both subjective and objective quality measurements, e.g., it achieves >2 dB gain compared with BM3D at a wide range of noise levels.

Correlation of angiography and MR imaging in cerebral vasculitis

International Nuclear Information System (INIS)

Cloft, H.J.; Phillips, C.D.; Dix, J.E.; McNulty, B.C.; Kallmes, D.F.; Zagardo, M.T.

1999-01-01

Purpose: MR imaging and cerebral angiography were correlated in patients with primary angiitis of the central nervous system (PACNS) to assess the relative roles of these imaging modalities in the diagnosis. Material and Methods: In 9 patients, MR imaging and angiography were compared with regard to the relative involvement of each major vascular territory. Vascular territories assessed were the anterior, middle, and posterior cerebral arteries, and the posterior fossa. Results: All patients had angiographic findings consistent with vasculitis in multiple vascular territories. MR findings ranged from normal to diffusely abnormal. One patient had a completely normal MR investigation. Of 50 territories affected by vasculitis on angiography, 17 (34%) were normal on MR. Conclusion: Relative to cerebral angiography, MR imaging is a poor indicator of the presence or absence of PACNS. Angiography is indicated when clinical suspicion of PACNS is strong, regardless of the findings on MR. (orig.)

Spatio-Temporal Metabolite Profiling of the Barley Germination Process by MALDI MS Imaging.

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Karin Gorzolka

Full Text Available MALDI mass spectrometry imaging was performed to localize metabolites during the first seven days of the barley germination. Up to 100 mass signals were detected of which 85 signals were identified as 48 different metabolites with highly tissue-specific localizations. Oligosaccharides were observed in the endosperm and in parts of the developed embryo. Lipids in the endosperm co-localized in dependency on their fatty acid compositions with changes in the distributions of diacyl phosphatidylcholines during germination. 26 potentially antifungal hordatines were detected in the embryo with tissue-specific localizations of their glycosylated, hydroxylated, and O-methylated derivates. In order to reveal spatio-temporal patterns in local metabolite compositions, multiple MSI data sets from a time series were analyzed in one batch. This requires a new preprocessing strategy to achieve comparability between data sets as well as a new strategy for unsupervised clustering. The resulting spatial segmentation for each time point sample is visualized in an interactive cluster map and enables simultaneous interactive exploration of all time points. Using this new analysis approach and visualization tool germination-dependent developments of metabolite patterns with single MS position accuracy were discovered. This is the first study that presents metabolite profiling of a cereals' germination process over time by MALDI MSI with the identification of a large number of peaks of agronomically and industrially important compounds such as oligosaccharides, lipids and antifungal agents. Their detailed localization as well as the MS cluster analyses for on-tissue metabolite profile mapping revealed important information for the understanding of the germination process, which is of high scientific interest.

Intrasubject correlation between static scan and distribution volume images for [11C]flumazenil PET

International Nuclear Information System (INIS)

Mishina, Masahiro; Senda, Michio; Kimura, Yuichi

2000-01-01

Accumulation of [ 11 C]flumazenil (FMZ) reflects central nervous system benzodiazepine receptor (BZR). We searched for the optimal time for a static PET scan with FMZ as semi-quantitative imaging of BZR distribution. In 10 normal subjects, a dynamic series of decay-corrected PET scans was performed for 60 minutes, and the arterial blood was sampled during the scan to measure radioactivity and labeled metabolites. We generated 13 kinds of ''static scan'' images from the dynamic scan in each subject, and analyzed the pixel correlation for these images versus distribution volume (DV) images. We also analyzed the time for the [ 11 C]FMZ in plasma and tissue to reach the equilibrium. The intra-subject pixel correlation demonstrated that the static scan'' images for the period centering around 30 minutes post-injection had the strongest linear correlation with the DV image. The ratio of radioactivity in the cortex to that in the plasma reached a peak at 40 minutes after injection. Considering the physical decay and patient burden, we conclude that the decay corrected static scan for [ 11 C]FMZ PET as semi-quantitative imaging of BZR distribution is to be optimally acquired from 20 to 40 minutes after injection. (author)

Imaging of congenital mesoblastic nephroma with pathological correlation

International Nuclear Information System (INIS)

Chaudry, Gulraiz; Perez-Atayde, Antonio R.; Ngan, Bo Yee; Gundogan, Munire; Daneman, Alan

2009-01-01

There are a variety of imaging findings for congenital mesoblastic nephroma (CMN) and two main pathological variants: classic and cellular. To determine whether imaging findings in children can predict the likely pathological variant. We reviewed imaging in children with pathology-proven CMN. Imaging findings correlated with gross and histological appearance. In 15 boys and 15 girls with CMN, US was performed in 27, CT in 19, and MRI in 7. Cystic components were readily identified on US; central hemorrhage was better differentiated on CT. MRI demonstrated high sensitivity for both. Histology confirmed classic CMN in 13 children, cellular CMN in 14 and ''mixed'' CMN in 3. Age at presentation was significantly higher in children with the cellular variant. Of 15 solid or predominantly solid tumors and 10 lesions with a hypoechoic ring, 12 and 7, respectively, had pathology consistent with classic CMN. In contrast, five of seven with intratumoral hemorrhage and all with a large cystic/necrotic component had pathology consistent with the cellular variant. The imaging appearance of CMN is often determined by the pathological type of tumor. Findings suggestive of the classic variant include a peripheral hypoechoic ring or large solid component. In comparison, cystic/necrotic change and hemorrhage is much more common in cellular CMN. (orig.)

Visualization and assessment of spatio-temporal covariance properties

KAUST Repository

Huang, Huang

2017-11-23

Spatio-temporal covariances are important for describing the spatio-temporal variability of underlying random fields in geostatistical data. For second-order stationary random fields, there exist subclasses of covariance functions that assume a simpler spatio-temporal dependence structure with separability and full symmetry. However, it is challenging to visualize and assess separability and full symmetry from spatio-temporal observations. In this work, we propose a functional data analysis approach that constructs test functions using the cross-covariances from time series observed at each pair of spatial locations. These test functions of temporal lags summarize the properties of separability or symmetry for the given spatial pairs. We use functional boxplots to visualize the functional median and the variability of the test functions, where the extent of departure from zero at all temporal lags indicates the degree of non-separability or asymmetry. We also develop a rank-based nonparametric testing procedure for assessing the significance of the non-separability or asymmetry. Essentially, the proposed methods only require the analysis of temporal covariance functions. Thus, a major advantage over existing approaches is that there is no need to estimate any covariance matrix for selected spatio-temporal lags. The performances of the proposed methods are examined by simulations with various commonly used spatio-temporal covariance models. To illustrate our methods in practical applications, we apply it to real datasets, including weather station data and climate model outputs.

Idiopathic interstitial pneumonias: imaging-pathology correlation

International Nuclear Information System (INIS)

Ellis, Stephen M.; Hansell, David M.

2002-01-01

The terminology related to idiopathic interstitial pneumonia (IIP) remains confusing and in some cases wholly inaccurate. In addition, a greater understanding of the correlation between high-resolution computed tomography (HRCT) appearances and the corresponding histopathological changes found in the interstitial pneumonias has resulted in a crucial role for HRCT in the investigation of IIPs. The role of the radiologist is becoming increasingly important with a strong emphasis on establishing a diagnosis without resorting to lung biopsy. We aim to clarify the current classification of the IIPs highlighting their clinical, pathological and imaging characteristics in order to assist the radiologist in performing their increasingly important diagnostic role. (orig.)

Dynamic decomposition of spatiotemporal neural signals.

Directory of Open Access Journals (Sweden)

Luca Ambrogioni

2017-05-01

Full Text Available Neural signals are characterized by rich temporal and spatiotemporal dynamics that reflect the organization of cortical networks. Theoretical research has shown how neural networks can operate at different dynamic ranges that correspond to specific types of information processing. Here we present a data analysis framework that uses a linearized model of these dynamic states in order to decompose the measured neural signal into a series of components that capture both rhythmic and non-rhythmic neural activity. The method is based on stochastic differential equations and Gaussian process regression. Through computer simulations and analysis of magnetoencephalographic data, we demonstrate the efficacy of the method in identifying meaningful modulations of oscillatory signals corrupted by structured temporal and spatiotemporal noise. These results suggest that the method is particularly suitable for the analysis and interpretation of complex temporal and spatiotemporal neural signals.

Cross-correlated imaging of distributed mode filtering rod fiber

DEFF Research Database (Denmark)

Laurila, Marko; Barankov, Roman; Jørgensen, Mette Marie

2013-01-01

We analyze the modal properties of an 85μm core distributed mode filtering rod fiber using cross-correlated (C2) imaging. We evaluate suppression of higher-order modes (HOMs) under severely misaligned mode excitation and identify a single-mode regime where HOMs are suppressed by more than 20dB....

Theta variation and spatiotemporal scaling along the septotemporal axis of the hippocampus

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Lauren L Long

2015-03-01

Full Text Available Hippocampal theta has been related to locomotor speed, attention, anxiety, sensorimotor integration and memory among other emergent phenomena. One difficulty in understanding the function of theta is that the hippocampus (HPC modulates voluntary behavior at the same time that it processes sensory input. Both functions are correlated with characteristic changes in theta indices. The current review highlights a series of studies examining theta local field potential (LFP signals across the septotemporal or longitudinal axis of the HPC. While the theta signal is coherent throughout the entirety of the HPC, the amplitude, but not the frequency, of theta varies significantly across its three-dimensional expanse. We suggest that the theta signal offers a rich vein of information about how distributed neuronal ensembles support emergent function. Further, we speculate that emergent function across the long axis varies with respect to spatiotemporal scale. Thus, septal hippocampus processes details of the proximal spatiotemporal environment while more temporal aspects process larger spaces and wider time-scales. The degree to which emergent functions are supported by the synchronization of theta across the septotemporal axis is an open question. Our working model is that theta synchrony serves to bind ensembles representing varying resolutions of spatiotemporal information at interdependent septotemporal areas of the HPC. Such synchrony and cooperative interactions along the septotemporal axis likely support memory formation and subsequent consolidation and retrieval.

Development of comprehensive image processing technique for differential diagnosis of liver disease by using multi-modality images. Pixel-based cross-correlation method using a profile

International Nuclear Information System (INIS)

Inoue, Akira; Okura, Yasuhiko; Akiyama, Mitoshi; Ishida, Takayuki; Kawashita, Ikuo; Ito, Katsuyoshi; Matsunaga, Naofumi; Sanada, Taizo

2009-01-01

Imaging techniques such as high magnetic field imaging and multidetector-row CT have been markedly improved recently. The final image-reading systems easily produce more than a thousand diagnostic images per patient. Therefore, we developed a comprehensive cross-correlation processing technique using multi-modality images, in order to decrease the considerable time and effort involved in the interpretation of a radiogram (multi-formatted display and/or stack display method, etc). In this scheme, the criteria of an attending radiologist for the differential diagnosis of liver cyst, hemangioma of liver, hepatocellular carcinoma, and metastatic liver cancer on magnetic resonance images with various sequences and CT images with and without contrast enhancement employ a cross-correlation coefficient. Using a one-dimensional cross-correlation method, comprehensive image processing could be also adapted for various artifacts (some depending on modality imaging, and some on patients), which may be encountered at the clinical scene. This comprehensive image-processing technique could assist radiologists in the differential diagnosis of liver diseases. (author)

Estimation bias from using nonlinear Fourier plane correlators for sub-pixel image shift measurement and implications for the binary joint transform correlator

Science.gov (United States)

Grycewicz, Thomas J.; Florio, Christopher J.; Franz, Geoffrey A.; Robinson, Ross E.

2007-09-01

When using Fourier plane digital algorithms or an optical correlator to measure the correlation between digital images, interpolation by center-of-mass or quadratic estimation techniques can be used to estimate image displacement to the sub-pixel level. However, this can lead to a bias in the correlation measurement. This bias shifts the sub-pixel output measurement to be closer to the nearest pixel center than the actual location. The paper investigates the bias in the outputs of both digital and optical correlators, and proposes methods to minimize this effect. We use digital studies and optical implementations of the joint transform correlator to demonstrate optical registration with accuracies better than 0.1 pixels. We use both simulations of image shift and movies of a moving target as inputs. We demonstrate bias error for both center-of-mass and quadratic interpolation, and discuss the reasons that this bias is present. Finally, we suggest measures to reduce or eliminate the bias effects. We show that when sub-pixel bias is present, it can be eliminated by modifying the interpolation method. By removing the bias error, we improve registration accuracy by thirty percent.

Automated method and system for the alignment and correlation of images from two different modalities

Science.gov (United States)

Giger, Maryellen L.; Chen, Chin-Tu; Armato, Samuel; Doi, Kunio

1999-10-26

A method and system for the computerized registration of radionuclide images with radiographic images, including generating image data from radiographic and radionuclide images of the thorax. Techniques include contouring the lung regions in each type of chest image, scaling and registration of the contours based on location of lung apices, and superimposition after appropriate shifting of the images. Specific applications are given for the automated registration of radionuclide lungs scans with chest radiographs. The method in the example given yields a system that spatially registers and correlates digitized chest radiographs with V/Q scans in order to correlate V/Q functional information with the greater structural detail of chest radiographs. Final output could be the computer-determined contours from each type of image superimposed on any of the original images, or superimposition of the radionuclide image data, which contains high activity, onto the radiographic chest image.

New robust algorithm for tracking cells in videos of Drosophila morphogenesis based on finding an ideal path in segmented spatio-temporal cellular structures.

Science.gov (United States)

Bellaïche, Yohanns; Bosveld, Floris; Graner, François; Mikula, Karol; Remesíková, Mariana; Smísek, Michal

2011-01-01

In this paper, we present a novel algorithm for tracking cells in time lapse confocal microscopy movie of a Drosophila epithelial tissue during pupal morphogenesis. We consider a 2D + time video as a 3D static image, where frames are stacked atop each other, and using a spatio-temporal segmentation algorithm we obtain information about spatio-temporal 3D tubes representing evolutions of cells. The main idea for tracking is the usage of two distance functions--first one from the cells in the initial frame and second one from segmented boundaries. We track the cells backwards in time. The first distance function attracts the subsequently constructed cell trajectories to the cells in the initial frame and the second one forces them to be close to centerlines of the segmented tubular structures. This makes our tracking algorithm robust against noise and missing spatio-temporal boundaries. This approach can be generalized to a 3D + time video analysis, where spatio-temporal tubes are 4D objects.

Preliminary study on the correlation between color measurement of dyed polyester and its image files

Science.gov (United States)

Park, Y. K.; Park, Y. C.

2017-10-01

As the internet becomes more popular, buyers send image files to manufacturers instead of sending swatches. However, this method may cause problems because different from the monitor between the buyer and the manufacturer, and also there is a problem depending on the light source. In order to overcome these problems, we investigated the relationship between color measurement values of dyed fabrics and RGB values of image files. The RGB values of image files tended to decrease with increasing dye concentration in all three colors. Correlation between RGB values and a*, b* values was observed at low concentration, but there was little correlation at high concentration. In the case of yellow color, there is no correlation between the L*a*b* values obtained from the dyed fabric and RGB values obtained from the image file.

