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Author Amir A.Amini; Yasheng Chen; Mohamed Elayyadi; Petia Radeva
Title Tag Surface Reconstruction and Tracking of Myocardial Beads from SPAMM-MRI with Parametric B-Spline Surfaces Type Journal
Year 2001 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI
Volume 20 Issue 2 Pages 94–103
Keywords B-spline surfaces, cardiac motion, myocardial beads, myocardial infarction, tagged MRI.
Abstract Magnetic resonance imaging (MRI) is unique in its ability to noninvasively and selectively alter tissue magnetization, and create tag planes intersecting image slices. The resulting grid of signal voids allows for tracking deformations of tissues in otherwise homogeneous-signal myocardial regions. In this paper, we propose a specific spatial modulation of magnetization (SPAMM) imaging protocol together with efficient techniques for measurement of three-dimensional (3-D) motion of material points of the human heart (referred to as myocardial beads) from images collected with the SPAMM method. The techniques make use of tagged images in orthogonal views by explicitly reconstructing 3-D B-spline surface representation of tag planes (tag planes in two orthogonal orientations intersecting the short-axis (SA) image slices and tag planes in an orientation orthogonal to the short-axis tag planes intersecting long-axis (LA) image slices). The developed methods allow for viewing deformations of 3-D tag surfaces, spatial correspondence of long-axis and short-axis image slice and tag positions, as well as nonrigid movement of myocardial beads as a function of time.
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Notes MILAB Approved no
Call Number (up) BCNPCL @ bcnpcl @ ACE2001; IAM @ iam @ ACE2001 Serial 180
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Author P. Andreeva; Maya Dimitrova; Petia Radeva
Title Data Mining Learning Models and Algorithms for Medical Applications Type Book Chapter
Year 2004 Publication 18 Conference Systems for Automation of Engineering and Research (SEAR 2004) Abbreviated Journal
Volume Issue Pages
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Abstract
Address Varna (Bulgaria)
Corporate Author Thesis
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Notes MILAB Approved no
Call Number (up) BCNPCL @ bcnpcl @ ADR2004 Serial 474
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Author Xavier Baro
Title Fast traffic sign detection on gray-scale images Type Report
Year 2005 Publication CVC Technical Report #82 Abbreviated Journal
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Address CVC (UAB)
Corporate Author Thesis
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Area Expedition Conference
Notes OR;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ Bar2005 Serial 550
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Author Xavier Baro
Title Probabilistic Darwin Machines: A New Approach to Develop Evolutionary Object Detection Type Book Whole
Year 2009 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal
Volume Issue Pages
Keywords
Abstract Ever since computers were invented, we have wondered whether they might perform some of the human quotidian tasks. One of the most studied and still nowadays less understood problem is the capacity to learn from our experiences and how we generalize the knowledge that we acquire. One of that unaware tasks for the persons and that more interest is awakening in different scientific areas since the beginning, is the one that is known as pattern recognition. The creation of models that represent the world that surrounds us, help us for recognizing objects in our environment, to predict situations, to identify behaviors... All this information allows us to adapt ourselves and to interact with our environment. The capacity of adaptation of individuals to their environment has been related to the amount of patterns that are capable of identifying.

This thesis faces the pattern recognition problem from a Computer Vision point of view, taking one of the most paradigmatic and extended approaches to object detection as starting point. After studying this approach, two weak points are identified: The first makes reference to the description of the objects, and the second is a limitation of the learning algorithm, which hampers the utilization of best descriptors.

In order to address the learning limitations, we introduce evolutionary computation techniques to the classical object detection approach.

After testing the classical evolutionary approaches, such as genetic algorithms, we develop a new learning algorithm based on Probabilistic Darwin Machines, which better adapts to the learning problem. Once the learning limitation is avoided, we introduce a new feature set, which maintains the benefits of the classical feature set, adding the ability to describe non localities. This combination of evolutionary learning algorithm and features is tested on different public data sets, outperforming the results obtained by the classical approach.
