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	Author	Aura Hernandez-Sabate
	Title	Exploring Arterial Dynamics and Structures in IntraVascular Ultrasound Sequences			Type	Book Whole
	Year	2009	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Cardiovascular diseases are a leading cause of death in developed countries. Most of them are caused by arterial (specially coronary) diseases, mainly caused by plaque accumulation. Such pathology narrows blood flow (stenosis) and affects artery bio- mechanical elastic properties (atherosclerosis). In the last decades, IntraVascular UltraSound (IVUS) has become a usual imaging technique for the diagnosis and follow up of arterial diseases. IVUS is a catheter-based imaging technique which shows a sequence of cross sections of the artery under study. Inspection of a single image gives information about the percentage of stenosis. Meanwhile, inspection of longitudinal views provides information about artery bio-mechanical properties, which can prevent a fatal outcome of the cardiovascular disease. On one hand, dynamics of arteries (due to heart pumping among others) is a major artifact for exploring tissue bio-mechanical properties. On the other one, manual stenosis measurements require a manual tracing of vessel borders, which is a time-consuming task and might suffer from inter-observer variations. This PhD thesis proposes several image processing tools for exploring vessel dy- namics and structures. We present a physics-based model to extract, analyze and correct vessel in-plane rigid dynamics and to retrieve cardiac phase. Furthermore, we introduce a deterministic-statistical method for automatic vessel borders detection. In particular, we address adventitia layer segmentation. An accurate validation pro- tocol to ensure reliable clinical applicability of the methods is a crucial step in any proposal of an algorithm. In this thesis we take special care in designing a valida- tion protocol for each approach proposed and we contribute to the in vivo dynamics validation with a quantitative and objective score to measure the amount of motion suppressed.
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Debora Gil
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-937261-6-4	Medium
	Area		Expedition		Conference
	Notes	IAM;			Approved	no
	Call Number	IAM @ iam @ Her2009			Serial	1543
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	Author	Jaume Garcia
	Title	Statistical Models of the Architecture and Function of the Left Ventricle			Type	Book Whole
	Year	2009	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Cardiovascular Diseases, specially those affecting the Left Ventricle (LV), are the leading cause of death in developed countries with approximately a 30% of all global deaths. In order to address this public health concern, physicians focus on diagnosis and therapy planning. On one hand, early and accurate detection of Regional Wall Motion Abnormalities (RWMA) significantly contributes to a quick diagnosis and prevents the patient to reach more severe stages. On the other hand, a thouroughly knowledge of the normal gross anatomy of the LV, as well as, the distribution of its muscular fibers is crucial for designing specific interventions and therapies (such as pacemaker implanction). Statistical models obtained from the analysis of different imaging modalities allow the computation of the normal ranges of variation within a given population. Normality models are a valuable tool for the definition of objective criterions quantifying the degree of (anomalous) deviation of the LV function and anatomy for a given subject. The creation of statistical models involve addressing three main issues: extraction of data from images, definition of a common domain for comparison of data across patients and designing appropriate statistical analysis schemes. In this PhD thesis we present generic image processing tools for the creation of statistical models of the LV anatomy and function. On one hand, we use differential geometry concepts to define a computational framework (the Normalized Parametric Domain, NPD) suitable for the comparison and fusion of several clinical scores obtained over the LV. On the other hand, we present a variational approach (the Harmonic Phase Flow, HPF) for the estimation of myocardial motion that provides dense and continuous vector fields without overestimating motion at injured areas. These tools are used for the creation of statistical models. Regarding anatomy, we obtain an atlas jointly modelling, both, LV gross anatomy and fiber architecture. Regarding function, we compute normality patterns of scores characterizing the (global and local) LV function and explore, for the first time, the configuration of local scores better suited for RWMA detection.
	Address
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	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	IAM @ iam @ Gar2009a			Serial	1499
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	Author	Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal
	Title	3D Stable Spatio-temporal Polyp Localization in Colonoscopy Videos			Type	Book Chapter
	Year	2015	Publication	Computer-Assisted and Robotic Endoscopy. Revised selected papers of Second International Workshop, CARE 2015, Held in Conjunction with MICCAI 2015	Abbreviated Journal
	Volume	9515	Issue		Pages	140-152
	Keywords	Colonoscopy, Polyp Detection, Polyp Localization, Region Extraction, Watersheds
	Abstract	Computational intelligent systems could reduce polyp miss rate in colonoscopy for colon cancer diagnosis and, thus, increase the efficiency of the procedure. One of the main problems of existing polyp localization methods is a lack of spatio-temporal stability in their response. We propose to explore the response of a given polyp localization across temporal windows in order to select those image regions presenting the highest stable spatio-temporal response. Spatio-temporal stability is achieved by extracting 3D watershed regions on the temporal window. Stability in localization response is statistically determined by analysis of the variance of the output of the localization method inside each 3D region. We have explored the benefits of considering spatio-temporal stability in two different tasks: polyp localization and polyp detection. Experimental results indicate an average improvement of 21:5% in polyp localization and 43:78% in polyp detection.