Detecting spatio-temporal modes in multivariate data by entropy field decomposition

International Nuclear Information System (INIS)

Frank, Lawrence R; Galinsky, Vitaly L

2016-01-01

A new data analysis method that addresses a general problem of detecting spatio-temporal variations in multivariate data is presented. The method utilizes two recent and complimentary general approaches to data analysis, information field theory (IFT) and entropy spectrum pathways (ESPs). Both methods reformulate and incorporate Bayesian theory, thus use prior information to uncover underlying structure of the unknown signal. Unification of ESP and IFT creates an approach that is non-Gaussian and nonlinear by construction and is found to produce unique spatio-temporal modes of signal behavior that can be ranked according to their significance, from which space–time trajectories of parameter variations can be constructed and quantified. Two brief examples of real world applications of the theory to the analysis of data bearing completely different, unrelated nature, lacking any underlying similarity, are also presented. The first example provides an analysis of resting state functional magnetic resonance imaging data that allowed us to create an efficient and accurate computational method for assessing and categorizing brain activity. The second example demonstrates the potential of the method in the application to the analysis of a strong atmospheric storm circulation system during the complicated stage of tornado development and formation using data recorded by a mobile Doppler radar. Reference implementation of the method will be made available as a part of the QUEST toolkit that is currently under development at the Center for Scientific Computation in Imaging. (paper)

Controlling spatiotemporal chaos in one- and two-dimensional coupled logistic map lattices

International Nuclear Information System (INIS)

Astakhov, V.V.; Anishchenko, V.S.; Strelkova, G.I.; Shabunin, A.V.

1996-01-01

A method of control of spatiotemporal chaos in lattices of coupled maps is proposed in this work. Forms of spatiotemporal perturbations of a system parameter are analytically determined for one- and two-dimensional logistic map lattices with different kinds of coupling to stabilize chosen spatiotemporal states previously unstable. The results are illustrated by numerical simulation. Controlled transition from the regime of spatiotemporal chaos to the previously chosen regular spatiotemporal patterns is demonstrated. copyright 1996 American Institute of Physics

Spatiotemporal psychopathology I: No rest for the brain's resting state activity in depression? Spatiotemporal psychopathology of depressive symptoms.

Science.gov (United States)

Northoff, Georg

2016-01-15

Despite intense neurobiological investigation in psychiatric disorders like major depressive disorder (MDD), the basic disturbance that underlies the psychopathological symptoms of MDD remains, nevertheless, unclear. Neuroimaging has focused mainly on the brain's extrinsic activity, specifically task-evoked or stimulus-induced activity, as related to the various sensorimotor, affective, cognitive, and social functions. Recently, the focus has shifted to the brain's intrinsic activity, otherwise known as its resting state activity. While various abnormalities have been observed during this activity, their meaning and significance for depression, along with its various psychopathological symptoms, are yet to be defined. Based on findings in healthy brain resting state activity and its particular spatial and temporal structure - defined in a functional and physiological sense rather than anatomical and structural - I claim that the various depressive symptoms are spatiotemporal disturbances of the resting state activity and its spatiotemporal structure. This is supported by recent findings that link ruminations and increased self-focus in depression to abnormal spatial organization of resting state activity. Analogously, affective and cognitive symptoms like anhedonia, suicidal ideation, and thought disorder can be traced to an increased focus on the past, increased past-focus as basic temporal disturbance o the resting state. Based on these findings, I conclude that the various depressive symptoms must be conceived as spatiotemporal disturbances of the brain's resting state's activity and its spatiotemporal structure. Importantly, this entails a new form of psychopathology, "Spatiotemporal Psychopathology" that directly links the brain and psyche, therefore having major diagnostic and therapeutic implications for clinical practice. Copyright © 2015 Elsevier B.V. All rights reserved.

Spatio-temporal environmental correlation and population variability in simple metacommunities.

Directory of Open Access Journals (Sweden)

Lasse Ruokolainen

Full Text Available Natural populations experience environmental conditions that vary across space and over time. This variation is often correlated between localities depending on the geographical separation between them, and different species can respond to local environmental fluctuations similarly or differently, depending on their adaptation. How this emerging structure in environmental correlation (between-patches and between-species affects spatial community dynamics is an open question. This paper aims at a general understanding of the interactions between the environmental correlation structure and population dynamics in spatial networks of local communities (metacommunities, by studying simple two-patch, two-species systems. Three different pairs of interspecific interactions are considered: competition, consumer-resource interaction, and host-parasitoid interaction. While the results paint a relatively complex picture of the effect of environmental correlation, the interaction between environmental forcing, dispersal, and local interactions can be understood via two mechanisms. While increasing between-patch environmental correlation couples immigration and local densities (destabilising effect, the coupling between local populations under increased between-species environmental correlation can either amplify or dampen population fluctuations, depending on the patterns in density dependence. This work provides a unifying framework for modelling stochastic metacommunities, and forms a foundation for a better understanding of population responses to environmental fluctuations in natural systems.

Spatiotemporal patterns formed by deformed adhesive in peeling

International Nuclear Information System (INIS)

Yamazaki, Yoshihiro; Toda, Akihiko

2007-01-01

Dynamical properties of peeling an adhesive tape are investigated experimentally as an analogy of sliding friction. An adhesive tape is peeled by pulling an elastic spring connected to the tape. Controlling its spring constant k and pulling speed V, peel force is measured and spatiotemporal patterns formed on the peeled tape by deformed adhesive are observed. It is found that there exist two kinds of adhesive state in peeling front. The emergence of multiple states is caused by the stability of a characteristic structure (tunnel structure) formed by deformed adhesive. Tunnel structures are distributed spatiotemporally on adhesive tape after peeling. Based on the spatiotemporal distribution, a morphology-dynamical phase diagram is constructed on k-V space and is divided into the four regions: (A) uniform pattern with tunnel structure, (B) uniform pattern without tunnel structure, (C) striped pattern with oscillatory peeling, and (D) spatiotemporally coexistent pattern

Atlantoaxial subluxation. Radiography and magnetic resonance imaging correlated to myelopathy

Energy Technology Data Exchange (ETDEWEB)

Yamashita, Y.; Takahashi, M.; Sakamoto, Y.; Kojima, R.

Twenty-nine patients with atlantoaxial subluxation (18 with rheumatoid arthritis, 2 due to trauma, 4 with os odontoideum, and one each with polyarteritis nodosa, rheumatic fever, Klippel-Feil syndrome, achondroplasia, and cause unknown) were evaluated using a 0.22 tesla resistive MRI unit. Cord compression was classified into four grades according to the degree on magnetic resonance imaging. There were 7 patients with no thecal sac compression (grade 0), 10 with a minimal degree of subarachnoid space compression without cord compression (grade 1), 7 with mild cord compression (grade 2), and 5 with severe cord compression or cord atrophy (grade 3). Although the severity of myelopathy showed poor correlation with the atlantodental interval on conventional radiography, high correlation was observed between MR grading and the degree of myelopathy. The high signal intensity foci were observed in 7 or 12 patients with cord compression (grades 2 and 3) on T2 weighted images. Other frequently observed findings in rheumatoid arthritis included soft tissue masses of low to intermediate signal intensity in the paraodontoid space, erosions of the odontoid processes, and atlanto-axial impaction on T1 and T2 weighted images.

Measurement of spatial correlation functions using image processing techniques

International Nuclear Information System (INIS)

Berryman, J.G.

1985-01-01

A procedure for using digital image processing techniques to measure the spatial correlation functions of composite heterogeneous materials is presented. Methods for eliminating undesirable biases and warping in digitized photographs are discussed. Fourier transform methods and array processor techniques for calculating the spatial correlation functions are treated. By introducing a minimal set of lattice-commensurate triangles, a method of sorting and storing the values of three-point correlation functions in a compact one-dimensional array is developed. Examples are presented at each stage of the analysis using synthetic photographs of cross sections of a model random material (the penetrable sphere model) for which the analytical form of the spatial correlations functions is known. Although results depend somewhat on magnification and on relative volume fraction, it is found that photographs digitized with 512 x 512 pixels generally have sufficiently good statistics for most practical purposes. To illustrate the use of the correlation functions, bounds on conductivity for the penetrable sphere model are calculated with a general numerical scheme developed for treating the singular three-dimensional integrals which must be evaluated

Intramuscular vascular malformations of an extremity: findings on MR imaging and pathologic correlation

International Nuclear Information System (INIS)

Kim, E.Y.; Ahn, J.M.; Yoon, H.K.; Do, Y.S.; Kim, S.H.; Choo, S.W.; Choo, I.W.; Suh, Y.L.; Kim, S.M.; Kang, H.S.

1999-01-01

Objective. To analyze the findings of intramuscular vascular malformations of an extremity on MR imaging and to correlate these findings with histopathologic examination.Design and patients. The findings on MR imaging and the medical records of 14 patients with an intramuscular vascular malformation of the extremity were retrospectively studied. All patients underwent surgical excision. Diagnoses were based on the results of pathologic examination. Findings on MR imaging were noted and correlated with the histopathologic findings.Results. Intramuscular vascular malformations of an extremity showed multi-septate, honeycomb, or mixed appearance on MR imaging. Multi-septate areas correlated with dilated and communicating vascular spaces with flattened endothelium. Honeycomb areas corresponded to vascular spaces with inconspicuous small lumina and thickened vascular walls. Areas of increased signal intensity on T2-weighted images were found in all intramuscular vascular malformations. Infiltrative margins were more commonly seen in intramuscular lymphaticovenous malformations. Adherence to neurovascular structures and orientation of the lesion along the long axis of the affected muscle were more commonly seen in intramuscular venous malformations.Conclusions. Intramuscular vascular malformations showed either a multi-septate, honeycomb, or mixed appearance, reflecting the size of the vascular spaces and the thickness of the smooth muscles of the vessel walls. Prediction of the subtype of an intramuscular vascular malformation of an extremity on MR imaging seems to be difficult, although there are associated findings that may be helpful in the differential diagnosis of each subtype. (orig.)

A symmetrical image encryption scheme in wavelet and time domain

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Luo, Yuling; Du, Minghui; Liu, Junxiu

2015-02-01

There has been an increasing concern for effective storages and secure transactions of multimedia information over the Internet. Then a great variety of encryption schemes have been proposed to ensure the information security while transmitting, but most of current approaches are designed to diffuse the data only in spatial domain which result in reducing storage efficiency. A lightweight image encryption strategy based on chaos is proposed in this paper. The encryption process is designed in transform domain. The original image is decomposed into approximation and detail components using integer wavelet transform (IWT); then as the more important component of the image, the approximation coefficients are diffused by secret keys generated from a spatiotemporal chaotic system followed by inverse IWT to construct the diffused image; finally a plain permutation is performed for diffusion image by the Logistic mapping in order to reduce the correlation between adjacent pixels further. Experimental results and performance analysis demonstrate the proposed scheme is an efficient, secure and robust encryption mechanism and it realizes effective coding compression to satisfy desirable storage.

Adductor-related groin pain in athletes: correlation of MR imaging with clinical findings

International Nuclear Information System (INIS)

Robinson, P.; Barron, D.A.; Grainger, A.J.; O'Connor, P.J.; Parsons, W.; Schilders, E.M.G.

2004-01-01

To evaluate gadolinium-enhanced MR imaging in athletes with chronic groin pain and correlate with the clinical features. MR examinations performed in 52 athletes (51 male, 1 female; median age 26 years) with chronic groin pain and 6 asymptomatic control athletes (6 male; median age 29 years) were independently reviewed by two radiologists masked to the clinical details. Symptom duration (median 6 months) and clinical side of severity were recorded. Anatomical areas in the pelvis were scored for abnormality (as normal, mildly abnormal or abnormal) and an overall assessment for side distribution of abnormality was recorded, initially without post-gadolinium sequences and then, 3 weeks later (median 29 days), the post-gadolinium sequences only. Correlation between radiological and clinical abnormality was calculated by Spearman's correlation. Abnormal anterior pubis and enthesis enhancement significantly correlated with clinical side for both radiologists (both P=0.008). Abnormal anterior pubis and adductor longus enthesis oedema was significant for one radiologist (P=0.009). All other features showed no significant correlation (P>0.05). In the control cases there was no soft tissue abnormality but symphyseal irregularity was present (n=2). For both radiologists assessment of imaging side severity significantly correlated with clinical side for post-gadolinium (P=0.048 and P=0.023) but not non-gadolinium sequences (P>0.05). The extent and side of anterior pubis and adductor longus enthesis abnormality on MR imaging significantly and reproducibly correlates with the athletes' current symptoms in chronic adductor-related groin pain. (orig.)

MEG source imaging method using fast L1 minimum-norm and its applications to signals with brain noise and human resting-state source amplitude images.

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Huang, Ming-Xiong; Huang, Charles W; Robb, Ashley; Angeles, AnneMarie; Nichols, Sharon L; Baker, Dewleen G; Song, Tao; Harrington, Deborah L; Theilmann, Rebecca J; Srinivasan, Ramesh; Heister, David; Diwakar, Mithun; Canive, Jose M; Edgar, J Christopher; Chen, Yu-Han; Ji, Zhengwei; Shen, Max; El-Gabalawy, Fady; Levy, Michael; McLay, Robert; Webb-Murphy, Jennifer; Liu, Thomas T; Drake, Angela; Lee, Roland R

2014-01-01

The present study developed a fast MEG source imaging technique based on Fast Vector-based Spatio-Temporal Analysis using a L1-minimum-norm (Fast-VESTAL) and then used the method to obtain the source amplitude images of resting-state magnetoencephalography (MEG) signals for different frequency bands. The Fast-VESTAL technique consists of two steps. First, L1-minimum-norm MEG source images were obtained for the dominant spatial modes of sensor-waveform covariance matrix. Next, accurate source time-courses with millisecond temporal resolution were obtained using an inverse operator constructed from the spatial source images of Step 1. Using simulations, Fast-VESTAL's performance was assessed for its 1) ability to localize multiple correlated sources; 2) ability to faithfully recover source time-courses; 3) robustness to different SNR conditions including SNR with negative dB levels; 4) capability to handle correlated brain noise; and 5) statistical maps of MEG source images. An objective pre-whitening method was also developed and integrated with Fast-VESTAL to remove correlated brain noise. Fast-VESTAL's performance was then examined in the analysis of human median-nerve MEG responses. The results demonstrated that this method easily distinguished sources in the entire somatosensory network. Next, Fast-VESTAL was applied to obtain the first whole-head MEG source-amplitude images from resting-state signals in 41 healthy control subjects, for all standard frequency bands. Comparisons between resting-state MEG sources images and known neurophysiology were provided. Additionally, in simulations and cases with MEG human responses, the results obtained from using conventional beamformer technique were compared with those from Fast-VESTAL, which highlighted the beamformer's problems of signal leaking and distorted source time-courses. © 2013.

Textural analysis of early-phase spatiotemporal changes in contrast enhancement of breast lesions imaged with an ultrafast DCE-MRI protocol.

