998 resultados para internal reconstruction


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La reconstruction en deux étapes par expanseur et implant est la technique la plus répandue pour la reconstruction mammmaire post mastectomie. La formation d’une capsule périprothétique est une réponse physiologique universelle à tout corps étranger présent dans le corps humain; par contre, la formation d’une capsule pathologique mène souvent à des complications et par conséquent à des résultats esthétiques sous-optimaux. Le microscope électronique à balayage (MEB) est un outil puissant qui permet d’effectuer une évaluation sans pareille de la topographie ultrastructurelle de spécimens. Le premier objectif de cette thèse est de comparer le MEB conventionnel (Hi-Vac) à une technologie plus récente, soit le MEB environnemental (ESEM), afin de déterminer si cette dernière mène à une évaluation supérieure des tissus capsulaires du sein. Le deuxième objectif est d‘appliquer la modalité de MEB supérieure et d’étudier les modifications ultrastructurelles des capsules périprothétiques chez les femmes subissant différents protocoles d’expansion de tissus dans le contexte de reconstruction mammaire prothétique. Deux études prospectives ont été réalisées afin de répondre à nos objectifs de recherche. Dix patientes ont été incluses dans la première, et 48 dans la seconde. La modalité Hi-Vac s’est avérée supérieure pour l’analyse compréhensive de tissus capsulaires mammaires. En employant le mode Hi-Vac dans notre protocole de recherche établi, un relief 3-D plus prononcé à été observé autour des expanseurs BIOCELL® dans le groupe d’approche d’intervention retardée (6 semaines). Des changements significatifs n’ont pas été observés au niveau des capsules SILTEX® dans les groupes d’approche d’intervention précoce (2 semaines) ni retardée.

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Les artéfacts métalliques entraînent un épaississement artéfactuel de la paroi des tuteurs en tomodensitométrie (TDM) avec réduction apparente de leur lumière. Cette étude transversale prospective, devis mesures répétées et observateurs avec méthode en aveugle, chez 24 patients consécutifs/71 tuteurs coronariens a pour objectif de comparer l’épaisseur de paroi des tuteurs en TDM après reconstruction par un algorithme avec renforcement des bords et un algorithme standard. Une angiographie coronarienne par TDM 256 coupes a été réalisée, avec reconstruction par algorithmes avec renforcement des bords et standard. L’épaisseur de paroi des tuteurs était mesurée par méthodes orthogonale (diamètres) et circonférentielle (circonférences). La qualité d’image des tuteurs était évaluée par échelle ordinale, et les données analysées par modèles linéaire mixte et régression logistique des cotes proportionnelles. L’épaisseur de paroi des tuteurs était inférieure avec l’algorithme avec renforcement des bords comparé à l’algorithme standard, avec les méthodes orthogonale (0,97±0,02 vs 1,09±0,03 mm, respectivement; p<0,001) et circonférentielle (1,13±0,02 vs 1,21±0,02 mm, respectivement; p<0,001). Le premier causait moins de surestimation par rapport à l’épaisseur nominale comparé au second, avec méthodes orthogonale (0,89±0,19 vs 1,00±0,26 mm, respectivement; p<0,001) et circonférentielle (1,06±0,26 vs 1,13±0,31 mm, respectivement; p=0,005) et diminuait de 6 % la surestimation. Les scores de qualité étaient meilleurs avec l’algorithme avec renforcement des bords (OR 3,71; IC 95% 2,33–5,92; p<0,001). En conclusion, la reconstruction des images avec l’algorithme avec renforcement des bords génère des parois de tuteurs plus minces, moins de surestimation, et de meilleurs scores de qualité d’image que l’algorithme standard.

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novel design of at internal PIFA integrated with an RF-shielding metal case for application in a clamshell or fielder-tvpe mobile phone is presented. The integrated PIFA has a bent and tapered radiating arm in order to easily fit in the casing of the clamshell mobile phone as an internal antenna. The integrated PlEA can also provide a wide operating bandwidth fir UM7S (1920-2170 MHz) operation. In addition, for the clamshell mobile phone in either the talk or standby condition, only a small effect on the operating bandwidth of the integrated PIFA is obtained. The experimental results of the proposed design are presented

