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Author |
Georg Langs; Petia Radeva; David Rotger; Francesc Carreras |
Title |
Explorative Building of 3D Vessel Tree Models |
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Miscellaneous |
Year |
2004 |
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“Digital Imaging in Media and Education”, 28th annual workshop of the Austrian Association for Pattern Recognition (OAGM/AAPR) |
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Hagenberg (Austria) |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ LRR2004a |
Serial |
467 |
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Author |
Petia Radeva; Maya Dimitrova; Ch. Roumenin; David Rotger; D. Nikolov; Juan J. Villanueva |
Title |
Integration of Multiple Sensor Modalities in ActiveVessel Cardiology Workstation |
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Miscellaneous |
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2004 |
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Varna (Bulgaria) |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ RDR2004 |
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473 |
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Author |
P. Andreeva; Maya Dimitrova; Petia Radeva |
Title |
Data Mining Learning Models and Algorithms for Medical Applications |
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2004 |
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18 Conference Systems for Automation of Engineering and Research (SEAR 2004) |
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Varna (Bulgaria) |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ ADR2004 |
Serial |
474 |
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Author |
E. Barakova; Maya Dimitrova; T. Lorents; Petia Radeva |
Title |
The Web as an “Autobiographical Agent” |
Type |
Miscellaneous |
Year |
2004 |
Publication |
Ch. Bussler and D. Fensel (Eds), Lecture Notes in Artificial Intelligence, vol. 3192, ISBN: 3–540–22959–0, pp. 510–519. |
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Springer-Verlag |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ BDL2004 |
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475 |
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Author |
Maya Dimitrova; I. Terziev; Petia Radeva; Juan J. Villanueva |
Title |
Java-Servlet Technology for Building New Web Document Classifiers |
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Miscellaneous |
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2004 |
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Varna (Bulgaria) |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ DTR2004 |
Serial |
476 |
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Author |
Maya Dimitrova; Petia Radeva; David Rotger; D. Boyadjiev; Juan J. Villanueva |
Title |
Advanced Cardiological Diagnosis via Intelligent Image Analysis |
Type |
Miscellaneous |
Year |
2004 |
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Varna (Bulgaria) |
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MILAB |
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no |
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BCNPCL @ bcnpcl @ DRR2004 |
Serial |
477 |
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Author |
O. Rodriguez; David Rotger; J. Mauri; E. Fernandez; V. Valle; Petia Radeva |
Title |
Active vessel workstation: three-dimensional reconstruction of coronary arteries by fusion of angiography and intravascular ultrasound |
Type |
Miscellaneous |
Year |
2004 |
Publication |
European Society of Cardiology Congress 2004 |
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Munich |
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MILAB |
Approved |
no |
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BCNPCL @ bcnpcl @ RRM2004a |
Serial |
479 |
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Author |
Jaume Amores; Petia Radeva |
Title |
Registration and retrieval of medical images. Application to IVUS |
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Report |
Year |
2004 |
Publication |
CVC Technical Report #77 |
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CVC (UAB) |
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Approved |
no |
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ADAS @ adas @ AmR2004 |
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513 |
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Author |
Misael Rosales; Petia Radeva; J. Mauri; Oriol Pujol |
Title |
Simulation Model of Intravascular Ultrasound Images |
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Miscellaneous |
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2004 |
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MICCAI, 2004, Saint Melo, France |
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Springer Verlag |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ RRM2004b |
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464 |
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Author |
Oriol Pujol; Oriol Rodriguez-Leor; J. Mauri; E. Fernandez; V. Valle; Petia Radeva |
Title |
Automatic segmentation and characterization of IVUS images by texture analysis |
Type |
Miscellaneous |
Year |
2004 |
Publication |
European Society of Cardiology Congress 2004 |
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Munich |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ PRM2004 |
Serial |
478 |
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Author |
Oriol Pujol; Petia Radeva |
Title |
Texture Segmentation by Statistical Deformable Models |
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Journal |
Year |
2004 |
Publication |
International Journal of Image and Graphics |
Abbreviated Journal |
IJIG |
Volume |
4 |
Issue |
3 |
Pages |
433-452 |
Keywords |
Texture segmentation, parametric active contours, statistic snakes |
Abstract |
Deformable models have received much popularity due to their ability to include high-level knowledge on the application domain into low-level image processing. Still, most proposed active contour models do not sufficiently profit from the application information and they are too generalized, leading to non-optimal final results of segmentation, tracking or 3D reconstruction processes. In this paper we propose a new deformable model defined in a statistical framework to segment objects of natural scenes. We perform a supervised learning of local appearance of the textured objects and construct a feature space using a set of co-occurrence matrix measures. Linear Discriminant Analysis allows us to obtain an optimal reduced feature space where a mixture model is applied to construct a likelihood map. Instead of using a heuristic potential field, our active model is deformed on a regularized version of the likelihood map in order to segment objects characterized by the same texture pattern. Different tests on synthetic images, natural scene and medical images show the advantages of our statistic deformable model. |
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MILAB;HuPBA |
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no |
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BCNPCL @ bcnpcl @ PuR2004a |
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505 |
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Author |
Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva |
Title |
Utilizacion de la estructura de los campos vectoriales para la deteccion de la Adventicia en imagenes de Ecografia Intracoronaria |
Type |
Journal |
Year |
2004 |
Publication |
Revista Española de Cardiología |
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REC |
Volume |
57 |
Issue |
2 |
Pages |
100 |
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MILAB;IAM |
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no |
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BCNPCL @ bcnpcl @ RMF2004 |
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566 |
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Author |
Jaume Amores; N. Sebe; Petia Radeva; Theo Gevers; A. Smeulders |
Title |
Boosting Contextual Information in Content-based Image Retrieval |
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Miscellaneous |
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2004 |
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6th ACM SIGMM International Workshop on Multimedia Information Retrieval |
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New York, USA |
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MILAB;ISE |
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no |
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ADAS @ adas @ ASR2004 |
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466 |
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Author |
Fernando Vilariño; Debora Gil; Petia Radeva |
Title |
A Novel FLDA Formulation for Numerical Stability Analysis |
Type |
Book Chapter |
Year |
2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
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113 |
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77-84 |
Keywords |
Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision |
Abstract |
Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision. |
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IOS Press |
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J. Vitrià, P. Radeva and I. Aguiló |
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978-1-58603-466-5 |
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MV;IAM;MILAB;SIAI |
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IAM @ iam @ VGR2004 |
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1663 |
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Author |
Oriol Pujol; Petia Radeva; Jordi Vitria; J. Mauri |
Title |
Adaboost to Classify Plaque Appearance in IVUS Images |
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Miscellaneous |
Year |
2004 |
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Progress in Pattern Recognition, Image Analysis and Applications, LNCS 3287:629–636 |
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Puebla (Mexico) |
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OR;MILAB;HuPBA;MV |
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BCNPCL @ bcnpcl @ PRV2004 |
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472 |
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