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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.
	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	MILAB			Approved	no
	Call Number	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
	Keywords
	Abstract
	Address	Varna (Bulgaria)
	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	MILAB			Approved	no
	Call Number	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
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	CVC (UAB)
	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	OR;HuPBA;MV			Approved	no
	Call Number	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
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;HuPBA;MV			Approved	no
	Call Number	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
	Volume		Issue		Pages
	Keywords
	Abstract
	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	OR;HuPBA;MV			Approved	no
	Call Number	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
	Volume		Issue		Pages
	Keywords
	Abstract
	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	OR;HuPBA;MV			Approved	no
	Call Number	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
	Keywords
	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	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
	Keywords
	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	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%.
	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	MILAB			Approved	no
	Call Number	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 classication 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 classiers. In this scope, the Error-Correcting Output Codes framework has demonstrated to be a powerful tool for the combination of classiers. However, most of the state-of-the-art ECOC approaches use a linear or exponential number of classiers, 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 classiers. Evolutionary computation is used for tuning the parameters of the classiers and looking for the best Minimal ECOC code conguration. 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
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference	SUEMA
	Notes	OR;MILAB;HUPBA;MV			Approved	no
	Call Number	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
	Keywords
	Abstract
	Address	Lyon (France)
	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	MILAB			Approved	no
	Call Number	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.
	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	MILAB			Approved	no
	Call Number	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
	Volume		Issue		Pages
	Keywords
	Abstract
	Address	Springer-Verlag
	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	MILAB			Approved	no
	Call Number	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	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.
	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	1524-9050	ISBN		Medium
	Area		Expedition		Conference
	Notes	OR;MILAB;HuPBA;MV			Approved	no
	Call Number	BCNPCL @ bcnpcl @ BEV2008			Serial	1116
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