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Author (up) Jorge Bernal; Debora Gil; Carles Sanchez; F. Javier Sanchez edit   pdf
doi  isbn
openurl 
  Title Discarding Non Informative Regions for Efficient Colonoscopy Image Analysis Type Conference Article
  Year 2014 Publication 1st MICCAI Workshop on Computer-Assisted and Robotic Endoscopy Abbreviated Journal  
  Volume 8899 Issue Pages 1-10  
  Keywords Image Segmentation; Polyps, Colonoscopy; Valley Information; Energy Maps  
  Abstract In this paper we present a novel polyp region segmentation method for colonoscopy videos. Our method uses valley information associated to polyp boundaries in order to provide an initial segmentation. This first segmentation is refined to eliminate boundary discontinuities caused by image artifacts or other elements of the scene. Experimental results over a publicly annotated database show that our method outperforms both general and specific segmentation methods by providing more accurate regions rich in polyp content. We also prove how image preprocessing is needed to improve final polyp region segmentation.  
  Address Boston; USA; September 2014  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN 0302-9743 ISBN 978-3-319-13409-3 Medium  
  Area Expedition Conference CARE  
  Notes MV; IAM; 600.044; 600.047; 600.060; 600.075 Approved no  
  Call Number Admin @ si @ BGS2014b Serial 2503  
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Author (up) Jorge Bernal; F. Javier Sanchez; Gloria Fernandez Esparrach; Debora Gil; Cristina Rodriguez de Miguel; Fernando Vilariño edit   pdf
doi  openurl
  Title WM-DOVA Maps for Accurate Polyp Highlighting in Colonoscopy: Validation vs. Saliency Maps from Physicians Type Journal Article
  Year 2015 Publication Computerized Medical Imaging and Graphics Abbreviated Journal CMIG  
  Volume 43 Issue Pages 99-111  
  Keywords Polyp localization; Energy Maps; Colonoscopy; Saliency; Valley detection  
  Abstract We introduce in this paper a novel polyp localization method for colonoscopy videos. Our method is based on a model of appearance for polyps which defines polyp boundaries in terms of valley information. We propose the integration of valley information in a robust way fostering complete, concave and continuous boundaries typically associated to polyps. This integration is done by using a window of radial sectors which accumulate valley information to create WMDOVA1 energy maps related with the likelihood of polyp presence. We perform a double validation of our maps, which include the introduction of two new databases, including the first, up to our knowledge, fully annotated database with clinical metadata associated. First we assess that the highest value corresponds with the location of the polyp in the image. Second, we show that WM-DOVA energy maps can be comparable with saliency maps obtained from physicians' fixations obtained via an eye-tracker. Finally, we prove that our method outperforms state-of-the-art computational saliency results. Our method shows good performance, particularly for small polyps which are reported to be the main sources of polyp miss-rate, which indicates the potential applicability of our method in clinical practice.  
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  Series Volume Series Issue Edition  
  ISSN 0895-6111 ISBN Medium  
  Area Expedition Conference  
  Notes MV; IAM; 600.047; 600.060; 600.075;SIAI Approved no  
  Call Number Admin @ si @ BSF2015 Serial 2609  
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Author (up) Jose Elias Yauri; Aura Hernandez-Sabate; Pau Folch; Debora Gil edit  doi
openurl 
  Title Mental Workload Detection Based on EEG Analysis Type Conference Article
  Year 2021 Publication Artificial Intelligent Research and Development. Proceedings 23rd International Conference of the Catalan Association for Artificial Intelligence. Abbreviated Journal  
  Volume 339 Issue Pages 268-277  
  Keywords Cognitive states; Mental workload; EEG analysis; Neural Networks.  
  Abstract The study of mental workload becomes essential for human work efficiency, health conditions and to avoid accidents, since workload compromises both performance and awareness. Although workload has been widely studied using several physiological measures, minimising the sensor network as much as possible remains both a challenge and a requirement.