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Milenković, Jana; Dalmış, Mehmet Ufuk; Žgajnar, Janez; Platel, Bram

2017-09-01

New ultrafast view-sharing sequences have enabled breast dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) to be performed at high spatial and temporal resolution. The aim of this study is to evaluate the diagnostic potential of textural features that quantify the spatiotemporal changes of the contrast-agent uptake in computer-aided diagnosis of malignant and benign breast lesions imaged with high spatial and temporal resolution DCE-MRI. The proposed approach is based on the textural analysis quantifying the spatial variation of six dynamic features of the early-phase contrast-agent uptake of a lesion's largest cross-sectional area. The textural analysis is performed by means of the second-order gray-level co-occurrence matrix, gray-level run-length matrix and gray-level difference matrix. This yields 35 textural features to quantify the spatial variation of each of the six dynamic features, providing a feature set of 210 features in total. The proposed feature set is evaluated based on receiver operating characteristic (ROC) curve analysis in a cross-validation scheme for random forests (RF) and two support vector machine classifiers, with linear and radial basis function (RBF) kernel. Evaluation is done on a dataset with 154 breast lesions (83 malignant and 71 benign) and compared to a previous approach based on 3D morphological features and the average and standard deviation of the same dynamic features over the entire lesion volume as well as their average for the smaller region of the strongest uptake rate. The area under the ROC curve (AUC) obtained by the proposed approach with the RF classifier was 0.8997, which was significantly higher (P = 0.0198) than the performance achieved by the previous approach (AUC = 0.8704) on the same dataset. Similarly, the proposed approach obtained a significantly higher result for both SVM classifiers with RBF (P = 0.0096) and linear kernel (P = 0.0417) obtaining AUC of 0.8876 and 0.8548, respectively

Spatio-temporal characteristics of self-pulse in hollow cathode discharge

International Nuclear Information System (INIS)

Jing, Ha; He, Shoujie

2015-01-01

The characteristics of self-pulse in hollow cathode discharge at low pressure have been investigated. The voltage-current (V-I) curves, the influence of ballast resistor on the self-pulses, and the evolution of current and voltage are measured. Both the axial and radial spatio-temporal discharge images of self-pulse are recorded. The results show that there exists the hysteresis effect in the present hollow cathode discharge. The high value of ballast resistors is favourable for the observation of self-pulses. The process of the self-pulse can be divided into three stages from the temporal discharge images, i.e., the pre-discharge, the transition from mainly axial electric field to mainly radial electric field, and the decaying process. The self-pulse is suggested to originate from the mode transition of the discharge in essence

Image Correlation Pattern Optimization for Micro-Scale In-Situ Strain Measurements

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Bomarito, G. F.; Hochhalter, J. D.; Cannon, A. H.

2016-01-01

The accuracy and precision of digital image correlation (DIC) is a function of three primary ingredients: image acquisition, image analysis, and the subject of the image. Development of the first two (i.e. image acquisition techniques and image correlation algorithms) has led to widespread use of DIC; however, fewer developments have been focused on the third ingredient. Typically, subjects of DIC images are mechanical specimens with either a natural surface pattern or a pattern applied to the surface. Research in the area of DIC patterns has primarily been aimed at identifying which surface patterns are best suited for DIC, by comparing patterns to each other. Because the easiest and most widespread methods of applying patterns have a high degree of randomness associated with them (e.g., airbrush, spray paint, particle decoration, etc.), less effort has been spent on exact construction of ideal patterns. With the development of patterning techniques such as microstamping and lithography, patterns can be applied to a specimen pixel by pixel from a patterned image. In these cases, especially because the patterns are reused many times, an optimal pattern is sought such that error introduced into DIC from the pattern is minimized. DIC consists of tracking the motion of an array of nodes from a reference image to a deformed image. Every pixel in the images has an associated intensity (grayscale) value, with discretization depending on the bit depth of the image. Because individual pixel matching by intensity value yields a non-unique scale-dependent problem, subsets around each node are used for identification. A correlation criteria is used to find the best match of a particular subset of a reference image within a deformed image. The reader is referred to references for enumerations of typical correlation criteria. As illustrated by Schreier and Sutton and Lu and Cary systematic errors can be introduced by representing the underlying deformation with under

A hybrid spatio-temporal data indexing method for trajectory databases.

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Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

2014-07-21

In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

Directory of Open Access Journals (Sweden)

Shengnan Ke

2014-07-01

Full Text Available In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type.

A Hybrid Spatio-Temporal Data Indexing Method for Trajectory Databases

Science.gov (United States)

Ke, Shengnan; Gong, Jun; Li, Songnian; Zhu, Qing; Liu, Xintao; Zhang, Yeting

2014-01-01

In recent years, there has been tremendous growth in the field of indoor and outdoor positioning sensors continuously producing huge volumes of trajectory data that has been used in many fields such as location-based services or location intelligence. Trajectory data is massively increased and semantically complicated, which poses a great challenge on spatio-temporal data indexing. This paper proposes a spatio-temporal data indexing method, named HBSTR-tree, which is a hybrid index structure comprising spatio-temporal R-tree, B*-tree and Hash table. To improve the index generation efficiency, rather than directly inserting trajectory points, we group consecutive trajectory points as nodes according to their spatio-temporal semantics and then insert them into spatio-temporal R-tree as leaf nodes. Hash table is used to manage the latest leaf nodes to reduce the frequency of insertion. A new spatio-temporal interval criterion and a new node-choosing sub-algorithm are also proposed to optimize spatio-temporal R-tree structures. In addition, a B*-tree sub-index of leaf nodes is built to query the trajectories of targeted objects efficiently. Furthermore, a database storage scheme based on a NoSQL-type DBMS is also proposed for the purpose of cloud storage. Experimental results prove that HBSTR-tree outperforms TB*-tree in some aspects such as generation efficiency, query performance and query type. PMID:25051028

Displacement measurement with nanoscale resolution using a coded micro-mark and digital image correlation

Science.gov (United States)

Huang, Wei; Ma, Chengfu; Chen, Yuhang

2014-12-01

A method for simple and reliable displacement measurement with nanoscale resolution is proposed. The measurement is realized by combining a common optical microscopy imaging of a specially coded nonperiodic microstructure, namely two-dimensional zero-reference mark (2-D ZRM), and subsequent correlation analysis of the obtained image sequence. The autocorrelation peak contrast of the ZRM code is maximized with well-developed artificial intelligence algorithms, which enables robust and accurate displacement determination. To improve the resolution, subpixel image correlation analysis is employed. Finally, we experimentally demonstrate the quasi-static and dynamic displacement characterization ability of a micro 2-D ZRM.

Multimodal imaging in cerebral gliomas and its neuropathological correlation

Energy Technology Data Exchange (ETDEWEB)

Gempt, Jens, E-mail: jens.gempt@lrz.tum.de [Neurochirurgische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Soehngen, Eric [Abteilung für Neuroradiologie, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Abteilung für Neuropathologie des Instituts für Allgemeine Pathologie und Pathologische Anatomie, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Förster, Stefan [Nuklearmedizinische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Ryang, Yu-Mi [Neurochirurgische Klinik und Poliklinik, Klinikum rechts der Isar, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); Schlegel, Jürgen [Abteilung für Neuropathologie des Instituts für Allgemeine Pathologie und Pathologische Anatomie, Technische Universität München, Ismaninger Str. 22, 81675 München (Germany); and others

2014-05-15

Introduction: Concerning the preoperative clinical diagnostic work-up of glioma patients, tumor heterogeneity challenges the oncological therapy. The current study assesses the performance of a multimodal imaging approach to differentiate between areas in malignant gliomas and to investigate the extent to which such a combinatorial imaging approach might predict the underlying histology. Methods: Prior to surgical resection, patients harboring intracranial gliomas underwent MRIs (MR-S, PWI) and {sup 18}F-FET-PETs. Intratumoral and peritumoral biopsy targets were defined, by MRI only, by FET-PET only, and by MRI and FET-PET combined, and biopsied prior to surgical resection and which then received separate histopathological examinations. Results: In total, 38 tissue samples were acquired (seven glioblastomas, one anaplastic astrocytoma, one anaplastic oligoastrocytoma, one diffuse astrocytoma, and one oligoastrocytoma) and underwent histopathological analysis. The highest mean values of Mib1 and CD31 were found in the target point “T’ defined by MRI and FET-PET combined. A significant correlation between NAA/Cr and PET tracer uptake (−0.845, p < 0.05) as well as Cho/Cr ratio and cell density (0.742, p < 0.05) and NAA/Cr ratio and MIB-1 (−0761, p < 0.05) was disclosed for this target point, though not for target points defined by MRI and FET-PET alone. Conclusion: Multimodal-imaging-guided stereotactic biopsy correlated more with histological malignancy indices, such as cell density and MIB-1 labeling, than targets that were based solely on the highest amino acid uptake or contrast enhancement on MRI. The results of our study indicate that a combined PET-MR multimodal imaging approach bears potential benefits in detecting glioma heterogeneity.

Assessing the Defoliation of Pine Forests in a Long Time-Series and Spatiotemporal Prediction of the Defoliation Using Landsat Data

Directory of Open Access Journals (Sweden)

Chenghao Zhu

2018-02-01

Full Text Available Pine forests (Pinus tabulaeformis have been in danger of defoliation by a caterpillar in the west Liaoning province of China for more than thirty years. This paper aims to assess and predict the degree of damage to pine forests by using remote sensing and ancillary data. Through regression analysis of the pine foliage remaining ratios of field plots with several vegetation indexes of Landsat data, a feasible inversion model was obtained to detect the degree of damage using the Normalized Difference Infrared Index of 5th band (NDII5. After comparing the inversion result of the degree of damage to the pine in 29 years and the historical damage record, quantized results of damage assessment in a long time-series were accurately obtained. Based on the correlation analysis between meteorological variables and the degree of damage from 1984 to 2015, the average degree of damage was predicted in temporal scale. By adding topographic and other variables, a linear prediction model in spatiotemporal scale was constructed. The spatiotemporal model was based on 5015 public pine points for 24 years and reached 0.6169 in the correlation coefficient. This paper provided a feasible and quantitative method in the spatiotemporal prediction of forest pest occurrence by remote sensing.

[Spatiotemporal variation of vegetation in northern Shaanxi of Northwest China based on SPOT-VGT NDVI].

Science.gov (United States)

Yang, Yan-Zheng; Zhao, Peng-Xiang; Hao, Hong-Ke; Chang, Ming

2012-07-01

By using 1998-2010 SPOT-VGT NDVI images, this paper analyzed the spatiotemporal variation of vegetation in northern Shaanxi. In 1998-2010, the NDVI in northern Shaanxi had an obvious seasonal variation. The average monthly NDVI was the minimum (0.14) in January and the maximum (0.46) in August, with a mean value of 0.28. The average annual NDVI presented an overall increasing trend, indicating that the vegetation in this area was in restoring. Spatially, the restoration of vegetation in this area was concentrated in central south part, and the degradation mainly occurred in the north of the Great Wall. Air temperature and precipitation were the important climate factors affecting the variation of vegetation, with the linear correlation coefficients to NDVI being 0.72 and 0.58, respectively. The regions with better restored vegetation were mainly on the slopes of 15 degrees-25 degrees, indicating that the Program of Conversion of Cropland to Forestland and Grassland had a favorable effect in the vegetation restoration in northern Shaanxi.

A Kinect based sign language recognition system using spatio-temporal features

Science.gov (United States)

Memiş, Abbas; Albayrak, Songül

2013-12-01

This paper presents a sign language recognition system that uses spatio-temporal features on RGB video images and depth maps for dynamic gestures of Turkish Sign Language. Proposed system uses motion differences and accumulation approach for temporal gesture analysis. Motion accumulation method, which is an effective method for temporal domain analysis of gestures, produces an accumulated motion image by combining differences of successive video frames. Then, 2D Discrete Cosine Transform (DCT) is applied to accumulated motion images and temporal domain features transformed into spatial domain. These processes are performed on both RGB images and depth maps separately. DCT coefficients that represent sign gestures are picked up via zigzag scanning and feature vectors are generated. In order to recognize sign gestures, K-Nearest Neighbor classifier with Manhattan distance is performed. Performance of the proposed sign language recognition system is evaluated on a sign database that contains 1002 isolated dynamic signs belongs to 111 words of Turkish Sign Language (TSL) in three different categories. Proposed sign language recognition system has promising success rates.

Digital image correlation based on a fast convolution strategy

Science.gov (United States)

Yuan, Yuan; Zhan, Qin; Xiong, Chunyang; Huang, Jianyong

2017-10-01

In recent years, the efficiency of digital image correlation (DIC) methods has attracted increasing attention because of its increasing importance for many engineering applications. Based on the classical affine optical flow (AOF) algorithm and the well-established inverse compositional Gauss-Newton algorithm, which is essentially a natural extension of the AOF algorithm under a nonlinear iterative framework, this paper develops a set of fast convolution-based DIC algorithms for high-efficiency subpixel image registration. Using a well-developed fast convolution technique, the set of algorithms establishes a series of global data tables (GDTs) over the digital images, which allows the reduction of the computational complexity of DIC significantly. Using the pre-calculated GDTs, the subpixel registration calculations can be implemented efficiently in a look-up-table fashion. Both numerical simulation and experimental verification indicate that the set of algorithms significantly enhances the computational efficiency of DIC, especially in the case of a dense data sampling for the digital images. Because the GDTs need to be computed only once, the algorithms are also suitable for efficiently coping with image sequences that record the time-varying dynamics of specimen deformations.

Triple correlation in temporomandibular joint dysfunction: MR imaging with arthrography, arthroscopy, and open surgery

International Nuclear Information System (INIS)

Rao, V.M.; Farole, A.; Karasick, D.

1988-01-01

Triple correlation of MR imaging with arthrography, arthroscopy, and open surgery was performed in 24 patients (34 temporomandibular joints) with ages ranging from 17 to 66 years. MR imaging showed disk position and morphologic features accurately in 30 joints (88%). It was false negative in one joint and false positive in three joints (9%). Degenerative changes were accurately detected with MR imaging, arthrography, and arthroscopy. Adhesions were diagnosed with arthrography in eight joints, arthroscopy in 14, and MR imaging in none. Disk perforations seen at open surgery were not detected with MR imaging. In conclusion, there is an overlap of information presented by various modalities. MR imaging is better than arthrography detecting disk morphologic features and displacement. Arthrography may add information by showing meniscal dynamics. Arthroscopy entails direct observation of superior joint space only and can detect adhesions and perforations better, but it may alter disk position and dynamics. In the more difficult cases, triple correlation may be needed, as modalities can be complementary

Spatiotemporal representation of cardiac vectorcardiogram (VCG signals

Directory of Open Access Journals (Sweden)

Yang Hui

2012-03-01

Full Text Available Abstract Background Vectorcardiogram (VCG signals monitor both spatial and temporal cardiac electrical activities along three orthogonal planes of the body. However, the absence of spatiotemporal resolution in conventional VCG representations is a major impediment for medical interpretation and clinical usage of VCG. This is especially so because time-domain features of 12-lead ECG, instead of both spatial and temporal characteristics of VCG, are widely used for the automatic assessment of cardiac pathological patterns. Materials and methods We present a novel representation approach that captures critical spatiotemporal heart dynamics by displaying the real time motion of VCG cardiac vectors in a 3D space. Such a dynamic display can also be realized with only one lead ECG signal (e.g., ambulatory ECG through an alternative lag-reconstructed ECG representation from nonlinear dynamics principles. Furthermore, the trajectories are color coded with additional dynamical properties of space-time VCG signals, e.g., the curvature, speed, octant and phase angles to enhance the information visibility. Results In this investigation, spatiotemporal VCG signal representation is used to characterize various spatiotemporal pathological patterns for healthy control (HC, myocardial infarction (MI, atrial fibrillation (AF and bundle branch block (BBB. The proposed color coding scheme revealed that the spatial locations of the peak of T waves are in the Octant 6 for the majority (i.e., 74 out of 80 of healthy recordings in the PhysioNet PTB database. In contrast, the peak of T waves from 31.79% (117/368 of MI subjects are found to remain in Octant 6 and the rest (68.21% spread over all other octants. The spatiotemporal VCG signal representation is shown to capture the same important heart characteristics as the 12-lead ECG plots and more. Conclusions Spatiotemporal VCG signal representation is shown to facilitate the characterization of space-time cardiac

Particle image velocimetry correlation signal-to-noise ratio metrics and measurement uncertainty quantification

International Nuclear Information System (INIS)

Xue, Zhenyu; Charonko, John J; Vlachos, Pavlos P

2014-01-01

In particle image velocimetry (PIV) the measurement signal is contained in the recorded intensity of the particle image pattern superimposed on a variety of noise sources. The signal-to-noise-ratio (SNR) strength governs the resulting PIV cross correlation and ultimately the accuracy and uncertainty of the resulting PIV measurement. Hence we posit that correlation SNR metrics calculated from the correlation plane can be used to quantify the quality of the correlation and the resulting uncertainty of an individual measurement. In this paper we extend the original work by Charonko and Vlachos and present a framework for evaluating the correlation SNR using a set of different metrics, which in turn are used to develop models for uncertainty estimation. Several corrections have been applied in this work. The SNR metrics and corresponding models presented herein are expanded to be applicable to both standard and filtered correlations by applying a subtraction of the minimum correlation value to remove the effect of the background image noise. In addition, the notion of a ‘valid’ measurement is redefined with respect to the correlation peak width in order to be consistent with uncertainty quantification principles and distinct from an ‘outlier’ measurement. Finally the type and significance of the error distribution function is investigated. These advancements lead to more robust and reliable uncertainty estimation models compared with the original work by Charonko and Vlachos. The models are tested against both synthetic benchmark data as well as experimental measurements. In this work, U 68.5 uncertainties are estimated at the 68.5% confidence level while U 95 uncertainties are estimated at 95% confidence level. For all cases the resulting calculated coverage factors approximate the expected theoretical confidence intervals, thus demonstrating the applicability of these new models for estimation of uncertainty for individual PIV measurements. (paper)

Particle image velocimetry correlation signal-to-noise ratio metrics and measurement uncertainty quantification

Science.gov (United States)

Xue, Zhenyu; Charonko, John J.; Vlachos, Pavlos P.