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Microarray data analysis is one of data mining tool which is used to extract meaningful information hidden in biological data. One of the major focuses on microarray data analysis is the reconstruction of gene regulatory network that may be used to provide a broader understanding on the functioning of complex cellular systems. Since cancer is a genetic disease arising from the abnormal gene function, the identification of cancerous genes and the regulatory pathways they control will provide a better platform for understanding the tumor formation and development. The major focus of this thesis is to understand the regulation of genes responsible for the development of cancer, particularly colorectal cancer by analyzing the microarray expression data. In this thesis, four computational algorithms namely fuzzy logic algorithm, modified genetic algorithm, dynamic neural fuzzy network and Takagi Sugeno Kang-type recurrent neural fuzzy network are used to extract cancer specific gene regulatory network from plasma RNA dataset of colorectal cancer patients. Plasma RNA is highly attractive for cancer analysis since it requires a collection of small amount of blood and it can be obtained at any time in repetitive fashion allowing the analysis of disease progression and treatment response.

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The organic agricultural sector of Uganda is among the most developed in Africa in terms of its professional institutional network and high growth rates of number of certified farmers and land area. Smallholder farmers are certified organic through contract production for export companies using a group certification scheme (internal control system - ICS). The ICS is a viable and well-accepted tool to certify small-scale producers in developing countries all over the world. Difficulties in certification are still stated to be among the main constraints for Uganda’s organic sector development. Therefore, this paper reports a qualitative case study comprising 34 expert interviews in two organic fresh-produce export companies in central Uganda, aiming to explore the challenges which underlie organic certification with ICS. The study shows that farmers cannot be labelled as ‘organic by default’ but deliberately engage in organic production as a marketing strategy. The small quantities purchased by the organic companies lead to a difficult marketing situation for the farmers, causing production and infiltration risks on the farm level. These risks require increased control that challenges the companies organizationally. The risks and control needs are a reason to involve farmers in ICS procedures and innovatively adapt the ICS by means of a bypass around formal perspective restrictions. The paper discusses different perspectives on risks, risk control and certification.

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This paper describes a simple method for internal camera calibration for computer vision. This method is based on tracking image features through a sequence of images while the camera undergoes pure rotation. The location of the features relative to the camera or to each other need not be known and therefore this method can be used both for laboratory calibration and for self calibration in autonomous robots working in unstructured environments. A second method of calibration is also presented. This method uses simple geometric objects such as spheres and straight lines to The camera parameters. Calibration is performed using both methods and the results compared.

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We present a statistical image-based shape + structure model for Bayesian visual hull reconstruction and 3D structure inference. The 3D shape of a class of objects is represented by sets of contours from silhouette views simultaneously observed from multiple calibrated cameras. Bayesian reconstructions of new shapes are then estimated using a prior density constructed with a mixture model and probabilistic principal components analysis. We show how the use of a class-specific prior in a visual hull reconstruction can reduce the effect of segmentation errors from the silhouette extraction process. The proposed method is applied to a data set of pedestrian images, and improvements in the approximate 3D models under various noise conditions are shown. We further augment the shape model to incorporate structural features of interest; unknown structural parameters for a novel set of contours are then inferred via the Bayesian reconstruction process. Model matching and parameter inference are done entirely in the image domain and require no explicit 3D construction. Our shape model enables accurate estimation of structure despite segmentation errors or missing views in the input silhouettes, and works even with only a single input view. Using a data set of thousands of pedestrian images generated from a synthetic model, we can accurately infer the 3D locations of 19 joints on the body based on observed silhouette contours from real images.

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This paper investigates the linear degeneracies of projective structure estimation from point and line features across three views. We show that the rank of the linear system of equations for recovering the trilinear tensor of three views reduces to 23 (instead of 26) in the case when the scene is a Linear Line Complex (set of lines in space intersecting at a common line) and is 21 when the scene is planar. The LLC situation is only linearly degenerate, and we show that one can obtain a unique solution when the admissibility constraints of the tensor are accounted for. The line configuration described by an LLC, rather than being some obscure case, is in fact quite typical. It includes, as a particular example, the case of a camera moving down a hallway in an office environment or down an urban street. Furthermore, an LLC situation may occur as an artifact such as in direct estimation from spatio-temporal derivatives of image brightness. Therefore, an investigation into degeneracies and their remedy is important also in practice.