Address Barcelona (Spain)
Corporate Author Thesis Ph.D. thesis
Publisher Ediciones Graficas Rey Place of Publication Editor Jordi Vitria
Language Summary Language Original Title
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Notes OR;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ Bar2009 Serial 1262
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Author Xavier Baro; Jordi Vitria
Title Feature Selection with Non-Parametric Mutual Information for Adaboost Learning Type Miscellaneous
Year 2005 Publication Abbreviated Journal
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Notes OR;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ BaV2005a Serial 582
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Author Xavier Baro; Jordi Vitria
Title Feature Selection with Non-Parametric Mutual Information for Adaboost Learning Type Book Chapter
Year 2005 Publication Frontiers in Artificial Intelligence and Applications / Artificial intelligence Research and Development, 131:131–138, Eds: B. Lopez, J. Melendez, P. Radeva, J. Vitria, IOS Press, ISBN: 1–58603–560–6 Abbreviated Journal
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Notes OR;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ BaV2005b Serial 583
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Author Xavier Baro; Jordi Vitria
Title Evolutionary Object Detection by Means of Naive Bayes Models Estimation Type Book Chapter
Year 2008 Publication Applications of Evolutionary Computing. EvoWorkshops Abbreviated Journal
Volume 4974 Issue Pages 235–244
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Abstract
Address Naples (Italy)
Corporate Author Thesis
Publisher Place of Publication Editor M. Giacobini
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ BaV2008a Serial 976
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Author Xavier Baro; Jordi Vitria
Title Weighted Dissociated Diploes: An Extended Visual Feature Set Type Book Chapter
Year 2008 Publication Computer Vision Systems. 6th International Conference ICVS Abbreviated Journal
Volume 5008 Issue Pages 281–290
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Abstract
Address Santorini (Greece)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title LNCS
Series Volume Series Issue Edition
ISSN ISBN Medium
Area Expedition Conference
Notes OR;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ BaV2008b Serial 977
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Author Simone Balocco; O. Basset; G. Courbebaisse; E. Boni; Alejandro F. Frangi; P. Tortoli; C. Cachard
Title Estimation Of Viscoelastic Properties Of Vessel Walls Using a Computational Model and Doppler Ultrasound Type Journal Article
Year 2010 Publication Physics in Medicine and Biology Abbreviated Journal PMB
Volume 55 Issue 12 Pages 3557–3575
Keywords
Abstract Human arteries affected by atherosclerosis are characterized by altered wall viscoelastic properties. The possibility of noninvasively assessing arterial viscoelasticity in vivo would significantly contribute to the early diagnosis and prevention of this disease. This paper presents a noniterative technique to estimate the viscoelastic parameters of a vascular wall Zener model. The approach requires the simultaneous measurement of flow variations and wall displacements, which can be provided by suitable ultrasound Doppler instruments. Viscoelastic parameters are estimated by fitting the theoretical constitutive equations to the experimental measurements using an ARMA parameter approach. The accuracy and sensitivity of the proposed method are tested using reference data generated by numerical simulations of arterial pulsation in which the physiological conditions and the viscoelastic parameters of the model can be suitably varied. The estimated values quantitatively agree with the reference values, showing that the only parameter affected by changing the physiological conditions is viscosity, whose relative error was about 27% even when a poor signal-to-noise ratio is simulated. Finally, the feasibility of the method is illustrated through three measurements made at different flow regimes on a cylindrical vessel phantom, yielding a parameter mean estimation error of 25%.
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Notes MILAB Approved no
Call Number (up) BCNPCL @ bcnpcl @ BBC2010 Serial 1312
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Author Miguel Angel Bautista; Xavier Baro; Oriol Pujol; Petia Radeva; Jordi Vitria; Sergio Escalera
Title Compact Evolutive Design of Error-Correcting Output Codes Type Conference Article
Year 2010 Publication Supervised and Unsupervised Ensemble Methods and their Applications in the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases Abbreviated Journal
Volume Issue Pages 119-128
Keywords Ensemble of Dichotomizers; Error-Correcting Output Codes; Evolutionary optimization
Abstract The classi cation of large number of object categories is a challenging trend in the Machine Learning eld. In literature, this is often addressed using an ensemble of classi ers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classi ers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classi ers, making the discrimination of a large number of classes unfeasible. In this paper, we explore and propose a minimal design of ECOC in terms of the number of classi ers. Evolutionary computation is used for tuning the parameters of the classi ers and looking for the best Minimal ECOC code con guration. The results over several public UCI data sets and a challenging multi-class Computer Vision problem show that the proposed methodology obtains comparable and even better results than state-of-the-art ECOC methodologies with far less number of dichotomizers.
Address Barcelona (Spain)
Corporate Author Thesis
Publisher Place of Publication Editor
Language Summary Language Original Title
Series Editor Series Title Abbreviated Series Title
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ISSN ISBN Medium
Area Expedition Conference SUEMA
Notes OR;MILAB;HUPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ BBP2010 Serial 1363
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Author Joel Barajas; Karla Lizbeth Caballero; Petia Radeva
Title Cardiac Phase Extraction in IVUS Sequences Using 1-D Gabor Filters Type Conference Article
Year 2007 Publication Engineering in Medicine and Biology Society, 29th Annual International Conference of the IEEE Abbreviated Journal
Volume Issue Pages 343–36
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Abstract
Address Lyon (France)
Corporate Author Thesis
Publisher Place of Publication Editor
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Notes MILAB Approved no
Call Number (up) BCNPCL @ bcnpcl @ BCR2007 Serial 924
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Author Simone Balocco; O. Camara; E. Vivas; T. Sola; L. Guimaraens; H. A. van Andel; C. B. Majoie; J. M. Pozo; B. H. Bijnens; Alejandro F. Frangi
Title Feasibility of Estimating Regional Mechanical Properties of Cerebral Aneurysms In Vivo Type Journal Article
Year 2010 Publication Medical Physics Abbreviated Journal MEDPHYS
Volume 37 Issue 4 Pages 1689–1706
Keywords
Abstract PURPOSE:
In this article, the authors studied the feasibility of estimating regional mechanical properties in cerebral aneurysms, integrating information extracted from imaging and physiological data with generic computational models of the arterial wall behavior.