2014-11-01

In particle image velocimetry (PIV) the measurement signal is contained in the recorded intensity of the particle image pattern superimposed on a variety of noise sources. The signal-to-noise-ratio (SNR) strength governs the resulting PIV cross correlation and ultimately the accuracy and uncertainty of the resulting PIV measurement. Hence we posit that correlation SNR metrics calculated from the correlation plane can be used to quantify the quality of the correlation and the resulting uncertainty of an individual measurement. In this paper we extend the original work by Charonko and Vlachos and present a framework for evaluating the correlation SNR using a set of different metrics, which in turn are used to develop models for uncertainty estimation. Several corrections have been applied in this work. The SNR metrics and corresponding models presented herein are expanded to be applicable to both standard and filtered correlations by applying a subtraction of the minimum correlation value to remove the effect of the background image noise. In addition, the notion of a ‘valid’ measurement is redefined with respect to the correlation peak width in order to be consistent with uncertainty quantification principles and distinct from an ‘outlier’ measurement. Finally the type and significance of the error distribution function is investigated. These advancements lead to more robust and reliable uncertainty estimation models compared with the original work by Charonko and Vlachos. The models are tested against both synthetic benchmark data as well as experimental measurements. In this work, {{U}68.5} uncertainties are estimated at the 68.5% confidence level while {{U}95} uncertainties are estimated at 95% confidence level. For all cases the resulting calculated coverage factors approximate the expected theoretical confidence intervals, thus demonstrating the applicability of these new models for estimation of uncertainty for individual PIV measurements.

Clinimetric properties of the Tinetti Mobility Test, Four Square Step Test, Activities-specific Balance Confidence Scale, and spatiotemporal gait measures in individuals with Huntington's disease.

Science.gov (United States)

Kloos, Anne D; Fritz, Nora E; Kostyk, Sandra K; Young, Gregory S; Kegelmeyer, Deb A

2014-09-01

Individuals with Huntington's disease (HD) experience balance and gait problems that lead to falls. Clinicians currently have very little information about the reliability and validity of outcome measures to determine the efficacy of interventions that aim to reduce balance and gait impairments in HD. This study examined the reliability and concurrent validity of spatiotemporal gait measures, the Tinetti Mobility Test (TMT), Four Square Step Test (FSST), and Activities-specific Balance Confidence (ABC) Scale in individuals with HD. Participants with HD [n = 20; mean age ± SD=50.9 ± 13.7; 7 male] were tested on spatiotemporal gait measures and the TMT, FSST, and ABC Scale before and after a six week period to determine test-retest reliability and minimal detectable change (MDC) values. Linear relationships between gait and clinical measures were estimated using Pearson's correlation coefficients. Spatiotemporal gait measures, the TMT total and the FSST showed good to excellent test-retest reliability (ICC > 0.75). MDC values were 0.30 m/s and 0.17 m/s for velocity in forward and backward walking respectively, four points for the TMT, and 3s for the FSST. The TMT and FSST were highly correlated with most spatiotemporal measures. The ABC Scale demonstrated lower reliability and less concurrent validity than other measures. The high test-retest reliability over a six week period and concurrent validity between the TMT, FSST, and spatiotemporal gait measures suggest that the TMT and FSST may be useful outcome measures for future intervention studies in ambulatory individuals with HD. Copyright © 2014 Elsevier B.V. All rights reserved.

Neuropsychological Correlates of Diffusion Tensor Imaging in Schizophrenia

Science.gov (United States)

Nestor, Paul G.; Kubicki, Marek; Gurrera, Ronald J.; Niznikiewicz, Margaret; Frumin, Melissa; McCarley, Robert W.; Shenton, Martha E.

2009-01-01

Patients with schizophrenia (n = 41) and healthy comparison participants (n = 46) completed neuropsychological measures of intelligence, memory, and executive function. A subset of each group also completed magnetic resonance diffusion tensor imaging (DTI) studies (fractional anisotropy and cross-sectional area) of the uncinate fasciculus (UF) and cingulate bundle (CB). Patients with schizophrenia showed reduced levels of functioning across all neuropsychological measures. In addition, selective neuropsychological–DTI relationships emerged. Among patients but not controls, lower levels of declarative–episodic verbal memory correlated with reduced left UF, whereas executive function errors related to performance monitoring correlated with reduced left CB. The data suggested abnormal DTI patterns linking declarative–episodic verbal memory deficits to the left UF and executive function deficits to the left CB among patients with schizophrenia. PMID:15506830

Full-Scale Approximations of Spatio-Temporal Covariance Models for Large Datasets

KAUST Repository

Zhang, Bohai

2014-01-01

Various continuously-indexed spatio-temporal process models have been constructed to characterize spatio-temporal dependence structures, but the computational complexity for model fitting and predictions grows in a cubic order with the size of dataset and application of such models is not feasible for large datasets. This article extends the full-scale approximation (FSA) approach by Sang and Huang (2012) to the spatio-temporal context to reduce computational complexity. A reversible jump Markov chain Monte Carlo (RJMCMC) algorithm is proposed to select knots automatically from a discrete set of spatio-temporal points. Our approach is applicable to nonseparable and nonstationary spatio-temporal covariance models. We illustrate the effectiveness of our method through simulation experiments and application to an ozone measurement dataset.

Measurement of the Young's modulus of thin or flexible specimen with digital-image correlation method

Science.gov (United States)

Xu, Lianyun; Hou, Zhende; Qin, Yuwen

2002-05-01

Because some composite material, thin film material, and biomaterial, are very thin and some of them are flexible, the classical methods for measuring their Young's moduli, by mounting extensometers on specimens, are not available. A bi-image method based on image correlation for measuring Young's moduli is developed in this paper. The measuring precision achieved is one order enhanced with general digital image correlation or called single image method. By this way, the Young's modulus of a SS301 stainless steel thin tape, with thickness 0.067mm, is measured, and the moduli of polyester fiber films, a kind of flexible sheet with thickness 0.25 mm, are also measured.

Correlative studies of structural and functional imaging in primary progressive aphasia.

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Panegyres, P K; McCarthy, M; Campbell, A; Lenzo, N; Fallon, M; Thompson, J

2008-01-01

To compare and contrast structural and functional imaging in primary progressive aphasia (PPA). A cohort of 8 patients diagnosed with PPA presenting with nonfluency were prospectively evaluated. All patients had structural imaging in the form of MRI and in 1 patient CAT scanning on account of a cardiac pacemaker. All patients had single-photon emission computed tomography (SPECT) and positron emission tomography (PET) imaging. SPECT and PET imaging had 100% correlation. Anatomical imaging was abnormal in only 6 of the 8 patients. Wernicke's area showed greater peak Z score reduction and extent of area affected than Broca's area (McNemar paired test: P = .008 for Z score reduction; P = .0003 for extent). PET scanning revealed significant involvement of the anterior cingulum. Functional imaging in PPA: (a) identified more patients correctly than anatomic imaging highlighting the importance of SPECT and PET in the diagnosis; and (b) demonstrated the heterogeneous involvement of disordered linguistic networks in PPA suggesting its syndromic nature.

Inter-chromosomal Contact Properties in Live-Cell Imaging and in Hi-C.

Science.gov (United States)

Maass, Philipp G; Barutcu, A Rasim; Weiner, Catherine L; Rinn, John L

2018-03-15

Imaging (fluorescence in situ hybridization [FISH]) and genome-wide chromosome conformation capture (Hi-C) are two major approaches to the study of higher-order genome organization in the nucleus. Intra-chromosomal and inter-chromosomal interactions (referred to as non-homologous chromosomal contacts [NHCCs]) have been observed by several FISH-based studies, but locus-specific NHCCs have not been detected by Hi-C. Due to crosslinking, neither of these approaches assesses spatiotemporal properties. Toward resolving the discrepancies between imaging and Hi-C, we sought to understand the spatiotemporal properties of NHCCs in living cells by CRISPR/Cas9 live-cell imaging (CLING). In mammalian cells, we find that NHCCs are stable and occur as frequently as intra-chromosomal interactions, but NHCCs occur at farther spatial distance that could explain their lack of detection in Hi-C. By revealing the spatiotemporal properties in living cells, our study provides fundamental insights into the biology of NHCCs. Copyright © 2018 Elsevier Inc. All rights reserved.

Spatiotemporal Variation of Karst Ecosystem Service Values and Its Correlation with Environmental Factors in Northwest Guangxi, China

Science.gov (United States)

Zhang, Mingyang; Zhang, Chunhua; Wang, Kelin; Yue, Yuemin; Qi, Xiangkun; Fan, Feide

2011-11-01

In this investigation we analyzed the spatiotemporal variation of ecosystem service values (ESVs) and its correlation with numerous environmental factors (EFs) for the karst region of Northwest Guangxi, China, from 1985 to 2005 using remote sensing, geographic information systems (GIS) and statistical techniques. The results indicate that historically ESVs for this karst region decreased from 1985 (109.652 billion Yuan) to 1990 (88.789 billion Yuan) and then increased at the turn of the twenty-first century. However, the ESVs in both 2000 (103.384 billion Yuan) and 2005 (106.257 billion Yuan) never achieved the level recorded in 1985. The total of nutrient cycling, organic production and gas regulation combined were 72.69, 64.57, 70.18 and 72.10% of ESVs in 1985, 1990, 2000 and 2005, respectively. In contrast, the ESVs of water conservation, soil reservation, recreation and culture were determined to be relatively low contributing only 17.44, 23.82, 19.26 and 24.76% of total ESVs, respectively, during these four years. With regards to the spatial distribution of ESVs, larger values were recorded in the west and smaller ones recorded in the east. The most significant factors that were deemed to influence ESVs are annual rainfall, per capita cropland, slope and vegetation coverage. Annual rainfall and slope exert a negative force, whereas per capita cropland and vegetation coverage exert a positive force on ESVs. The results of the study would suggest that ecosystem conditions of this important karst region have been improved as the result of the implementation of rocky desertification control policies.

A hybrid spatiotemporal drought forecasting model for operational use

Science.gov (United States)

Vasiliades, L.; Loukas, A.

2010-09-01

Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. This study develops a hybrid spatiotemporal scheme for integrated spatial and temporal forecasting. Temporal forecasting is achieved using feed-forward neural networks and the temporal forecasts are extended to the spatial dimension using a spatial recurrent neural network model. The methodology is demonstrated for an operational meteorological drought index the Standardized Precipitation Index (SPI) calculated at multiple timescales. 48 precipitation stations and 18 independent precipitation stations, located at Pinios river basin in Thessaly region, Greece, were used for the development and spatiotemporal validation of the hybrid spatiotemporal scheme. Several quantitative temporal and spatial statistical indices were considered for the performance evaluation of the models. Furthermore, qualitative statistical criteria based on contingency tables between observed and forecasted drought episodes were calculated. The results show that the lead time of forecasting for operational use depends on the SPI timescale. The hybrid spatiotemporal drought forecasting model could be operationally used for forecasting up to three months ahead for SPI short timescales (e.g. 3-6 months) up to six months ahead for large SPI timescales (e.g. 24 months). The above findings could be useful in developing a drought preparedness plan in the region.

A quantitative spatiotemporal analysis of microglia morphology during ischemic stroke and reperfusion

Directory of Open Access Journals (Sweden)

Morrison Helena W

2013-01-01

Full Text Available Abstract Background Microglia cells continuously survey the healthy brain in a ramified morphology and, in response to injury, undergo progressive morphological and functional changes that encompass microglia activation. Although ideally positioned for immediate response to ischemic stroke (IS and reperfusion, their progressive morphological transformation into activated cells has not been quantified. In addition, it is not well understood if diverse microglia morphologies correlate to diverse microglia functions. As such, the dichotomous nature of these cells continues to confound our understanding of microglia-mediated injury after IS and reperfusion. The purpose of this study was to quantitatively characterize the spatiotemporal pattern of microglia morphology during the evolution of cerebral injury after IS and reperfusion. Methods Male C57Bl/6 mice were subjected to focal cerebral ischemia and periods of reperfusion (0, 8 and 24 h. The microglia process length/cell and number of endpoints/cell was quantified from immunofluorescent confocal images of brain regions using a skeleton analysis method developed for this study. Live cell morphology and process activity were measured from movies acquired in acute brain slices from GFP-CX3CR1 transgenic mice after IS and 24-h reperfusion. Regional CD11b and iNOS expressions were measured from confocal images and Western blot, respectively, to assess microglia proinflammatory function. Results Quantitative analysis reveals a significant spatiotemporal relationship between microglia morphology and evolving cerebral injury in the ipsilateral hemisphere after IS and reperfusion. Microglia were both hyper- and de-ramified in striatal and cortical brain regions (respectively after 60 min of focal cerebral ischemia. However, a de-ramified morphology was prominent when ischemia was coupled to reperfusion. Live microglia were de-ramified, and, in addition, process activity was severely blunted proximal to

Abnormal Event Detection in Wireless Sensor Networks Based on Multiattribute Correlation

Directory of Open Access Journals (Sweden)

Mengdi Wang

2017-01-01

Full Text Available Abnormal event detection is one of the vital tasks in wireless sensor networks. However, the faults of nodes and the poor deployment environment have brought great challenges to abnormal event detection. In a typical event detection technique, spatiotemporal correlations are collected to detect an event, which is susceptible to noises and errors. To improve the quality of detection results, we propose a novel approach for abnormal event detection in wireless sensor networks. This approach considers not only spatiotemporal correlations but also the correlations among observed attributes. A dependency model of observed attributes is constructed based on Bayesian network. In this model, the dependency structure of observed attributes is obtained by structure learning, and the conditional probability table of each node is calculated by parameter learning. We propose a new concept named attribute correlation confidence to evaluate the fitting degree between the sensor reading and the abnormal event pattern. On the basis of time correlation detection and space correlation detection, the abnormal events are identified. Experimental results show that the proposed algorithm can reduce the impact of interference factors and the rate of the false alarm effectively; it can also improve the accuracy of event detection.

