1000 resultados para Dubois, Pierre, active 1300.
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This paper presents a new non parametric atlas registration framework, derived from the optical flow model and the active contour theory, applied to automatic subthalamic nucleus (STN) targeting in deep brain stimulation (DBS) surgery. In a previous work, we demonstrated that the STN position can be predicted based on the position of surrounding visible structures, namely the lateral and third ventricles. A STN targeting process can thus be obtained by registering these structures of interest between a brain atlas and the patient image. Here we aim to improve the results of the state of the art targeting methods and at the same time to reduce the computational time. Our simultaneous segmentation and registration model shows mean STN localization errors statistically similar to the most performing registration algorithms tested so far and to the targeting expert's variability. Moreover, the computational time of our registration method is much lower, which is a worthwhile improvement from a clinical point of view.
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Référence bibliographique : Weigert, 597
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This paper presents automated segmentation of structuresin the Head and Neck (H\&N) region, using an activecontour-based joint registration and segmentation model.A new atlas selection strategy is also used. Segmentationis performed based on the dense deformation fieldcomputed from the registration of selected structures inthe atlas image that have distinct boundaries, onto thepatient's image. This approach results in robustsegmentation of the structures of interest, even in thepresence of tumors, or anatomical differences between theatlas and the patient image. For each patient, an atlasimage is selected from the available atlas-database,based on the similarity metric value, computed afterperforming an affine registration between each image inthe atlas-database and the patient's image. Unlike manyof the previous approaches in the literature, thesimilarity metric is not computed over the entire imageregion; rather, it is computed only in the regions ofsoft tissue structures to be segmented. Qualitative andquantitative evaluation of the results is presented.
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[Vente. Art. 1860-02-16. Paris]
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Contient : « Catalogue des manuscrits de la bibliothèque de feu Mgr. le cardinal Mazarin..., » par les mêmes
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BACKGROUND: It is well established that high adherence to HIV-infected patients on highly active antiretroviral treatment (HAART) is a major determinant of virological and immunologic success. Furthermore, psychosocial research has identified a wide range of adherence factors including patients' subjective beliefs about the effectiveness of HAART. Current statistical approaches, mainly based on the separate identification either of factors associated with treatment effectiveness or of those associated with adherence, fail to properly explore the true relationship between adherence and treatment effectiveness. Adherence behavior may be influenced not only by perceived benefits-which are usually the focus of related studies-but also by objective treatment benefits reflected in biological outcomes. METHODS: Our objective was to assess the bidirectional relationship between adherence and response to treatment among patients enrolled in the ANRS CO8 APROCO-COPILOTE study. We compared a conventional statistical approach based on the separate estimations of an adherence and an effectiveness equation to an econometric approach using a 2-equation simultaneous system based on the same 2 equations. RESULTS: Our results highlight a reciprocal relationship between adherence and treatment effectiveness. After controlling for endogeneity, adherence was positively associated with treatment effectiveness. Furthermore, CD4 count gain after baseline was found to have a positive significant effect on adherence at each observation period. This immunologic parameter was not significant when the adherence equation was estimated separately. In the 2-equation model, the covariances between disturbances of both equations were found to be significant, thus confirming the statistical appropriacy of studying adherence and treatment effectiveness jointly. CONCLUSIONS: Our results, which suggest that positive biological results arising as a result of high adherence levels, in turn reinforce continued adherence and strengthen the argument that patients who do not experience rapid improvement in their immunologic and clinical statuses after HAART initiation should be prioritized when developing adherence support interventions. Furthermore, they invalidate the hypothesis that HAART leads to "false reassurance" among HIV-infected patients.
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In this paper, we present an efficient numerical scheme for the recently introduced geodesic active fields (GAF) framework for geometric image registration. This framework considers the registration task as a weighted minimal surface problem. Hence, the data-term and the regularization-term are combined through multiplication in a single, parametrization invariant and geometric cost functional. The multiplicative coupling provides an intrinsic, spatially varying and data-dependent tuning of the regularization strength, and the parametrization invariance allows working with images of nonflat geometry, generally defined on any smoothly parametrizable manifold. The resulting energy-minimizing flow, however, has poor numerical properties. Here, we provide an efficient numerical scheme that uses a splitting approach; data and regularity terms are optimized over two distinct deformation fields that are constrained to be equal via an augmented Lagrangian approach. Our approach is more flexible than standard Gaussian regularization, since one can interpolate freely between isotropic Gaussian and anisotropic TV-like smoothing. In this paper, we compare the geodesic active fields method with the popular Demons method and three more recent state-of-the-art algorithms: NL-optical flow, MRF image registration, and landmark-enhanced large displacement optical flow. Thus, we can show the advantages of the proposed FastGAF method. It compares favorably against Demons, both in terms of registration speed and quality. Over the range of example applications, it also consistently produces results not far from more dedicated state-of-the-art methods, illustrating the flexibility of the proposed framework.
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Labile or mutation-sensitised proteins may spontaneously convert into aggregation-prone conformations that may be toxic and infectious. This hazardous behavior, which can be described as a form of "molecular criminality", can be actively counteracted in the cell by a network of molecular chaperone and proteases. Similar to law enforcement agents, molecular chaperones and proteases can specifically identify, apprehend, unfold and thus neutralize "criminal" protein conformers, allowing them to subsequently refold into harmless functional proteins. Irreversibly damaged polypeptides that have lost the ability to natively refold are preferentially degraded by highly controlled ATP-consuming proteases. Damaged proteins that escape proteasomal degradation can also be "incarcerated" into dense amyloids, "evicted" from the cell, or internally "exiled" to the lysosome to be hydrolysed and recycled. Thus, remarkable parallels exist between molecular and human forms of criminality, as well as in the cellular and social responses to various forms of crime. Yet, differences also exist: whereas programmed death is the preferred solution chosen by aged and aggregation-stressed cells, collective suicide is seldom chosen by lawless societies. Significantly, there is no cellular equivalent for the role of familial care and of education in general, which is so crucial to the proper shaping of functional persons in the society. Unlike in the cell, humanism introduces a bias against radical solutions such as capital punishment, favouring crime prevention, reeducation and social reinsertion of criminals.
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Collection : Nouvelle bibliothèque illustrée de vulgarisation