Jaume Garcia, Debora Gil, Joel Barajas, Francesc Carreras, Sandra Pujades, & Petia Radeva. (2006). Characterization of ventricular torsion in healthy subjects using Gabor filters and a variational framework. In Proc. Computers in Cardiology (pp. 877–880).
Abstract: In this work, we present a fully automated method for tissue deformation estimation in tagged magnetic resonance images (TMRI). Gabor filter banks, tuned independently for each left ventricle level, provide optimally filtered complex images which phase remains constant along the cardiac cycle. This fact can be thought as the brightness constancy condition required by classical optical flow (OF) methods. Pairs of these filtered sequences, together with a variational formulation are used in a second step to obtain dense continuous deformation maps that we call Harmonic Phase Flow. This method has been used to determine reference values of ventricular torsion (VT) in a set of 8 healthy volunteers. The results encourage the use of VT as a useful parameter for ventricular function assessment in clinical routine.
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Jaume Garcia, Francesc Carreras, Sandra Pujades, & Debora Gil. (2008). Regional motion patterns for the Left Ventricle function assessment. In Proc. 19th Int. Conf. Pattern Recognition ICPR 2008 (pp. 1–4).
Abstract: Regional scores (e.g. strain, perfusion) of the Left Ventricle (LV) functionality are playing an increasing role in the diagnosis of cardiac diseases. A main limitation is the lack of normality models for complementary scores oriented to assessment of the LV integrity. This paper introduces an original framework based on a parametrization of the LV domain, which allows comparison across subjects of local physiological measures of different nature. We compute regional normality patterns in a feature space characterizing the LV function. We show the consistency of the model for the regional motion on healthy and hypokinetic pathological cases
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Enrique Cabello, Cristina Conde, Angel Serrano, Licesio Rodriguez, & David Vazquez. (2006). Empleo de sistemas biométricos para el reconocimiento de personas en aeropuertos.
Abstract: El presente proyecto se desarrolló a lo largo del año 2005, probando un prototipo de un sistema de verificación facial con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. Se diseñaron varios experimentos, agrupados en dos clases. En el primer tipo, el sistema es entrenado con imágenes obtenidas en condiciones de laboratorio y luego probado con imágenes extraídas de las cámaras de video vigilancia del aeropuerto de Barajas. En el segundo caso, tanto las imágenes de entrenamiento como las de prueba corresponden a imágenes extraídas de Barajas. Se ha desarrollado un sistema completo, que incluye adquisición y digitalización de las imágenes, localización y recorte de las caras en escena, verificación de sujetos y obtención de resultados. Los resultados muestran, que, en general, un sistema de verificación facial basado en imágenes puede ser una ayuda a un operario que deba estar vigilando amplias zonas.
Keywords: Surveillance; Face detection; Face recognition
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Jaume Garcia. (2004). Generalized Active Shape Models Applied to Cardiac Function Analysis. Master's thesis, , .
Abstract: Medical imaging is very useful in the assessment and treatment of many diseases. To deal with the great amount of data provided by imaging scanners and extract quantitative information that physicians can interpret, many analysis algorithms have been developed. Any process of analysis always consists of a first step of segmenting some particular structure. In medical imaging, structures are not always well defined and suffer from noise artifacts thus, ordinary segmentation methods are not well suited. The ones that seem to give better results are those based on deformable models. Nevertheless, despite their capability of mixing image features together with smoothness constraints that may compensate for image irregularities, these are naturally local methods, i. e., each node of the active contour evolve taking into account information about its neighbors and some other weak constraints about flexibility and smoothness, but not about the global shape that they should find. Due to the fact that structures to be segmented are the same for all cases but with some inter and intra-patient variation, the incorporation of a priori knowledge about shape in the segmentation method will provide robustness to it. Active Shape Models is an algorithm based on the creation of a shape model called Point Distribution Model. It performs a segmentation using only shapes similar than those previously learned from a training set that capture most of the variation presented by the structure. This algorithm works by updating shape nodes along a normal segment which often can be too restrictive. For this reason we propose a generalization of this algorithm that we call Generalized Active Shape Models and fully integrates the a priori knowledge given by the Point Distribution Model with deformable models or any other appropriate segmentation method. Two different applications to cardiac imaging of this generalized method are developed and promising results are shown.
Keywords: Cardiac Analysis; Deformable Models; Active Contour Models; Active Shape Models; Tagged MRI; HARP; Contrast Echocardiography.