Optical Probes for Neurobiological Sensing and Imaging.

Science.gov (United States)

Kim, Eric H; Chin, Gregory; Rong, Guoxin; Poskanzer, Kira E; Clark, Heather A

2018-04-13

Fluorescent nanosensors and molecular probes are next-generation tools for imaging chemical signaling inside and between cells. Electrophysiology has long been considered the gold standard in elucidating neural dynamics with high temporal resolution and precision, particularly on the single-cell level. However, electrode-based techniques face challenges in illuminating the specific chemicals involved in neural cell activation with adequate spatial information. Measuring chemical dynamics is of fundamental importance to better understand synergistic interactions between neurons as well as interactions between neurons and non-neuronal cells. Over the past decade, significant technological advances in optical probes and imaging methods have enabled entirely new possibilities for studying neural cells and circuits at the chemical level. These optical imaging modalities have shown promise for combining chemical, temporal, and spatial information. This potential makes them ideal candidates to unravel the complex neural interactions at multiple scales in the brain, which could be complemented by traditional electrophysiological methods to obtain a full spatiotemporal picture of neurochemical dynamics. Despite the potential, only a handful of probe candidates have been utilized to provide detailed chemical information in the brain. To date, most live imaging and chemical mapping studies rely on fluorescent molecular indicators to report intracellular calcium (Ca 2+ ) dynamics, which correlates with neuronal activity. Methodological advances for monitoring a full array of chemicals in the brain with improved spatial, temporal, and chemical resolution will thus enable mapping of neurochemical circuits with finer precision. On the basis of numerous studies in this exciting field, we review the current efforts to develop and apply a palette of optical probes and nanosensors for chemical sensing in the brain. There is a strong impetus to further develop technologies capable of

Spatio-temporal features for tracking and quadruped/biped discrimination

Science.gov (United States)

Rickman, Rick; Copsey, Keith; Bamber, David C.; Page, Scott F.

2012-05-01

Techniques such as SIFT and SURF facilitate efficient and robust image processing operations through the use of sparse and compact spatial feature descriptors and show much potential for defence and security applications. This paper considers the extension of such techniques to include information from the temporal domain, to improve utility in applications involving moving imagery within video data. In particular, the paper demonstrates how spatio-temporal descriptors can be used very effectively as the basis of a target tracking system and as target discriminators which can distinguish between bipeds and quadrupeds. Results using sequences of video imagery of walking humans and dogs are presented, and the relative merits of the approach are discussed.

Noise Gating Solar Images

Science.gov (United States)

DeForest, Craig; Seaton, Daniel B.; Darnell, John A.

2017-08-01

I present and demonstrate a new, general purpose post-processing technique, "3D noise gating", that can reduce image noise by an order of magnitude or more without effective loss of spatial or temporal resolution in typical solar applications.Nearly all scientific images are, ultimately, limited by noise. Noise can be direct Poisson "shot noise" from photon counting effects, or introduced by other means such as detector read noise. Noise is typically represented as a random variable (perhaps with location- or image-dependent characteristics) that is sampled once per pixel or once per resolution element of an image sequence. Noise limits many aspects of image analysis, including photometry, spatiotemporal resolution, feature identification, morphology extraction, and background modeling and separation.Identifying and separating noise from image signal is difficult. The common practice of blurring in space and/or time works because most image "signal" is concentrated in the low Fourier components of an image, while noise is evenly distributed. Blurring in space and/or time attenuates the high spatial and temporal frequencies, reducing noise at the expense of also attenuating image detail. Noise-gating exploits the same property -- "coherence" -- that we use to identify features in images, to separate image features from noise.Processing image sequences through 3-D noise gating results in spectacular (more than 10x) improvements in signal-to-noise ratio, while not blurring bright, resolved features in either space or time. This improves most types of image analysis, including feature identification, time sequence extraction, absolute and relative photometry (including differential emission measure analysis), feature tracking, computer vision, correlation tracking, background modeling, cross-scale analysis, visual display/presentation, and image compression.I will introduce noise gating, describe the method, and show examples from several instruments (including SDO

MR imaging and histopathologic correlations of thermal injuries induced by interstitial laser applications

International Nuclear Information System (INIS)

Anzai, Y.; Lufkin, R.B.; Castro, D.J.; Farahani, K.; Chen, H.W.; Hirchowiz, S.

1991-01-01

Interstitial laser phototherapy for deep-seated tumors may become an attractive therapeutic modality when a noninvasive, accurate monitoring system is developed. In this paper, to devaluate the ability of MR imaging to differentiate reversible and irreversible thermal injuries induced by laser therapy, the precise correlation of MR and histopathologic findings are investigated in the in vivo model. Nd:YAG lasers were applied to normal musculature of rabbits, and MR examinations were performed immediately after laser exposure and followed up for up to 10 weeks. The sequential MR images were correlated with histopathologic findings. T2-weighted MR imaging clearly showed laser-induced thermal injuries on any postoperative day. MR imaging of acute thermal injuries showed a central cavity, low-signal zone of coagulative necrosis and a peripheral high-signal layer of interstitial edema. The infiltration of neutrophils followed by fibrovascular response was identified on the marginal edema layer after 6 postoperative days

Spatiotemporal drought forecasting using nonlinear models

Science.gov (United States)

Vasiliades, Lampros; Loukas, Athanasios

2010-05-01

Spatiotemporal data mining is the extraction of unknown and implicit knowledge, structures, spatiotemporal relationships, or patterns not explicitly stored in spatiotemporal databases. As one of data mining techniques, forecasting is widely used to predict the unknown future based upon the patterns hidden in the current and past data. In order to achieve spatiotemporal forecasting, some mature analysis tools, e.g., time series and spatial statistics are extended to the spatial dimension and the temporal dimension, respectively. Drought forecasting plays an important role in the planning and management of natural resources and water resource systems in a river basin. Early and timelines forecasting of a drought event can help to take proactive measures and set out drought mitigation strategies to alleviate the impacts of drought. Despite the widespread application of nonlinear mathematical models, comparative studies on spatiotemporal drought forecasting using different models are still a huge task for modellers. This study uses a promising approach, the Gamma Test (GT), to select the input variables and the training data length, so that the trial and error workload could be greatly reduced. The GT enables to quickly evaluate and estimate the best mean squared error that can be achieved by a smooth model on any unseen data for a given selection of inputs, prior to model construction. The GT is applied to forecast droughts using monthly Standardized Precipitation Index (SPI) timeseries at multiple timescales in several precipitation stations at Pinios river basin in Thessaly region, Greece. Several nonlinear models have been developed efficiently, with the aid of the GT, for 1-month up to 12-month ahead forecasting. Several temporal and spatial statistical indices were considered for the performance evaluation of the models. The predicted results show reasonably good agreement with the actual data for short lead times, whereas the forecasting accuracy decreases with

Spatio-temporal variations of vegetation indicators in Eastern Siberia under global warming

Science.gov (United States)

Varlamova, Eugenia V.; Solovyev, Vladimir S.

2017-11-01

Study of spatio-temporal variations of NDVI (Normalized Difference Vegetation Index) and phenological parameters of Eastern Siberia vegetation cover under global warming was carried out on AVHRR/NOAA data (1982-2014). Trend maps of NDVI and annual variations of phenological parameters and NDVI are analyzed. A method based on stable transition of air temperature through +5°C was used to estimate the beginning, end and the length of the growing season. Correlation between NDVI and phenological parameters, surface air temperature and precipitation are discussed.

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

International Nuclear Information System (INIS)

Aggarwal, Nitin; Bresler, Yoram

2008-01-01

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

Spatio-Temporal Change of Vegetation Coverage and its Driving Forces Based on Landsat Images: a Case Study of Changchun City

Science.gov (United States)

Dong, L.; Jiang, H.; Yang, L.

2018-04-01

Based on the Landsat images in 2006, 2011 and 2015, and the method of dimidiate pixel model, the Normalized Difference Vegetation Index (NDVI) and the vegetation coverage, this paper analyzes the spatio-temporal variation of vegetation coverage in Changchun, China from 2006 to 2015, and investigates the response of vegetation coverage change to natural and artificial factors. The research results show that in nearly 10 years, the vegetation coverage in Changchun dropped remarkably, and reached the minimum in 2011. Moreover, the decrease of maximum NDVI was significant, with a decrease of about 27.43 %, from 2006 to 2015. The vegetation coverage change in different regions of the research area was significantly different. Among them, the vegetation change in Changchun showed a little drop, and it decreased firstly and then increased slowly in Yushu, Nong'an and Dehui. In addition, the temperature and precipitation change, land reclamation all affect the vegetation coverage. In short, the study of vegetation coverage change contributes scientific and technical support to government and environmental protection department, so as to promote the coordinated development of ecology and economy.

Distal insertions of the semimembranosus tendon: MR imaging with anatomic correlation

Energy Technology Data Exchange (ETDEWEB)

Maeseneer, Michel de [Universitair Ziekenhuis Brussel, Department of Radiology, Jette, Brussels (Belgium); Vrije Universiteit Brussel, Department of Experimental Anatomy, Brussels (Belgium); Shahabpour, Maryam; Milants, Annemieke; Ridder, Filip de; Mey, Johan de [Universitair Ziekenhuis Brussel, Department of Radiology, Jette, Brussels (Belgium); Lenchik, Leon [Wake Forest University, Department of Radiology, Winston-Salem, NC (United States); Cattrysse, Erik [Vrije Universiteit Brussel, Department of Experimental Anatomy, Brussels (Belgium)

2014-06-15

The purpose of this study is to investigate the distal insertions of the semimembranosus tendon with MR imaging, correlated with findings in cadavers. Four fresh cadaveric specimens were studied with 3-T MR imaging. Sequences included proton density (PD) sequences (TE, 13; TR, 4957; FOV, 170 x 170; matrix, 424 x 413; NA, 2; slice thickness, 2.5 mm) in the axial, coronal, and sagittal planes and 3D fast field echo (FFE) sequences (TR 9.4; TE 6.9; FOV, 159 x 105; matrix, 200 x 211; NA, 2; slice thickness, 0.57 mm). One specimen was dissected and three specimens were sectioned with a bandsaw in the axial, coronal, and sagittal plane. The sections were photographed and correlated with MR images. To standardize the analysis, the semimembranosus muscle and tendon were assessed at seven levels for the axial sections, and at three levels for the coronal and sagittal sections. Anatomic dissection revealed six insertions of the distal semimembranosus tendon: direct arm, anterior arm, posterior oblique ligament extension, oblique popliteal ligament extension, distal tibial expansion (popliteus aponeurosis), and meniscal arm. Axial MR images showed five of six insertions: direct arm, anterior arm, oblique popliteal ligament extension, posterior oblique ligament extension, and distal tibial expansion. Sagittal MR images showed four of six insertions: direct arm, anterior arm, oblique popliteal ligament arm, and distal tibial expansion. Sagittal MR images were ideal for showing the direct arm insertion, but were less optimal than the axial images for showing the other insertions. The anterior arm was seen but volume averaging was present with the gracilis tendon. Coronal MR images optimally revealed the anterior arm, although magic angle artifact was present at its posterior aspect. The common semimembranosus tendon and meniscal arm were also well depicted. The division in anterior arm, direct arm, and oblique popliteal ligament arm was poorly seen on coronal images due to

Resting-state hemodynamics are spatiotemporally coupled to synchronized and symmetric neural activity in excitatory neurons

Science.gov (United States)

Ma, Ying; Shaik, Mohammed A.; Kozberg, Mariel G.; Portes, Jacob P.; Timerman, Dmitriy

2016-01-01

Brain hemodynamics serve as a proxy for neural activity in a range of noninvasive neuroimaging techniques including functional magnetic resonance imaging (fMRI). In resting-state fMRI, hemodynamic fluctuations have been found to exhibit patterns of bilateral synchrony, with correlated regions inferred to have functional connectivity. However, the relationship between resting-state hemodynamics and underlying neural activity has not been well established, making the neural underpinnings of functional connectivity networks unclear. In this study, neural activity and hemodynamics were recorded simultaneously over the bilateral cortex of awake and anesthetized Thy1-GCaMP mice using wide-field optical mapping. Neural activity was visualized via selective expression of the calcium-sensitive fluorophore GCaMP in layer 2/3 and 5 excitatory neurons. Characteristic patterns of resting-state hemodynamics were accompanied by more rapidly changing bilateral patterns of resting-state neural activity. Spatiotemporal hemodynamics could be modeled by convolving this neural activity with hemodynamic response functions derived through both deconvolution and gamma-variate fitting. Simultaneous imaging and electrophysiology confirmed that Thy1-GCaMP signals are well-predicted by multiunit activity. Neurovascular coupling between resting-state neural activity and hemodynamics was robust and fast in awake animals, whereas coupling in urethane-anesthetized animals was slower, and in some cases included lower-frequency (resting-state hemodynamics in the awake and anesthetized brain are coupled to underlying patterns of excitatory neural activity. The patterns of bilaterally-symmetric spontaneous neural activity revealed by wide-field Thy1-GCaMP imaging may depict the neural foundation of functional connectivity networks detected in resting-state fMRI. PMID:27974609

Optical Spectroscopy and Imaging of Correlated Spin Orbit Phases

Science.gov (United States)

2016-06-14

Unlimited UU UU UU UU 14-06-2016 15-Mar-2013 14-Mar-2016 Final Report: Optical Spectroscopy and Imaging of Correlated Spin-Orbit Phases The views...Box 12211 Research Triangle Park, NC 27709-2211 Ultrafast optical spectroscopy , nonlinear optical spectroscopy , iridates, cuprates REPORT...California Blvd. Pasadena, CA 91125 -0001 ABSTRACT Number of Papers published in peer-reviewed journals: Final Report: Optical Spectroscopy and

Spatio-temporal scaling of channels in braided streams.

Science.gov (United States)

A.G. Hunt; G.E. Grant; V.K. Gupta

2006-01-01

The spatio-temporal scaling relationship for individual channels in braided streams is shown to be identical to the spatio-temporal scaling associated with constant Froude number, e.g., Fr = l. A means to derive this relationship is developed from a new theory of sediment transport. The mechanism by which the Fr = l condition apparently governs the scaling seems to...

Visual representation of spatiotemporal structure

Science.gov (United States)

Schill, Kerstin; Zetzsche, Christoph; Brauer, Wilfried; Eisenkolb, A.; Musto, A.

1998-07-01

The processing and representation of motion information is addressed from an integrated perspective comprising low- level signal processing properties as well as higher-level cognitive aspects. For the low-level processing of motion information we argue that a fundamental requirement is the existence of a spatio-temporal memory. Its key feature, the provision of an orthogonal relation between external time and its internal representation, is achieved by a mapping of temporal structure into a locally distributed activity distribution accessible in parallel by higher-level processing stages. This leads to a reinterpretation of the classical concept of `iconic memory' and resolves inconsistencies on ultra-short-time processing and visual masking. The spatial-temporal memory is further investigated by experiments on the perception of spatio-temporal patterns. Results on the direction discrimination of motion paths provide evidence that information about direction and location are not processed and represented independent of each other. This suggests a unified representation on an early level, in the sense that motion information is internally available in form of a spatio-temporal compound. For the higher-level representation we have developed a formal framework for the qualitative description of courses of motion that may occur with moving objects.