Electroencephalogram (EEG) signals have shown a high correlation to specific cognitive and mental states like workload. However, there is not enough evidence in the literature to validate how well models generalize in case of new subjects performing tasks of a workload similar to the ones included during model’s training.
In this paper we propose a binary neural network to classify EEG features across different mental workloads. Two workloads, low and medium, are induced using two variants of the N-Back Test. The proposed model was validated in a dataset collected from 16 subjects and shown a high level of generalization capability: model reported an average recall of 81.81% in a leave-one-out subject evaluation.
 
  Address Virtual; October 20-22 2021  
  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 CCIA  
  Notes IAM; 600.139; 600.118; 600.145 Approved no  
  Call Number Admin @ si @ Serial 3723  
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Author (up) Josefina Mauri; Eduard Fernandez-Nofrerias; J. Comin; B. Garcia del Blanco; E. Iraculis; J.A. Gomez-Hospital; P. Valdovinos; F. Jara; A. Cequier; E. Esplugas; Oriol Pujol; Cristina Cañero; Debora Gil; Petia Radeva; Ricardo Toledo edit  openurl
  Title Avaluació del Conjunt Stent/Artèria mitjançant ecografia intracoronària: lentorn informàtic Type Conference Article
  Year 2000 Publication Congrés de la Societat Catalana de Cardiologia. Abbreviated Journal  
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  Notes IAM;RV;MILAB;ADAS;HuPBA Approved no  
  Call Number IAM @ iam @ MNC2000 Serial 1622  
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Author (up) Josefina Mauri; Eduard Fernandez-Nofrerias; B. Garcia del Blanco; E. Iraculis; J.A. Gomez-Hospital; J. Comin; M.A. Sanchez Corral; F. Jara; A. Cequier; E. Esplugas; Debora Gil; J. Saludes; Petia Radeva; Ricardo Toledo; Juan J.Villanueva edit  openurl
  Title Moviment del vas en l anàlisi d imatges d ecografia intracoronària: un model matemàtic Type Conference Article
  Year 2000 Publication Congrés de la Societat Catalana de Cardiologia. Abbreviated Journal  
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  Notes IAM;RV;ISE;MILAB;ADAS Approved no  
  Call Number IAM @ iam @ MNG2000 Serial 1621  
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Author (up) Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil edit   pdf
doi  openurl
  Title BronchoPose: an analysis of data and model configuration for vision-based bronchoscopy pose estimation Type Journal Article
  Year 2023 Publication Computer Methods and Programs in Biomedicine Abbreviated Journal CMPB  
  Volume 228 Issue Pages 107241  
  Keywords Videobronchoscopy guiding; Deep learning; Architecture optimization; Datasets; Standardized evaluation framework; Pose estimation  
  Abstract Vision-based bronchoscopy (VB) models require the registration of the virtual lung model with the frames from the video bronchoscopy to provide effective guidance during the biopsy. The registration can be achieved by either tracking the position and orientation of the bronchoscopy camera or by calibrating its deviation from the pose (position and orientation) simulated in the virtual lung model. Recent advances in neural networks and temporal image processing have provided new opportunities for guided bronchoscopy. However, such progress has been hindered by the lack of comparative experimental conditions.
In the present paper, we share a novel synthetic dataset allowing for a fair comparison of methods. Moreover, this paper investigates several neural network architectures for the learning of temporal information at different levels of subject personalization. In order to improve orientation measurement, we also present a standardized comparison framework and a novel metric for camera orientation learning. Results on the dataset show that the proposed metric and architectures, as well as the standardized conditions, provide notable improvements to current state-of-the-art camera pose estimation in video bronchoscopy.
