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Space Data (space + data)
Selected AbstractsEmpirical Bayes estimators and non-parametric mixture models for space and time,space disease mapping and surveillanceENVIRONMETRICS, Issue 5 2003Dankmar Böhning Abstract The analysis of the geographic variation of disease and its representation on a map is an important topic in epidemiological research and in public health in general. Identification of spatial heterogeneity of relative risk using morbidity and mortality data is required. Frequently, interest is also in the analysis of space data with respect to time, where typically data are used which are aggregated in certain time windows like 5 or 10 years. The occurrence measure of interest is usually the standardized mortality (morbidity) ratio (SMR). It is well known that disease maps in space or in space and time should not solely be based upon the crude SMR but rather some smoothed version of it. This fact has led to a tremendous amount of theoretical developments in spatial methodology, in particular in the area of hierarchical modeling in connection with fully Bayesian estimation techniques like Markov chain Monte Carlo. It seems, however, that at the same time, where these theoretical developments took place, on the practical side only very few of these developments have found their way into daily practice of epidemiological work and surveillance routines. In this article we focus on developments that avoid the pitfalls of the crude SMR and simultaneously retain a simplicity and, at least approximately, the validity of more complex models. After an illustration of the typical pitfalls of the crude SMR the article is centered around three issues: (a) the separation of spatial random variation from spatial structural variation; (b) a simple mixture model for capturing spatial heterogeneity; (c) an extension of this model for capturing temporal information. The techniques are illustrated by numerous examples. Public domain software like Dismap is mentioned that enables easy mixture modeling in the context of disease mapping. Copyright © 2003 John Wiley & Sons, Ltd. [source] Accelerating non-contrast-enhanced MR angiography with inflow inversion recovery imaging by skipped phase encoding and edge deghosting (SPEED)JOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 3 2010Zheng Chang PhD Abstract Purpose: To accelerate non-contrast-enhanced MR angiography (MRA) with inflow inversion recovery (IFIR) with a fast imaging method, Skipped Phase Encoding and Edge Deghosting (SPEED). Materials and Methods: IFIR imaging uses a preparatory inversion pulse to reduce signals from static tissue, while leaving inflow arterial blood unaffected, resulting in sparse arterial vasculature on modest tissue background. By taking advantage of vascular sparsity, SPEED can be simplified with a single-layer model to achieve higher efficiency in both scan time reduction and image reconstruction. SPEED can also make use of information available in multiple coils for further acceleration. The techniques are demonstrated with a three-dimensional renal non-contrast-enhanced IFIR MRA study. Results: Images are reconstructed by SPEED based on a single-layer model to achieve an undersampling factor of up to 2.5 using one skipped phase encoding direction. By making use of information available in multiple coils, SPEED can achieve an undersampling factor of up to 8.3 with four receiver coils. The reconstructed images generally have comparable quality as that of the reference images reconstructed from full k -space data. Conclusion: As demonstrated with a three-dimensional renal IFIR scan, SPEED based on a single-layer model is able to reduce scan time further and achieve higher computational efficiency than the original SPEED. J. Magn. Reson. Imaging 2010;31:757,765. © 2010 Wiley-Liss, Inc. [source] Feasibility of k-t BLAST technique for measuring "seven-dimensional" fluid flowJOURNAL OF MAGNETIC RESONANCE IMAGING, Issue 2 2006Ian Marshall PhD Abstract Purpose To investigate the feasibility of rapid MR measurement of "seven-dimensional" (three velocity components, three dimensions, and time) fluid flow using the k-t Broad-use Linear Acquisition Speed-Up Technique (BLAST). Materials and Methods Complete k -space data were acquired for pulsatile fluid flow in a model of a stenosed carotid bifurcation. The data was subsampled to simulate "training" and "accelerated acquisition" data for reconstruction using k-t BLAST. Results Flow waveforms estimated from k-t BLAST reconstructions were in good agreement with those measured from the full data set for overall speedup factors up to approximately four times when slice-by-slice undersampling in ky was used. Accuracy was better than 25 mm/second or 7% (root-mean-square error) for individual time frames under these conditions. Flow patterns in the plane