Radar correlated imaging for extended target by the combination of negative exponential restraint and total variation

Science.gov (United States)

Qian, Tingting; Wang, Lianlian; Lu, Guanghua

2017-07-01

Radar correlated imaging (RCI) introduces the optical correlated imaging technology to traditional microwave imaging, which has raised widespread concern recently. Conventional RCI methods neglect the structural information of complex extended target, which makes the quality of recovery result not really perfect, thus a novel combination of negative exponential restraint and total variation (NER-TV) algorithm for extended target imaging is proposed in this paper. The sparsity is measured by a sequential order one negative exponential function, then the 2D total variation technique is introduced to design a novel optimization problem for extended target imaging. And the proven alternating direction method of multipliers is applied to solve the new problem. Experimental results show that the proposed algorithm could realize high resolution imaging efficiently for extended target.

Determining spatio-temporal distribution of bee forage species of Al-Baha region based on ground inventorying supported with GIS applications and Remote Sensed Satellite Image analysis

Directory of Open Access Journals (Sweden)

Nuru Adgaba

2017-07-01

Full Text Available In arid zones, the shortage of bee forage is critical and usually compels beekeepers to move their colonies in search of better forages. Identifying and mapping the spatiotemporal distribution of the bee forages over given area is important for better management of bee colonies. In this study honey bee plants in the target areas were inventoried following, ground inventory work supported with GIS applications. The study was conducted on 85 large plots of 50 × 50 m each. At each plot, data on species name, height, base diameter, crown height, crown diameter has been taken for each plant with their respective geographical positions. The data were stored, and processed using Trimble GPS supported with ArcGIS10 software program. The data were used to estimate the relative frequency, density, abundance and species diversity, species important value index and apicultural value of the species. In addition, Remotely Sensed Satellite Image of the area was obtained and processed using Hopfield Artificial Neural Network techniques. During the study, 182 species from 49 plant families were identified as bee forages of the target area. From the total number of species; shrubs, herbs and trees were accounting for 61%, 27.67%, and 11.53% respectively. Of which Ziziphus spina-christi, Acacia tortilis, Acacia origina, Acacia asak, Lavandula dentata, and Hypoestes forskaolii were the major nectar source plants of the area in their degree of importance. The average vegetation cover values of the study areas were low (<30% with low Shannon’s species diversity indices (H′ of 0.5–1.52 for different sites. Based on the eco-climatological factors and the variations in their flowering period, these major bee forage species were found to form eight distinct spatiotemporal categories which allow beekeepers to migrate their colonies to exploit the resources at different seasons and place. The Remote Sensed Satellite Image analysis confirmed the spatial

Using Deep Learning Model for Meteorological Satellite Cloud Image Prediction

Science.gov (United States)

Su, X.

2017-12-01

A satellite cloud image contains much weather information such as precipitation information. Short-time cloud movement forecast is important for precipitation forecast and is the primary means for typhoon monitoring. The traditional methods are mostly using the cloud feature matching and linear extrapolation to predict the cloud movement, which makes that the nonstationary process such as inversion and deformation during the movement of the cloud is basically not considered. It is still a hard task to predict cloud movement timely and correctly. As deep learning model could perform well in learning spatiotemporal features, to meet this challenge, we could regard cloud image prediction as a spatiotemporal sequence forecasting problem and introduce deep learning model to solve this problem. In this research, we use a variant of Gated-Recurrent-Unit(GRU) that has convolutional structures to deal with spatiotemporal features and build an end-to-end model to solve this forecast problem. In this model, both the input and output are spatiotemporal sequences. Compared to Convolutional LSTM(ConvLSTM) model, this model has lower amount of parameters. We imply this model on GOES satellite data and the model perform well.

A three-dimensional correlation method for registration of medical images in radiology

Energy Technology Data Exchange (ETDEWEB)

Georgiou, Michalakis; Sfakianakis, George N [Department of Radiology, University of Miami, Jackson Memorial Hospital, Miami, FL 33136 (United States); Nagel, Joachim H [Institute of Biomedical Engineering, University of Stuttgart, Stuttgart 70174 (Germany)

1999-12-31

The availability of methods to register multi-modality images in order to `fuse` them to correlate their information is increasingly becoming an important requirement for various diagnostic and therapeutic procedures. A variety of image registration methods have been developed but they remain limited to specific clinical applications. Assuming rigid body transformation, two images can be registered if their differences are calculated in terms of translation, rotation and scaling. This paper describes the development and testing of a new correlation based approach for three-dimensional image registration. First, the scaling factors introduced by the imaging devices are calculated and compensated for. Then, the two images become translation invariant by computing their three-dimensional Fourier magnitude spectra. Subsequently, spherical coordinate transformation is performed and then the three-dimensional rotation is computed using a novice approach referred to as {sup p}olar Shells{sup .} The method of polar shells maps the three angles of rotation into one rotation and two translations of a two-dimensional function and then proceeds to calculate them using appropriate transformations based on the Fourier invariance properties. A basic assumption in the method is that the three-dimensional rotation is constrained to one large and two relatively small angles. This assumption is generally satisfied in normal clinical settings. The new three-dimensional image registration method was tested with simulations using computer generated phantom data as well as actual clinical data. Performance analysis and accuracy evaluation of the method using computer simulations yielded errors in the sub-pixel range. (authors) 6 refs., 3 figs.

A three-dimensional correlation method for registration of medical images in radiology

International Nuclear Information System (INIS)

Georgiou, Michalakis; Sfakianakis, George N.; Nagel, Joachim H.

1998-01-01

The availability of methods to register multi-modality images in order to 'fuse' them to correlate their information is increasingly becoming an important requirement for various diagnostic and therapeutic procedures. A variety of image registration methods have been developed but they remain limited to specific clinical applications. Assuming rigid body transformation, two images can be registered if their differences are calculated in terms of translation, rotation and scaling. This paper describes the development and testing of a new correlation based approach for three-dimensional image registration. First, the scaling factors introduced by the imaging devices are calculated and compensated for. Then, the two images become translation invariant by computing their three-dimensional Fourier magnitude spectra. Subsequently, spherical coordinate transformation is performed and then the three-dimensional rotation is computed using a novice approach referred to as p olar Shells . The method of polar shells maps the three angles of rotation into one rotation and two translations of a two-dimensional function and then proceeds to calculate them using appropriate transformations based on the Fourier invariance properties. A basic assumption in the method is that the three-dimensional rotation is constrained to one large and two relatively small angles. This assumption is generally satisfied in normal clinical settings. The new three-dimensional image registration method was tested with simulations using computer generated phantom data as well as actual clinical data. Performance analysis and accuracy evaluation of the method using computer simulations yielded errors in the sub-pixel range. (authors)

NCI Workshop Report: Clinical and Computational Requirements for Correlating Imaging Phenotypes with Genomics Signatures

Directory of Open Access Journals (Sweden)

Rivka Colen

2014-10-01

Full Text Available The National Cancer Institute (NCI Cancer Imaging Program organized two related workshops on June 26–27, 2013, entitled “Correlating Imaging Phenotypes with Genomics Signatures Research” and “Scalable Computational Resources as Required for Imaging-Genomics Decision Support Systems.” The first workshop focused on clinical and scientific requirements, exploring our knowledge of phenotypic characteristics of cancer biological properties to determine whether the field is sufficiently advanced to correlate with imaging phenotypes that underpin genomics and clinical outcomes, and exploring new scientific methods to extract phenotypic features from medical images and relate them to genomics analyses. The second workshop focused on computational methods that explore informatics and computational requirements to extract phenotypic features from medical images and relate them to genomics analyses and improve the accessibility and speed of dissemination of existing NIH resources. These workshops linked clinical and scientific requirements of currently known phenotypic and genotypic cancer biology characteristics with imaging phenotypes that underpin genomics and clinical outcomes. The group generated a set of recommendations to NCI leadership and the research community that encourage and support development of the emerging radiogenomics research field to address short-and longer-term goals in cancer research.

Noise-immune complex correlation for vasculature imaging based on standard and Jones-matrix optical coherence tomography

Science.gov (United States)

Makita, Shuichi; Kurokawa, Kazuhiro; Hong, Young-Joo; Li, En; Miura, Masahiro; Yasuno, Yoshiaki

2016-03-01

A new optical coherence angiography (OCA) method, called correlation mapping OCA (cmOCA), is presented by using the SNR-corrected complex correlation. An SNR-correction theory for the complex correlation calculation is presented. The method also integrates a motion-artifact-removal method for the sample motion induced decorrelation artifact. The theory is further extended to compute more reliable correlation by using multi- channel OCT systems, such as Jones-matrix OCT. The high contrast vasculature imaging of in vivo human posterior eye has been obtained. Composite imaging of cmOCA and degree of polarization uniformity indicates abnormalities of vasculature and pigmented tissues simultaneously.

A stream cipher based on a spatiotemporal chaotic system

International Nuclear Information System (INIS)

Li Ping; Li Zhong; Halang, Wolfgang A.; Chen Guanrong

2007-01-01

A stream cipher based on a spatiotemporal chaotic system is proposed. A one-way coupled map lattice consisting of logistic maps is served as the spatiotemporal chaotic system. Multiple keystreams are generated from the coupled map lattice by using simple algebraic computations, and then are used to encrypt plaintext via bitwise XOR. These make the cipher rather simple and efficient. Numerical investigation shows that the cryptographic properties of the generated keystream are satisfactory. The cipher seems to have higher security, higher efficiency and lower computation expense than the stream cipher based on a spatiotemporal chaotic system proposed recently

Optimization of Spatiotemporal Apertures in Channel Sounding

DEFF Research Database (Denmark)

Pedersen, Troels; Pedersen, Claus; Yin, Xuefeng

2008-01-01

a spatiotemporal model which can describe parallel as well as switched sounding systems. The proposed model is applicable for arbitrary layouts of the spatial arrays. To simplify the derivations we investigate the special case of linear spatial arrays. However, the results obtained for linear arrays can......In this paper we investigate the impact of the spatio-temporal aperture of a channel sounding system equipped with antenna arrays at the transmitter and receiver on the accuracy of joint estimation of Doppler frequency and bi-direction. The contribution of this work is three-fold. Firstly, we state...... be generalized to arbitrary arrays. Secondly, we give the necessary and sufficient conditions for a spatio-temporal array to yield the minimum Cramér-Rao lower bound in the single-path case and Bayesian Cramér-Rao Lower Bound in the multipath case. The obtained conditions amount to an orthogonality condition...

Ranking Businesses and Municipal Locations by Spatiotemporal Cardiac Arrest Risk to Guide Public Defibrillator Placement.

Science.gov (United States)

Sun, Christopher L F; Brooks, Steven C; Morrison, Laurie J; Chan, Timothy C Y

2017-03-21

Efforts to guide automated external defibrillator placement for out-of-hospital cardiac arrest (OHCA) treatment have focused on identifying broadly defined location categories without considering hours of operation. Broad location categories may be composed of many businesses with varying accessibility. Identifying specific locations for automated external defibrillator deployment incorporating operating hours and time of OHCA occurrence may improve automated external defibrillator accessibility. We aim to identify specific businesses and municipal locations that maximize OHCA coverage on the basis of spatiotemporal assessment of OHCA risk in the immediate vicinity of franchise locations. This study was a retrospective population-based cohort study using data from the Toronto Regional RescuNET Epistry cardiac arrest database. We identified all nontraumatic public OHCAs occurring in Toronto, ON, Canada, from January 2007 through December 2015. We identified 41 unique businesses and municipal location types with ≥20 locations in Toronto from the YellowPages, Canadian Franchise Association, and the City of Toronto Open Data Portal. We obtained their geographic coordinates and hours of operation from Web sites, by phone, or in person. We determined the number of OHCAs that occurred within 100 m of each location when it was open (spatiotemporal coverage) for Toronto overall and downtown. The businesses and municipal locations were then ranked by spatiotemporal OHCA coverage. To evaluate temporal stability of the rankings, we calculated intraclass correlation of the annual coverage values. There were 2654 nontraumatic public OHCAs. Tim Hortons ranked first in Toronto, covering 286 OHCAs. Starbucks ranked first in downtown, covering 110 OHCAs. Coffee shops and bank machines from the 5 largest Canadian banks occupied 8 of the top 10 spots in both Toronto and downtown. The rankings exhibited high temporal stability with intraclass correlation values of 0.88 (95

Spatio-chromatic adaptation via higher-order canonical correlation analysis of natural images.

Science.gov (United States)

Gutmann, Michael U; Laparra, Valero; Hyvärinen, Aapo; Malo, Jesús

2014-01-01

Independent component and canonical correlation analysis are two general-purpose statistical methods with wide applicability. In neuroscience, independent component analysis of chromatic natural images explains the spatio-chromatic structure of primary cortical receptive fields in terms of properties of the visual environment. Canonical correlation analysis explains similarly chromatic adaptation to different illuminations. But, as we show in this paper, neither of the two methods generalizes well to explain both spatio-chromatic processing and adaptation at the same time. We propose a statistical method which combines the desirable properties of independent component and canonical correlation analysis: It finds independent components in each data set which, across the two data sets, are related to each other via linear or higher-order correlations. The new method is as widely applicable as canonical correlation analysis, and also to more than two data sets. We call it higher-order canonical correlation analysis. When applied to chromatic natural images, we found that it provides a single (unified) statistical framework which accounts for both spatio-chromatic processing and adaptation. Filters with spatio-chromatic tuning properties as in the primary visual cortex emerged and corresponding-colors psychophysics was reproduced reasonably well. We used the new method to make a theory-driven testable prediction on how the neural response to colored patterns should change when the illumination changes. We predict shifts in the responses which are comparable to the shifts reported for chromatic contrast habituation.

Spatio-temporal distribution of fecal indicators in three rivers of the Haihe River Basin, China.

Science.gov (United States)

Wang, Yawei; Chen, Yanan; Zheng, Xiang; Gui, Chengmin; Wei, Yuansong

2017-04-01

Because of their significant impact on public health, waterborne pathogens, especially bacteria and viruses, are frequently monitored in surface water to assess microbial quality of water bodies. However, more than one billion people worldwide currently lack access to safe drinking water, and a diversity of waterborne outbreaks caused by pathogens is reported in nations at all levels of economic development. Spatio-temporal distribution of conventional pollutants and five pathogenic microorganisms were discussed for the Haihe River Basin. Land use and socio-economic assessments were coupled with comprehensive water quality monitoring. Physical, chemical, and biological parameters were measured at 20 different sites in the watershed for 1 year, including pH, temperature, conductivity, dissolved oxygen, turbidity, chemical oxygen demand, ammonia-N, total and fecal coliforms, E. coli, and Enterococcus. The results highlighted the high spatio-temporal variability in pathogen distribution at watershed scale: high concentration of somatic coliphages and fecal indicator bacteria in March and December and their very low concentration in June and September. All pathogens were positively correlated to urban/rural residential/industrial land and negatively correlated to other four land use types. Microbial pollution was greatly correlated with population density, urbanization rate, and percentage of the tertiary industry in the gross domestic product. In the future, river microbial risk control strategy should focus more on the effective management of secondary effluent of wastewater treatment plant and land around rivers.