 
  Address  
  Corporate Author Thesis  
  Publisher Elsevier 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 IAM; Approved no  
  Call Number Admin @ si @ BSC2023 Serial 3702  
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Author (up) Juan Borrego-Carazo; Carles Sanchez; David Castells; Jordi Carrabina; Debora Gil edit  openurl
  Title A benchmark for the evaluation of computational methods for bronchoscopic navigation Type Journal Article
  Year 2022 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCARS  
  Volume 17 Issue 1 Pages  
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  Area Expedition Conference  
  Notes IAM Approved no  
  Call Number Admin @ si @ BSC2022 Serial 3832  
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Author (up) Katerine Diaz; Jesus Martinez del Rincon; Aura Hernandez-Sabate; Debora Gil edit   pdf
doi  openurl
  Title Continuous head pose estimation using manifold subspace embedding and multivariate regression Type Journal Article
  Year 2018 Publication IEEE Access Abbreviated Journal ACCESS  
  Volume 6 Issue Pages 18325 - 18334  
  Keywords Head Pose estimation; HOG features; Generalized Discriminative Common Vectors; B-splines; Multiple linear regression  
  Abstract In this paper, a continuous head pose estimation system is proposed to estimate yaw and pitch head angles from raw facial images. Our approach is based on manifold learningbased methods, due to their promising generalization properties shown for face modelling from images. The method combines histograms of oriented gradients, generalized discriminative common vectors and continuous local regression to achieve successful performance. Our proposal was tested on multiple standard face datasets, as well as in a realistic scenario. Results show a considerable performance improvement and a higher consistence of our model in comparison with other state-of-art methods, with angular errors varying between 9 and 17 degrees.  
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  Series Volume Series Issue Edition  
  ISSN 2169-3536 ISBN Medium  
  Area Expedition Conference  
  Notes ADAS; 600.118 Approved no  
  Call Number Admin @ si @ DMH2018b Serial 3091  
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Author (up) M.Gomez; Josefina Mauri; Eduard Fernandez-Nofrerias; Oriol Rodriguez-Leon; Carme Julia; Debora Gil; Petia Radeva edit  openurl
  Title Reconstrucción de un modelo espacio-temporal de la luz del vaso a partir de secuencias de ecografía intracoronaria Type Conference Article
  Year 2002 Publication XXXVIII Congreso Nacional de la Sociedad Española de Cardiología. Abbreviated Journal  
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  Notes IAM;ADAS;MILAB Approved no  
  Call Number IAM @ iam @ GMF2002d Serial 1516  
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Author (up) Mariano Vazquez; Ruth Aris; Guillaume Hozeaux; R.Aubry; P.Villar;Jaume Garcia ; Debora Gil; Francesc Carreras edit   pdf
url  doi
openurl 
  Title A massively parallel computational electrophysiology model of the heart Type Journal Article
  Year 2011 Publication International Journal for Numerical Methods in Biomedical Engineering Abbreviated Journal IJNMBE  
  Volume 27 Issue Pages 1911-1929  
  Keywords computational electrophysiology; parallelization; finite element methods  
  Abstract This paper presents a patient-sensitive simulation strategy capable of using the most efficient way the high-performance computational resources. The proposed strategy directly involves three different players: Computational Mechanics Scientists (CMS), Image Processing Scientists and Cardiologists, each one mastering its own expertise area within the project. This paper describes the general integrative scheme but focusing on the CMS side presents a massively parallel implementation of computational electrophysiology applied to cardiac tissue simulation. The paper covers different angles of the computational problem: equations, numerical issues, the algorithm and parallel implementation. The proposed methodology is illustrated with numerical simulations testing all the different possibilities, ranging from small domains up to very large ones. A key issue is the almost ideal scalability not only for large and complex problems but also for medium-size meshes. The explicit formulation is particularly well suited for solving this highly transient problems, with very short time-scale.  
  Address Swansea (UK)  
  Corporate Author John Wiley & Sons, Ltd. Thesis  
  Publisher John Wiley & Sons, Ltd. 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 IAM Approved no  
  Call Number IAM @ iam @ VAH2011 Serial 1198  
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