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Sandra Pujades, Francesc Carreras, Manuel Ballester, Jaume Garcia, & Debora Gil. (2008). "A Normalized Parametric Domain for the Analysis of the Left Ventricular Function " In Proceedings of the Third International Conference on Computer Vision Theory and Applications (VISAPP’08) (Vol. 1, pp. 267–274).
Abstract: Impairment of left ventricular (LV) contractility due to cardiovascular diseases is reflected in LV motion patterns. The mechanics of any muscle strongly depends on the spatial orientation of its muscular fibers since the motion that the muscle undergoes mainly takes place along the fiber. The helical ventricular myocardial band (HVMB) concept describes the myocardial muscle as a unique muscular band that twists in space in a non homogeneous fashion. The 3D anisotropy of the ventricular band fibers suggests a regional analysis of the heart motion. Computation of normality models of such motion can help in the detection and localization of any cardiac disorder. In this paper we introduce, for the first time, a normalized parametric domain that allows comparison of the left ventricle motion across patients. We address, both, extraction of the LV motion from Tagged Magnetic Resonance images, as well as, defining a mapping of the LV to a common normalized domain. Extraction of normality motion patterns from 17 healthy volunteers shows the clinical potential of our LV parametrization.
Keywords: Helical Ventricular Myocardial Band; Myocardial Fiber; Tagged Magnetic Resonance; HARP; Optical Flow Variational Framework; Gabor Filters; B-Splines.
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Debora Gil, Agnes Borras, Ruth Aris, Mariano Vazquez, Pierre Lafortune, & Guillame Houzeaux. (2012). "What a difference in biomechanics cardiac fiber makes " In Statistical Atlases And Computational Models Of The Heart: Imaging and Modelling Challenges (Vol. 7746, pp. 253–260). Springer Berlin Heidelberg.
Abstract: Computational simulations of the heart are a powerful tool for a comprehensive understanding of cardiac function and its intrinsic relationship with its muscular architecture. Cardiac biomechanical models require a vector field representing the orientation of cardiac fibers. A wrong orientation of the fibers can lead to a
non-realistic simulation of the heart functionality. In this paper we explore the impact of the fiber information on the simulated biomechanics of cardiac muscular anatomy. We have used the John Hopkins database to perform a biomechanical simulation using both a synthetic benchmark fiber distribution and the data obtained experimentally from DTI. Results illustrate how differences in fiber orientation affect heart deformation along cardiac cycle.
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Ernest Valveny, & Enric Marti. (2000). "Hand-drawn symbol recognition in graphic documents using deformable template matching and a Bayesian framework " In Proc. 15th Int Pattern Recognition Conf (Vol. 2, pp. 239–242).
Abstract: Hand-drawn symbols can take many different and distorted shapes from their ideal representation. Then, very flexible methods are needed to be able to handle unconstrained drawings. We propose here to extend our previous work in hand-drawn symbol recognition based on a Bayesian framework and deformable template matching. This approach gets flexibility enough to fit distorted shapes in the drawing while keeping fidelity to the ideal shape of the symbol. In this work, we define the similarity measure between an image and a symbol based on the distance from every pixel in the image to the lines in the symbol. Matching is carried out using an implementation of the EM algorithm. Thus, we can improve recognition rates and computation time with respect to our previous formulation based on a simulated annealing algorithm.
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Patricia Marquez, H. Kause, A. Fuster, Aura Hernandez-Sabate, L. Florack, Debora Gil, et al. (2014). "Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging " In 17th International Conference on Medical Image Computing and Computer Assisted Intervention (Vol. 8896, pp. 231–238). Springer International Publishing.
Abstract: Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across di erent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three di erent OF methods, including HARP.
Keywords: Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging
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Aura Hernandez-Sabate, Debora Gil, Petia Radeva, & E.N.Nofrerias. (2004). "Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images " In Proc. Computers in Cardiology (Vol. 31, pp. 229–232). Chicago (USA).
Abstract: The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles
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Josep Llados, Jaime Lopez-Krahe, Gemma Sanchez, & Enric Marti. (2000)." Interprétation de cartes et plans par mise en correspondance de graphes de attributs" In 12 Congrès Francophone AFRIF–AFIA (Vol. 3, pp. 225–234).
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Sergio Vera, Debora Gil, Agnes Borras, F. Javier Sanchez, Frederic Perez, & Marius G. Linguraru. (2011)." Computation and Evaluation of Medial Surfaces for Shape Representation of Abdominal Organs" In In H. Yoshida et al (Ed.), Workshop on Computational and Clinical Applications in Abdominal Imaging (Vol. 7029, pp. 223–230). Springer Berlin Heidelberg.
Abstract: Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing 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 avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.
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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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Petia Radeva, A.Amini, J.Huang, & Enric Marti. (1996). "Deformable B-Solids and Implicit Snakes for Localization and Tracking of SPAMM MRI-Data " In Workshop on Mathematical Methods in Biomedical Image Analysis (pp. 192–201). IEEE Computer Society.
Abstract: To date, MRI-SPAMM data from different image slices have been analyzed independently. In this paper, we propose an approach for 3D tag localization and tracking of SPAMM data by a novel deformable B-solid. The solid is defined in terms of a 3D tensor product B-spline. The isoparametric curves of the B-spline solid have special importance. These are termed implicit snakes as they deform under image forces from tag lines in different image slices. The localization and tracking of tag lines is performed under constraints of continuity and smoothness of the B-solid. The framework unifies the problems of localization, and displacement fitting and interpolation into the same procedure utilizing B-spline bases for interpolation. To track motion from boundaries and restrict image forces to the myocardium, a volumetric model is employed as a pair of coupled endocardial and epicardial B-spline surfaces. To recover deformations in the LV an energy-minimization problem is posed where both tag and ...
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Patricia Marquez, Debora Gil, & Aura Hernandez-Sabate. (2012). "Error Analysis for Lucas-Kanade Based Schemes " In 9th International Conference on Image Analysis and Recognition (Vol. 7324, pp. 184–191). Lecture Notes in Computer Science. Springer-Verlag Berlin Heidelberg.
Abstract: Optical flow is a valuable tool for motion analysis in medical imaging sequences. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in medical sequences. This paper presents an error analysis of Lucas-Kanade schemes in terms of intrinsic design errors and numerical stability of the algorithm. Our analysis provides a confidence measure that is naturally correlated to the accuracy of the flow field. Our experiments show the higher predictive value of our confidence measure compared to existing measures.
Keywords: Optical flow, Confidence measure, Lucas-Kanade, Cardiac Magnetic Resonance
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