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Enric Marti; Ferran Poveda; Antoni Gurgui; Jaume Rocarias; Debora Gil; Aura Hernandez-Sabate |
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Una experiencia de estructura, funcionamiento y evaluación de la asignatura de graficos por computador con metodologia de aprendizaje basado en proyectos |
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Miscellaneous |
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2013 |
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IV Congreso Internacional UNIVEST |
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IV Congreso Internacional UNIVEST |
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UNIVEST |
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IAM; ADAS |
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no |
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Admin @ si @ MPG2013b |
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2384 |
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Author |
Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta |
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Title |
Structure-preserving smoothing of biomedical images |
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Journal Article |
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Year |
2011 |
Publication |
Pattern Recognition |
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PR |
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Volume |
44 |
Issue |
9 |
Pages |
1842-1851 |
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Keywords |
Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography |
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Abstract |
Smoothing of biomedical images should preserve gray-level transitions between adjacent tissues, while restoring contours consistent with anatomical structures. Anisotropic diffusion operators are based on image appearance discontinuities (either local or contextual) and might fail at weak inter-tissue transitions. Meanwhile, the output of block-wise and morphological operations is prone to present a block structure due to the shape and size of the considered pixel neighborhood. In this contribution, we use differential geometry concepts to define a diffusion operator that restricts to image consistent level-sets. In this manner, the final state is a non-uniform intensity image presenting homogeneous inter-tissue transitions along anatomical structures, while smoothing intra-structure texture. Experiments on different types of medical images (magnetic resonance, computerized tomography) illustrate its benefit on a further process (such as segmentation) of images. |
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0031-3203 |
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IAM; ADAS |
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IAM @ iam @ GHB2011 |
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1526 |
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Author |
Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie |
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Title |
Inferring the Performance of Medical Imaging Algorithms |
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Conference Article |
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Year |
2011 |
Publication |
14th International Conference on Computer Analysis of Images and Patterns |
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6854 |
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520-528 |
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Validation, Statistical Inference, Medical Imaging Algorithms. |
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Evaluation of the performance and limitations of medical imaging algorithms is essential to estimate their impact in social, economic or clinical aspects. However, validation of medical imaging techniques is a challenging task due to the variety of imaging and clinical problems involved, as well as, the difficulties for systematically extracting a reliable solely ground truth. Although specific validation protocols are reported in any medical imaging paper, there are still two major concerns: definition of standardized methodologies transversal to all problems and generalization of conclusions to the whole clinical data set.
We claim that both issues would be fully solved if we had a statistical model relating ground truth and the output of computational imaging techniques. Such a statistical model could conclude to what extent the algorithm behaves like the ground truth from the analysis of a sampling of the validation data set. We present a statistical inference framework reporting the agreement and describing the relationship of two quantities. We show its transversality by applying it to validation of two different tasks: contour segmentation and landmark correspondence. |
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Sevilla |
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Springer-Verlag Berlin Heidelberg |
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Berlin |
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Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch |
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CAIP |
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IAM; ADAS |
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no |
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IAM @ iam @ HGR2011 |
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1676 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth |
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Conference Article |
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Year |
2011 |
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IEEE International Conference on Computer Vision – Workshops |
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2042-2049 |
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IEEE International Conference on Computer Vision – Workshops |
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Optical flow is a valuable tool for motion analysis in autonomous navigation systems. A reliable application requires determining the accuracy of the computed optical flow. This is a main challenge given the absence of ground truth in real world sequences. This paper introduces a measure of optical flow accuracy for Lucas-Kanade based flows in terms of the numerical stability of the data-term. We call this measure optical flow condition number. A statistical analysis over ground-truth data show a good statistical correlation between the condition number and optical flow error. Experiments on driving sequences illustrate its potential for autonomous navigation systems. |
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IEEE |
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Barcelona (Spain) |
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English |
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English |
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ICCVW |
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IAM; ADAS |
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no |
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IAM @ iam @ MGH2011 |
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1682 |
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Author |
Aura Hernandez-Sabate; Debora Gil |
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Title |
The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries |
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Book Chapter |
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Year |
2012 |
Publication |
Intravascular Ultrasound |
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185-206 |
