1000 resultados para Linear Resonance Accelerator


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PURPOSE: To evaluate the utility of inversion recovery with on-resonant water suppression (IRON) in combination with injection of the long-circulating monocrystalline iron oxide nanoparticle (MION)-47 for contrast material-enhanced magnetic resonance (MR) angiography. MATERIALS AND METhods: Experiments were approved by the institutional animal care committee. Eleven rabbits were imaged at baseline before injection of a contrast agent and then serially 5-30 minutes, 2 hours, 1 day, and 3 days after a single intravenous bolus injection of 80 micromol of MION-47 per kilogram of body weight (n = 6) or 250 micromol/kg MION-47 (n = 5). Conventional T1-weighted MR angiography and IRON MR angiography were performed on a clinical 3.0-T imager. Signal-to-noise and contrast-to-noise ratios were measured in the aorta of rabbits in vivo. Venous blood was obtained from the rabbits before and after MION-47 injection for use in phantom studies. RESULTS: In vitro blood that contained MION-47 appeared signal attenuated on T1-weighted angiograms, while characteristic signal-enhanced dipolar fields were observed on IRON angiograms. In vivo, the vessel lumen was signal attenuated on T1-weighted MR angiograms after MION-47 injection, while IRON supported high intravascular contrast by simultaneously providing positive signal within the vessels and suppressing background tissue (mean contrast-to-noise ratio, 61.9 +/- 12.4 [standard deviation] after injection vs 1.1 +/- 0.4 at baseline, P < .001). Contrast-to-noise ratio was higher on IRON MR angiograms than on conventional T1-weighted MR angiograms (9.0 +/- 2.5, P < .001 vs IRON MR angiography) and persisted up to 24 hours after MION-47 injection (76.2 +/- 15.9, P < .001 vs baseline). CONCLUSION: IRON MR angiography in conjunction with superparamagnetic nanoparticle administration provides high intravascular contrast over a long time and without the need for image subtraction.

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O problema de otimização de mínimos quadrados e apresentado como uma classe importante de problemas de minimização sem restrições. A importância dessa classe de problemas deriva das bem conhecidas aplicações a estimação de parâmetros no contexto das analises de regressão e de resolução de sistemas de equações não lineares. Apresenta-se uma revisão dos métodos de otimização de mínimos quadrados lineares e de algumas técnicas conhecidas de linearização. Faz-se um estudo dos principais métodos de gradiente usados para problemas não lineares gerais: Métodos de Newton e suas modificações incluindo os métodos Quasi-Newton mais usados (DFP e BFGS). Introduzem-se depois métodos específicos de gradiente para problemas de mínimos quadrados: Gauss-Newton e Levenberg-Larquardt. Apresenta-se uma variedade de exemplos selecionados na literatura para testar os diferentes métodos usando rotinas MATLAB. Faz-se uma an alise comparativa dos algoritmos baseados nesses ensaios computacionais que exibem as vantagens e desvantagens dos diferentes métodos.

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We present a new unifying framework for investigating throughput-WIP(Work-in-Process) optimal control problems in queueing systems,based on reformulating them as linear programming (LP) problems withspecial structure: We show that if a throughput-WIP performance pairin a stochastic system satisfies the Threshold Property we introducein this paper, then we can reformulate the problem of optimizing alinear objective of throughput-WIP performance as a (semi-infinite)LP problem over a polygon with special structure (a thresholdpolygon). The strong structural properties of such polygones explainthe optimality of threshold policies for optimizing linearperformance objectives: their vertices correspond to the performancepairs of threshold policies. We analyze in this framework theversatile input-output queueing intensity control model introduced byChen and Yao (1990), obtaining a variety of new results, including (a)an exact reformulation of the control problem as an LP problem over athreshold polygon; (b) an analytical characterization of the Min WIPfunction (giving the minimum WIP level required to attain a targetthroughput level); (c) an LP Value Decomposition Theorem that relatesthe objective value under an arbitrary policy with that of a giventhreshold policy (thus revealing the LP interpretation of Chen andYao's optimality conditions); (d) diminishing returns and invarianceproperties of throughput-WIP performance, which underlie thresholdoptimality; (e) a unified treatment of the time-discounted andtime-average cases.

