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Author  |
Javier Varona; Juan J. Villanueva |
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Title |
Neural networks as spatial filters for image processing: Neurofilters |
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1996 |
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Technical Report #07 |
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ISE @ ise @ VaV1996 |
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95 |
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Author |
Javier Marin |
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Title |
Virtual learning for real testing |
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2009 |
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CVC Technical Report |
Abbreviated Journal |
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150 |
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Computer Vision Center |
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Master's thesis |
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ADAS |
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Admin @ si @ Mar2009c |
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2403 |
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Author |
Jaume Rodriguez; S. Yacoub; Gemma Sanchez; Josep Llados |
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Title |
Performance Evaluation, Comparison and Combination of Commercial Handwriting Recognition Engines |
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2006 |
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CVC Technical Report #93 |
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DAG @ dag @ RYS2006 |
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657 |
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Author |
Jaume Gibert |
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Title |
Learning structural representations and graph matching paradigms in the context of object recognition |
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2009 |
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CVC Technical Report |
Abbreviated Journal |
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143 |
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Computer Vision Center |
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Master's thesis |
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DAG |
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Admin @ si @ Gib2009 |
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2397 |
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Author |
Jaume Garcia |
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Title |
Propagacio de fronts per a la segmentacio en imatges IVUS |
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Year |
2002 |
Publication |
Technical Report |
Abbreviated Journal |
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65 |
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CVC (UAB) |
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IAM |
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Call Number |
IAM @ iam @ Gar2002 |
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328 |
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Author |
Jaume Garcia |
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Title |
Generalized Active Shape Models Applied to Cardiac Function Analysis |
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2004 |
Publication |
CVC Technical Report |
Abbreviated Journal |
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78 |
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Keywords |
Cardiac Analysis; Deformable Models; Active Contour Models; Active Shape Models; Tagged MRI; HARP; Contrast Echocardiography. |
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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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no |
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Call Number |
IAM @ iam @ Gar2004 |
Serial |
1513 |
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Author |
Jaume Amores; Petia Radeva |
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Title |
Registration and retrieval of medical images. Application to IVUS |
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Year |
2004 |
Publication |
CVC Technical Report #77 |
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MILAB |
Approved |
no |
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Call Number |
ADAS @ adas @ AmR2004 |
Serial |
513 |
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Author |
Jaime Lopez-Krahe; Josep Llados; Enric Marti |
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Title |
Architectural Floor Plan Analysis |
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Year |
2000 |
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CVonline |
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Edimburg, UK |
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University of Edinburgh |
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Editor |
Robert B. Fisher |
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DAG;IAM |
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IAM @ iam @ LLM2000 |
Serial |
1561 |
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Author |
J.R. Serra; J.B. Subirana |
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Title |
Extraccion de estructuras interesantes en imagenes |
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1996 |
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CVC Tecnical Report #14 |
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Admin @ si @ SeS1996c |
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216 |
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Author |
J.R. Serra; J.B. Subirana |
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Title |
Perceptual grouping on texture images using non-cartesian networks |
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1996 |
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CVC Technical Report #11 |
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Admin @ si @ SeS1996b |
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218 |
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Author |
J.M. Sanchez; X. Binefa |
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Title |
Color normalization for digital video processing |
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1999 |
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CVC Technical Report #37 |
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Admin @ si @ SaB1999 |
Serial |
525 |
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Author |
J.M. Sanchez |
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Title |
Semantic retrieval from digital video libraries in the TV commercials domain |
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1999 |
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CVC Technical Report #29 |
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Admin @ si @ San1999 |
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191 |
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Author |
J. Queralt |
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Title |
Un metode de vectoritzacio basat en la correspondencia de contorns i en la Teoria de Grafs |
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2000 |
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CVC Technical Report #39 |
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Admin @ si @ Que2000 |
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340 |
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Author |
Ivet Rafegas |
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Exploring Low-Level Vision Models. Case Study: Saliency Prediction |
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2013 |
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CVC Technical Report |
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175 |
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CIC |
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Admin @ si @ Raf2013 |
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2409 |
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Author |
Ivan Huerta |
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Title |
Image-Sequence Segmentation in Uncontrolled Environments |
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2007 |
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CVC Technical Report #115 |
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ISE @ ise @ Hue2007 |
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827 |
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