The iMars WebGIS - Spatio-Temporal Data Queries and Single Image Map Web Services

Science.gov (United States)

Walter, Sebastian; Steikert, Ralf; Schreiner, Bjoern; Muller, Jan-Peter; van Gasselt, Stephan; Sidiropoulos, Panagiotis; Lanz-Kroechert, Julia

2017-04-01

Introduction: Web-based planetary image dissemination platforms usually show outline coverages of the data and offer querying for metadata as well as preview and download, e.g. the HRSC Mapserver (Walter & van Gasselt, 2014). Here we introduce a new approach for a system dedicated to change detection by simultanous visualisation of single-image time series in a multi-temporal context. While the usual form of presenting multi-orbit datasets is the merge of the data into a larger mosaic, we want to stay with the single image as an important snapshot of the planetary surface at a specific time. In the context of the EU FP-7 iMars project we process and ingest vast amounts of automatically co-registered (ACRO) images. The base of the co-registration are the high precision HRSC multi-orbit quadrangle image mosaics, which are based on bundle-block-adjusted multi-orbit HRSC DTMs. Additionally we make use of the existing bundle-adjusted HRSC single images available at the PDS archives. A prototype demonstrating the presented features is available at http://imars.planet.fu-berlin.de. Multi-temporal database: In order to locate multiple coverage of images and select images based on spatio-temporal queries, we converge available coverage catalogs for various NASA imaging missions into a relational database management system with geometry support. We harvest available metadata entries during our processing pipeline using the Integrated Software for Imagers and Spectrometers (ISIS) software. Currently, this database contains image outlines from the MGS/MOC, MRO/CTX and the MO/THEMIS instruments with imaging dates ranging from 1996 to the present. For the MEx/HRSC data, we already maintain a database which we automatically update with custom software based on the VICAR environment. Web Map Service with time support: The MapServer software is connected to the database and provides Web Map Services (WMS) with time support based on the START_TIME image attribute. It allows temporal

On the genesis of spatio-temporal self-organized structures in plasma devices

International Nuclear Information System (INIS)

Talasman, S.J.; Sanduloviciu, M.

1995-01-01

The genesis of luminous sharply defined nearly spherical space charges structures formed in an Argon plasma column was experimental investigated. The results reveal spatio-temporal characteristics proper to systems resulting after a self-organization process. Their phenomenology involves electrical charges separation produced by symmetry breaking and spatial separation of the excitation and ionization cross sections functions in a region where electrons are accelerated and, as a result, the appearance of electrostatic forces that, acting as long range correlations, assures, together with dissipative effects, its stability. (Author) 8 Figs., 31 Refs

Triceps brachii tendon: anatomic-MR imaging study in cadavers with histologic correlation

International Nuclear Information System (INIS)

Belentani, Clarissa; Pastore, Daniel; Wangwinyuvirat, Mani; Dirim, Berna; Trudell, Debra J.; Resnick, Donald; Haghighi, Parviz

2009-01-01

The purpose of this cadaveric study was to describe the normal MR anatomy of the triceps brachii tendon (TBT) insertion, to correlate the findings with those seen in anatomic sections and histopathologic analysis, and to review triceps tendon injuries. Twelve cadaveric elbows were used according to institution guidelines. T1-weighted spin-echo MR images were acquired in three planes. Findings on MR imaging were correlated with those derived from anatomic and histologic study. On MR images, the TBT had a bipartite appearance as it inserted on olecranon in all specimens. The insertion of the medial head was deeper than that of the long and lateral heads and was mainly muscular at its insertion, with a small amount of the tendon blending with the muscle distally, necessitating histologic analysis to determine if there was tendon blending with the muscle at the site of insertion and if the medial head inserted together with the common tendon or as a single unit. At histopathologic analysis, the three heads of the triceps tendon had a common insertion on the olecranon. The bipartite aspect of the tendon that was identified in the MR images was not seen by histologic study, indicating that there was a union of the medial and common tendons just before they inserted into bone. TBT has a bipartite appearance on MR images and inserts on olecranon as a single unit. (orig.)

Triceps brachii tendon: anatomic-MR imaging study in cadavers with histologic correlation

Energy Technology Data Exchange (ETDEWEB)

Belentani, Clarissa [University of California, Department of Radiology, San Diego, CA (United States); Pastore, Daniel; Wangwinyuvirat, Mani; Dirim, Berna; Trudell, Debra J.; Resnick, Donald [University of California, Department of Radiology, San Diego, CA (United States); University of California, VA Medical Center, San Diego, CA (United States); Haghighi, Parviz [University of California, VA Medical Center, San Diego, CA (United States); University of California, Department of Histology, San Diego (United States)

2009-02-15

The purpose of this cadaveric study was to describe the normal MR anatomy of the triceps brachii tendon (TBT) insertion, to correlate the findings with those seen in anatomic sections and histopathologic analysis, and to review triceps tendon injuries. Twelve cadaveric elbows were used according to institution guidelines. T1-weighted spin-echo MR images were acquired in three planes. Findings on MR imaging were correlated with those derived from anatomic and histologic study. On MR images, the TBT had a bipartite appearance as it inserted on olecranon in all specimens. The insertion of the medial head was deeper than that of the long and lateral heads and was mainly muscular at its insertion, with a small amount of the tendon blending with the muscle distally, necessitating histologic analysis to determine if there was tendon blending with the muscle at the site of insertion and if the medial head inserted together with the common tendon or as a single unit. At histopathologic analysis, the three heads of the triceps tendon had a common insertion on the olecranon. The bipartite aspect of the tendon that was identified in the MR images was not seen by histologic study, indicating that there was a union of the medial and common tendons just before they inserted into bone. TBT has a bipartite appearance on MR images and inserts on olecranon as a single unit. (orig.)

Spatiotemporal Diffusive Evolution and Fractal Structure of Ground Motion

Science.gov (United States)

Suwada, Tsuyoshi

2018-02-01

The spatiotemporal diffusive evolution and fractal structure of ground motion have been investigated at the in-ground tunnel of the KEK B-Factory (KEKB) injector linear accelerator (linac). The slow dynamic fluctuating displacements of the tunnel floor are measured in real time with a new remote-controllable sensing system based on a laser-based alignment system. Based on spatiotemporal analyses with linear-regression models, which were applied in both the time and frequency domains to time-series data recorded over a period of approximately 8 months, both coherent and stochastic components in the displacements of the tunnel floor were clearly observed along the entire length of the linac. In particular, it was clearly observed that the stochastic components exhibited characteristic spatiotemporal diffusive evolution with the fractal structure and fractional dimension. This report describes in detail the experimental techniques and analyses of the spatiotemporal diffusive evolution of ground motion observed at the in-ground tunnel of the injector linac using a real-time remote-controllable sensing system.

Indeterminacy and Spatiotemporal Data

DEFF Research Database (Denmark)

Pfoser, D.; Tryfona, N.; Jensen, Christian Søndergaard

2005-01-01

For some spatiotemporal applications, it can be assumed that the modeled world is precise and bounded, and that our record of it is precise. While these simplifying assumptions are sufficient in applications like a land information system, they are unnecessarily crude for many other applications...

Spatiotemporal Simulation of Tourist Town Growth Based on the Cellular Automata Model: The Case of Sanpo Town in Hebei Province

Directory of Open Access Journals (Sweden)

Jun Yang

2013-01-01

Full Text Available Spatiotemporal simulation of tourist town growth is important for research on land use/cover change under the influence of urbanization. Many scholars have shown great interest in the unique pattern of driving urban development with tourism development. Based on the cellular automata (CA model, we simulated and predicted the spatiotemporal growth of Sanpo town in Hebei Province, using the tourism urbanization growth model. Results showed that (1 average annual growth rate of the entire region was 1.5 Ha2 per year from 2005 to 2010, 4 Ha2 per year from 2010 to 2015, and 2.5 Ha2 per year from 2015 to 2020; (2 urban growth rate increased yearly, with regional differences, and had a high degree of correlation with the Euclidean distance of town center, traffic route, attractions, and other factors; (3 Gougezhuang, an important village center in the west of the town, demonstrated traffic advantages and increased growth rate since 2010; (4 Magezhuang village has the largest population in the region, so economic advantages have driven the development of rural urbanization. It showed that CA had high reliability in simulating the spatiotemporal evolution of tourist town, which assists the study of spatiotemporal growth under urbanization and rational protection of tourism resources.

Some practical considerations in finite element-based digital image correlation

KAUST Repository

Wang, Bo

2015-04-20

As an alternative to subset-based digital image correlation (DIC), finite element-based (FE-based) DIC method has gained increasing attention in the experimental mechanics community. However, the literature survey reveals that some important issues have not been well addressed in the published literatures. This work therefore aims to point out a few important considerations in the practical algorithm implementation of the FE-based DIC method, along with simple but effective solutions that can effectively tackle these issues. First, to better accommodate the possible intensity variations of the deformed images practically occurred in real experiments, a robust zero-mean normalized sum of squared difference criterion, instead of the commonly used sum of squared difference criterion, is introduced to quantify the similarity between reference and deformed elements in FE-based DIC. Second, to reduce the bias error induced by image noise and imperfect intensity interpolation, low-pass filtering of the speckle images with a 5×5 pixels Gaussian filter prior to correlation analysis, is presented. Third, to ensure the iterative calculation of FE-based DIC converges correctly and rapidly, an efficient subset-based DIC method, instead of simple integer-pixel displacement searching, is used to provide accurate initial guess of deformation for each calculation point. Also, the effects of various convergence criteria on the efficiency and accuracy of FE-based DIC are carefully examined, and a proper convergence criterion is recommended. The efficacy of these solutions is verified by numerical and real experiments. The results reveal that the improved FE-based DIC offers evident advantages over existing FE-based DIC method in terms of accuracy and efficiency. © 2015 Elsevier Ltd. All rights reserved.

Correlated topographic and spectroscopic imaging by combined atomic force microscopy and optical microscopy

International Nuclear Information System (INIS)

Hu Dehong; Micic, Miodrag; Klymyshyn, Nicholas; Suh, Y.D.; Lu, H.P.

2004-01-01

Near-field scanning microscopy is a powerful approach to obtain topographic and spectroscopic characterization simultaneously for imaging biological and nanoscale systems. To achieve optical imaging at high spatial resolution beyond the diffraction limit, aperture-less metallic scanning tips have been utilized to enhance the laser illumination local electromagnetic field at the apex of the scanning tips. In this paper, we discuss and review our work on combined fluorescence imaging with AFM-metallic tip enhancement, finite element method simulation of the tip enhancement, and their applications on AFM-tip enhanced fluorescence lifetime imaging (AFM-FLIM) and correlated AFM and FLIM imaging of the living cells

Medulloblastoma: correlation among findings of conventional magnetic resonance imaging, diffusion-weighted imaging and proton magnetic resonance spectroscopy

Energy Technology Data Exchange (ETDEWEB)

Fonte, Mariana Vieira de Melo da; Otaduy, Maria Concepcion Garcia; Lucato, Leandro Tavares; Reed, Umbertina Conti; Leite, Claudia da Costa [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Hospital das Clinicas. Inst. de Radiologia]. E-mail: mvmfonte@uol.com.br; Costa, Maria Olivia Rodrigues; Amaral, Raquel Portugal Guimaraes [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Faculdade de Medicina. Dept. de Radiologia; Reed, Umbertina Conti [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Faculdade de Medicina. Dept. de Neurologia; Rosemberg, Sergio [Universidade de Sao Paulo (USP), Sao Paulo, SP (Brazil). Hospital das Clinicas. Dept. de Patologia

2008-11-15

To correlate imaging findings of medulloblastomas at conventional magnetic resonance imaging, diffusion-weighted imaging and proton magnetic resonance spectroscopy, comparing them with data in the literature. Preoperative magnetic resonance imaging studies of nine pediatric patients with histologically confirmed medulloblastomas (eight desmoplastic medulloblastoma, and one giant cell medulloblastoma) were retrospectively reviewed, considering demographics as well as tumors characteristics such as localization, morphology, signal intensity, contrast-enhancement, dissemination, and diffusion-weighted imaging and spectroscopy findings. In most of cases the tumors were centered in the cerebellar vermis (77.8%), predominantly solid (88.9%), hypointense on T 1-weighted images and intermediate/hyperintense on T 2-FLAIR-weighted images, with heterogeneous enhancement (100%), tumor dissemination/extension (77.8%) and limited water molecule mobility (100%). Proton spectroscopy acquired with STEAM technique (n = 6) demonstrated decreased Na a / Cr ratio (83.3%) and increased Co/Cr (100%) and ml/Cr (66.7%) ratios; and with PRESS technique (n = 7) demonstrated lactate peak (57.1%). Macroscopic magnetic resonance imaging findings in association with biochemical features of medulloblastomas have been useful in the differentiation among the most frequent posterior fossa tumors. (author)

Medulloblastoma: correlation among findings of conventional magnetic resonance imaging, diffusion-weighted imaging and proton magnetic resonance spectroscopy

International Nuclear Information System (INIS)

Fonte, Mariana Vieira de Melo da; Otaduy, Maria Concepcion Garcia; Lucato, Leandro Tavares; Reed, Umbertina Conti; Leite, Claudia da Costa; Costa, Maria Olivia Rodrigues; Amaral, Raquel Portugal Guimaraes; Reed, Umbertina Conti; Rosemberg, Sergio

2008-01-01

To correlate imaging findings of medulloblastomas at conventional magnetic resonance imaging, diffusion-weighted imaging and proton magnetic resonance spectroscopy, comparing them with data in the literature. Preoperative magnetic resonance imaging studies of nine pediatric patients with histologically confirmed medulloblastomas (eight desmoplastic medulloblastoma, and one giant cell medulloblastoma) were retrospectively reviewed, considering demographics as well as tumors characteristics such as localization, morphology, signal intensity, contrast-enhancement, dissemination, and diffusion-weighted imaging and spectroscopy findings. In most of cases the tumors were centered in the cerebellar vermis (77.8%), predominantly solid (88.9%), hypointense on T 1-weighted images and intermediate/hyperintense on T 2-FLAIR-weighted images, with heterogeneous enhancement (100%), tumor dissemination/extension (77.8%) and limited water molecule mobility (100%). Proton spectroscopy acquired with STEAM technique (n = 6) demonstrated decreased Na a / Cr ratio (83.3%) and increased Co/Cr (100%) and ml/Cr (66.7%) ratios; and with PRESS technique (n = 7) demonstrated lactate peak (57.1%). Macroscopic magnetic resonance imaging findings in association with biochemical features of medulloblastomas have been useful in the differentiation among the most frequent posterior fossa tumors. (author)

High-speed technique based on a parallel projection correlation procedure for digital image correlation

Science.gov (United States)

Zaripov, D. I.; Renfu, Li

2018-05-01

The implementation of high-efficiency digital image correlation methods based on a zero-normalized cross-correlation (ZNCC) procedure for high-speed, time-resolved measurements using a high-resolution digital camera is associated with big data processing and is often time consuming. In order to speed-up ZNCC computation, a high-speed technique based on a parallel projection correlation procedure is proposed. The proposed technique involves the use of interrogation window projections instead of its two-dimensional field of luminous intensity. This simplification allows acceleration of ZNCC computation up to 28.8 times compared to ZNCC calculated directly, depending on the size of interrogation window and region of interest. The results of three synthetic test cases, such as a one-dimensional uniform flow, a linear shear flow and a turbulent boundary-layer flow, are discussed in terms of accuracy. In the latter case, the proposed technique is implemented together with an iterative window-deformation technique. On the basis of the results of the present work, the proposed technique is recommended to be used for initial velocity field calculation, with further correction using more accurate techniques.

Dynamical topology and statistical properties of spatiotemporal chaos.

Science.gov (United States)

Zhuang, Quntao; Gao, Xun; Ouyang, Qi; Wang, Hongli

2012-12-01

For spatiotemporal chaos described by partial differential equations, there are generally locations where the dynamical variable achieves its local extremum or where the time partial derivative of the variable vanishes instantaneously. To a large extent, the location and movement of these topologically special points determine the qualitative structure of the disordered states. We analyze numerically statistical properties of the topologically special points in one-dimensional spatiotemporal chaos. The probability distribution functions for the number of point, the lifespan, and the distance covered during their lifetime are obtained from numerical simulations. Mathematically, we establish a probabilistic model to describe the dynamics of these topologically special points. In spite of the different definitions in different spatiotemporal chaos, the dynamics of these special points can be described in a uniform approach.