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The purpose of this study was to investigate the impact of navigator timing on image quality in navigator-gated and real-time motion-corrected, free-breathing, three-dimensional (3D) coronary MR angiography (MRA) with submillimeter spatial image resolution. Both phantom and in vivo investigations were performed. 3D coronary MRA with real-time navigator technology was applied using variable navigator time delays (time delay between the navigator and imaging sequences) and varying spatial resolutions. Quantitative objective and subjective image quality parameters were assessed. For high-resolution imaging, reduced image quality was found as a function of increasing navigator time delay. Lower spatial resolution coronary MRA showed only minor sensitivity to navigator timing. These findings were consistent among volunteers and phantom experiments. In conclusion, for submillimeter navigator-gated and real-time motion-corrected 3D coronary MRA, shortening the time delay between the navigator and the imaging portion of the sequence becomes increasingly important for improved spatial resolution.

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We present an exact test for whether two random variables that have known bounds on their support are negatively correlated. The alternative hypothesis is that they are not negatively correlated. No assumptions are made on the underlying distributions. We show by example that the Spearman rank correlation test as the competing exact test of correlation in nonparametric settings rests on an additional assumption on the data generating process without which it is not valid as a test for correlation.We then show how to test for the significance of the slope in a linear regression analysis that invovles a single independent variable and where outcomes of the dependent variable belong to a known bounded set.

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This paper presents a test of the predictive validity of various classes ofQALY models (i.e., linear, power and exponential models). We first estimatedTTO utilities for 43 EQ-5D chronic health states and next these states wereembedded in health profiles. The chronic TTO utilities were then used topredict the responses to TTO questions with health profiles. We find that thepower QALY model clearly outperforms linear and exponential QALY models.Optimal power coefficient is 0.65. Our results suggest that TTO-based QALYcalculations may be biased. This bias can be avoided using a power QALY model.

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This paper introduces the approach of using Total Unduplicated Reach and Frequency analysis (TURF) to design a product line through a binary linear programming model. This improves the efficiency of the search for the solution to the problem compared to the algorithms that have been used to date. The results obtained through our exact algorithm are presented, and this method shows to be extremely efficient both in obtaining optimal solutions and in computing time for very large instances of the problem at hand. Furthermore, the proposed technique enables the model to be improved in order to overcome the main drawbacks presented by TURF analysis in practice.

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Acute myocarditis was until recently one of the most difficult diagnoses in cardiology. The spectrum of signs and symptoms is very wide, the usual non-invasive tests lack specificity and the myocardial biopsy is only performed in a minority of cases to confirm the diagnosis. Due to its unique ability to directly image myocardial necrosis, fibrosis and oedema, cardiac magnetic resonance (CMR) is now considered the primary tool for noninvasive assessment of patients with suspected myocarditis. CMR is also useful for monitoring disease activity under treatment. Myocarditis has been associated with the development of dilated cardiomyopathy; CMR could play a role in the follow-up of such cases to detect the progression toward a dilatative phenotype. Precise mapping of myocardial lesions with cardiac MRI is invaluable to guide myocardial biopsy and increase its diagnostic yield by improving sensitivity.

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To be diagnostically useful, structural MRI must reliably distinguish Alzheimer's disease (AD) from normal aging in individual scans. Recent advances in statistical learning theory have led to the application of support vector machines to MRI for detection of a variety of disease states. The aims of this study were to assess how successfully support vector machines assigned individual diagnoses and to determine whether data-sets combined from multiple scanners and different centres could be used to obtain effective classification of scans. We used linear support vector machines to classify the grey matter segment of T1-weighted MR scans from pathologically proven AD patients and cognitively normal elderly individuals obtained from two centres with different scanning equipment. Because the clinical diagnosis of mild AD is difficult we also tested the ability of support vector machines to differentiate control scans from patients without post-mortem confirmation. Finally we sought to use these methods to differentiate scans between patients suffering from AD from those with frontotemporal lobar degeneration. Up to 96% of pathologically verified AD patients were correctly classified using whole brain images. Data from different centres were successfully combined achieving comparable results from the separate analyses. Importantly, data from one centre could be used to train a support vector machine to accurately differentiate AD and normal ageing scans obtained from another centre with different subjects and different scanner equipment. Patients with mild, clinically probable AD and age/sex matched controls were correctly separated in 89% of cases which is compatible with published diagnosis rates in the best clinical centres. This method correctly assigned 89% of patients with post-mortem confirmed diagnosis of either AD or frontotemporal lobar degeneration to their respective group. Our study leads to three conclusions: Firstly, support vector machines successfully separate patients with AD from healthy aging subjects. Secondly, they perform well in the differential diagnosis of two different forms of dementia. Thirdly, the method is robust and can be generalized across different centres. This suggests an important role for computer based diagnostic image analysis for clinical practice.