of symmetry, near the bifurcation, and in the stenosis were also in good agreement with those reconstructed from the full data set. Improved performance was obtained from undersampling in both ky and kz, when acceleration factors up to 12 times gave acceptable results. Conclusion The k-t BLAST technique can be applied to flow quantification, and may make feasible the acquisition of time-resolved blood flow from extended arterial regions within acceptable examination times. J. Magn. Reson. Imaging 2006. © 2006 Wiley-Liss, Inc. [source] Application of k -space energy spectrum analysis for inherent and dynamic B0 mapping and deblurring in spiral imagingMAGNETIC RESONANCE IN MEDICINE, Issue 4 2010Trong-Kha Truong Abstract Spiral imaging is vulnerable to spatial and temporal variations of the amplitude of the static magnetic field (B0) caused by susceptibility effects, eddy currents, chemical shifts, subject motion, physiological noise, and system instabilities, resulting in image blurring. Here, a novel off-resonance correction method is proposed to address these issues. A k -space energy spectrum analysis algorithm is first applied to inherently and dynamically generate a B0 map from the k -space data at each time point, without requiring any additional data acquisition, pulse sequence modification, or phase unwrapping. A simulated phase evolution rewinding algorithm and an automatic residual deblurring algorithm are then used to correct for the blurring caused by both spatial and temporal B0 variations, resulting in a high spatial and temporal fidelity. This method is validated against conventional B0 mapping and deblurring methods, and its advantages for dynamic MRI applications are demonstrated in functional MRI studies. Magn Reson Med, 2010. © 2010 Wiley-Liss, Inc. [source] Photometric redshifts with surface brightness priorsMONTHLY NOTICES OF THE ROYAL ASTRONOMICAL SOCIETY, Issue 3 2008Hans F. Stabenau ABSTRACT We use galaxy surface brightness as prior information to improve photometric redshift (photo- z) estimation. We apply our template-based photo- z method to imaging data from the ground-based VVDS survey and the space-based GOODS field from HST, and use spectroscopic redshifts to test our photometric redshifts for different galaxy types and redshifts. We find that the surface brightness prior eliminates a large fraction of outliers by lifting the degeneracy between the Lyman and 4000-Å breaks. Bias and scatter are improved by about a factor of 2 with the prior in each redshift bin in the range 0.4 < z < 1.3, for both the ground and space data. Ongoing and planned surveys from the ground and space will benefit, provided that care is taken in measurements of galaxy sizes and in the application of the prior. We discuss the image quality and signal-to-noise ratio requirements that enable the surface brightness prior to be successfully applied. [source] Modeling solar cell degradation in space: A comparison of the NRL displacement damage dose and the JPL equivalent fluence approaches,PROGRESS IN PHOTOVOLTAICS: RESEARCH & APPLICATIONS, Issue 2 2001S. R. Messenger The method for predicting solar cell degradation in space radiation environments developed recently at the US Naval Research Laboratory (NRL) is compared in detail with the earlier method developed at the US Jet Propulsion Laboratory (JPL). Although both methods are similar, the key difference is that in the NRL approach, the energy dependence of the damage coefficients is determined from a calculation of the nonionizing energy loss (NIEL) and requires relatively few experimental measurements, whereas in the JPL method the damage coefficients have to be determined using an extensive set of experimental measurements. The end result of the NRL approach is a determination of a single characteristic degradation curve for a cell technology, which is measured against displacement damage dose rather than fluence. The end-of-life (EOL) cell performance for a particular mission can be read from the characteristic curve once the displacement damage dose for the mission has been determined. In the JPL method, the end result is a determination of the equivalent 1,MeV electron fluence, which would cause the same level of degradation as the actual space environment. The two approaches give similar results for GaAs/Ge solar cells, for which a large database exists. Because the NRL method requires far less experimental data than the JPL method, it is more readily applied to emerging cell technologies for which extensive radiation measurements are not available. The NRL approach is being incorporated into a code named SAVANT by researchers at NASA Glenn Research Center. The predictions of SAVANT are shown to agree closely with actual space data for GaAs/Ge and CuInSe2 cells flown on the Equator-S mission. Published in 2001 by John Wiley & Sons, Ltd. [source] | ||||||||||