154 resultados para Noise mapping

em Université de Lausanne, Switzerland


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The large spatial inhomogeneity in transmit B, field (B-1(+)) observable in human MR images at hi h static magnetic fields (B-0) severely impairs image quality. To overcome this effect in brain T-1-weighted images the, MPRAGE sequence was modified to generate two different images at different inversion times MP2RAGE By combining the two images in a novel fashion, it was possible to create T-1-weigthed images where the result image was free of proton density contrast, T-2* contrast, reception bias field, and, to first order transmit field inhomogeneity. MP2RAGE sequence parameters were optimized using Bloch equations to maximize contrast-to-noise ratio per unit of time between brain tissues and minimize the effect of B-1(+) variations through space. Images of high anatomical quality and excellent brain tissue differentiation suitable for applications such as segmentation and voxel-based morphometry were obtained at 3 and 7 T. From such T-1-weighted images, acquired within 12 min, high-resolution 3D T-1 maps were routinely calculated at 7 T with sub-millimeter voxel resolution (0.65-0.85 mm isotropic). T-1 maps were validated in phantom experiments. In humans, the T, values obtained at 7 T were 1.15 +/- 0.06 s for white matter (WM) and 1.92 +/- 0.16 s for grey matter (GM), in good agreement with literature values obtained at lower spatial resolution. At 3 T, where whole-brain acquisitions with 1 mm isotropic voxels were acquired in 8 min the T-1 values obtained (0.81 +/- 0.03 S for WM and 1.35 +/- 0.05 for GM) were once again found to be in very good agreement with values in the literature. (C) 2009 Elsevier Inc. All rights reserved.

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MRI visualization of devices is traditionally based on signal loss due to T(2)* effects originating from local susceptibility differences. To visualize nitinol devices with positive contrast, a recently introduced postprocessing method is adapted to map the induced susceptibility gradients. This method operates on regular gradient-echo MR images and maps the shift in k-space in a (small) neighborhood of every voxel by Fourier analysis followed by a center-of-mass calculation. The quantitative map of the local shifts generates the positive contrast image of the devices, while areas without susceptibility gradients render a background with noise only. The positive signal response of this method depends only on the choice of the voxel neighborhood size. The properties of the method are explained and the visualizations of a nitinol wire and two stents are shown for illustration.

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The large spatial inhomogeneity in transmit B(1) field (B(1)(+)) observable in human MR images at high static magnetic fields (B(0)) severely impairs image quality. To overcome this effect in brain T(1)-weighted images, the MPRAGE sequence was modified to generate two different images at different inversion times, MP2RAGE. By combining the two images in a novel fashion, it was possible to create T(1)-weighted images where the result image was free of proton density contrast, T(2) contrast, reception bias field, and, to first order, transmit field inhomogeneity. MP2RAGE sequence parameters were optimized using Bloch equations to maximize contrast-to-noise ratio per unit of time between brain tissues and minimize the effect of B(1)(+) variations through space. Images of high anatomical quality and excellent brain tissue differentiation suitable for applications such as segmentation and voxel-based morphometry were obtained at 3 and 7 T. From such T(1)-weighted images, acquired within 12 min, high-resolution 3D T(1) maps were routinely calculated at 7 T with sub-millimeter voxel resolution (0.65-0.85 mm isotropic). T(1) maps were validated in phantom experiments. In humans, the T(1) values obtained at 7 T were 1.15+/-0.06 s for white matter (WM) and 1.92+/-0.16 s for grey matter (GM), in good agreement with literature values obtained at lower spatial resolution. At 3 T, where whole-brain acquisitions with 1 mm isotropic voxels were acquired in 8 min, the T(1) values obtained (0.81+/-0.03 s for WM and 1.35+/-0.05 for GM) were once again found to be in very good agreement with values in the literature.

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Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.

