Browsing by Author "Camara, Oscar"

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  • A computational model of the fetal circulation to quantify blood redistribution in intrauterine growth restriction
    García Cañadilla, Patricia, 1985-; Rudenick, Paula A.; Crispi Brillas, Fàtima; Cruz-Lemini, Mónica; Palau, Georgina; Camara, Oscar; Gratacós Solsona, Eduard; Bijnens, Bart (Public Library of Science, 2014)
    Intrauterine growth restriction (IUGR) due to placental insufficiency is associated with blood flow redistribution in order to/nmaintain delivery of oxygenated blood to the brain. Given that, in the fetus the aortic isthmus ...
  • A global benchmark of algorithms for segmenting the left atrium from late gadolinium-enhanced cardiac magnetic resonance imaging
    Xiong, Zhaohan; Xia, Qing; Hu, Zhiqiang; Huang, Ning; Bian, Cheng; Zheng, Yefeng; Vesal, Sulaiman; Ravikumar, Nishant; Maier, Andreas; Yang, Xin; Heng, Pheng-Ann; Ni, Dong; Li, Caizi; Tong, Qianqian; Si, Weixin; Puybareau, Elodie; Khoudli, Younes; Géraud, Thierry; Chen, Chen; Bai, Wenjia; Rueckert, Daniel; Xu, Lingchao; Zhuang, Xiahai; Luo, Xinzhe; Jia, Shuman; Sermesant, Maxime; Liu, Yashu; Wang, Kuanquan; Borra, Davide; Masci, Alessandro; Corsi, Cristiana; Vente, Coen de; Veta, Mitko; Karim, Rashed; Jayachandran Preetha, Chandrakanth; Engelhardt, Sandy; Qiao, Menyun; Wang, Yuanyuan; Tao, Qian; Nuñez-Garcia, Marta; Camara, Oscar; Savioli, Nicolo; Lamata, Pablo; Zhao, Jichao (Elsevier, 2021)
    Segmentation of medical images, particularly late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) used for visualizing diseased atrial structures, is a crucial first step for ablation treatment of atrial fibrillation. ...
  • A Monte Carlo tree search approach to learning decision trees
    Nunes, Cecília; Craene, Mathieu de; Langet, Hélène; Camara, Oscar; Jonsson, Anders, 1973- (Institute of Electrical and Electronics Engineers (IEEE), 2019)
    Decision trees (DTs) are a widely used prediction tool, owing to their interpretability. Standard learning methods follow a locally-optimal approach that trades off prediction performance for computational efficiency. Such ...
  • A Rule-Based method to model myocardial fiber orientation for simulating ventricular outflow tract arrhythmias
    Doste Beltrán, Rubén; Soto-Iglesias, David; Bernardino Perez, Gabriel; Sebastián Aguilar, Rafael, 1978-; Giffard-Roisin, Sophie; Cabrera-Lozoya, Rocío; Sermesant, Maxime; Berruezo Sánchez, Antonio; Sánchez-Quintana, Damián; Camara, Oscar (Springer, 2017)
    Myocardial fiber orientation determines the propagation of electrical waves in the heart and the contraction of cardiac tissue. One common approach for assigning fiber orientation to cardiac anatomi- cal models are ...
  • A two dimensional electromechanical model of a cardiomyocyte to assess intra-cellular regional mechanical heterogeneities
    Garcia Canadilla, Patricia; Rodriguez, Jose F.; Palazzi, Maria J.; Gonzalez-Tendero, Anna; Schönleitner, Patrick; Balicevic, Vedrana; Loncaric, Sven; Luiken, Joost J. F. P.; Ceresa, Mario; Camara, Oscar; Antoons, Gudrun; Crispi Brillas, Fàtima; Gratacós Solsona, Eduard; Bijnens, Bart (Public Library of Science (PLoS), 2017)
    Experimental studies on isolated cardiomyocytes from different animal species and human hearts have demonstrated that there are regional differences in the Ca2+ release, Ca2+ decay and sarcomere deformation. Local deformation ...
