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Author Aura Hernandez-Sabate; Debora Gil;Eduard Fernandez-Nofrerias;Petia Radeva; Enric Marti edit   pdf
doi  openurl
  Title Approaching Artery Rigid Dynamics in IVUS Type Journal Article
  Year 2009 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI  
  Volume 28 Issue 11 Pages 1670-1680  
  Keywords (down) Fourier analysis; intravascular ultrasound (IVUS) dynamics; longitudinal motion; quality measures; tissue deformation.  
  Abstract Tissue biomechanical properties (like strain and stress) are playing an increasing role in diagnosis and long-term treatment of intravascular coronary diseases. Their assessment strongly relies on estimation of vessel wall deformation. Since intravascular ultrasound (IVUS) sequences allow visualizing vessel morphology and reflect its dynamics, this technique represents a useful tool for evaluation of tissue mechanical properties. Image misalignment introduced by vessel-catheter motion is a major artifact for a proper tracking of tissue deformation. In this work, we focus on compensating and assessing IVUS rigid in-plane motion due to heart beating. Motion parameters are computed by considering both the vessel geometry and its appearance in the image. Continuum mechanics laws serve to introduce a novel score measuring motion reduction in in vivo sequences. Synthetic experiments validate the proposed score as measure of motion parameters accuracy; whereas results in in vivo pullbacks show the reliability of the presented methodologies in clinical cases.  
  Address  
  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 0278-0062 ISBN Medium  
  Area Expedition Conference  
  Notes IAM; MILAB Approved no  
  Call Number IAM @ iam @ HGF2009 Serial 1545  
Permanent link to this record
 

 
Author Antoni Gurgui; Debora Gil; Enric Marti edit  url
doi  isbn
openurl 
  Title Laplacian Unitary Domain for Texture Morphing Type Conference Article
  Year 2015 Publication Proceedings of the 10th International Conference on Computer Vision Theory and Applications VISIGRAPP2015 Abbreviated Journal  
  Volume 1 Issue Pages 693-699  
  Keywords (down) Facial; metamorphosis;LaplacianMorphing  
  Abstract Deformation of expressive textures is the gateway to realistic computer synthesis of expressions. By their good mathematical properties and flexible formulation on irregular meshes, most texture mappings rely on solutions to the Laplacian in the cartesian space. In the context of facial expression morphing, this approximation can be seen from the opposite point of view by neglecting the metric. In this paper, we use the properties of the Laplacian in manifolds to present a novel approach to warping expressive facial images in order to generate a morphing between them.  
  Address Munich; Germany; February 2015  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-758-089-5 Medium  
  Area Expedition Conference VISAPP  
  Notes IAM; 600.075 Approved no  
  Call Number Admin @ si @ GGM2015 Serial 2614  
Permanent link to this record
 

 
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 (down) 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 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 Debora Gil; David Roche; Agnes Borras; Jesus Giraldo edit  doi
openurl 
  Title Terminating Evolutionary Algorithms at their Steady State Type Journal Article
  Year 2015 Publication Computational Optimization and Applications Abbreviated Journal COA  
  Volume 61 Issue 2 Pages 489-515  
  Keywords (down) Evolutionary algorithms; Termination condition; Steady state; Differential evolution  
  Abstract Assessing the reliability of termination conditions for evolutionary algorithms (EAs) is of prime importance. An erroneous or weak stop criterion can negatively affect both the computational effort and the final result. We introduce a statistical framework for assessing whether a termination condition is able to stop an EA at its steady state, so that its results can not be improved anymore. We use a regression model in order to determine the requirements ensuring that a measure derived from EA evolving population is related to the distance to the optimum in decision variable space. Our framework is analyzed across 24 benchmark test functions and two standard termination criteria based on function fitness value in objective function space and EA population decision variable space distribution for the differential evolution (DE) paradigm. Results validate our framework as a powerful tool for determining the capability of a measure for terminating EA and the results also identify the decision variable space distribution as the best-suited for accurately terminating DE in real-world applications.  
  Address  
  Corporate Author Thesis  
  Publisher Springer US Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN 0926-6003 ISBN Medium  
  Area Expedition Conference  
  Notes IAM; 600.044; 605.203; 600.060; 600.075 Approved no  
  Call Number Admin @ si @ GRB2015 Serial 2560  
Permanent link to this record
 

