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Author Debora Gil; Guillermo Torres; Carles Sanchez edit  openurl
  Title Transforming radiomic features into radiological words Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Pòster  
  Address Cartagena de Indias; Colombia; April 2023  
  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 ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ GTS2023 Serial 3952  
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Author Pau Cano; Debora Gil; Eva Musulen edit  openurl
  Title Towards automatic detection of helicobacter pylori in histological samples of gastric tissue Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Cartagena de Indias; Colombia; April 2023  
  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 ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ CGM2023 Serial 3953  
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Author Guillermo Torres; Debora Gil; Antonio Rosell; Sonia Baeza; Carles Sanchez edit  openurl
  Title A radiomic biopsy for virtual histology of pulmonary nodules Type Conference Article
  Year 2023 Publication IEEE International Symposium on Biomedical Imaging Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Pòster  
  Address Cartagena de Indias; Colombia; April 2023  
  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 ISBI  
  Notes IAM Approved no  
  Call Number Admin @ si @ TGR2023b Serial 3954  
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Author Jose Elias Yauri edit  openurl
  Title Deep Learning Based Data Fusion Approaches for the Assessment of Cognitive States on EEG Signals Type Book Whole
  Year 2023 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract For millennia, the study of the couple brain-mind has fascinated the humanity in order to understand the complex nature of cognitive states. A cognitive state is the state of the mind at a specific time and involves cognition activities to acquire and process information for making a decision, solving a problem, or achieving a goal.
While normal cognitive states assist in the successful accomplishment of tasks; on the contrary, abnormal states of the mind can lead to task failures due to a reduced cognition capability. In this thesis, we focus on the assessment of cognitive states by means of the analysis of ElectroEncephaloGrams (EEG) signals using deep learning methods. EEG records the electrical activity of the brain using a set of electrodes placed on the scalp that output a set of spatiotemporal signals that are expected to be correlated to a specific mental process.
From the point of view of artificial intelligence, any method for the assessment of cognitive states using EEG signals as input should face several challenges. On the one hand, one should determine which is the most suitable approach for the optimal combination of the multiple signals recorded by EEG electrodes. On the other hand, one should have a protocol for the collection of good quality unambiguous annotated data, and an experimental design for the assessment of the generalization and transfer of models. In order to tackle them, first, we propose several convolutional neural architectures to perform data fusion of the signals recorded by EEG electrodes, at raw signal and feature levels. Four channel fusion methods, easy to incorporate into any neural network architecture, are proposed and assessed. Second, we present a method to create an unambiguous dataset for the prediction of cognitive mental workload using serious games and an Airbus-320 flight simulator. Third, we present a validation protocol that takes into account the levels of generalization of models based on the source and amount of test data.
Finally, the approaches for the assessment of cognitive states are applied to two use cases of high social impact: the assessment of mental workload for personalized support systems in the cockpit and the detection of epileptic seizures. The results obtained from the first use case show the feasibility of task transfer of models trained to detect workload in serious games to real flight scenarios. The results from the second use case show the generalization capability of our EEG channel fusion methods at k-fold cross-validation, patient-specific, and population levels.
