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M.Gomez; Josefina Mauri; Eduard Fernandez-Nofrerias; Oriol Rodriguez-Leon; Carme Julia; Debora Gil; Petia Radeva |
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Reconstrucción de un modelo espacio-temporal de la luz del vaso a partir de secuencias de ecografía intracoronaria |
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2002 |
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XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. |
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IAM;ADAS;MILAB |
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IAM @ iam @ GMF2002d |
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1516 |
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Author |
Debora Gil |
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Title |
Geometric Differential Operators for Shape Modelling |
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2004 |
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PhD Thesis, Universitat Autonoma de Barcelona-CVC |
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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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Ph.D. thesis |
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Ediciones Graficas Rey |
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Barcelona (Spain) |
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Jordi Saludes i Closa;Petia Radeva |
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84-933652-0-3 |
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prit |
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IAM; |
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IAM @ iam @ GIL2004 |
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1517 |
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Author |
Debora Gil |
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Title |
Regularized Curvature Flow |
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2002 |
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CVC Technical Report |
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63 |
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Computer Vision Centre |
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IAM @ iam @ Gil2002 |
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1518 |
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Author |
Debora Gil; Jaume Garcia; Ruth Aris; Guillaume Houzeaux; Manuel Vazquez |
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Title |
A Riemmanian approach to cardiac fiber architecture modelling |
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2009 |
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1st International Conference on Mathematical & Computational Biomedical Engineering |
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59-62 |
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cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry. |
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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. |
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Swansea (UK) |
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Nithiarasu, R.L.R.V.L. |
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CMBE |
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IAM @ iam @ FGA2009 |
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1520 |
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Author |
Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva |
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Title |
A Deterministic-Statistic Adventitia Detection in IVUS Images |
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2005 |
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ESC Congress |
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Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation |
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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. |
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Stockholm; Sweden; September 2005 |
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ESC |
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IAM;MILAB |
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IAM @ iam @ RMF2005a |
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1523 |
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Author |
Debora Gil; Oriol Rodriguez; Josepa Mauri; Petia Radeva |
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Title |
Statistical descriptors of the Myocardial perfusion in angiographic images |
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2006 |
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Proc. Computers in Cardiology |
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677-680 |
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Anisotropic processing; intravascular ultrasound (IVUS); vessel border segmentation; vessel structure classification. |
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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. |
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IAM;MILAB |
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IAM @ iam @ GRR2006 |
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1528 |
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Author |
Debora Gil; Petia Radeva |
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Title |
Inhibition of False Landmarks |
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2004 |
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Recent Advances in Artificial Intelligence Research and Development |
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233-244 |
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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. |
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IOS Press |
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Barcelona (Spain) |
Editor |
al, J.V. et |
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IAM @ iam @ GiR2004a |
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1533 |
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Debora Gil; Petia Radeva |
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Curvature based Distance Maps |
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2003 |
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CVC Technical Report |
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70 |
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Computer Vision Center |
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IAM @ iam @ GIR2003a |
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1534 |
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Debora Gil; Petia Radeva; Josefina Mauri |
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Title |
Ivus Segmentation Via a Regularized Curvature Flow |
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2002 |
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X Congreso Anual de la Sociedad Española de Ingeniería Biomédica CASEIB 2002 |
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133-136 |
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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. |
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Saragossa, Espanya |
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IAM @ iam @ GRM2002 |
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1536 |
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Author |
Debora Gil; Petia Radeva; Jordi Saludes; Josefina Mauri |
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Title |
Automatic Segmentation of Artery Wall in Coronary IVUS Images: a Probabilistic Approach |
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2000 |
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Proceedings of CIC’2000 |
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Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results. |
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Cambridge, Massachussets |
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CIC |
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IAM @ iam @ GRS2000 |
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1538 |
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