Spatiotemporal Psychopathology II: How does a psychopathology of the brain's resting state look like? Spatiotemporal approach and the history of psychopathology.

Science.gov (United States)

Northoff, Georg

2016-01-15

Psychopathology as the investigation and classification of experience, behavior and symptoms in psychiatric patients is an old discipline that ranges back to the end of the 19th century. Since then different approaches to psychopathology have been suggested. Recent investigations showing abnormalities in the brain on different levels raise the question how the gap between brain and psyche, between neural abnormalities and alteration in experience and behavior can be bridged. Historical approaches like descriptive (Jaspers) and structural (Minkoswki) psychopathology as well as the more current phenomenological psychopathology (Paarnas, Fuchs, Sass, Stanghellini) remain on the side of the psyche giving detailed description of the phenomenal level of experience while leaving open the link to the brain. In contrast, the recently introduced Research Domain Classification (RDoC) aims at explicitly linking brain and psyche by starting from so-called 'neuro-behavioral constructs'. How does Spatiotemporal Psychopathology, as demonstrated in the first paper on depression, stand in relation to these approaches? In a nutshell, Spatiotemporal Psychopathology aims to bridge the gap between brain and psyche. Specifically, as demonstrated in depression in the first paper, the focus is on the spatiotemporal features of the brain's intrinsic activity and how they are transformed into corresponding spatiotemporal features in experience on the phenomenal level and behavioral changes, which can well account for the symptoms in these patients. This second paper focuses on some of the theoretical background assumptions in Spatiotemporal Psychopathology by directly comparing it to descriptive, structural, and phenomenological psychopathology as well as to RDoC. Copyright © 2015 Elsevier B.V. All rights reserved.

Histopathologic correlation of magnetic resonance imaging signal patterns in a spinal cord injury model.

Science.gov (United States)

Weirich, S D; Cotler, H B; Narayana, P A; Hazle, J D; Jackson, E F; Coupe, K J; McDonald, C L; Langford, L A; Harris, J H

1990-07-01

Magnetic resonance imaging (MRI) provides a noninvasive method of monitoring the pathologic response to spinal cord injury. Specific MR signal intensity patterns appear to correlate with degrees of improvement in the neurologic status in spinal cord injury patients. Histologic correlation of two types of MR signal intensity patterns are confirmed in the current study using a rat animal model. Adult male Sprague-Dawley rats underwent spinal cord trauma at the midthoracic level using a weight-dropping technique. After laminectomy, 5- and 10-gm brass weights were dropped from designated heights onto a 0.1-gm impounder placed on the exposed dura. Animals allowed to regain consciousness demonstrated variable recovery of hind limb paraplegia. Magnetic resonance images were obtained from 2 hours to 1 week after injury using a 2-tesla MRI/spectrometer. Sacrifice under anesthesia was performed by perfusive fixation; spinal columns were excised en bloc, embedded, sectioned, and observed with the compound light microscope. Magnetic resonance axial images obtained during the time sequence after injury demonstrate a distinct correlation between MR signal intensity patterns and the histologic appearance of the spinal cord. Magnetic resonance imaging delineates the pathologic processes resulting from acute spinal cord injury and can be used to differentiate the type of injury and prognosis.

Building spatio-temporal database model based on ontological approach using relational database environment

International Nuclear Information System (INIS)

Mahmood, N.; Burney, S.M.A.

2017-01-01

Everything in this world is encapsulated by space and time fence. Our daily life activities are utterly linked and related with other objects in vicinity. Therefore, a strong relationship exist with our current location, time (including past, present and future) and event through with we are moving as an object also affect our activities in life. Ontology development and its integration with database are vital for the true understanding of the complex systems involving both spatial and temporal dimensions. In this paper we propose a conceptual framework for building spatio-temporal database model based on ontological approach. We have used relational data model for modelling spatio-temporal data content and present our methodology with spatio-temporal ontological accepts and its transformation into spatio-temporal database model. We illustrate the implementation of our conceptual model through a case study related to cultivated land parcel used for agriculture to exhibit the spatio-temporal behaviour of agricultural land and related entities. Moreover, it provides a generic approach for designing spatiotemporal databases based on ontology. The proposed model is capable to understand the ontological and somehow epistemological commitments and to build spatio-temporal ontology and transform it into a spatio-temporal data model. Finally, we highlight the existing and future research challenges. (author)

Posteromedial corner of the knee: MR imaging with gross anatomic correlation

Energy Technology Data Exchange (ETDEWEB)

Loredo, R. (Texas Univ., San Antonio, TX (United States). Dept. of Radiology); Hodler, J. (Department of Radiology, Univ. of Zurich (Switzerland)); Pedowitz, R. (Department of Orthopedic Surgery, Veterans Administration Medical Center (VAMC), San Diego, CA (United States)); Yeh, L.-R.; Trudell, D.; Resnick, D. (Department of Radiology, Veterans Administration Medical Center (VAMC), 3350 La Jolla Village Drive, San Diego, CA 92161 (United States))

1999-06-01

Objective. The objective of this study was to illustrate the magnetic resonance (MR) image appearance of the structures of the posteromedial ''corner'' of the knee with particular emphasis on the anatomy and differentiation between the medial collateral ligament and the posterior oblique ligament.Design. Six cadaveric knee specimens underwent MR imaging, before and following instillation of intra-articular contrast material. The knees were sectioned in the axial, coronal, and coronal oblique planes and the gross morphology of the posteromedial corner and surrounding structures was studied and correlated with the MR images.Patients. The human cadaveric specimens were from two female and four male patients (age at death, 72-86 years; average, 78 years).Results and conclusions. The contrast-enhanced sequences and the coronal oblique images allowed for improved visualization of the structures. (orig.) With 8 figs., 7 refs.

Magnetic resonance imaging for extramammary Paget's disease: radiological and pathological correlations

International Nuclear Information System (INIS)

Akaike, Gensuke; Nozaki, Taiki; Matsusako, Masaki; Saida, Yukihisa; Matsui, Mizuko; Ohtake, Naoyuki; Eto, Hikaru; Suzuki, Koyu

2013-01-01

Extramammary Paget's disease (EMPD) is a rare cutaneous neoplasm that is thought to represent intraepithelial adenocarcinoma developing in an area rich in apocrine glands. Magnetic resonance imaging (MRI) findings for this disease are not well established. We report three cases of pathologically confirmed EMPD in which MRI was performed before surgery. The lesions were widespread in the epidermis and the dermis. Lesions were sharply well enhanced on gadolinium-enhanced T1-weighted imaging and appeared hyperintense on diffusion-weighted imaging in all cases. Areas with enhancement in depth corresponded well with the pathological lesion. In addition, different malignant legions were found on the same images from MRI in two cases, indicating potential associations with other malignancies. We describe the MRI findings and their pathological correlation. MRI could be useful for preoperative evaluation of disease spread and detection of associated malignancies. (orig.)

Segmentation and classification of cell cycle phases in fluorescence imaging.

Science.gov (United States)

Ersoy, Ilker; Bunyak, Filiz; Chagin, Vadim; Cardoso, M Christina; Palaniappan, Kannappan

2009-01-01

Current chemical biology methods for studying spatiotemporal correlation between biochemical networks and cell cycle phase progression in live-cells typically use fluorescence-based imaging of fusion proteins. Stable cell lines expressing fluorescently tagged protein GFP-PCNA produce rich, dynamically varying sub-cellular foci patterns characterizing the cell cycle phases, including the progress during the S-phase. Variable fluorescence patterns, drastic changes in SNR, shape and position changes and abundance of touching cells require sophisticated algorithms for reliable automatic segmentation and cell cycle classification. We extend the recently proposed graph partitioning active contours (GPAC) for fluorescence-based nucleus segmentation using regional density functions and dramatically improve its efficiency, making it scalable for high content microscopy imaging. We utilize surface shape properties of GFP-PCNA intensity field to obtain descriptors of foci patterns and perform automated cell cycle phase classification, and give quantitative performance by comparing our results to manually labeled data.

Monitoring of civil engineering structures using Digital Image Correlation technique

Science.gov (United States)

Malesa, M.; Szczepanek, D.; Kujawińska, M.; Świercz, A.; Kołakowski, P.

2010-06-01

The Digital Image Correlation (DIC) technique enables full field, noncontact measurements of displacements and strains of a wide variety of objects. An adaptation of the DIC technique for monitoring of civil-engineering structures is presented in the paper. A general concept of the complex, automatic monitoring system, in which the DIC sensor plays an important role is described. Some new software features, which aim to facilitate outdoor measurements and speed up the correlation analysis, is also introduced. As an example of application, measurements of a railway bridge in Nieporet (Poland) are presented. The experimental results are compared with displacements of a FEM model of the bridge.

High Spatio-Temporal Resolution Bathymetry Estimation and Morphology

Science.gov (United States)

Bergsma, E. W. J.; Conley, D. C.; Davidson, M. A.; O'Hare, T. J.

2015-12-01

In recent years, bathymetry estimates using video images have become increasingly accurate. With the cBathy code (Holman et al., 2013) fully operational, bathymetry results with 0.5 metres accuracy have been regularly obtained at Duck, USA. cBathy is based on observations of the dominant frequencies and wavelengths of surface wave motions and estimates the depth (and hence allows inference of bathymetry profiles) based on linear wave theory. Despite the good performance at Duck, large discrepancies were found related to tidal elevation and camera height (Bergsma et al., 2014) and on the camera boundaries. A tide dependent floating pixel and camera boundary solution have been proposed to overcome these issues (Bergsma et al., under review). The video-data collection is set estimate depths hourly on a grid with resolution in the order of 10x25 meters. Here, the application of the cBathy at Porthtowan in the South-West of England is presented. Hourly depth estimates are combined and analysed over a period of 1.5 years (2013-2014). In this work the focus is on the sub-tidal region, where the best cBathy results are achieved. The morphology of the sub-tidal bar is tracked with high spatio-temporal resolution on short and longer time scales. Furthermore, the impact of the storm and reset (sudden and large changes in bathymetry) of the sub-tidal area is clearly captured with the depth estimations. This application shows that the high spatio-temporal resolution of cBathy makes it a powerful tool for coastal research and coastal zone management.

Chondroid lipoma: correlation of imaging findings and histopathology of an unusual benign lesion

International Nuclear Information System (INIS)

Green, R.A.R.; Cannon, S.R.; Flanagan, A.M.

2004-01-01

The imaging findings of soft tissue tumours are often non-specific and generally require biopsy to differentiate between benign and malignant lesions. The finding of curvilinear, annular or amorphous mineralisation in an enlarging mass has sinister connotations. In this case report, we present the imaging findings with histological correlation of a chondroid lipoma, an unusual benign soft tissue tumour, which presented with radiographic evidence of calcification, an imaging finding not previously described. We also describe the ultrasound appearance and certain MR imaging appearances that have not been previously attributed to this tumour in the few reported cases. (orig.)

Ischemic lesion volume determination on diffusion weighted images vs. apparent diffusion coefficient maps.

Science.gov (United States)

Bråtane, Bernt Tore; Bastan, Birgul; Fisher, Marc; Bouley, James; Henninger, Nils

2009-07-07

Though diffusion weighted imaging (DWI) is frequently used for identifying the ischemic lesion in focal cerebral ischemia, the understanding of spatiotemporal evolution patterns observed with different analysis methods remains imprecise. DWI and calculated apparent diffusion coefficient (ADC) maps were serially obtained in rat stroke models (MCAO): permanent, 90 min, and 180 min temporary MCAO. Lesion volumes were analyzed in a blinded and randomized manner by 2 investigators using (i) a previously validated ADC threshold, (ii) visual determination of hypointense regions on ADC maps, and (iii) visual determination of hyperintense regions on DWI. Lesion volumes were correlated with 24 hour 2,3,5-triphenyltetrazoliumchloride (TTC)-derived infarct volumes. TTC-derived infarct volumes were not significantly different from the ADC and DWI-derived lesion volumes at the last imaging time points except for significantly smaller DWI lesions in the pMCAO model (p=0.02). Volumetric calculation based on TTC-derived infarct also correlated significantly stronger to volumetric calculation based on last imaging time point derived lesions on ADC maps than DWI (pdetermined lesion volumes on ADC maps and DWI by both investigators correlated significantly with threshold-derived lesion volumes on ADC maps with the former method demonstrating a stronger correlation. There was also a better interrater agreement for ADC map analysis than for DWI analysis. Ischemic lesion determination by ADC was more accurate in final infarct prediction, rater independent, and provided exclusive information on ischemic lesion reversibility.

Urban heat island effect: A systematic review of spatio-temporal factors, data, methods, and mitigation measures

Science.gov (United States)

Deilami, Kaveh; Kamruzzaman, Md.; Liu, Yan

2018-05-01

Despite research on urban heat island (UHI) effect has increased exponentially over the last few decades, a systematic review of factors contributing to UHI effect has scarcely been reported in the literature. This paper provides a systematic and overarching review of different spatial and temporal factors affecting the UHI effect. UHI is a phenomenon when urban areas experience a higher temperature than their surrounding non-urban areas and is considered as a critical factor contributing to global warming, heat related mortalities, and unpredictable climatic changes. Therefore, there is a pressing need to identify the spatio-temporal factors that contribute to (or mitigate) the UHI effect in order to develop a thorough understanding of their causal mechanism so that these are addressed through urban planning policies. This paper systematically identified 75 eligible studies on UHI effect and reviews the nature and type of satellite images used, the techniques applied to classify land cover/use changes, the models to assess the link between spatio-temporal factors and UHI effect, and the effects of these factors on UHI. The review results show that: a) 54% of the studies used Landsat TM images for modelling the UHI effect followed by Landsat ETM (34%), and MODIS (28%); b) land cover indices (46%), followed by supervised classification (17%) were the dominant methods to derive land cover/use changes associated with UHI effect; c) ordinary least square regression is the most commonly applied method (68%) to investigate the link between different spatio-temporal factors and the UHI effect followed by comparative analysis (33%); and d) the most common factors affecting the UHI effect as reported in the reviewed studies, include vegetation cover (44%), season (33%), built-up area (28%), day/night (25%), population density (14%), water body (12%) together with others. This research discusses the findings in policy terms and provides directions for future research.

Automated correlation and classification of secondary ion mass spectrometry images using a k-means cluster method.

Science.gov (United States)

Konicek, Andrew R; Lefman, Jonathan; Szakal, Christopher

2012-08-07

We present a novel method for correlating and classifying ion-specific time-of-flight secondary ion mass spectrometry (ToF-SIMS) images within a multispectral dataset by grouping images with similar pixel intensity distributions. Binary centroid images are created by employing a k-means-based custom algorithm. Centroid images are compared to grayscale SIMS images using a newly developed correlation method that assigns the SIMS images to classes that have similar spatial (rather than spectral) patterns. Image features of both large and small spatial extent are identified without the need for image pre-processing, such as normalization or fixed-range mass-binning. A subsequent classification step tracks the class assignment of SIMS images over multiple iterations of increasing n classes per iteration, providing information about groups of images that have similar chemistry. Details are discussed while presenting data acquired with ToF-SIMS on a model sample of laser-printed inks. This approach can lead to the identification of distinct ion-specific chemistries for mass spectral imaging by ToF-SIMS, as well as matrix-assisted laser desorption ionization (MALDI), and desorption electrospray ionization (DESI).