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Author Oriol Rodriguez-Leon; Josefina Mauri; Eduard Fernandez-Nofrerias; M.Gomez; Antonio Tovar; L.Cano; C.Diego; Carme Julia; Vicente del Valle; Debora Gil; Petia Radeva edit  openurl
  Title Ecografia Intracoronaria: Segmentacio Automatica de area de la llum Type Journal
  Year 2002 Publication Revista Societat Catalana de Cardiologia Abbreviated Journal  
  Volume 4 Issue (down) 4 Pages 42  
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  Address Barcelona  
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  Area Expedition Conference XIVe Congres de la Societat Catalana de Cardiologia  
  Notes MILAB;IAM Approved no  
  Call Number BCNPCL @ bcnpcl @ RMF2002 Serial 435  
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Author Marta Diez-Ferrer; Debora Gil; Elena Carreño; Susana Padrones; Samantha Aso; Vanesa Vicens; Cubero Noelia; Rosa Lopez Lisbona; Carles Sanchez; Agnes Borras; Antoni Rosell edit  url
openurl 
  Title Positive Airway Pressure-Enhanced CT to Improve Virtual Bronchoscopic Navigation Type Journal Article
  Year 2016 Publication Chest Journal Abbreviated Journal CHEST  
  Volume 150 Issue (down) 4 Pages 1003A  
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  Notes IAM; 600.096; 600.075 Approved no  
  Call Number Admin @ si @ DGC2016 Serial 3099  
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Author Aura Hernandez-Sabate; Jose Elias Yauri; Pau Folch; Daniel Alvarez; Debora Gil edit  url
openurl 
  Title EEG Dataset Collection for Mental Workload Predictions in Flight-Deck Environment Type Journal Article
  Year 2024 Publication Sensors Abbreviated Journal SENS  
  Volume 24 Issue (down) 4 Pages 1174  
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  Abstract High mental workload reduces human performance and the ability to correctly carry out complex tasks. In particular, aircraft pilots enduring high mental workloads are at high risk of failure, even with catastrophic outcomes. Despite progress, there is still a lack of knowledge about the interrelationship between mental workload and brain functionality, and there is still limited data on flight-deck scenarios. Although recent emerging deep-learning (DL) methods using physiological data have presented new ways to find new physiological markers to detect and assess cognitive states, they demand large amounts of properly annotated datasets to achieve good performance. We present a new dataset of electroencephalogram (EEG) recordings specifically collected for the recognition of different levels of mental workload. The data were recorded from three experiments, where participants were induced to different levels of workload through tasks of increasing cognition demand. The first involved playing the N-back test, which combines memory recall with arithmetical skills. The second was playing Heat-the-Chair, a serious game specifically designed to emphasize and monitor subjects under controlled concurrent tasks. The third was flying in an Airbus320 simulator and solving several critical situations. The design of the dataset has been validated on three different levels: (1) correlation of the theoretical difficulty of each scenario to the self-perceived difficulty and performance of subjects; (2) significant difference in EEG temporal patterns across the theoretical difficulties and (3) usefulness for the training and evaluation of AI models.  
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  Notes IAM Approved no  
  Call Number Admin @ si @ HYF2024 Serial 4019  
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Author Jaume Garcia; Debora Gil; Sandra Pujades; Francesc Carreras edit   pdf
openurl 
  Title Valoracion de la Funcion del Ventriculo Izquierdo mediante Modelos Regionales Hiperparametricos Type Journal Article
  Year 2008 Publication Revista Española de Cardiologia Abbreviated Journal  
  Volume 61 Issue (down) 3 Pages 79  
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  Abstract La mayoría de la enfermedades cardiovasculares afectan a las propiedades contráctiles de la banda ventricular helicoidal. Esto se refleja en una variación del comportamiento normal de la función ventricular. Parámetros locales tales como los strains, o la deformación experimentada por el tejido, son indicadores capaces de detectar anomalías funcionales en territorios específicos. A menudo, dichos parámetros son considerados de forma separada. En este trabajo presentamos un marco computacional (el Dominio Paramétrico Normalizado, DPN) que permite integrarlos en hiperparámetros funcionales y estudiar sus rangos de normalidad. Dichos rangos permiten valorar de forma objetiva la función regional de cualquier nuevo paciente. Para ello, consideramos secuencias de resonancia magnética etiquetada a nivel basal, medio y apical. Los hiperparámetros se obtienen a partir del movimiento intramural del VI estimado mediante el método Harmonic Phase Flow. El DPN se define a partir de en una parametrización del Ventrículo Izquierdo (VI) en sus coordenadas radiales y circunferencial basada en criterios anatómicos. El paso de los hiperparámetros al DPN hace posible la comparación entre distintos pacientes. Los rangos de normalidad se definen mediante análisis estadístico de valores de voluntarios sanos en 45 regiones del DPN a lo largo de 9 fases sistólicas. Se ha usado un conjunto de 19 (14 H; E: 30.7±7.5) voluntarios sanos para crear los patrones de normalidad y se han validado usando 2 controles sanos y 3 pacientes afectados de contractilidad global reducida. Para los controles los resultados regionales se han ajustado dentro de la normalidad, mientras que para los pacientes se han obtenido valores anormales en las zonas descritas, localizando y cuantificando así el diagnóstico empírico.  
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  Notes IAM; Approved no  
  Call Number IAM @ iam @ GRP2008 Serial 1032  
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Author Jaume Garcia; Debora Gil; Luis Badiella; Aura Hernandez-Sabate; Francesc Carreras; Sandra Pujades; Enric Marti edit   pdf
doi  openurl
  Title A Normalized Framework for the Design of Feature Spaces Assessing the Left Ventricular Function Type Journal Article
  Year 2010 Publication IEEE Transactions on Medical Imaging Abbreviated Journal TMI  
  Volume 29 Issue (down) 3 Pages 733-745  
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  Abstract A through description of the left ventricle functionality requires combining complementary regional scores. A main limitation is the lack of multiparametric normality models oriented to the assessment of regional wall motion abnormalities (RWMA). This paper covers two main topics involved in RWMA assessment. We propose a general framework allowing the fusion and comparison across subjects of different regional scores. Our framework is used to explore which combination of regional scores (including 2-D motion and strains) is better suited for RWMA detection. Our statistical analysis indicates that for a proper (within interobserver variability) identification of RWMA, models should consider motion and extreme strains.  
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  Series Volume Series Issue Edition  
  ISSN 0278-0062 ISBN Medium  
  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number IAM @ iam @ GGH2010b Serial 1507  
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