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Author |
Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; C. Garcia; R. Villuendas; Vicente del Valle; Debora Gil; Petia Radeva |
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Reconstruction of a spatio-temporal model of the intima layer from intravascular ultrasound sequences |
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Journal Article |
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2003 |
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European Heart Journal |
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IAM;MILAB |
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IAM @ iam @ RMF2003c |
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1641 |
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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 |
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Title |
Utilización de la Estructura de los Campos Vectoriales para la Detección de la Adventicia en Imágenes de Ecografía Intracoronaria |
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Journal Article |
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Year |
2004 |
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Revista Internacional de Enfermedades Cardiovasculares Revista Española de Cardiología |
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57 |
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2 |
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100 |
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IAM;MILAB |
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IAM @ iam @ RMF2004 |
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1642 |
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Oriol Rodriguez-Leor; Eduard Fernandez-Nofrerias; J. Mauri; Vicente del Valle; Debora Gil; A.Barrios; E.Garcia; Petia Radeva |
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Title |
Perfusion ratio: A new tool to objectively assess microcirculation perfusion after primary Percutaneous Coronary Intervention |
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Conference Article |
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2006 |
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World Congress of Cardiology |
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859 |
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Barcelona (Spain) |
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IAM;MILAB |
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IAM @ iam @ RFM2006c |
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1643 |
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Oriol Rodriguez-Leor; J. Mauri; Eduard Fernandez-Nofrerias; Vicente de Valle; E. Garcia; A. Barrios; Debora Gil; Petia Radeva |
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Title |
Analysis of the changes in angiography local grey-level values to determine myocardial perfusion |
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Conference Article |
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2006 |
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World Congress of Cardiology |
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862 |
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Barcelona (Spain) |
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IAM;MILAB |
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IAM @ iam @ RMF2006 |
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1644 |
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Author |
Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil |
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Title |
Suppression of IVUS Image Rotation. A Kinematic Approach |
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Book Chapter |
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Year |
2005 |
Publication |
Functional Imaging and Modeling of the Heart |
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LNCS |
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3504 |
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889-892 |
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IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology. |
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Springer Berlin / Heidelberg |
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Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica |
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Lecture Notes in Computer Science |
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LNCS |
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3504 |
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IAM;MILAB |
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IAM @ iam @ RRR2005 |
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1645 |
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Author |
Misael Rosales; Petia Radeva; Oriol Rodriguez-Leor; Debora Gil |
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Title |
Modelling of image-catheter motion for 3-D IVUS |
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Journal Article |
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Year |
2009 |
Publication |
Medical image analysis |
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MIA |
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13 |
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1 |
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91-104 |
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Intravascular ultrasound (IVUS); Motion estimation; Motion decomposition; Fourier |
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Three-dimensional intravascular ultrasound (IVUS) allows to visualize and obtain volumetric measurements of coronary lesions through an exploration of the cross sections and longitudinal views of arteries. However, the visualization and subsequent morpho-geometric measurements in IVUS longitudinal cuts are subject to distortion caused by periodic image/vessel motion around the IVUS catheter. Usually, to overcome the image motion artifact ECG-gating and image-gated approaches are proposed, leading to slowing the pullback acquisition or disregarding part of IVUS data. In this paper, we argue that the image motion is due to 3-D vessel geometry as well as cardiac dynamics, and propose a dynamic model based on the tracking of an elliptical vessel approximation to recover the rigid transformation and align IVUS images without loosing any IVUS data. We report an extensive validation with synthetic simulated data and in vivo IVUS sequences of 30 patients achieving an average reduction of the image artifact of 97% in synthetic data and 79% in real-data. Our study shows that IVUS alignment improves longitudinal analysis of the IVUS data and is a necessary step towards accurate reconstruction and volumetric measurements of 3-D IVUS. |
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IAM;MILAB |
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IAM @ iam @ RRR2009 |
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1646 |
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Author |
Fernando Vilariño; Debora Gil; Petia Radeva |
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Title |
A Novel FLDA Formulation for Numerical Stability Analysis |
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Book Chapter |
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Year |
2004 |
Publication |
Recent Advances in Artificial Intelligence Research and Development |
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113 |
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77-84 |
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Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision |
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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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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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Keywords |
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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IAM @ iam @ HGR2011 |
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1676 |
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David Roche; Debora Gil; Jesus Giraldo |
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Title |
An inference model for analyzing termination conditions of Evolutionary Algorithms |
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Conference Article |
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2011 |
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14th Congrès Català en Intel·ligencia Artificial |
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216-225 |
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Evolutionary Computation Convergence, Termination Conditions, Statistical Inference |
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In real-world problems, it is mandatory to design a termination condition for Evolutionary Algorithms (EAs) ensuring stabilization close to the unknown optimum. Distribution-based quantities are good candidates as far as suitable parameters are used. A main limitation for application to real-world problems is that such parameters strongly depend on the topology of the objective function, as well as, the EA paradigm used.
We claim that the termination problem would be fully solved if we had a model measuring to what extent a distribution-based quantity asymptotically behaves like the solution accuracy. We present a regression-prediction model that relates any two given quantities and reports if they can be statistically swapped as termination conditions. Our framework is applied to two issues. First, exploring if the parameters involved in the computation of distribution-based quantities influence their asymptotic behavior. Second, to what extent existing distribution-based quantities can be asymptotically exchanged for the accuracy of the EA solution. |
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Lleida, Catalonia (Spain) |
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Associació Catalana Intel·ligència Artificial |
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978-1-60750-841-0 |
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CCIA |
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IAM |
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IAM @ iam @ RGG2011a |
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1677 |
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Author |
David Roche; Debora Gil; Jesus Giraldo |
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Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms |
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Conference Article |
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2011 |
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11th European Conference on Artificial Life |
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A main challenge in Evolutionary Algorithms (EAs) is determining a termination condition ensuring stabilization close to the optimum in real-world applications. Although for known test functions distribution-based quantities are good candidates (as far as suitable parameters are used), in real-world problems an open question still remains unsolved. How can we estimate an upper-bound for the termination condition value ensuring a given accuracy for the (unknown) EA solution?
We claim that the termination problem would be fully solved if we defined a quantity (depending only on the EA output) behaving like the solution accuracy. The open question would be, then, satisfactorily answered if we had a model relating both quantities, since accuracy could be predicted from the alternative quantity. We present a statistical inference framework addressing two topics: checking the correlation between the two quantities and defining a regression model for predicting (at a given confidence level) accuracy values from the EA output. |
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Paris, France |
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ECAL |
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IAM; |
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IAM @ iam @ RGG2011b |
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1678 |
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