  • A web-based tool for cardiac dyssynchrony assessment on ultrasound data
    Pezzatini, Daniele; Yagüe, Carlos; Rudenick, Paula A.; Blat, Josep; Bijnens, Bart; Camara, Oscar (Eurographics Association, 2017)
    Cardiac resynchronization therapy (CRT) is a broadly used therapy in patients that suffers from heart failure (HF). The positive outcome of CRT depends strongly on the parameters criteria used to select patients and a lot ...
  • Attri-VAE: attribute-based interpretable representations of medical images with variational autoencoders
    Cetin, Irem; Stephens, Maialen; Camara, Oscar; González Ballester, Miguel Ángel, 1973- (Elsevier, 2023)
    Deep learning (DL) methods where interpretability is intrinsically considered as part of the model are required to better understand the relationship of clinical and imaging-based attributes with DL outcomes, thus facilitating ...
  • Automatic activation mapping and origin identification of idiopathic outflow tract ventricular arrhythmias
    Alcaine, Alejandro; Soto-Iglesias, David; Acosta, Juan Carlos; Korshunov, Viatcheslav; Penela, Diego; Martínez, Mikel; Linhart, Markus; Andreu Martínez, David; Fernández-Armenta, Juan; Laguna, Pablo; Martínez, Juan Pablo; Camara, Oscar; Berruezo Sánchez, Antonio (Elsevier, 2018)
    Purpose: Activation mapping is used to guide ablation of idiopathic outflow tract ventricular arrhythmias (OTVAs). Isochronal activation maps help to predict the site of origin (SOO): left vs right outflow tract (OT). We ...
  • Automatic detection of slow conducting channels during substrate ablation of scar-related ventricular arrhythmias
    Alcaine, Alejandro; Jáuregui, Beatriz; Soto-Iglesias, David; Acosta, Juan Carlos; Penela, Diego; Fernández-Armenta, Juan; Linhart, Markus; Andreu Martínez, David; Mont, Lluís; Laguna, Pablo; Camara, Oscar; Martínez, Juan Pablo; Berruezo Sánchez, Antonio (Hindawi, 2020)
    Background. Voltage mapping allows identifying the arrhythmogenic substrate during scar-related ventricular arrhythmia (VA) ablation procedures. Slow conducting channels (SCCs), defined by the presence of electrogram (EGM) ...
  • Benchmark of deep learning algorithms for the automatic screening in electrocardiograms transmitted by implantable cardiac devices
    Gassa, Narimane; Sacristan, Benjamin; Zemzemi, Nejib; Laborde, Maxime; Garrido Oliver, Juan; Matencio Perabla, Clara; Jimenez-Perez, Guillermo; Camara, Oscar; Ploux, Sylvain; Strik, Marc; Bordachar, Pierre; Dubois, Remi (Institute of Electrical and Electronics Engineers (IEEE), 2021)
    The objective of this work was to benchmark different deep learning architectures for noise detection against cardiac arrhythmia episodes recorded by pacemakers and implantable cardioverter-defibrillators (PM/ICDs) and ...
  • Breaking the state of the heart: meshless model for cardiac mechanics
    Lluch Alvarez, Èric; Craene, Mathieu de; Bijnens, Bart; Sermesant, Maxime; Noailly, Jérôme; Camara, Oscar; Morales, Hernán G. (Springer, 2019)
    Cardiac modeling has recently emerged as a promising tool to study pathophysiology mechanisms and to predict treatment outcomes for personalized clinical decision support. Nevertheless, achieving convergence under large ...
  • Characterization and modeling of the purkinje system for biophysical simulations
    Romero García, Daniel (Universitat Pompeu Fabra, 2016-01-18)
    The usability of computer models of the heart depends mostly on their capacity to accurately represent heart anatomy, microstructure and function. However, integrating such a variety of biological data is often not possible. ...
  • Computational fluid simulations in clinical datasets for understanding thrombus formation before and after left atrial appendage occlusion
    Mill Tena, Jordi (Universitat Pompeu Fabra, 2022-10-25)
    Atrial fibrillation is considered the most common arrhythmia in humans. Because the left atrium of the heart stops beating properly and begins to do so in an arrhythmic manner, the blood may become stagnant in a small ...