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Intech |
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Yasuhiro Honda |
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English |
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english |
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978-953-307-900-4 |
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IAM; ADAS |
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no |
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IAM @ iam @ HeG2012 |
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1684 |
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Author |
Patricia Marquez; Debora Gil; Aura Hernandez-Sabate |
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Title |
Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality |
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Conference Article |
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2013 |
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ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars |
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624-631 |
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Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field. |
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Sydney; Australia; December 2013 |
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CVTT:E2M |
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IAM; ADAS; 600.044; 600.057; 601.145 |
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no |
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Admin @ si @ MGH2013b |
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2351 |
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Author |
Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate |
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Title |
Local Analysis of Confidence Measures for Optical Flow Quality Evaluation |
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Conference Article |
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2014 |
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9th International Conference on Computer Vision Theory and Applications |
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3 |
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450-457 |
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Optical Flow; Confidence Measure; Performance Evaluation. |
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Optical Flow (OF) techniques facing the complexity of real sequences have been developed in the last years. Even using the most appropriate technique for our specific problem, at some points the output flow might fail to achieve the minimum error required for the system. Confidence measures computed from either input data or OF output should discard those points where OF is not accurate enough for its further use. It follows that evaluating the capabilities of a confidence measure for bounding OF error is as important as the definition
itself. In this paper we analyze different confidence measures and point out their advantages and limitations for their use in real world settings. We also explore the agreement with current tools for their evaluation of confidence measures performance. |
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Lisboa; January 2014 |
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VISAPP |
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IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 |
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no |
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Call Number |
Admin @ si @ MGM2014 |
Serial |
2432 |
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Author |
Patricia Marquez; H. Kause; A. Fuster; Aura Hernandez-Sabate; L. Florack; Debora Gil; Hans van Assen |
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Title |
Factors Affecting Optical Flow Performance in Tagging Magnetic Resonance Imaging |
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Conference Article |
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2014 |
Publication |
17th International Conference on Medical Image Computing and Computer Assisted Intervention |
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8896 |
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231-238 |
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Optical flow; Performance Evaluation; Synthetic Database; ANOVA; Tagging Magnetic Resonance Imaging |
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Changes in cardiac deformation patterns are correlated with cardiac pathologies. Deformation can be extracted from tagging Magnetic Resonance Imaging (tMRI) using Optical Flow (OF) techniques. For applications of OF in a clinical setting it is important to assess to what extent the performance of a particular OF method is stable across di erent clinical acquisition artifacts. This paper presents a statistical validation framework, based on ANOVA, to assess the motion and appearance factors that have the largest in uence on OF accuracy drop.
In order to validate this framework, we created a database of simulated tMRI data including the most common artifacts of MRI and test three di erent OF methods, including HARP. |
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Boston; USA; September 2014 |
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Springer International Publishing |
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0302-9743 |
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978-3-319-14677-5 |
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STACOM |
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IAM; ADAS; 600.060; 601.145; 600.076; 600.075 |
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no |
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Admin @ si @ MKF2014 |
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2495 |
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Author |
Enric Marti; Antoni Gurgui; Debora Gil; Aura Hernandez-Sabate; Jaume Rocarias; Ferran Poveda |
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Title |
ABP on line: Seguimiento, estregas y evaluación en aprendizaje basado en proyectos |
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Miscellaneous |
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2014 |
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8th International Congress on University Teaching and Innovation |
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Tarragona; juliol 2014 |
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CIDUI |
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IAM; ADAS; 600.076; 600.063; 600.075 |
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Admin @ si @ MGG2014 |
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2457 |
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Enric Marti; J.Roncaries; Debora Gil; Aura Hernandez-Sabate; Antoni Gurgui; Ferran Poveda |
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Title |
PBL On Line: A proposal for the organization, part-time monitoring and assessment of PBL group activities |
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2015 |
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Journal of Technology and Science Education |
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JOTSE |
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5 |
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2 |
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87-96 |
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IAM; ADAS; 600.076; 600.075 |
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Admin @ si @ MRG2015 |
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2608 |
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