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Author Jaume Garcia edit   pdf
openurl 
  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 (up) 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  
Permanent link to this record
 
 
Author Debora Gil; F. Javier Sanchez; Gloria Fernandez Esparrach; Jorge Bernal edit   pdf
doi  openurl
  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 (up) 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  
Permanent link to this record
 
 
Author David Roche; Debora Gil; Jesus Giraldo edit  doi
isbn  openurl
  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 (up) 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  
Permanent link to this record
 
 
Author Fernando Vilariño; Debora Gil; Petia Radeva edit   pdf
url  isbn
openurl 
  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 (up) 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  
Permanent link to this record
 
 
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 (up) 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  
Permanent link to this record
 
 
Author Sergio Vera edit  isbn
openurl 
  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 (up) 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 di erent 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 speci c 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 speci c 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 de nition of a depth coordinate. However, given that di erent methods for generation of medial surfaces generate di erent 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  
Permanent link to this record
 
 
Author Jaume Garcia; Debora Gil; Aura Hernandez-Sabate edit   pdf
doi  openurl
  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 (up) 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  
Permanent link to this record
 
 
Author Misael Rosales; Petia Radeva; Oriol Rodriguez; Debora Gil edit   pdf
doi  openurl
  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 (up) 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  
Permanent link to this record
 
 
Author Enric Marti; Jordi Vitria; Alberto Sanfeliu edit   pdf
isbn  openurl
  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 (up) 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  
Permanent link to this record
 
 
Author Antonio Esteban Lansaque edit  isbn
openurl 
  Title An Endoscopic Navigation System for Lung Cancer Biopsy Type Book Whole
  Year 2019 Publication PhD Thesis, Universitat Autonoma de Barcelona-CVC Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract (up) Lung cancer is one of the most diagnosed cancers among men and women. Actually,
lung cancer accounts for 13% of the total cases with a 5-year global survival
rate in patients. Although Early detection increases survival rate from 38% to 67%, accurate diagnosis remains a challenge. Pathological confirmation requires extracting a sample of the lesion tissue for its biopsy. The preferred procedure for tissue biopsy is called bronchoscopy. A bronchoscopy is an endoscopic technique for the internal exploration of airways which facilitates the performance of minimal invasive interventions with low risk for the patient. Recent advances in bronchoscopic devices have increased their use for minimal invasive diagnostic and intervention procedures, like lung cancer biopsy sampling. Despite the improvement in bronchoscopic device quality, there is a lack of intelligent computational systems for supporting in-vivo clinical decision during examinations. Existing technologies fail to accurately reach the lesion due to several aspects at intervention off-line planning and poor intra-operative guidance at exploration time. Existing guiding systems radiate patients and clinical staff,might be expensive and achieve a suboptimlal 70% of yield boost. Diagnostic yield could be improved reducing radiation and costs by developing intra-operative support systems able to guide the bronchoscopist to the lesion during the intervention. The goal of this PhD thesis is to develop an image-based navigation systemfor intra-operative guidance of bronchoscopists to a target lesion across a path previously planned on a CT-scan. We propose a 3D navigation system which uses the anatomy of video bronchoscopy frames to locate the bronchoscope within the airways. Once the bronchoscope is located, our navigation system is able to indicate the bifurcation which needs to be followed to reach the lesion. In order to facilitate an off-line validation
as realistic as possible, we also present a method for augmenting simulated virtual bronchoscopies with the appearance of intra-operative videos. Experiments performed on augmented and intra-operative videos, prove that our algorithm can be speeded up for an on-line implementation in the operating room.		  
  Address October 2019  
  Corporate Author Thesis Ph.D. thesis  
  Publisher Ediciones Graficas Rey Place of Publication Editor Debora Gil;Carles Sanchez  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-121011-0-2 Medium  
  Area Expedition Conference  
  Notes IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ Est2019 Serial 3392  
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