 
  Address  
  Corporate Author Thesis Ph.D. thesis  
  Publisher IMPRIMA Place of Publication Editor Aura Hernandez;Debora Gil  
  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 @ Yau2023 Serial 3962  
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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 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  
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Author Eric Amiel edit   pdf
url  openurl
  Title Visualisation de vaisseaux sanguins Type Report
  Year 2005 Publication Rapport de Stage Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address  
  Corporate Author Université Paul Sabatier Toulouse III Thesis Bachelor's thesis  
  Publisher Université Paul Sabatier Toulouse III Place of Publication Toulouse Editor Enric Marti  
  Language French Summary Language French Original Title  
  Series Editor IUP Systèmes Intelligents Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ Ami2005 Serial 1690  
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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 ISBN 978-1-60750-841-0 Medium  
  Area Expedition Conference CCIA  
  Notes IAM Approved no  
  Call Number IAM @ iam @ RGG2011a Serial 1677  
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Author Debora Gil; Petia Radeva edit   pdf
url  doi
isbn  openurl
  Title Curvature Vector Flow to Assure Convergent Deformable Models for Shape Modelling Type Book Chapter
  Year 2003 Publication Energy Minimization Methods In Computer Vision And Pattern Recognition Abbreviated Journal LNCS  
  Volume 2683 Issue Pages 357-372  
  Keywords Initial condition; Convex shape; Non convex analysis; Increase; Segmentation; Gradient; Standard; Standards; Concave shape; Flow models; Tracking; Edge detection; Curvature  
  Abstract Poor convergence to concave shapes is a main limitation of snakes as a standard segmentation and shape modelling technique. The gradient of the external energy of the snake represents a force that pushes the snake into concave regions, as its internal energy increases when new inexion points are created. In spite of the improvement of the external energy by the gradient vector ow technique, highly non convex shapes can not be obtained, yet. In the present paper, we develop a new external energy based on the geometry of the curve to be modelled. By tracking back the deformation of a curve that evolves by minimum curvature ow, we construct a distance map that encapsulates the natural way of adapting to non convex shapes. The gradient of this map, which we call curvature vector ow (CVF), is capable of attracting a snake towards any contour, whatever its geometry. Our experiments show that, any initial snake condition converges to the curve to be modelled in optimal time.  
  Address  
  Corporate Author Thesis  
  Publisher Springer, Berlin Place of Publication Lisbon, PORTUGAL Editor Springer, B.  
  Language Summary Language Original Title  
  Series Editor Series Title Lecture Notes in Computer Science Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 3-540-40498-8 Medium  
  Area Expedition Conference  
  Notes IAM;MILAB Approved no  
  Call Number IAM @ iam @ GIR2003b Serial 1535  
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Author Debora Gil; Petia Radeva; Jordi Saludes; Josefina Mauri edit   pdf
url  openurl
  Title Automatic Segmentation of Artery Wall in Coronary IVUS Images: A Probabilistic Approach Type Conference Article
  Year 2000 Publication International Conference on Pattern Recognition Abbreviated Journal  
  Volume 4 Issue Pages 352-355  
  Keywords  
  Abstract Intravascular ultrasound images represent a unique tool to analyze the morphology of arteries and vessels (plaques, restenosis, etc). The poor quality of these images makes unsupervised segmentation based on traditional segmentation algorithms (such as edge or ridge/valley detection) fail to achieve the expected results. In this paper we present a probabilistic flexible template to separate different regions in the image. In particular, we use elliptic templates to model and detect the shape of the vessel inner wall in IVUS images. We present the results of successful segmentation obtained from patients undergoing stent treatment. A physician team has validated these results.  
  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;MILAB Approved no  
  Call Number IAM @ iam @ GRS2000a Serial 1537  
Permanent link to this record
 

 
Author Petia Radeva; A.Amini; J.Huang; Enric Marti edit   pdf
url  doi
isbn  openurl
  Title Deformable B-Solids and Implicit Snakes for Localization and Tracking of SPAMM MRI-Data Type Conference Article
  Year 1996 Publication Workshop on Mathematical Methods in Biomedical Image Analysis Abbreviated Journal  
  Volume Issue Pages 192-201  
  Keywords  
  Abstract To date, MRI-SPAMM data from different image slices have been analyzed independently. In this paper, we propose an approach for 3D tag localization and tracking of SPAMM data by a novel deformable B-solid. The solid is defined in terms of a 3D tensor product B-spline. The isoparametric curves of the B-spline solid have special importance. These are termed implicit snakes as they deform under image forces from tag lines in different image slices. The localization and tracking of tag lines is performed under constraints of continuity and smoothness of the B-solid. The framework unifies the problems of localization, and displacement fitting and interpolation into the same procedure utilizing B-spline bases for interpolation. To track motion from boundaries and restrict image forces to the myocardium, a volumetric model is employed as a pair of coupled endocardial and epicardial B-spline surfaces. To recover deformations in the LV an energy-minimization problem is posed where both tag and ...  
  Address San Francisco CA  
  Corporate Author Thesis  
  Publisher IEEE Computer Society Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 0-8186-7368-0 Medium  
  Area Expedition Conference MMBIA ’96  
  Notes MILAB;IAM; Approved no  
  Call Number IAM @ iam @ RAH1996 Serial 1630  
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