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Author |
Debora Gil; Petia Radeva; Fernando Vilariño |
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Title |
Anisotropic Contour Completion |
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2003 |
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Proceedings of the IEEE International Conference on Image Processing |
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I-869 |
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In this paper we introduce a novel application of the diffusion tensor for anisotropic image processing. The Anisotropic Contour Completion (ACC) we suggest consists in extending the characteristic function of the open curve by means of a degenerated diffusion tensor that prevents any diffusion in the normal direction. We show that ACC is equivalent to a dilation with a continuous elliptic structural element that takes into account the local orientation of the contours to be closed. Experiments on contours extracted from real images show that ACC produces shapes able to adapt to any curve in an active contour framework. 1. |
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Barcelona, Spain |
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Barcelona, Spain |
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0-7803-7751-6 |
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ICIP |
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IAM;MV;MILAB;SIAI |
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IAM @ iam @ GRV2003 |
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1539 |
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Josep Llados; Ernest Valveny; Gemma Sanchez; Enric Marti |
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Title |
A Case Study of Pattern Recognition: Symbol Recognition in Graphic Documentsa |
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2003 |
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Proceedings of Pattern Recognition in Information Systems |
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1-13 |
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Angers, France |
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ICEIS Press |
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972-98816-3-4 |
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PRIS'03 |
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DAG;IAM; |
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IAM @ iam @ LVS2003 |
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1576 |
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Gemma Sanchez; Ernest Valveny; Josep Llados; Enric Marti; Oriol Ramos Terrades; N.Lozano; Joan Mas |
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A system for virtual prototyping of architectural projects |
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2003 |
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Proceedings of Fifth IAPR International Workshop on Pattern Recognition |
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65-74 |
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IAM @ iam @ SVL2003 |
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1650 |
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M. Gomez; J. Mauri; Eduard Fernandez-Nofrerias; Oriol Rodriguez-Leor; Carme Julia; Debora Gil; Petia Radeva |
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Title |
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; Petia Radeva; J. 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;MILAB |
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IAM @ iam @ GRM2002 |
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1536 |
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Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; M. Gomez; Antonio Tovar; L. Cano; C. Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva |
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Title |
Ecografia Intracoronària: Segmentació Automàtica de area de la llum |
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Conference Article |
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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 @ RMF2002 |
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1638 |
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Author |
Ernest Valveny; Ricardo Toledo; Ramon Baldrich; Enric Marti |
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Combining recognition-based in segmentation-based approaches for graphic symol recognition using deformable template matching |
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2002 |
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Proceeding of the Second IASTED International Conference Visualization, Imaging and Image Proceesing VIIP 2002 |
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502–507 |
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DAG;RV;CAT;IAM;CIC;ADAS |
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IAM @ iam @ VTB2002 |
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1660 |
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Author |
Ernest Valveny; Enric Marti |
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Learning of structural descriptions of graphic symbols using deformable template matching |
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2001 |
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Proc. Sixth Int Document Analysis and Recognition Conf |
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455-459 |
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Accurate symbol recognition in graphic documents needs an accurate representation of the symbols to be recognized. If structural approaches are used for recognition, symbols have to be described in terms of their shape, using structural relationships among extracted features. Unlike statistical pattern recognition, in structural methods, symbols are usually manually defined from expertise knowledge, and not automatically infered from sample images. In this work we explain one approach to learn from examples a representative structural description of a symbol, thus providing better information about shape variability. The description of a symbol is based on a probabilistic model. It consists of a set of lines described by the mean and the variance of line parameters, respectively providing information about the model of the symbol, and its shape variability. The representation of each image in the sample set as a set of lines is achieved using deformable template matching. |
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DAG;IAM; |
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IAM @ iam @ VMA2001 |
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1654 |
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Author |
Debora Gil; Petia Radeva; Jordi Saludes; J. 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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International Conference on Pattern Recognition |
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4 |
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352-355 |
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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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IAM @ iam @ GRS2000a |
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1537 |
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Debora Gil; Petia Radeva; Jordi Saludes; J. Mauri |
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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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