	Address
	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	CARE
	Notes	IAM; MV; 600.075			Approved	no
	Call Number	Admin @ si @ GSF2015			Serial	2733
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	Author	David Roche; Debora Gil; Jesus Giraldo
	Title	Mathematical modeling of G protein-coupled receptor function: What can we learn from empirical and mechanistic models?			Type	Book Chapter
	Year	2014	Publication	G Protein-Coupled Receptors – Modeling and Simulation Advances in Experimental Medicine and Biology	Abbreviated Journal
	Volume	796	Issue	3	Pages	159-181
	Keywords	β-arrestin; biased agonism; curve fitting; empirical modeling; evolutionary algorithm; functional selectivity; G protein; GPCR; Hill coefficient; intrinsic efficacy; inverse agonism; mathematical modeling; mechanistic modeling; operational model; parameter optimization; receptor dimer; receptor oligomerization; receptor constitutive activity; signal transduction; two-state model
	Abstract	Empirical and mechanistic models differ in their approaches to the analysis of pharmacological effect. Whereas the parameters of the former are not physical constants those of the latter embody the nature, often complex, of biology. Empirical models are exclusively used for curve fitting, merely to characterize the shape of the E/[A] curves. Mechanistic models, on the contrary, enable the examination of mechanistic hypotheses by parameter simulation. Regretfully, the many parameters that mechanistic models may include can represent a great difficulty for curve fitting, representing, thus, a challenge for computational method development. In the present study some empirical and mechanistic models are shown and the connections, which may appear in a number of cases between them, are analyzed from the curves they yield. It may be concluded that systematic and careful curve shape analysis can be extremely useful for the understanding of receptor function, ligand classification and drug discovery, thus providing a common language for the communication between pharmacologists and medicinal chemists.
	Address
	Corporate Author				Thesis
	Publisher	Springer Netherlands	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN	0065-2598	ISBN	978-94-007-7422-3	Medium
	Area		Expedition		Conference
	Notes	IAM; 600.075			Approved	no
	Call Number	IAM @ iam @ RGG2014			Serial	2197
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	Author	Fernando Vilariño; Debora Gil; Petia Radeva
	Title	A Novel FLDA Formulation for Numerical Stability Analysis			Type	Book Chapter
	Year	2004	Publication	Recent Advances in Artificial Intelligence Research and Development	Abbreviated Journal
	Volume	113	Issue		Pages	77-84
	Keywords	Supervised Learning; Linear Discriminant Analysis; Numerical Stability; Computer Vision
	Abstract	Fisher Linear Discriminant Analysis (FLDA) is one of the most popular techniques used in classification applying dimensional reduction. The numerical scheme involves the inversion of the within-class scatter matrix, which makes FLDA potentially ill-conditioned when it becomes singular. In this paper we present a novel explicit formulation of FLDA in terms of the eccentricity ratio and eigenvector orientations of the within-class scatter matrix. An analysis of this function will characterize those situations where FLDA response is not reliable because of numerical instability. This can solve common situations of poor classification performance in computer vision.
	Address
	Corporate Author				Thesis
	Publisher	IOS Press	Place of Publication		Editor	J. Vitrià, P. Radeva and I. Aguiló
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-1-58603-466-5	Medium
	Area		Expedition		Conference
	Notes	MV;IAM;MILAB;SIAI			Approved	no
	Call Number	IAM @ iam @ VGR2004			Serial	1663
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	Author	Jose Elias Yauri
	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	Sergio Vera
	Title	Anatomic Registration based on Medial Axis Parametrizations			Type	Book Whole
	Year	2015	Publication	PhD Thesis, Universitat Autonoma de Barcelona-CVC	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Image registration has been for many years the gold standard method to bring two images into correspondence. It has been used extensively in the eld of medical imaging in order to put images of dierent patients into a common overlapping spatial position. However, medical image registration is a slow, iterative optimization process, where many variables and prone to fall into the pit traps local minima. A coordinate system parameterizing the interior of organs is a powerful tool for a systematic localization of injured tissue. If the same coordinate values are assigned to specic anatomical sites, parameterizations ensure integration of data across different medical image modalities. Harmonic mappings have been used to produce parametric meshes over the surface of anatomical shapes, given their ability to set values at specic locations through boundary conditions. However, most of the existing implementations in medical imaging restrict to either anatomical surfaces, or the depth coordinate with boundary conditions is given at discrete sites of limited geometric diversity. The medial surface of the shape can be used to provide a continuous basis for the denition of a depth coordinate. However, given that dierent methods for generation of medial surfaces generate dierent manifolds, not all of them are equally suited to be the basis of radial coordinate for a parameterization. It would be desirable that the medial surface will be smooth, and robust to surface shape noise, with low number of spurious branches or surfaces. In this thesis we present methods for computation of smooth medial manifolds and apply them to the generation of for anatomical volumetric parameterization that extends current harmonic parameterizations to the interior anatomy using information provided by the volume medial surface. This reference system sets a solid base for creating anatomical models of the anatomical shapes, and allows comparing several patients in a common framework of reference.