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PURPOSE: To implement and characterize an isotropic three-dimensional cardiac T2 mapping technique. METHODS: A self-navigated three-dimensional radial segmented balanced steady-state free precession pulse sequence with an isotropic 1.7-mm spatial resolution was implemented at 3T with a variable T2 preparation module. Bloch equation and Monte Carlo simulations were performed to determine the influence of the heart rate, B1 inhomogeneity and noise on the T2 fitting accuracy. In a phantom study, the accuracy of the pulse sequence was studied through comparison with a gold-standard spin-echo T2 mapping method. The robustness and homogeneity of the technique were ascertained in a study of 10 healthy adult human volunteers, while first results obtained in patients are reported. RESULTS: The numerical simulations demonstrated that the heart rate and B1 inhomogeneity cause only minor deviations in the T2 fitting, whereas the phantom study showed good agreement of the technique with the gold standard. The volunteer study demonstrated an average myocardial T2 of 40.5 ± 3.3 ms and a <15% T2 gradient in the base-apex and anterior-inferior direction. In three patients, elevated T2 values were measured in regions with expected edema. CONCLUSION: This respiratory self-navigated isotropic three-dimensional technique allows for accurate and robust in vitro and in vivo T2 quantification. Magn Reson Med 73:1549-1554, 2015. © 2014 Wiley Periodicals, Inc.

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PURPOSE: All methods presented to date to map both conductivity and permittivity rely on multiple acquisitions to compute quantitatively the magnitude of radiofrequency transmit fields, B1+. In this work, we propose a method to compute both conductivity and permittivity based solely on relative receive coil sensitivities ( B1-) that can be obtained in one single measurement without the need to neither explicitly perform transmit/receive phase separation nor make assumptions regarding those phases. THEORY AND METHODS: To demonstrate the validity and the noise sensitivity of our method we used electromagnetic finite differences simulations of a 16-channel transceiver array. To experimentally validate our methodology at 7 Tesla, multi compartment phantom data was acquired using a standard 32-channel receive coil system and two-dimensional (2D) and 3D gradient echo acquisition. The reconstructed electric properties were correlated to those measured using dielectric probes. RESULTS: The method was demonstrated both in simulations and in phantom data with correlations to both the modeled and bench measurements being close to identity. The noise properties were modeled and understood. CONCLUSION: The proposed methodology allows to quantitatively determine the electrical properties of a sample using any MR contrast, with the only constraint being the need to have 4 or more receive coils and high SNR. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.

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BACKGROUND: Highway maintenance workers are constantly and simultaneously exposed to traffic-related particle and noise emissions, and both have been linked to increased cardiovascular morbidity and mortality in population-based epidemiology studies. OBJECTIVES: We aimed to investigate short-term health effects related to particle and noise exposure. METHODS: We monitored 18 maintenance workers, during as many as five 24-hour periods from a total of 50 observation days. We measured their exposure to fine particulate matter (PM2.5), ultrafine particles, noise, and the cardiopulmonary health endpoints: blood pressure, pro-inflammatory and pro-thrombotic markers in the blood, lung function and fractional exhaled nitric oxide (FeNO) measured approximately 15 hours post-work. Heart rate variability was assessed during a sleep period approximately 10 hours post-work. RESULTS: PM2.5 exposure was significantly associated with C-reactive protein and serum amyloid A, and negatively associated with tumor necrosis factor α. None of the particle metrics were significantly associated with von Willebrand factor or tissue factor expression. PM2.5 and work noise were associated with markers of increased heart rate variability, and with increased HF and LF power. Systolic and diastolic blood pressure on the following morning were significantly associated with noise exposure after work, and non-significantly associated with PM2.5. We observed no significant associations between any of the exposures and lung function or FeNO. CONCLUSIONS: Our findings suggest that exposure to particles and noise during highway maintenance work might pose a cardiovascular health risk. Actions to reduce these exposures could lead to better health for this population of workers.