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Jaume Garcia, Debora Gil, & Aura Hernandez-Sabate. (2010). Endowing Canonical Geometries to Cardiac Structures. In O. Camara, M. Pop, K. Rhode, M. Sermesant, N. Smith, & A. Young (Eds.), Statistical Atlases And Computational Models Of The Heart (Vol. 6364, pp. 124–133). LNCS. Springer Berlin / Heidelberg.
Abstract: International conference on Cardiac electrophysiological simulation challenge
In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view.
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M. Gomez, J. Mauri, Eduard Fernandez-Nofrerias, Oriol Rodriguez-Leor, Carme Julia, Debora Gil, et al. (2002). Reconstrucción de un modelo espacio-temporal de la luz del vaso a partir de secuencias de ecografía intracoronaria. In XXXVIII Congreso Nacional de la Sociedad Española de Cardiología..
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Debora Gil. (2004). Geometric Differential Operators for Shape Modelling (Jordi Saludes i Closa, & Petia Radeva, Eds.). Ph.D. thesis, Ediciones Graficas Rey, Barcelona (Spain).
Abstract: Medical imaging feeds research in many computer vision and image processing fields: image filtering, segmentation, shape recovery, registration, retrieval and pattern matching. Because of their low contrast changes and large variety of artifacts and noise, medical imaging processing techniques relying on an analysis of the geometry of image level sets rather than on intensity values result in more robust treatment. From the starting point of treatment of intravascular images, this PhD thesis ad- dresses the design of differential image operators based on geometric principles for a robust shape modelling and restoration. Among all fields applying shape recovery, we approach filtering and segmentation of image objects. For a successful use in real images, the segmentation process should go through three stages: noise removing, shape modelling and shape recovery. This PhD addresses all three topics, but for the sake of algorithms as automated as possible, techniques for image processing will be designed to satisfy three main principles: a) convergence of the iterative schemes to non-trivial states avoiding image degeneration to a constant image and representing smooth models of the originals; b) smooth asymptotic behav- ior ensuring stabilization of the iterative process; c) fixed parameter values ensuring equal (domain free) performance of the algorithms whatever initial images/shapes. Our geometric approach to the generic equations that model the different processes approached enables defining techniques satisfying all the former requirements. First, we introduce a new curvature-based geometric flow for image filtering achieving a good compromise between noise removing and resemblance to original images. Sec- ond, we describe a new family of diffusion operators that restrict their scope to image level curves and serve to restore smooth closed models from unconnected sets of points. Finally, we design a regularization of snake (distance) maps that ensures its smooth convergence towards any closed shape. Experiments show that performance of the techniques proposed overpasses that of state-of-the-art algorithms.
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Debora Gil. (2002). Regularized Curvature Flow. Computer Vision Centre.
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Debora Gil, Jaume Garcia, Ruth Aris, Guillaume Houzeaux, & Manuel Vazquez. (2009). A Riemmanian approach to cardiac fiber architecture modelling. In R. L. R. V. L. Nithiarasu (Ed.), 1st International Conference on Mathematical & Computational Biomedical Engineering (pp. 59–62). Swansea (UK).
Abstract: There is general consensus that myocardial fiber architecture should be modelled in order to fully understand the electromechanical properties of the Left Ventricle (LV). Diffusion Tensor magnetic resonance Imaging (DTI) is the reference image modality for rapid measurement of fiber orientations by means of the tensor principal eigenvectors. In this work, we present a mathematical framework for across subject comparison of the local geometry of the LV anatomy including the fiber architecture from the statistical analysis of DTI studies. We use concepts of differential geometry for defining a parametric domain suitable for statistical analysis of a low number of samples. We use Riemannian metrics to define a consistent computation of DTI principal eigenvector modes of variation. Our framework has been applied to build an atlas of the LV fiber architecture from 7 DTI normal canine hearts.
Keywords: cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry.
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Debora Gil, Jaume Garcia, Aura Hernandez-Sabate, & Enric Marti. (2010). Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy. In 8th Medical Imaging (Vol. 7623, 304). SPIE.