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We develop a mathematical programming approach for the classicalPSPACE - hard restless bandit problem in stochastic optimization.We introduce a hierarchy of n (where n is the number of bandits)increasingly stronger linear programming relaxations, the lastof which is exact and corresponds to the (exponential size)formulation of the problem as a Markov decision chain, while theother relaxations provide bounds and are efficiently computed. Wealso propose a priority-index heuristic scheduling policy fromthe solution to the first-order relaxation, where the indices aredefined in terms of optimal dual variables. In this way wepropose a policy and a suboptimality guarantee. We report resultsof computational experiments that suggest that the proposedheuristic policy is nearly optimal. Moreover, the second-orderrelaxation is found to provide strong bounds on the optimalvalue.

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Research on judgment and decision making presents a confusing picture of human abilities. For example, much research has emphasized the dysfunctional aspects of judgmental heuristics, and yet, other findings suggest that these can be highly effective. A further line of research has modeled judgment as resulting from as if linear models. This paper illuminates the distinctions in these approaches by providing a common analytical framework based on the central theoretical premise that understanding human performance requires specifying how characteristics of the decision rules people use interact with the demands of the tasks they face. Our work synthesizes the analytical tools of lens model research with novel methodology developed to specify the effectiveness of heuristics in different environments and allows direct comparisons between the different approaches. We illustrate with both theoretical analyses and simulations. We further link our results to the empirical literature by a meta-analysis of lens model studies and estimate both human andheuristic performance in the same tasks. Our results highlight the trade-off betweenlinear models and heuristics. Whereas the former are cognitively demanding, the latterare simple to use. However, they require knowledge and thus maps of when andwhich heuristic to employ.

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At 3 T, the effective wavelength of the RF field is comparable to the dimension of the human body, resulting in B1 standing wave effects and extra variations in phase. This effect is accompanied by an increase in B0 field inhomogeneity compared to 1.5 T. This combination results in nonuniform magnetization preparation by the composite MLEV weighted T2 preparation (T2 Prep) sequence used for coronary magnetic resonance angiography (MRA). A new adiabatic refocusing T2 Prep sequence is presented in which the magnetization is tipped into the transverse plane with a hard RF pulse and refocused using a pair of adiabatic fast-passage RF pulses. The isochromats are subsequently returned to the longitudinal axis using a hard RF pulse. Numerical simulations predict an excellent suppression of artifacts originating from B1 inhomogeneity while achieving good contrast enhancement between coronary arteries and surrounding tissue. This was confirmed by an in vivo study, in which coronary MR angiograms were obtained without a T2 Prep, with an MLEV weighted T2 Prep and the proposed adiabatic T2 Prep. Improved quantitative and qualitative coronary MRA image measurement was achieved using the adiabatic T2 Prep at 3 T.

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O tema da Programação Linear, com as suas particularizações do Problema dos Transportes e do Problema da Afectação de Recursos, é hoje estudado em cursos diversos onde uma disciplina de Investigação Operacional esteja presente. Trata-se, em última análise, de um problema de cálculo de extremos condicionados, seja de máximo ou de mínimo, que apresenta características muito particulares e de grande elegância simbólica. Também os Problemas dos Transportes e da Afectação de Recursos se podem resolver como problemas de Programação Linear, através do Algoritmo Simplex, embora seja preferível o recurso a algoritmos próprios, de muitíssimo maior simplicidade: o Algoritmo dos Transportes e o Algoritmo Húngaro, respectivamente. De molde a facilitar a compreensão do que realmente está em jogo, consideram-se aqui dois casos de determinação de extremos e de extremos condicionados, mas ao nível do final do ensino secundário.