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After ischemic stroke, the ischemic damage to brain tissue evolves over time and with an uneven spatial distribution. Early irreversible changes occur in the ischemic core, whereas, in the penumbra, which receives more collateral blood flow, the damage is more mild and delayed. A better characterization of the penumbra, irreversibly damaged and healthy tissues is needed to understand the mechanisms involved in tissue death. MRSI is a powerful tool for this task if the scan time can be decreased whilst maintaining high sensitivity. Therefore, we made improvements to a (1) H MRSI protocol to study middle cerebral artery occlusion in mice. The spatial distribution of changes in the neurochemical profile was investigated, with an effective spatial resolution of 1.4 μL, applying the protocol on a 14.1-T magnet. The acquired maps included the difficult-to-separate glutamate and glutamine resonances and, to our knowledge, the first mapping of metabolites γ-aminobutyric acid and glutathione in vivo, within a metabolite measurement time of 45 min. The maps were in excellent agreement with findings from single-voxel spectroscopy and offer spatial information at a scan time acceptable for most animal models. The metabolites measured differed with respect to the temporal evolution of their concentrations and the localization of these changes. Specifically, lactate and N-acetylaspartate concentration changes largely overlapped with the T(2) -hyperintense region visualized with MRI, whereas changes in cholines and glutathione affected the entire middle cerebral artery territory. Glutamine maps showed elevated levels in the ischemic striatum until 8 h after reperfusion, and until 24 h in cortical tissue, indicating differences in excitotoxic effects and secondary energy failure in these tissue types. Copyright © 2011 John Wiley & Sons, Ltd.

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Background: Plasmodium falciparum(P. falciparum) merozoite surfaceprotein 2 (MSP-2) is one of bloodstage proteins that are associated withprotection from malaria. MSP-2 consistsof a highly polymorphic centralrepeat region flanked by a dimorphicregion that defines the two allelicfamilies, 3D7 and FC27; N- and Cterminalregions are conserved domains.Long synthetic peptides (LSP)representing the two allelic familiesof MSP-2 and constant regions arerecognized by sera from donors livingin endemic areas; and specific antibodies(Abs) are associated with protectionand active in antibody dependentcellular inhibition (ADCI) in vitro.However, the fine specificity ofAb response to the two allelic familiesof MSP-2 is unknown. Methods: Peptidesrepresenting dimorphic regionof 3D7 and FC27 families and theirC-terminal (common fragment to thetwo families) termed 3D7-D (88 aa),FC27-D (48 aa) and C (40 aa) respectivelywere synthesized. Overlapping20 mer peptides covering dimorphicand constant regions of two familieswere also synthesized for epitopemapping. Human sera were obtainedfrom donors living in malaria endemicareas. SpecificDand CregionsAbs were purified from single or poolhuman sera. Sera from mice were obtainedafter immunization with thetwo families LSP mixture in three differentadjuvants: alhydrogel (Alum),Glucopyranosyl Lipid Adjuvant-Stableoil-in-water Emulsion (GLA-SE)and Virosome. For ADCI, P. falciparum(strain 3D7) parasite wasmaintained in culture at 0.5% parasitemiaand 4% hematocrit in air tightbox at love oxygen (2%) and 37 ºC.Results: We identified several epitopesfrom the dimorphic and constantregions of both families of MSP-2, inmice and humans (adults and children).In human, most recognizedepitopes were the same in differentendemic regions for each domain ofthe two families of MSP-2. In mice,the differential recognition of epitopewas depending on the strain of mouseand interestingly on the adjuvantused. GLA-SE and alum as adjuvantswere more often associated with therecognition of multiple epitopes thanvirosomes. Epitope-specific Abs recognizednative merozoites of P.falciparum and were active in ADCIto block development of parasite.Conclusion: The delineation of a limitednumber of epitopes could be exploitedto develop MSP-2 vaccinesactive on both allelic families ofMSP-2.