METHODS:
A data assimilation framework was developed to incorporate patient-specific geometries into a given biomechanical model, whereas wall motion estimates were obtained from applying registration techniques to a pair of simulated MR images and guided the mechanical parameter estimation. A simple incompressible linear and isotropic Hookean model coupled with computational fluid-dynamics was employed as a first approximation for computational purposes. Additionally, an automatic clustering technique was developed to reduce the number of parameters to assimilate at the optimization stage and it considerably accelerated the convergence of the simulations. Several in silico experiments were designed to assess the influence of aneurysm geometrical characteristics and the accuracy of wall motion estimates on the mechanical property estimates. Hence, the proposed methodology was applied to six real cerebral aneurysms and tested against a varying number of regions with different elasticity, different mesh discretization, imaging resolution, and registration configurations.
RESULTS:
Several in silico experiments were conducted to investigate the feasibility of the proposed workflow, results found suggesting that the estimation of the mechanical properties was mainly influenced by the image spatial resolution and the chosen registration configuration. According to the in silico experiments, the minimal spatial resolution needed to extract wall pulsation measurements with enough accuracy to guide the proposed data assimilation framework was of 0.1 mm.
CONCLUSIONS:
Current routine imaging modalities do not have such a high spatial resolution and therefore the proposed data assimilation framework cannot currently be used on in vivo data to reliably estimate regional properties in cerebral aneurysms. Besides, it was observed that the incorporation of fluid-structure interaction in a biomechanical model with linear and isotropic material properties did not have a substantial influence in the final results.
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Notes MILAB Approved no
Call Number (up) BCNPCL @ bcnpcl @ BCV2010 Serial 1313
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Author E. Barakova; Maya Dimitrova; T. Lorents; Petia Radeva
Title The Web as an “Autobiographical Agent” Type Miscellaneous
Year 2004 Publication Ch. Bussler and D. Fensel (Eds), Lecture Notes in Artificial Intelligence, vol. 3192, ISBN: 3–540–22959–0, pp. 510–519. Abbreviated Journal
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Address Springer-Verlag
Corporate Author Thesis
Publisher Place of Publication Editor
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Notes MILAB Approved no
Call Number (up) BCNPCL @ bcnpcl @ BDL2004 Serial 475
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Author Xavier Baro; Sergio Escalera; Petia Radeva; Jordi Vitria
Title Visual Content Layer for Scalable Recognition in Urban Image Databases, Internet Multimedia Search and Mining Type Conference Article
Year 2009 Publication 10th IEEE International Conference on Multimedia and Expo Abbreviated Journal
Volume Issue Pages 1616–1619
Keywords
Abstract Rich online map interaction represents a useful tool to get multimedia information related to physical places. With this type of systems, users can automatically compute the optimal route for a trip or to look for entertainment places or hotels near their actual position. Standard maps are defined as a fusion of layers, where each one contains specific data such height, streets, or a particular business location. In this paper we propose the construction of a visual content layer which describes the visual appearance of geographic locations in a city. We captured, by means of a Mobile Mapping system, a huge set of georeferenced images (> 500K) which cover the whole city of Barcelona. For each image, hundreds of region descriptions are computed off-line and described as a hash code. This allows an efficient and scalable way of accessing maps by visual content.
Address New York (USA)
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 978-1-4244-4291-1 Medium
Area Expedition Conference ICME
Notes OR;MILAB;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ BER2009 Serial 1189
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Author Xavier Baro; Sergio Escalera; Jordi Vitria; Oriol Pujol; Petia Radeva
Title Traffic Sign Recognition Using Evolutionary Adaboost Detection and Forest-ECOC Classification Type Journal Article
Year 2009 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS
Volume 10 Issue 1 Pages 113–126
Keywords
Abstract The high variability of sign appearance in uncontrolled environments has made the detection and classification of road signs a challenging problem in computer vision. In this paper, we introduce a novel approach for the detection and classification of traffic signs. Detection is based on a boosted detectors cascade, trained with a novel evolutionary version of Adaboost, which allows the use of large feature spaces. Classification is defined as a multiclass categorization problem. A battery of classifiers is trained to split classes in an Error-Correcting Output Code (ECOC) framework. We propose an ECOC design through a forest of optimal tree structures that are embedded in the ECOC matrix. The novel system offers high performance and better accuracy than the state-of-the-art strategies and is potentially better in terms of noise, affine deformation, partial occlusions, and reduced illumination.
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ISSN 1524-9050 ISBN Medium
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Notes OR;MILAB;HuPBA;MV Approved no
Call Number (up) BCNPCL @ bcnpcl @ BEV2008 Serial 1116
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