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This paper presents a new paradigm for signal reconstruction and superresolution, Correlation Kernel Analysis (CKA), that is based on the selection of a sparse set of bases from a large dictionary of class- specific basis functions. The basis functions that we use are the correlation functions of the class of signals we are analyzing. To choose the appropriate features from this large dictionary, we use Support Vector Machine (SVM) regression and compare this to traditional Principal Component Analysis (PCA) for the tasks of signal reconstruction, superresolution, and compression. The testbed we use in this paper is a set of images of pedestrians. This paper also presents results of experiments in which we use a dictionary of multiscale basis functions and then use Basis Pursuit De-Noising to obtain a sparse, multiscale approximation of a signal. The results are analyzed and we conclude that 1) when used with a sparse representation technique, the correlation function is an effective kernel for image reconstruction and superresolution, 2) for image compression, PCA and SVM have different tradeoffs, depending on the particular metric that is used to evaluate the results, 3) in sparse representation techniques, L_1 is not a good proxy for the true measure of sparsity, L_0, and 4) the L_epsilon norm may be a better error metric for image reconstruction and compression than the L_2 norm, though the exact psychophysical metric should take into account high order structure in images.

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The central challenge in face recognition lies in understanding the role different facial features play in our judgments of identity. Notable in this regard are the relative contributions of the internal (eyes, nose and mouth) and external (hair and jaw-line) features. Past studies that have investigated this issue have typically used high-resolution images or good-quality line drawings as facial stimuli. The results obtained are therefore most relevant for understanding the identification of faces at close range. However, given that real-world viewing conditions are rarely optimal, it is also important to know how image degradations, such as loss of resolution caused by large viewing distances, influence our ability to use internal and external features. Here, we report experiments designed to address this issue. Our data characterize how the relative contributions of internal and external features change as a function of image resolution. While we replicated results of previous studies that have shown internal features of familiar faces to be more useful for recognition than external features at high resolution, we found that the two feature sets reverse in importance as resolution decreases. These results suggest that the visual system uses a highly non-linear cue-fusion strategy in combining internal and external features along the dimension of image resolution and that the configural cues that relate the two feature sets play an important role in judgments of facial identity.

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Photo-mosaicing techniques have become popular for seafloor mapping in various marine science applications. However, the common methods cannot accurately map regions with high relief and topographical variations. Ortho-mosaicing borrowed from photogrammetry is an alternative technique that enables taking into account the 3-D shape of the terrain. A serious bottleneck is the volume of elevation information that needs to be estimated from the video data, fused, and processed for the generation of a composite ortho-photo that covers a relatively large seafloor area. We present a framework that combines the advantages of dense depth-map and 3-D feature estimation techniques based on visual motion cues. The main goal is to identify and reconstruct certain key terrain feature points that adequately represent the surface with minimal complexity in the form of piecewise planar patches. The proposed implementation utilizes local depth maps for feature selection, while tracking over several views enables 3-D reconstruction by bundle adjustment. Experimental results with synthetic and real data validate the effectiveness of the proposed approach

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Pocos estudios han evaluado el tratamiento de las fracturas desplazadas de cuello femoral en pacientes menores de 65 años de edad, y no han sido claramente definidos los factores de riesgo para necrosis avascular o no-unión dentro de este rango de edad. Para determinar los factores asociados a la necrosis avascular de la cabeza femoral (AVN) y no-unión en pacientes menores de 65 años de edad con fracturas desplazadas del cuello femoral tratados con reducción y fijación interna, se realizó un estudio retrospectivo de 29 fracturas desplazadas del cuello femoral en 29 pacientes consecutivos tratados en una sola institución. La influencia de la edad, la energía del trauma, tipo de reducción, y el tiempo entre la fractura y el tratamiento en desarrollo de la AVN y no-unión fueron evaluados. Los pacientes que desarrollaron NAV fueron significativamente mayores y sufrieron un trauma de más baja energía que en los casos sin AVN. Ninguna variable fue asociada con la no-unión. La regresión logística determinó que sólo la edad se asoció de forma independiente a NAV. La edad es un buen predictor para el desarrollo de NAV, con un C-estadístico de 0.861, y un mejor corte-determinado en 53,5 años. Conclusión: Los pacientes de entre 53,5 y 65 años presentan un riesgo más alto de NAV. La artroplastia primaria se debe considerar en este subgrupo.

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El desarrollo social de un departamento está determinado por factores tanto internos como externos. Sin embargo, la existencia de recursos no renovables con gran valor, en algunos casos representan el núcleo de grandes problemas sociales en estos departamentos.

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Esta Monografía se centra en mostrar cómo el intento por conservar la identidad colectiva de la Liga de los Estados Árabes impide ceder ante el deseo de Somalilandia de ser reconocida como Estado independiente.