29 resultados para Image analysis method


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In-plane deformation of foams was studied experimentally by subjecting bidisperse foams to cycles of traction and compression at a prescribed rate. Each foam contained bubbles of two sizes with given area ratio and one of three initial arrangements: sorted perpendicular to the axis of deformation (iso-strain), sorted parallel to the axis of deformation (iso-stress), or randomly mixed. Image analysis was used to measure the characteristics of the foams, including the number of edges separating small from large bubbles N-sl, the perimeter (surface energy), the distribution of the number of sides of the bubbles, and the topological disorder mu(2)(N). Foams that were initially mixed were found to remain mixed after the deformation. The response of sorted foams, however, depended on the initial geometry, including the area fraction of small bubbles and the total number of bubbles. For a given experiment we found that (i) the perimeter of a sorted foam varied little; (ii) each foam tended towards a mixed state, measured through the saturation of N-sl; and (iii) the topological disorder mu(2)(N) increased up to an "equilibrium" value. The results of different experiments showed that (i) the change in disorder, Delta mu(2)(N), decreased with the area fraction of small bubbles under iso-strain, but was independent of it under iso-stress; and (ii) Delta mu(2)(N) increased with Delta N-sl under iso-strain, but was again independent of it under iso-stress. We offer explanations for these effects in terms of elementary topological processes induced by the deformations that occur at the bubble scale.

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This paper presents an integrated system for vehicle classification. This system aims to classify vehicles using different approaches: 1) based on the height of the first axle and_the number of axles; 2) based on volumetric measurements and; 3) based on features extracted from the captured image of the vehicle. The system uses a laser sensor for measurements and a set of image analysis algorithms to compute some visual features. By combining different classification methods, it is shown that the system improves its accuracy and robustness, enabling its usage in more difficult environments satisfying the proposed requirements established by the Portuguese motorway contractor BRISA.

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The amount of fat is a component that complicates the clinical evaluation and the differential diagnostic between benign and malign lesions in the breast MRI examinations. To overcome this problem, an effective erasing of the fat signal over the images acquisition process, is essentials. This study aims to compare three fat suppression techniques (STIR, SPIR, SPAIR) in the MR images of the breast and to evaluate the best image quality regarding its clinical usefulness. To mimic breast women, a breast phantom was constructed. First the exterior contour and, in second time, its content which was selected based on 7 samples with different components. Finally it was undergone to a MRI breast protocol with the three different fat saturation techniques. The examinations were performed on a 1.5 T MRI system (Philips®). A group of 5 experts evaluated 9 sequences, 3 of each with fat suppression techniques, in which the frequency offset and TI (Inversion Time) were the variables changed. This qualitative image analysis was performed according 4 parameters (saturation uniformity, saturation efficacy, detail of the anatomical structures and differentiation between the fibroglandular and adipose tissue), using a five-point Likert scale. The statistics analysis showed that anyone of the fat suppression techniques demonstrated significant differences compared to the others with (p > 0.05) and regarding each parameter independently. By Fleiss’ kappa coefficient there was a good agreement among observers P(e) = 0.68. When comparing STIR, SPIR and SPAIR techniques it was confirmed that all of them have advantages in the study of the breast MRI. For the studied parameters, the results through the Friedman Test showed that there are similar advantages applying anyone of these techniques.