	Address	November 2015
	Corporate Author				Thesis	Ph.D. thesis
	Publisher	Ediciones Graficas Rey	Place of Publication		Editor	Debora Gil;Miguel Angel Gonzalez Ballester
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	978-84-943427-8-3	Medium
	Area		Expedition		Conference
	Notes	IAM; 600.075			Approved	no
	Call Number	Admin @ si @ Ver2015			Serial	2708
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	Author	Jaume Garcia; Debora Gil; Aura Hernandez-Sabate
	Title	Endowing Canonical Geometries to Cardiac Structures			Type	Book Chapter
	Year	2010	Publication	Statistical Atlases And Computational Models Of The Heart	Abbreviated Journal
	Volume	6364	Issue		Pages	124-133
	Keywords
	Abstract	International conference on Cardiac electrophysiological simulation challenge In this paper, we show that canonical (shape-based) geometries can be endowed to cardiac structures using tubular coordinates defined over their medial axis. We give an analytic formulation of these geometries by means of B-Splines. Since B-Splines present vector space structure PCA can be applied to their control points and statistical models relating boundaries and the interior of the anatomical structures can be derived. We demonstrate the applicability in two cardiac structures, the 3D Left Ventricular volume, and the 2D Left-Right ventricle set in 2D Short Axis view.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin / Heidelberg	Place of Publication		Editor	Camara, O.; Pop, M.; Rhode, K.; Sermesant, M.; Smith, N.; Young, A.
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume		Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM			Approved	no
	Call Number	IAM @ iam @ GGH2010b			Serial	1515
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	Author	Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil
	Title	Suppression of IVUS Image Rotation. A Kinematic Approach			Type	Book Chapter
	Year	2005	Publication	Functional Imaging and Modeling of the Heart	Abbreviated Journal	LNCS
	Volume	3504	Issue		Pages	889-892
	Keywords
	Abstract	IntraVascular Ultrasound (IVUS) is an exploratory technique used in interventional procedures that shows cross section images of arteries and provides qualitative information about the causes and severity of the arterial lumen narrowing. Cross section analysis as well as visualization of plaque extension in a vessel segment during the catheter imaging pullback are the technique main advantages. However, IVUS sequence exhibits a periodic rotation artifact that makes difficult the longitudinal lesion inspection and hinders any segmentation algorithm. In this paper we propose a new kinematic method to estimate and remove the image rotation of IVUS images sequences. Results on several IVUS sequences show good results and prompt some of the clinical applications to vessel dynamics study, and relation to vessel pathology.
	Address
	Corporate Author				Thesis
	Publisher	Springer Berlin / Heidelberg	Place of Publication		Editor	Frangi, Alejandro and Radeva, Petia and Santos, Andres and Hernandez, Monica
	Language		Summary Language		Original Title
	Series Editor		Series Title	Lecture Notes in Computer Science	Abbreviated Series Title	LNCS
	Series Volume	3504	Series Issue		Edition
	ISSN		ISBN		Medium
	Area		Expedition		Conference
	Notes	IAM;MILAB			Approved	no
	Call Number	IAM @ iam @ RRR2005			Serial	1645
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	Author	Enric Marti; Jordi Vitria; Alberto Sanfeliu
	Title	Reconocimiento de Formas y Análisis de Imágenes			Type	Book Whole
	Year	1998	Publication	Asociación Española de Reconocimientos de Formas y Análisis de Imágenes	Abbreviated Journal
	Volume		Issue		Pages
	Keywords
	Abstract	Los sistemas actuales de reconocimiento automático del lenguaje oral se basan en dos etapas básicas de procesado: la parametrización, que extrae la evolución temporal de los parámetros que caracterizan la voz, y el reconocimiento propiamente dicho, que identifica la cadena de palabras de la elocución recibida con ayuda de los modelos que representan el conocimiento adquirido en la etapa de aprendizaje. Tomando como línea divisoria la palabra, dichos modelos son de tipo acústicofonético o gramatical. Los primeros caracterizan las palabras incluidas en el vocabulario de la aplicación o tarea a la que está orientado el sistema de reconocimiento, usando a menudo para ello modelos de unidades de habla de extensión inferior a la palabra, es decir, de unidades subléxicas. Por otro lado, la gramática incluye el conocimiento acerca de las combinaciones permitidas de palabras para formar las frases o su probabilidad. Queda fuera del esquema la denominada comprensión del habla, que utiliza adicionalmente el conocimiento semántico y pragmático para captar el significado de la elocución de entrada al sistema a partir de la cadena (o cadenas alternativas) de palabras que suministra el reconocedor.
	Address
	Corporate Author				Thesis
	Publisher	AERFAI	Place of Publication		Editor
	Language		Summary Language		Original Title
	Series Editor		Series Title		Abbreviated Series Title
	Series Volume		Series Issue		Edition
	ISSN		ISBN	84–922529–4–4	Medium
	Area		Expedition		Conference
	Notes	IAM;OR;MV			Approved	no
	Call Number	IAM @ iam @ MVS1998			Serial	1620
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