Abstract: Distortion of Left Ventricle (LV) external anatomy is related to some dysfunctions, such as hypertrophy. The architecture of myocardial fibers determines LV electromechanical activation patterns as well as mechanics. Thus, their joined modelling would allow the design of specific interventions (such as peacemaker implantation and LV remodelling) and therapies (such as resynchronization). On one hand, accurate modelling of external anatomy requires either a dense sampling or a continuous infinite dimensional approach, which requires non-Euclidean statistics. On the other hand, computation of fiber models requires statistics on Riemannian spaces. Most approaches compute separate statistical models for external anatomy and fibers architecture. In this work we propose a general mathematical framework based on differential geometry concepts for computing a statistical model including, both, external and fiber anatomy. Our framework provides a continuous approach to external anatomy supporting standard statistics. We also provide a straightforward formula for the computation of the Riemannian fiber statistics. We have applied our methodology to the computation of complete anatomical atlas of canine hearts from diffusion tensor studies. The orientation of fibers over the average external geometry agrees with the segmental description of orientations reported in the literature.
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Debora Gil, Aura Hernandez-Sabate, Antoni Carol, Oriol Rodriguez, & Petia Radeva. (2005). A Deterministic-Statistic Adventitia Detection in IVUS Images. In ESC Congress. ,Sweden (EU).
Abstract: Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.
Keywords: Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
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Debora Gil, Aura Hernandez-Sabate, Antoni Carol, Oriol Rodriguez, & Petia Radeva. (2005). A Deterministic-Statistic Adventitia Detection in IVUS Images. In 3rd International workshop on International Workshop on Functional Imaging and Modeling of the Heart (pp. 65–74).
Abstract: Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.
Keywords: Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
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Debora Gil, Aura Hernandez-Sabate, Oriol Rodriguez, J. Mauri, & Petia Radeva. (2006). Statistical Strategy for Anisotropic Adventitia Modelling in IVUS. IEEE Transactions on Medical Imaging, 25(6), 768–778.
Abstract: Vessel plaque assessment by analysis of intravascular ultrasound sequences is a useful tool for cardiac disease diagnosis and intervention. Manual detection of luminal (inner) and mediaadventitia (external) vessel borders is the main activity of physicians in the process of lumen narrowing (plaque) quantification. Difficult definition of vessel border descriptors, as well as, shades, artifacts, and blurred signal response due to ultrasound physical properties trouble automated adventitia segmentation. In order to efficiently approach such a complex problem, we propose blending advanced anisotropic filtering operators and statistical classification techniques into a vessel border modelling strategy. Our systematic statistical analysis shows that the reported adventitia detection achieves an accuracy in the range of interobserver variability regardless of plaque nature, vessel geometry, and incomplete vessel borders. Index Terms–-Anisotropic processing, intravascular ultrasound (IVUS), vessel border segmentation, vessel structure classification.
Keywords: Corners; T-junctions; Wavelets
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Debora Gil, Oriol Rodriguez, J. Mauri, & Petia Radeva. (2006). Statistical descriptors of the Myocardial perfusion in angiographic images. In Proc. Computers in Cardiology (pp. 677–680).
Abstract: Restoration of coronary flow after primary percutaneous coronary intervention in acute myocardial infarction does not always correlate with adequate myocardial perfusion. Recently, coronary angiography has been used to assess microcirculation integrity (Myocardial BlushAnalysis, MBA). Although MBA correlates with patient prognosis there are few image processing methods addressing objective perfusion quantification. The goal of this work is to develop statistical descriptors of the myocardial dyeing pattern allowing objective assessment of myocardial perfusion. Experiments on healthy right coronary arteries show that our approach allows reliable measurements without any specific image acquisition protocol.
Keywords: Anisotropic processing; intravascular ultrasound (IVUS); vessel border segmentation; vessel structure classification.
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Debora Gil, & Petia Radeva. (2004). Shape Restoration via a Regularized Curvature Flow. Journal of Mathematical Imaging and Vision, 21(3), 205–223.
Abstract: Any image filtering operator designed for automatic shape restoration should satisfy robustness (whatever the nature and degree of noise is) as well as non-trivial smooth asymptotic behavior. Moreover, a stopping criterion should be determined by characteristics of the evolved image rather than dependent on the number of iterations. Among the several PDE based techniques, curvature flows appear to be highly reliable for strongly noisy images compared to image diffusion processes.
In the present paper, we introduce a regularized curvature flow (RCF) that admits non-trivial steady states. It is based on a measure of the local curve smoothness that takes into account regularity of the curve curvature and serves as stopping term in the mean curvature flow. We prove that this measure decreases over the orbits of RCF, which endows the method with a natural stop criterion in terms of the magnitude of this measure. Further, in its discrete version it produces steady states consisting of piece-wise regular curves. Numerical experiments made on synthetic shapes corrupted with different kinds of noise show the abilities and limitations of each of the current geometric flows and the benefits of RCF. Finally, we present results on real images that illustrate the usefulness of the present approach in practical applications.
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