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Mariano Vazquez; Ruth Aris; Guillaume Hozeaux; R.Aubry; P.Villar;Jaume Garcia ; Debora Gil; Francesc Carreras |
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Title |
A massively parallel computational electrophysiology model of the heart |
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Journal Article |
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Year |
2011 |
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International Journal for Numerical Methods in Biomedical Engineering |
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IJNMBE |
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27 |
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1911-1929 |
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Keywords |
computational electrophysiology; parallelization; finite element methods |
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This paper presents a patient-sensitive simulation strategy capable of using the most efficient way the high-performance computational resources. The proposed strategy directly involves three different players: Computational Mechanics Scientists (CMS), Image Processing Scientists and Cardiologists, each one mastering its own expertise area within the project. This paper describes the general integrative scheme but focusing on the CMS side presents a massively parallel implementation of computational electrophysiology applied to cardiac tissue simulation. The paper covers different angles of the computational problem: equations, numerical issues, the algorithm and parallel implementation. The proposed methodology is illustrated with numerical simulations testing all the different possibilities, ranging from small domains up to very large ones. A key issue is the almost ideal scalability not only for large and complex problems but also for medium-size meshes. The explicit formulation is particularly well suited for solving this highly transient problems, with very short time-scale. |
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Swansea (UK) |
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John Wiley & Sons, Ltd. |
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John Wiley & Sons, Ltd. |
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IAM @ iam @ VAH2011 |
Serial |
1198 |
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Author |
Ernest Valveny; Enric Marti |
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Title |
A model for image generation and symbol recognition through the deformation of lineal shapes |
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Journal Article |
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Year |
2003 |
Publication |
Pattern Recognition Letters |
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PRL |
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Volume |
24 |
Issue |
15 |
Pages |
2857-2867 |
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We describe a general framework for the recognition of distorted images of lineal shapes, which relies on three items: a model to represent lineal shapes and their deformations, a model for the generation of distorted binary images and the combination of both models in a common probabilistic framework, where the generation of deformations is related to an internal energy, and the generation of binary images to an external energy. Then, recognition consists in the minimization of a global energy function, performed by using the EM algorithm. This general framework has been applied to the recognition of hand-drawn lineal symbols in graphic documents. |
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Elsevier Science Inc. |
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New York, NY, USA |
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0167-8655 |
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DAG; IAM |
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IAM @ iam @ VAM2003 |
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1653 |
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Author |
Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester |
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Title |
Geometric Steerable Medial Maps |
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Journal Article |
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Year |
2013 |
Publication |
Machine Vision and Applications |
Abbreviated Journal |
MVA |
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24 |
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6 |
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1255-1266 |
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Keywords |
Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction |
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In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume. |
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Springer Berlin Heidelberg |
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Mubarak Shah |
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0932-8092 |
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IAM; 605.203; 600.060; 600.044 |
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IAM @ iam @ VGB2013 |
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2192 |
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Sergio Vera; Debora Gil; Antonio Lopez; Miguel Angel Gonzalez Ballester |
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Title |
Multilocal Creaseness Measure |
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2012 |
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The Insight Journal |
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IJ |
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Ridges, Valley, Creaseness, Structure Tensor, Skeleton, |
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This document describes the implementation using the Insight Toolkit of an algorithm for detecting creases (ridges and valleys) in N-dimensional images, based on the Local Structure Tensor of the image. In addition to the filter used to calculate the creaseness image, a filter for the computation of the structure tensor is also included in this submission. |
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Alma IT Systems |
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english |
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english |
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IAM;ADAS; |
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IAM @ iam @ VGL2012 |
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1840 |
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