  • Computational models of the heart for planning and treatment of outflow tract ventricular arrhythmias
    Doste Beltrán, Rubén (Universitat Pompeu Fabra, 2019-11-18)
    The purpose of this thesis was to develop personalised cardiovascular therapy guided by multimodal noninvasive imaging and simulations, combined with artificial intelligence tools, for the management of the outflow tract ...
  • Computational pipeline for the generation and validation of patient-specific mechanical models of brain development
    Alenyà, Mireia; Wang, Xiaoyu; Lefèvre, Julien; Auzias, Guillaume; Fouquet, Benjamin; Eixarch, Elisenda; Rousseau, François; Camara, Oscar (Elsevier, 2022)
    The human brain develops from a smooth cortical surface in early stages of fetal life to a convoluted one postnatally, creating an organized ensemble of folds. Abnormal folding patterns are linked to neurodevelopmental ...
  • Deep learning and unsupervised machine learning for the quantification and interpretation of electrocardiographic signals
    Jiménez-Pérez, Guillermo (Universitat Pompeu Fabra, 2022-02-17)
    Las señales electrocardiográficas, ya sea adquiridas en la piel del paciente (electrocardiogamas de superficie, ECG) o de forma invasiva mediante cateterismo (electrocardiogramas intracavitarios, iECG) ayudan a explorar ...
  • Deep learning framework for real-time estimation of in-silico thrombotic risk indices in the left atrial appendage
    Morales Ferez, Xabier; Mill, Jordi; Juhl, Kristine Aavild; Acebes Pinilla, César; Iriart, Xavier; Legghe, Benoit; Cochet, Hubert; De Backer, Ole; Paulsen, Rasmus R.; Camara, Oscar (Frontiers, 2021)
    Patient-specific computational fluid dynamics (CFD) simulations can provide invaluable insight into the interaction of left atrial appendage (LAA) morphology, hemodynamics, and the formation of thrombi in atrial fibrillation ...
  • Deep learning techniques for automatic MRI cardiac multi-structures segmentation and diagnosis: is the problem solved?
    Bernard, Olivier; Lalande, Alain; Zotti, Clement; Cervenansky, Frederick; Yang, Xin; Heng, Pheng-Ann; Cetin, Irem; Lekadir, Karim, 1977-; Camara, Oscar; González Ballester, Miguel Ángel, 1973-; Sanromà, Gerard; Napel, Sandy; Petersen, Steffen; Tziritas, Georgios; Grinias, Elias; Khened, Mahendra; Kollerathu, Varghese Alex; Krishnamurthi, Ganapathy; Rohé, Marc-Michel; Pennec, Xavier; Sermesant, Maxime; Isensee, Fabian; Jäger, Paul; Maier-Hein, Klaus H.; Full, Peter M.; Wolf, Ivo; Engelhardt, Sandy; Baumgartner, Christian F.; Koch, Lisa M.; Wolterink, Jelmer M.; Išgum, Ivana; Jang, Yeonggul; Hong, Yoonmi; Patravali, Jay; Jain, Shubham; Humbert, Olivier; Jodoin, Pierre-Marc (Institute of Electrical and Electronics Engineers (IEEE), 2018)
    Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding ...
  • Delineation of the electrocardiogram with a mixed-quality-annotations dataset using convolutional neural networks
    Jimenez-Perez, Guillermo; Alcaine, Alejandro; Camara, Oscar (Nature Research, 2021)
    Detection and delineation are key steps for retrieving and structuring information of the electrocardiogram (ECG), being thus crucial for numerous tasks in clinical practice. Digital signal processing (DSP) algorithms are ...
  • Detection of lesions in the optic nerve with magnetic resonance imaging using a 3D convolutional neural network
    Martí Juan, Gerard; Frías Nestares, Marcos; Garcia Vidal, Aran; Vidal Jordana, Angela; Alberich, Manel; Calderon, Willem; Piella Fenoy, Gemma; Camara, Oscar; Montalban, Xavier; Sastre-Garriga, Jaume; Rovira, Àlex; Pareto, Deborah (Elsevier, 2022)
    Background: Optic neuritis (ON) is one of the first manifestations of multiple sclerosis, a disabling disease with rising prevalence. Detecting optic nerve lesions could be a relevant diagnostic marker in patients with ...