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Introdução – Os estudos Gated – Single Photon Emission Computed Tomography (SPECT) são uma das técnicas de imagiologia cardíaca que mais evoluiu nas últimas décadas. Para a análise das imagens obtidas, a utilização de softwares de quantificação leva a um aumento da reprodutibilidade e exatidão das interpretações. O objetivo deste estudo consiste em avaliar, em estudos Gated-SPECT, a variabilidade intra e interoperador de parâmetros quantitativos de função e perfusão do miocárdio, obtidos com os softwares Quantitative Gated SPECT (QGS) e Quantitative Perfusion SPECT (QPS). Material e métodos – Recorreu-se a uma amostra não probabilística por conveniência de 52 pacientes, que realizaram estudos Gated-SPECT do miocárdio por razões clínicas e que integravam a base de dados da estação de processamento da Xeleris da ESTeSL. Os cinquenta e dois estudos foram divididos em dois grupos distintos: Grupo I (GI) de 17 pacientes com imagens com perfusão do miocárdio normal; Grupo II (GII) de 35 pacientes que apresentavam defeito de perfusão nas imagens Gated-SPECT. Todos os estudos foram processados 5 vezes por 4 operadores independentes (com experiência de 3 anos em Serviços de Medicina Nuclear com casuística média de 15 exames/semana de estudos Gated-SPECT). Para a avaliação da variabilidade intra e interoperador foi utilizado o teste estatístico de Friedman, considerando α=0,01. Resultados e discussão – Para todos os parâmetros avaliados, os respectivos valores de p não traduziram diferenças estatisticamente significativas (p>α). Assim, não foi verificada variabilidade intra ou interoperador significativa no processamento dos estudos Gated-SPECT do miocárdio. Conclusão – Os softwares QGS e QPS são reprodutíveis na quantificação dos parâmetros de função e perfusão avaliados, não existindo variabilidade introduzida pelo operador.

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Introdução – O presente estudo avaliou o efeito da cafeína no valor da razão contraste ruído (CNR) em imagens SWI. Objetivos – Avaliar o efeito da cafeína qualitativamente e quantificado pelo cálculo do valor CNR em imagens de magnitude e MIP para as estruturas: veia cerebral interna, seio sagital superior, tórcula e artéria cerebral média. Metodologia – A população do estudo incluiu 24 voluntários saudáveis que estiveram pelo menos 24h privados da ingestão de cafeína. Adquiriram-se imagens SWI antes e após a ingestão de 100ml de café. Os voluntários foram subdivididos em quatro grupos de seis indivíduos/grupo e avaliados separadamente após decorrido um intervalo de tempo diferente para cada grupo (15, 25, 30 ou 45min pós-cafeína). Utilizou-se um scanner Siemens Avanto 1,5 T com bobine standard de crânio e os parâmetros: T2* GRE 3D de alta resolução no plano axial, TR=49; TE=40; FA=15; FOV=187x230; matriz=221x320. O processamento de imagem foi efetuado no software OsiriX® e a análise estatística no GraphPadPrism®. Resultados e Discussão – As alterações de sinal e diferenças de contraste predominaram nas estruturas venosas e não foram significantes na substância branca, LCR e artéria cerebral média. Os valores CNR pré-cafeína diferiram significativamente do pós-cafeína nas imagens de magnitude e MIP na veia cerebral interna e nas imagens de magnitude do seio sagital superior e da tórcula (p<0,0001). Não se verificaram diferenças significativas entre os grupos avaliados nos diferentes tempos pós-cafeína. Conclusões – Especulamos que a cafeína possa vir a ser usada como agente de contraste nas imagens SWI barato, eficaz e de fácil administração.

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Electrocardiographic (ECG) signals are emerging as a recent trend in the field of biometrics. In this paper, we propose a novel ECG biometric system that combines clustering and classification methodologies. Our approach is based on dominant-set clustering, and provides a framework for outlier removal and template selection. It enhances the typical workflows, by making them better suited to new ECG acquisition paradigms that use fingers or hand palms, which lead to signals with lower signal to noise ratio, and more prone to noise artifacts. Preliminary results show the potential of the approach, helping to further validate the highly usable setups and ECG signals as a complementary biometric modality.

