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Author Jaume Garcia
Title Generalized Active Shape Models Applied to Cardiac Function Analysis Type Report
Year 2004 Publication CVC Technical Report Abbreviated Journal
Volume Issue 78 Pages
Keywords Cardiac Analysis; Deformable Models; Active Contour Models; Active Shape Models; Tagged MRI; HARP; Contrast Echocardiography.
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.
Address CVC (UAB)
Corporate Author Thesis Master's thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM; Approved no
Call Number IAM @ iam @ Gar2004 Serial 1513
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Author Jaume Garcia; Debora Gil; Aura Hernandez-Sabate
Title Endowing Canonical Geometries to Cardiac Structures Type Book Chapter
Year 2010 Publication Statistical Atlases And Computational Models Of The Heart Abbreviated Journal
Volume 6364 Issue Pages 124-133
Keywords
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.
Address
Corporate Author Thesis
Publisher Springer Berlin / Heidelberg Place of Publication Editor Camara, O.; Pop, M.; Rhode, K.; Sermesant, M.; Smith, N.; Young, A.
Language Summary Language Original Title
Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM Approved no
Call Number IAM @ iam @ GGH2010b Serial 1515
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Author M.Gomez; Josefina Mauri; Eduard Fernandez-Nofrerias; Oriol Rodriguez-Leon; Carme Julia; Debora Gil; Petia Radeva
Title Reconstrucción de un modelo espacio-temporal de la luz del vaso a partir de secuencias de ecografía intracoronaria Type Conference Article
Year 2002 Publication XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. Abbreviated Journal
Volume Issue Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM;ADAS;MILAB Approved no
Call Number IAM @ iam @ GMF2002d Serial 1516
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Author Debora Gil
Title Geometric Differential Operators for Shape Modelling Type Book Whole
Year 2004 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
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.
Address
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Barcelona (Spain) Editor Jordi Saludes i Closa;Petia Radeva
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN 84-933652-0-3 Medium prit
Area Expedition Conference
Notes IAM; Approved no
Call Number IAM @ iam @ GIL2004 Serial 1517
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Author Debora Gil
Title Regularized Curvature Flow Type Report
Year 2002 Publication CVC Technical Report Abbreviated Journal
Volume Issue 63 Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Computer Vision Centre Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM; Approved no
Call Number IAM @ iam @ Gil2002 Serial 1518
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Author Debora Gil; Jaume Garcia; Ruth Aris; Guillaume Houzeaux; Manuel Vazquez
Title A Riemmanian approach to cardiac fiber architecture modelling Type Conference Article
Year 2009 Publication 1st International Conference on Mathematical & Computational Biomedical Engineering Abbreviated Journal
Volume Issue Pages 59-62
Keywords cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry.
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.
Address
Corporate Author Thesis
Publisher Place of Publication Swansea (UK) Editor Nithiarasu, R.L.R.V.L.
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference CMBE
Notes IAM Approved no
Call Number IAM @ iam @ FGA2009 Serial 1520
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Author Debora Gil; Jaume Garcia; Aura Hernandez-Sabate; Enric Marti
Title Manifold parametrization of the left ventricle for a statistical modelling of its complete anatomy Type Conference Article
Year 2010 Publication 8th Medical Imaging Abbreviated Journal
Volume 7623 Issue 762304 Pages 304
Keywords
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.
Address
Corporate Author Thesis
Publisher SPIE Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference SPIE
Notes IAM Approved no
Call Number IAM @ iam @ GGH2010a Serial 1522
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Author Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva
Title A Deterministic-Statistic Adventitia Detection in IVUS Images Type Conference Article
Year 2005 Publication ESC Congress Abbreviated Journal
Volume Issue Pages
Keywords Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
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.
Address Stockholm; Sweden; September 2005
Corporate Author Thesis
Publisher Place of Publication ,Sweden (EU) Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference ESC
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ RMF2005a Serial 1523
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Author Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva
Title A Deterministic-Statistic Adventitia Detection in IVUS Images Type Conference Article
Year 2005 Publication 3rd International workshop on International Workshop on Functional Imaging and Modeling of the Heart Abbreviated Journal
Volume Issue Pages 65-74
Keywords Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation
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.