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Rats were treated postnatally (PND 5-16) with BSO (l-buthionine-(S,R)-sulfoximine) in an animal model of schizophrenia based on transient glutathione deficit. The BSO treated rats were impaired in patrolling a maze or a homing table when adult, yet demonstrated preserved escape learning, place discrimination and reversal in a water maze task [37]. In the present work, BSO rats' performance in the water maze was assessed in conditions controlling for the available visual cues. First, in a completely curtained environment with two salient controlled cues, BSO rats showed little accuracy compared to control rats. Secondly, pre-trained BSO rats were impaired in reaching the familiar spatial position when curtains partially occluded different portions of the room environment in successive sessions. The apparently preserved place learning in a classical water maze task thus appears to require the stability and the richness of visual landmarks from the surrounding environment. In other words, the accuracy of BSO rats in place and reversal learning is impaired in a minimal cue condition or when the visual panorama changes between trials. However, if the panorama remains rich and stable between trials, BSO rats are equally efficient in reaching a familiar position or in learning a new one. This suggests that the BSO accurate performance in the water maze does not satisfy all the criteria for a cognitive map based navigation on the integration of polymodal cues. It supports the general hypothesis of a binding deficit in BSO rats.

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Debris flow susceptibility mapping at a regional scale has been the subject of various studies. The complexity of the phenomenon and the variability of local controlling factors limit the use of process-based models for a first assessment. GISbased approaches associating an automatic detection of the source areas and a simple assessment of the debris flow spreading may provide a substantial basis for a preliminary susceptibility assessment at the regional scale. The use of a digital elevation model, with a 10 m resolution, for the Canton de Vaud territory (Switzerland), a lithological map and a land use map, has allowed automatic identification of the potential source areas. The spreading estimates are based on basic probabilistic and energy calculations that allow to define the maximal runout distance of a debris flow.

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The aim of this study is to perform a thorough comparison of quantitative susceptibility mapping (QSM) techniques and their dependence on the assumptions made. The compared methodologies were: two iterative single orientation methodologies minimizing the l2, l1TV norm of the prior knowledge of the edges of the object, one over-determined multiple orientation method (COSMOS) and anewly proposed modulated closed-form solution (MCF). The performance of these methods was compared using a numerical phantom and in-vivo high resolution (0.65mm isotropic) brain data acquired at 7T using a new coil combination method. For all QSM methods, the relevant regularization and prior-knowledge parameters were systematically changed in order to evaluate the optimal reconstruction in the presence and absence of a ground truth. Additionally, the QSM contrast was compared to conventional gradient recalled echo (GRE) magnitude and R2* maps obtained from the same dataset. The QSM reconstruction results of the single orientation methods show comparable performance. The MCF method has the highest correlation (corrMCF=0.95, r(2)MCF =0.97) with the state of the art method (COSMOS) with additional advantage of extreme fast computation time. The l-curve method gave the visually most satisfactory balance between reduction of streaking artifacts and over-regularization with the latter being overemphasized when the using the COSMOS susceptibility maps as ground-truth. R2* and susceptibility maps, when calculated from the same datasets, although based on distinct features of the data, have a comparable ability to distinguish deep gray matter structures.

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Interaural intensity and time differences (IID and ITD) are two binaural auditory cues for localizing sounds in space. This study investigated the spatio-temporal brain mechanisms for processing and integrating IID and ITD cues in humans. Auditory-evoked potentials were recorded, while subjects passively listened to noise bursts lateralized with IID, ITD or both cues simultaneously, as well as a more frequent centrally presented noise. In a separate psychophysical experiment, subjects actively discriminated lateralized from centrally presented stimuli. IID and ITD cues elicited different electric field topographies starting at approximately 75 ms post-stimulus onset, indicative of the engagement of distinct cortical networks. By contrast, no performance differences were observed between IID and ITD cues during the psychophysical experiment. Subjects did, however, respond significantly faster and more accurately when both cues were presented simultaneously. This performance facilitation exceeded predictions from probability summation, suggestive of interactions in neural processing of IID and ITD cues. Supra-additive neural response interactions as well as topographic modulations were indeed observed approximately 200 ms post-stimulus for the comparison of responses to the simultaneous presentation of both cues with the mean of those to separate IID and ITD cues. Source estimations revealed differential processing of IID and ITD cues initially within superior temporal cortices and also at later stages within temporo-parietal and inferior frontal cortices. Differences were principally in terms of hemispheric lateralization. The collective psychophysical and electrophysiological results support the hypothesis that IID and ITD cues are processed by distinct, but interacting, cortical networks that can in turn facilitate auditory localization.