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Mecânica

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Trabalho Final de Mestrado para obtenção do grau de Mestre em Engenharia Civil na Área de Especialização de Hidráulica

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Mestrado em Intervenção Sócio-Organizacional na Saúde - Área de especialização: Políticas de Administração e Gestão de Serviços de Saúde

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Relatório de Estágio apresentado à Escola Superior de Educação de Lisboa para obtenção de grau de mestre em Ensino do 1.º e do 2.º Ciclo do Ensino Básico

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The basic objective of this work is to evaluate the durability of self-compacting concrete (SCC) produced in binary and ternary mixes using fly ash (FA) and limestone filler (LF) as partial replacement of cement. The main characteristics that set SCC apart from conventional concrete (fundamentally its fresh state behaviour) essentially depend on the greater or lesser content of various constituents, namely: greater mortar volume (more ultrafine material in the form of cement and mineral additions); proper control of the maximum size of the coarse aggregate; use of admixtures such as superplasticizers. Significant amounts of mineral additions are thus incorporated to partially replace cement, in order to improve the workability of the concrete. These mineral additions necessarily affect the concrete’s microstructure and its durability. Therefore, notwithstanding the many well-documented and acknowledged advantages of SCC, a better understanding its behaviour is still required, in particular when its composition includes significant amounts of mineral additions. An ambitious working plan was devised: first, the SCC’s microstructure was studied and characterized and afterwards the main transport and degradation mechanisms of the SCC produced were studied and characterized by means of SEM image analysis, chloride migration, electrical resistivity, and carbonation tests. It was then possible to draw conclusions about the SCC’s durability. The properties studied are strongly affected by the type and content of the additions. Also, the use of ternary mixes proved to be extremely favourable, confirming the expected beneficial effect of the synergy between LF and FA. © 2015 RILEM.

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In this work, we present the explicit series solution of a specific mathematical model from the literature, the Deng bursting model, that mimics the glucose-induced electrical activity of pancreatic beta-cells (Deng, 1993). To serve to this purpose, we use a technique developed to find analytic approximate solutions for strongly nonlinear problems. This analytical algorithm involves an auxiliary parameter which provides us with an efficient way to ensure the rapid and accurate convergence to the exact solution of the bursting model. By using the homotopy solution, we investigate the dynamical effect of a biologically meaningful bifurcation parameter rho, which increases with the glucose concentration. Our analytical results are found to be in excellent agreement with the numerical ones. This work provides an illustration of how our understanding of biophysically motivated models can be directly enhanced by the application of a newly analytic method.

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In this article we analytically solve the Hindmarsh-Rose model (Proc R Soc Lond B221:87-102, 1984) by means of a technique developed for strongly nonlinear problems-the step homotopy analysis method. This analytical algorithm, based on a modification of the standard homotopy analysis method, allows us to obtain a one-parameter family of explicit series solutions for the studied neuronal model. The Hindmarsh-Rose system represents a paradigmatic example of models developed to qualitatively reproduce the electrical activity of cell membranes. By using the homotopy solutions, we investigate the dynamical effect of two chosen biologically meaningful bifurcation parameters: the injected current I and the parameter r, representing the ratio of time scales between spiking (fast dynamics) and resting (slow dynamics). The auxiliary parameter involved in the analytical method provides us with an elegant way to ensure convergent series solutions of the neuronal model. Our analytical results are found to be in excellent agreement with the numerical simulations.

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In machine learning and pattern recognition tasks, the use of feature discretization techniques may have several advantages. The discretized features may hold enough information for the learning task at hand, while ignoring minor fluctuations that are irrelevant or harmful for that task. The discretized features have more compact representations that may yield both better accuracy and lower training time, as compared to the use of the original features. However, in many cases, mainly with medium and high-dimensional data, the large number of features usually implies that there is some redundancy among them. Thus, we may further apply feature selection (FS) techniques on the discrete data, keeping the most relevant features, while discarding the irrelevant and redundant ones. In this paper, we propose relevance and redundancy criteria for supervised feature selection techniques on discrete data. These criteria are applied to the bin-class histograms of the discrete features. The experimental results, on public benchmark data, show that the proposed criteria can achieve better accuracy than widely used relevance and redundancy criteria, such as mutual information and the Fisher ratio.