| Records |
| Author |
Oriol Ramos Terrades; Ernest Valveny |
| Title |
Indexing Technical Symbols Using Ridgelets Transform |
Type |
Miscellaneous |
| Year |
2004 |
Publication |
Graphics Recognition: Recent Advances and Perspectives, J. Llados, Y.B. Kwon (Eds.), Lecture Notes in Computer Science, 3088:177–187, ISBN: 3–540–22478–5 |
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DAG |
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no |
| Call Number |
DAG @ dag @ VaD2004c |
Serial |
503 |
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| Author |
Oriol Pujol; Petia Radeva |
| Title |
Texture Segmentation by Statistical Deformable Models |
Type |
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 |
Carme Julia |
| Title |
Motion segmentation through factorization. Application to night driving assistance |
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Report |
| Year |
2004 |
Publication |
CVC Technical Report #79 |
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no |
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Admin @ si @ 38169 |
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506 |
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| Author |
Raul Chaves |
| Title |
Sistema de identificacion mediante huellas dactilares |
Type |
Report |
| Year |
2004 |
Publication |
CVC Technical Report #81 |
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no |
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Admin @ si @ Cha2004 |
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507 |
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| Author |
Oriol Martinez |
| Title |
Semantic Retrieval of Memory Color Content |
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Report |
| Year |
2004 |
Publication |
CVC Technical Report #80 |
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no |
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Admin @ si @ 38047 |
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508 |
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| Author |
Jordi Vitria; Petia Radeva; I. Aguilo |
| Title |
Recent Advances in Artificial Intelligence Research and Development |
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Book Chapter |
| Year |
2004 |
Publication |
Frontiers in Artificial Intelligence and Applications, 113, J. Vitria, P. Radeva, I. Aguilo (Eds.), ISBN: 1–58603–466–9 |
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Amsterdam |
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OR;MILAB;MV |
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no |
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BCNPCL @ bcnpcl @ VRA2004 |
Serial |
509 |
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| Author |
David Masip; Jordi Vitria |
| Title |
Boosted Linear Projections for Discriminant Analysis |
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Miscellaneous |
| Year |
2004 |
Publication |
CCIA 2004, 45–52, ISBN: 1–58603–466–9 |
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IOS Press |
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OR;MV |
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no |
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BCNPCL @ bcnpcl @ MaV2004c |
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510 |
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| Author |
Jaume Amores; Petia Radeva |
| Title |
Registration and retrieval of medical images. Application to IVUS |
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Report |
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2004 |
Publication |
CVC Technical Report #77 |
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MILAB |
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no |
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ADAS @ adas @ AmR2004 |
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513 |
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| Author |
Petia Radeva; Jordi Vitria |
| Title |
Corkinspect: Statistical Learning of Natural Material |
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2004 |
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Italian Beverage Technology, 13(38):11–18 |
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OR;MILAB;MV |
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no |
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BCNPCL @ bcnpcl @ RaV2004b |
Serial |
514 |
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| Author |
Josep Llados; Young-Bin Kwon |
| Title |
Graphics Recognition. Recent Advances and Perspectives |
Type |
Miscellaneous |
| Year |
2004 |
Publication |
LNCS 3080, ISBN: 3–540–22478–5 |
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Springer-Verlag |
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DAG |
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no |
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DAG @ dag @ LlK2004 |
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515 |
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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 |
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2004 |
Publication |
Revista Española de Cardiología |
Abbreviated Journal |
REC |
| Volume |
57 |
Issue |
2 |
Pages |
100 |
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SEC |
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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 Garcia; Petia Radeva; Francesc Carreras |
| Title |
Combining Spectral and Active Shape methods to Track Tagged MRI |
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2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
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37-44 |
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MR; tagged MR; ASM; LV segmentation; motion estimation. |
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Tagged magnetic resonance is a very usefull and unique tool that provides a complete local and global knowledge of the left ventricle (LV) motion. In this article we introduce a method capable of tracking and segmenting the LV. Spectral methods are applied in order to obtain the so called HARP images which encode information about movement and are the base for LV point-tracking. For segmentation we use Active Shapes (ASM) that model LV shape variation in order to overcome possible local misplacements of the boundary. We finally show experiments on both synthetic and real data which appear to be very promising. |
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IOS Press |
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CCIA |
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IAM;MILAB |
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no |
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IAM @ iam @ GRC2004 |
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1488 |
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| Author |
Jaume Garcia |
| Title |
Generalized Active Shape Models Applied to Cardiac Function Analysis |
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Report |
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2004 |
Publication |
CVC Technical Report |
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78 |
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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. |
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CVC (UAB) |
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Master's thesis |
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IAM; |
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IAM @ iam @ Gar2004 |
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1513 |
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| Author |
Debora Gil; Petia Radeva |
| Title |
Shape Restoration via a Regularized Curvature Flow |
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Journal Article |
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2004 |
Publication |
Journal of Mathematical Imaging and Vision |
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21 |
Issue |
3 |
Pages |
205-223 |
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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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IAM;MILAB |
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no |
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IAM @ iam @ GiR2004c |
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1532 |
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| Author |
Aura Hernandez-Sabate; Debora Gil; Petia Radeva; E.N.Nofrerias |
| Title |
Anisotropic processing of image structures for adventitia detection in intravascular ultrasound images |
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Conference Article |
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2004 |
Publication |
Proc. Computers in Cardiology |
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31 |
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229-232 |
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The adventitia layer appears as a weak edge in IVUS images with a non-uniform grey level, which difficulties its detection. In order to enhance edges, we apply an anisotropic filter that homogenizes the grey level along the image significant structures (ridges, valleys and edges). A standard edge detector applied to the filtered image yields a set of candidate points prone to be unconnected. The final model is obtained by interpolating the former line segments along the tangent direction to the level curves of the filtered image with an anisotropic contour closing technique based on functional extension principles |
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Chicago (USA) |
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IAM; MILAB |
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IAM @ iam @ HGR2004 |
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1555 |
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