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Author Oriol Rodriguez-Leon; Josefina Mauri;Eduard Fernandez-Nofrerias; Antonio Tovar; Vicente del Valle; Aura Hernandez-Sabate; Debora Gil; Petia Radeva edit  openurl
  Title Utilización de la Estructura de los Campos Vectoriales para la Detección de la Adventicia en Imágenes de Ecografía Intracoronaria Type Journal Article
  Year 2004 Publication Revista Internacional de Enfermedades Cardiovasculares Revista Española de Cardiología Abbreviated Journal  
  Volume 57 Issue 2 Pages 100  
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  ISSN (up) ISBN Medium  
  Area Expedition Conference SEC  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RMF2004 Serial 1642  
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Author Oriol Rodriguez-Leon; Eduard Fernandez-Nofrerias; Josefina Mauri; Vicente del Valle; Debora Gil; A.Barrios; E.Garcia; Petia Radeva edit  openurl
  Title Perfusion ratio: A new tool to objectively assess microcirculation perfusion after primary Percutaneous Coronary Intervention Type Conference Article
  Year 2006 Publication World Congress of Cardiology Abbreviated Journal  
  Volume Issue Pages 859  
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  Corporate Author Thesis  
  Publisher Place of Publication Barcelona (Spain) Editor  
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  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RFM2006c Serial 1643  
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Author Oriol Rodriguez-Leon; Josefina Mauri; Eduard Fernandez-Nofrerias; Vicente de Valle; E.Garcia; A.Barrios; Debora Gil; Petia Radeva edit  openurl
  Title Analysis of the changes in angiography local grey-level values to determine myocardial perfusion Type Conference Article
  Year 2006 Publication World Congress of Cardiology Abbreviated Journal  
  Volume Issue Pages 862  
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  Publisher Place of Publication Barcelona (Spain) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RMF2006 Serial 1644  
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Author Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil edit   pdf
doi  openurl
  Title Suppression of IVUS Image Rotation. A Kinematic Approach Type Book Chapter
  Year 2005 Publication Functional Imaging and Modeling of the Heart Abbreviated Journal LNCS  
  Volume 3504 Issue Pages 889-892  
  Keywords  
  Abstract 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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  Publisher Springer Berlin / Heidelberg Place of Publication Editor Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume 3504 Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RRR2005 Serial 1645  
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Author Misael Rosales; Petia Radeva;Oriol Rodriguez-Leon; Debora Gil edit   pdf
doi  openurl
  Title Modelling of image-catheter motion for 3-D IVUS Type Journal Article
  Year 2009 Publication Medical image analysis Abbreviated Journal MIA  
  Volume 13 Issue 1 Pages 91-104  
  Keywords Intravascular ultrasound (IVUS); Motion estimation; Motion decomposition; Fourier  
  Abstract 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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  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RRR2009 Serial 1646  
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Author Fernando Vilariño; Debora Gil; Petia Radeva edit   pdf
url  isbn
openurl 
  Title A Novel FLDA Formulation for Numerical Stability Analysis Type Book Chapter
  Year 2004 Publication Recent Advances in Artificial Intelligence Research and Development Abbreviated Journal  
  Volume 113 Issue Pages 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.  
  Address  
  Corporate Author Thesis  
  Publisher IOS Press Place of Publication Editor J. Vitrià, P. Radeva and I. Aguiló  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN 978-1-58603-466-5 Medium  
  Area Expedition Conference  
  Notes MV;IAM;MILAB;SIAI Approved no  
  Call Number IAM @ iam @ VGR2004 Serial 1663  
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Author Aura Hernandez-Sabate; Debora Gil; David Roche; Monica M. S. Matsumoto; Sergio S. Furuie edit   pdf
url  openurl
  Title Inferring the Performance of Medical Imaging Algorithms Type Conference Article
  Year 2011 Publication 14th International Conference on Computer Analysis of Images and Patterns Abbreviated Journal  
  Volume 6854 Issue Pages 520-528  
  Keywords Validation, Statistical Inference, Medical Imaging Algorithms.  
  Abstract 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.
 
  Address Sevilla  
  Corporate Author Thesis  
  Publisher Springer-Verlag Berlin Heidelberg Place of Publication Berlin Editor Pedro Real; Daniel Diaz-Pernil; Helena Molina-Abril; Ainhoa Berciano; Walter Kropatsch  
  Language Summary Language Original Title  
  Series Editor Series Title L Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference CAIP  
  Notes IAM; ADAS Approved no  
  Call Number IAM @ iam @ HGR2011 Serial 1676  
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Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
url  isbn
openurl 
  Title An inference model for analyzing termination conditions of Evolutionary Algorithms Type Conference Article
  Year 2011 Publication 14th Congrès Català en Intel·ligencia Artificial Abbreviated Journal  
  Volume Issue Pages 216-225  
  Keywords Evolutionary Computation Convergence, Termination Conditions, Statistical Inference  
  Abstract 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.
 
  Address Lleida, Catalonia (Spain)  
  Corporate Author Associació Catalana Intel·ligència Artificial Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN (up) ISBN 978-1-60750-841-0 Medium  
  Area Expedition Conference CCIA  
  Notes IAM Approved no  
  Call Number IAM @ iam @ RGG2011a Serial 1677  
Permanent link to this record
 

 
Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
openurl 
  Title Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms Type Conference Article
  Year 2011 Publication 11th European Conference on Artificial Life Abbreviated Journal  
  Volume Issue Pages  
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  Abstract 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.
 
  Address Paris, France  
  Corporate Author Thesis  
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  Series Volume Series Issue Edition  
  ISSN (up) ISBN Medium  
  Area Expedition Conference ECAL  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ RGG2011b Serial 1678  
Permanent link to this record
 

 
Author Ferran Poveda; Debora Gil ;Albert Andaluz ;Enric Marti edit   pdf
url  doi
openurl 
  Title Multiscale Tractography for Representing Heart Muscular Architecture Type Conference Article
  Year 2011 Publication In MICCAI 2011 Workshop on Computational Diffusion MRI Abbreviated Journal  
  Volume Issue Pages  
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  Abstract Deep understanding of myocardial structure of the heart would unravel crucial knowledge for clinical and medical procedures. Although the muscular architecture of the heart has been debated by countless researchers, the controversy is still alive. Diffusion Tensor MRI, DT-MRI, is a unique imaging technique for computational validation of the muscular structure of the heart. By the complex arrangement of myocites, existing techniques can not provide comprehensive descriptions of the global muscular architecture. In this paper we introduce a multiresolution reconstruction technique based on DT-MRI streamlining for simplified global myocardial model generation. Our reconstructions can restore the most complex myocardial structures and indicate a global helical organization  
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  Language English Summary Language english Original Title  
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  ISSN (up) ISBN Medium  
  Area Expedition Conference CDRMI  
  Notes IAM Approved no  
  Call Number IAM @ iam @ PGA2011 Serial 1681  
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