 
Author Jose Elias Yauri; M. Lagos; H. Vega-Huerta; P. de-la-Cruz; G.L.E Maquen-Niño; E. Condor-Tinoco edit  doi
openurl 
  Title Detection of Epileptic Seizures Based-on Channel Fusion and Transformer Network in EEG Recordings Type Journal Article
  Year 2023 Publication International Journal of Advanced Computer Science and Applications Abbreviated Journal IJACSA  
  Volume 14 Issue 5 Pages 1067-1074  
  Keywords (down) Epilepsy; epilepsy detection; EEG; EEG channel fusion; convolutional neural network; self-attention  
  Abstract According to the World Health Organization, epilepsy affects more than 50 million people in the world, and specifically, 80% of them live in developing countries. Therefore, epilepsy has become among the major public issue for many governments and deserves to be engaged. Epilepsy is characterized by uncontrollable seizures in the subject due to a sudden abnormal functionality of the brain. Recurrence of epilepsy attacks change people’s lives and interferes with their daily activities. Although epilepsy has no cure, it could be mitigated with an appropriated diagnosis and medication. Usually, epilepsy diagnosis is based on the analysis of an electroencephalogram (EEG) of the patient. However, the process of searching for seizure patterns in a multichannel EEG recording is a visual demanding and time consuming task, even for experienced neurologists. Despite the recent progress in automatic recognition of epilepsy, the multichannel nature of EEG recordings still challenges current methods. In this work, a new method to detect epilepsy in multichannel EEG recordings is proposed. First, the method uses convolutions to perform channel fusion, and next, a self-attention network extracts temporal features to classify between interictal and ictal epilepsy states. The method was validated in the public CHB-MIT dataset using the k-fold cross-validation and achieved 99.74% of specificity and 99.15% of sensitivity, surpassing current approaches.  
  Address  
  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  
  Notes IAM Approved no  
  Call Number Admin @ si @ Serial 3856  
Permanent link to this record
 

 
Author Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva edit   pdf
openurl 
  Title A Deterministic-Statistic Adventitia Detection in IVUS Images Type Conference Article
  Year 2005 Publication ESC Congress Abbreviated Journal  
  Volume Issue Pages  
  Keywords (down) Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation  
  Abstract Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.  
  Address Stockholm; Sweden; September 2005  
  Corporate Author Thesis  
  Publisher Place of Publication ,Sweden (EU) Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ESC  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RMF2005a Serial 1523  
Permanent link to this record
 

 
Author Debora Gil; Aura Hernandez-Sabate; Antoni Carol; Oriol Rodriguez; Petia Radeva edit   pdf
doi  openurl
  Title A Deterministic-Statistic Adventitia Detection in IVUS Images Type Conference Article
  Year 2005 Publication 3rd International workshop on International Workshop on Functional Imaging and Modeling of the Heart Abbreviated Journal  
  Volume Issue Pages 65-74  
  Keywords (down) Electron microscopy; Unbending; 2D crystal; Interpolation; Approximation  
  Abstract Plaque analysis in IVUS planes needs accurate intima and adventitia models. Large variety in adventitia descriptors difficulties its detection and motivates using a classification strategy for selecting points on the structure. Whatever the set of descriptors used, the selection stage suffers from fake responses due to noise and uncompleted true curves. In order to smooth background noise while strengthening responses, we apply a restricted anisotropic filter that homogenizes grey levels along the image significant structures. Candidate points are extracted by means of a simple semi supervised adaptive classification of the filtered image response to edge and calcium detectors. The final model is obtained by interpolating the former line segments with an anisotropic contour closing technique based on functional extension principles.  
  Address Barcelona; June 2005  
  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 FIMH  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ RMF2005 Serial 1524  
Permanent link to this record
 

