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Oriol Rodriguez-Leon, Debora Gil, & Eduard Fernandez-Nofrerias. (2006)." Analisis en los cambios en el nivel de gris en las secuencias angiograficas mediante descriptores estadisticos para determinar la perfusion miocardica" . Revista Española de Cardiología, 59 Supl 2-166(2), 128.
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Oriol Rodriguez-Leon, Josefina Mauri, Eduard Fernandez-Nofrerias, C.Garcia, R.Villuendas, Vicente del Valle, et al. (2003)." Reconstruction of a spatio-temporal model of the intima layer from intravascular ultrasound sequences" . European Heart Journal, .
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Oriol Rodriguez-Leon, Josefina Mauri, Eduard Fernandez-Nofrerias, Antonio Tovar, Vicente del Valle, Aura Hernandez-Sabate, et al. (2004)." Utilización de la Estructura de los Campos Vectoriales para la Detección de la Adventicia en Imágenes de Ecografía Intracoronaria" . Revista Internacional de Enfermedades Cardiovasculares Revista Española de Cardiología, 57(2), 100.
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Oriol Rodriguez-Leon, Eduard Fernandez-Nofrerias, Josefina Mauri, Vicente del Valle, Debora Gil, A.Barrios, et al. (2006)." Perfusion ratio: A new tool to objectively assess microcirculation perfusion after primary Percutaneous Coronary Intervention" In World Congress of Cardiology (859). Barcelona (Spain).
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Oriol Rodriguez-Leon, Josefina Mauri, Eduard Fernandez-Nofrerias, Vicente de Valle, E.Garcia, A.Barrios, et al. (2006)." Analysis of the changes in angiography local grey-level values to determine myocardial perfusion" In World Congress of Cardiology (862). Barcelona (Spain).
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Misael Rosales, Petia Radeva, Oriol Rodriguez-Leon, & Debora Gil. (2009). "Modelling of image-catheter motion for 3-D IVUS " . Medical image analysis, 13(1), 91–104.
Abstract: Three-dimensional intravascular ultrasound (IVUS) allows to visualize and obtain volumetric measurements of coronary lesions through an exploration of the cross sections and longitudinal views of arteries. However, the visualization and subsequent morpho-geometric measurements in IVUS longitudinal cuts are subject to distortion caused by periodic image/vessel motion around the IVUS catheter. Usually, to overcome the image motion artifact ECG-gating and image-gated approaches are proposed, leading to slowing the pullback acquisition or disregarding part of IVUS data. In this paper, we argue that the image motion is due to 3-D vessel geometry as well as cardiac dynamics, and propose a dynamic model based on the tracking of an elliptical vessel approximation to recover the rigid transformation and align IVUS images without loosing any IVUS data. We report an extensive validation with synthetic simulated data and in vivo IVUS sequences of 30 patients achieving an average reduction of the image artifact of 97% in synthetic data and 79% in real-data. Our study shows that IVUS alignment improves longitudinal analysis of the IVUS data and is a necessary step towards accurate reconstruction and volumetric measurements of 3-D IVUS.
Keywords: Intravascular ultrasound (IVUS); Motion estimation; Motion decomposition; Fourier
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Fernando Vilariño, Debora Gil, & Petia Radeva. (2004). "A Novel FLDA Formulation for Numerical Stability Analysis " In P. R. and I. A. J. Vitrià (Ed.), Recent Advances in Artificial Intelligence Research and Development (Vol. 113, pp. 77–84). IOS Press.
Abstract: Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.
Keywords: Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision
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David Roche, Debora Gil, & Jesus Giraldo. (2011). "An inference model for analyzing termination conditions of Evolutionary Algorithms " In 14th Congrès Català en Intel·ligencia Artificial (pp. 216–225).
Abstract: In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution.
Keywords: Evolutionary Computation Convergence, Termination Conditions, Statistical Inference
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David Roche, Debora Gil, & Jesus Giraldo. (2011). "Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms " In 11th European Conference on Artificial Life.
Abstract: A main challenge in Evolutionary Algorithms (EAs) is determining a termination condition ensuring stabilization close to the optimum in real-world applications. Although for known test functions distribution-based quantities are good candidates (as far as suitable parameters are used), in real-world problems an open question still remains unsolved. How can we estimate an upper-bound for the termination condition value ensuring a given accuracy for the (unknown) EA solution?
We claim that the termination problem would be fully solved if we defined a quantity (depending only on the EA output) behaving like the solution accuracy. The open question would be, then, satisfactorily answered if we had a model relating both quantities, since accuracy could be predicted from the alternative quantity. We present a statistical inference framework addressing two topics: checking the correlation between the two quantities and defining a regression model for predicting (at a given confidence level) accuracy values from the EA output.
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Ferran Poveda, Debora Gil, Albert Andaluz, & Enric Marti. (2011). "Multiscale Tractography for Representing Heart Muscular Architecture " In In MICCAI 2011 Workshop on Computational Diffusion MRI.
Abstract: Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diffusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and indicate a global helical organization
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