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Author Esmitt Ramirez; Carles Sanchez; Debora Gil edit   pdf
url  doi
openurl 
  Title Localizing Pulmonary Lesions Using Fuzzy Deep Learning Type Conference Article
  Year 2019 Publication 21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages 290-294  
  Keywords  
  Abstract The usage of medical images is part of the clinical daily in several healthcare centers around the world. Particularly, Computer Tomography (CT) images are an important key in the early detection of suspicious lung lesions. The CT image exploration allows the detection of lung lesions before any invasive procedure (e.g. bronchoscopy, biopsy). The effective localization of lesions is performed using different image processing and computer vision techniques. Lately, the usage of deep learning models into medical imaging from detection to prediction shown that is a powerful tool for Computer-aided software. In this paper, we present an approach to localize pulmonary lung lesion using fuzzy deep learning. Our approach uses a simple convolutional neural network based using the LIDC-IDRI dataset. Each image is divided into patches associated a probability vector (fuzzy) according their belonging to anatomical structures on a CT. We showcase our approach as part of a full CAD system to exploration, planning, guiding and detection of pulmonary lesions.  
  Address Timisoara; Rumania; September 2019  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference SYNASC  
  Notes (up) IAM; 600.145; 600.140; 601.337; 601.323 Approved no  
  Call Number Admin @ si @ RSG2019 Serial 3531  
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Author Sergio Vera; Debora Gil; Agnes Borras; Marius George Linguraru; Miguel Angel Gonzalez Ballester edit   pdf
url  doi
openurl 
  Title Geometric Steerable Medial Maps Type Journal Article
  Year 2013 Publication Machine Vision and Applications Abbreviated Journal MVA  
  Volume 24 Issue 6 Pages 1255-1266  
  Keywords Medial Representations ,Medial Manifolds Comparation , Surface , Reconstruction  
  Abstract In order to provide more intuitive and easily interpretable representations of complex shapes/organs, medial manifolds should reach a compromise between simplicity in geometry and capability for restoring the anatomy/shape of the organ/volume. Existing morphological methods show excellent results when applied to 2D objects, but their quality drops across dimensions.
This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoids degenerated medial axis segments. Second, we introduce a continuous operator for accurate and efficient computation of medial structures of arbitrary dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to syn- thetic shapes of known medial geometry. We also show its higher performance for medical imaging applications in terms of simplicity of medial structures and capability for reconstructing the anatomical volume.
 
  Address  
  Corporate Author Thesis  
  Publisher Springer Berlin Heidelberg Place of Publication Editor Mubarak Shah  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0932-8092 ISBN Medium  
  Area Expedition Conference  
  Notes (up) IAM; 605.203; 600.060; 600.044 Approved no  
  Call Number IAM @ iam @ VGB2013 Serial 2192  
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Author Enric Marti; Ferran Poveda; Antoni Gurgui; Jaume Rocarias; Debora Gil; Aura Hernandez-Sabate edit   pdf
openurl 
  Title Una experiencia de estructura, funcionamiento y evaluación de la asignatura de graficos por computador con metodologia de aprendizaje basado en proyectos Type Miscellaneous
  Year 2013 Publication IV Congreso Internacional UNIVEST Abbreviated Journal  
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  Abstract IV Congreso Internacional UNIVEST  
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  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference UNIVEST  
  Notes (up) IAM; ADAS Approved no  
  Call Number Admin @ si @ MPG2013b Serial 2384  
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Author Debora Gil; Aura Hernandez-Sabate; Mireia Brunat;Steven Jansen; Jordi Martinez-Vilalta edit   pdf
doi  openurl
  Title Structure-preserving smoothing of biomedical images Type Journal Article
  Year 2011 Publication Pattern Recognition Abbreviated Journal PR  
  Volume 44 Issue 9 Pages 1842-1851  
  Keywords Non-linear smoothing; Differential geometry; Anatomical structures; segmentation; Cardiac magnetic resonance; Computerized tomography  
  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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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0031-3203 ISBN Medium  
  Area Expedition Conference  
  Notes (up) IAM; ADAS Approved no  
  Call Number IAM @ iam @ GHB2011 Serial 1526  
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Author Enric Marti; Debora Gil; Marc Vivet; Carme Julia edit  openurl
  Title Balance de cuatro años de experiencia en la implantación de la metodología de Aprendizaje Basado en Proyectos en la asignatura de Gráficos por Computador en ingeniería Informática Type Miscellaneous
  Year 2008 Publication VIII Jornadas de Innovación Universitaria Abbreviated Journal  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes (up) IAM; ADAS Approved no  
  Call Number IAM @ iam @ MGV2008b Serial 1599  
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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 ISBN Medium  
  Area Expedition Conference CAIP  
  Notes (up) IAM; ADAS Approved no  
  Call Number IAM @ iam @ HGR2011 Serial 1676  
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Author Patricia Marquez; Debora Gil; Aura Hernandez-Sabate edit   pdf
url  doi
openurl 
  Title A Confidence Measure for Assessing Optical Flow Accuracy in the Absence of Ground Truth Type Conference Article
  Year 2011 Publication IEEE International Conference on Computer Vision – Workshops Abbreviated Journal  
  Volume Issue Pages 2042-2049  
  Keywords IEEE International Conference on Computer Vision – Workshops  
  Abstract 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.  
  Address  
  Corporate Author Thesis  
  Publisher IEEE Place of Publication Barcelona (Spain) Editor  
  Language English Summary Language English Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ICCVW  
  Notes (up) IAM; ADAS Approved no  
  Call Number IAM @ iam @ MGH2011 Serial 1682  
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Author Aura Hernandez-Sabate; Debora Gil edit   pdf
url  doi
isbn  openurl
  Title The Benefits of IVUS Dynamics for Retrieving Stable Models of Arteries Type Book Chapter
  Year 2012 Publication Intravascular Ultrasound Abbreviated Journal  
  Volume Issue Pages 185-206  
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  Abstract  
  Address  
  Corporate Author Thesis  
  Publisher Intech Place of Publication Editor Yasuhiro Honda  
  Language English Summary Language english Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-953-307-900-4 Medium  
  Area Expedition Conference  
  Notes (up) IAM; ADAS Approved no  
  Call Number IAM @ iam @ HeG2012 Serial 1684  
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Author Patricia Marquez; Debora Gil; Aura Hernandez-Sabate edit   pdf
url  doi
openurl 
  Title Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality Type Conference Article
  Year 2013 Publication ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars Abbreviated Journal  
  Volume Issue Pages 624-631  
  Keywords  
  Abstract 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.  
  Address Sydney; Australia; December 2013  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CVTT:E2M  
  Notes (up) IAM; ADAS; 600.044; 600.057; 601.145 Approved no  
  Call Number Admin @ si @ MGH2013b Serial 2351  
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Author Patricia Marquez; Debora Gil; R.Mester; Aura Hernandez-Sabate edit   pdf
openurl 
  Title Local Analysis of Confidence Measures for Optical Flow Quality Evaluation Type Conference Article
  Year 2014 Publication 9th International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 3 Issue Pages 450-457  
  Keywords Optical Flow; Confidence Measure; Performance Evaluation.  
  Abstract 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.
 
  Address Lisboa; January 2014  
  Corporate Author Thesis  
  Publisher Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference VISAPP  
  Notes (up) IAM; ADAS; 600.044; 600.060; 600.057; 601.145; 600.076; 600.075 Approved no  
  Call Number Admin @ si @ MGM2014 Serial 2432  
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