 
Author Debora Gil; Jose Maria-Carazo; Roberto Marabini edit   pdf
doi  openurl
  Title On the nature of 2D crystal unbending Type Journal Article
  Year 2006 Publication Journal of Structural Biology Abbreviated Journal  
  Volume 156 Issue 3 Pages 546-555  
  Keywords (down) Electron microscopy  
  Abstract Crystal unbending, the process that aims to recover a perfect crystal from experimental data, is one of the more important steps in electron crystallography image processing. The unbending process involves three steps: estimation of the unit cell displacements from their ideal positions, extension of the deformation field to the whole image and transformation of the image in order to recover an ideal crystal. In this work, we present a systematic analysis of the second step oriented to address two issues. First, whether the unit cells remain undistorted and only the distance between them should be changed (rigid case) or should be modified with the same deformation suffered by the whole crystal (elastic case). Second, the performance of different extension algorithms (interpolation versus approximation) is explored. Our experiments show that there is no difference between elastic and rigid cases or among the extension algorithms. This implies that the deformation fields are constant over large areas. Furthermore, our results indicate that the main source of error is the transformation of the crystal image.  
  Address  
  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 1047-8477 ISBN Medium  
  Area Expedition Conference  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ GCM2006 Serial 1519  
Permanent link to this record
 

 
Author Sonia Baeza; Debora Gil; Ignasi Garcia Olive; Maite Salcedo Pujantell; Jordi Deportos; Carles Sanchez; Guillermo Torres; Gloria Moragas; Antoni Rosell edit  url
doi  openurl
  Title Correction: A novel intelligent radiomic analysis of perfusion SPECT/CT images to optimize pulmonary embolism diagnosis in COVID-19 patients Type Journal Article
  Year 2023 Publication European Journal of Nuclear Medicine and Molecular Imaging Abbreviated Journal EJNMMI PHYSICS  
  Volume 10 Issue 1 Pages 13  
  Keywords (down) early diagnosis; Lung Cancer; nodule diagnosis; nodule diagnosis; Radiomics; Screening  
  Abstract This study shows the generation process and the subsequent study of the representation space obtained by extracting GLCM texture features from computer-aided tomography (CT) scans of pulmonary nodules (PN). For this, data from 92 patients from the Germans Trias i Pujol University Hospital were used. The workflow focuses on feature extraction using Pyradiomics and the VGG16 Convolutional Neural Network (CNN). The aim of the study is to assess whether the data obtained have a positive impact on the diagnosis of lung cancer (LC). To design a machine learning (ML) model training method that allows generalization, we train SVM and neural network (NN) models, evaluating diagnosis performance using metrics defined at slice and nodule level.  
  Address  
  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  
  Notes IAM Approved no  
  Call Number BGG2023 Serial 3858  
Permanent link to this record
 

 
Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
doi  isbn
openurl 
  Title Detecting loss of diversity for an efficient termination of EAs Type Conference Article
  Year 2013 Publication 15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages 561 - 566  
  Keywords (down) EA termination; EA population diversity; EA steady state  
  Abstract Termination of Evolutionary Algorithms (EA) at its steady state so that useless iterations are not performed is a main point for its efficient application to black-box problems. Many EA algorithms evolve while there is still diversity in their population and, thus, they could be terminated by analyzing the behavior some measures of EA population diversity. This paper presents a numeric approximation to steady states that can be used to detect the moment EA population has lost its diversity for EA termination. Our condition has been applied to 3 EA paradigms based on diversity and a selection of functions
covering the properties most relevant for EA convergence.
Experiments show that our condition works regardless of the search space dimension and function landscape.
 
  Address Timisoara; Rumania;  
  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 978-1-4799-3035-7 Medium  
  Area Expedition Conference SYNASC  
  Notes IAM; 600.044; 600.060; 605.203 Approved no  
  Call Number Admin @ si @ RGG2013c Serial 2299  
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