Address Barcelona; June 2005
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference FIMH
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ RMF2005 Serial 1524
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Author Debora Gil; Aura Hernandez-Sabate; Oriol Rodriguez; Josepa Mauri; Petia Radeva
Title Statistical Strategy for Anisotropic Adventitia Modelling in IVUS Type Journal Article
Year 2006 Publication IEEE Transactions on Medical Imaging Abbreviated Journal
Volume 25 Issue 6 Pages 768-778
Keywords Corners; T-junctions; Wavelets
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.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GHR2006 Serial 1525
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Author Debora Gil; Oriol Rodriguez; Josepa Mauri; Petia Radeva
Title Statistical descriptors of the Myocardial perfusion in angiographic images Type Conference Article
Year 2006 Publication Proc. Computers in Cardiology Abbreviated Journal
Volume Issue Pages 677-680
Keywords Anisotropic processing; intravascular ultrasound (IVUS); vessel border segmentation; vessel structure classification.
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.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GRR2006 Serial 1528
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva
Title Shape Restoration via a Regularized Curvature Flow Type Journal Article
Year 2004 Publication Journal of Mathematical Imaging and Vision Abbreviated Journal
Volume 21 Issue 3 Pages 205-223
Keywords
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.
Address
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GiR2004c Serial 1532
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva
Title Inhibition of False Landmarks Type Book Chapter
Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal
Volume Issue Pages 233-244
Keywords
Abstract We argue that a corner detector should be based on the degree of continuity of the tangent vector to the image level sets, work on the image domain and need no assumptions on neither the image local structure nor the particular geometry of the corner/junction. An operator measuring the degree of differentiability of the projection matrix on the image gradient fulfills the above requirements. Its high sensitivity to changes in vector directions makes it suitable for landmark location in real images prone to need smoothing to reduce the impact of noise. Because using smoothing kernels leads to corner misplacement, we suggest an alternative fake response remover based on the receptive field inhibition of spurious details. The combination of both orientation discontinuity detection and noise inhibition produce our Inhibition Orientation Energy (IOE) landmark locator.
Address
Corporate Author Thesis
Publisher IOS Press Place of Publication Barcelona (Spain) Editor al, J.V. et
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GiR2004a Serial 1533
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva
Title Curvature based Distance Maps Type Report
Year 2003 Publication CVC Technical Report Abbreviated Journal
Volume Issue 70 Pages
Keywords
Abstract
Address
Corporate Author Thesis
Publisher Computer Vision Center Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GIR2003a Serial 1534
Permanent link to this record
 

 
Author Debora Gil; Petia Radeva; Josefina Mauri
Title Ivus Segmentation Via a Regularized Curvature Flow Type Conference Article
Year 2002 Publication X Congreso Anual de la Sociedad Española de Ingeniería Biomédica CASEIB 2002 Abbreviated Journal
Volume Issue Pages 133-136
Keywords
Abstract Cardiac diseases are diagnosed and treated through a study of the morphology and dynamics of cardiac arteries. In- travascular Ultrasound (IVUS) imaging is of high interest to physicians since it provides both information. At the current state-of-the-art in image segmentation, a robust detection of the arterial lumen in IVUS demands manual intervention or ECG-gating. Manual intervention is a tedious and time consuming task that requires experienced observers, meanwhile ECG-gating is an acquisition technique not available in all clinical centers. We introduce a parametric algorithm that detects the arterial luminal border in in vivo sequences. The method consist in smoothing the sequences’ level surfaces under a regularized mean curvature flow that admits non-trivial steady states. The flow is based on a measure of the surface local smoothness that takes into account regularity of the surface curvature.
Address
Corporate Author Thesis
Publisher Place of Publication Saragossa, Espanya Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
Series Volume Series Issue Edition
ISSN (down) ISBN Medium
Area Expedition Conference
Notes IAM;MILAB Approved no
Call Number IAM @ iam @ GRM2002 Serial 1536
Permanent link to this record