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Author Carles Sanchez; Jorge Bernal; Debora Gil; F. Javier Sanchez edit   pdf
doi  isbn
openurl 
  Title On-line lumen centre detection in gastrointestinal and respiratory endoscopy Type Conference Article
  Year 2013 Publication Second International Workshop Clinical Image-Based Procedures Abbreviated Journal  
  Volume 8361 Issue Pages 31-38  
  Keywords Lumen centre detection; Bronchoscopy; Colonoscopy  
  Abstract We present in this paper a novel lumen centre detection for gastrointestinal and respiratory endoscopic images. The proposed method is based on the appearance and geometry of the lumen, which we defined as the darkest image region which centre is a hub of image gradients. Experimental results validated on the first public annotated gastro-respiratory database prove the reliability of the method for a wide range of images (with precision over 95 %).  
  Address Nagoya; Japan; September 2013  
  Corporate Author Thesis  
  Publisher Springer International Publishing Place of Publication Editor Erdt, Marius and Linguraru, Marius George and Oyarzun Laura, Cristina and Shekhar, Raj and Wesarg, Stefan and González Ballester, Miguel Angel and Drechsler, Klaus  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-319-05665-4 Medium  
  Area 800 Expedition Conference (up) CLIP  
  Notes MV; IAM; 600.047; 600.044; 600.060 Approved no  
  Call Number Admin @ si @ SBG2013 Serial 2302  
Permanent link to this record
 

 
Author Debora Gil; Oriol Ramos Terrades; Elisa Minchole; Carles Sanchez; Noelia Cubero de Frutos; Marta Diez-Ferrer; Rosa Maria Ortiz; Antoni Rosell edit  url
openurl 
  Title Classification of Confocal Endomicroscopy Patterns for Diagnosis of Lung Cancer Type Conference Article
  Year 2017 Publication 6th Workshop on Clinical Image-based Procedures: Translational Research in Medical Imaging Abbreviated Journal  
  Volume 10550 Issue Pages 151-159  
  Keywords  
  Abstract Confocal Laser Endomicroscopy (CLE) is an emerging imaging technique that allows the in-vivo acquisition of cell patterns of potentially malignant lesions. Such patterns could discriminate between inflammatory and neoplastic lesions and, thus, serve as a first in-vivo biopsy to discard cases that do not actually require a cell biopsy.

The goal of this work is to explore whether CLE images obtained during videobronchoscopy contain enough visual information to discriminate between benign and malign peripheral lesions for lung cancer diagnosis. To do so, we have performed a pilot comparative study with 12 patients (6 adenocarcinoma and 6 benign-inflammatory) using 2 different methods for CLE pattern analysis: visual analysis by 3 experts and a novel methodology that uses graph methods to find patterns in pre-trained feature spaces. Our preliminary results indicate that although visual analysis can only achieve a 60.2% of accuracy, the accuracy of the proposed unsupervised image pattern classification raises to 84.6%.

We conclude that CLE images visual information allow in-vivo detection of neoplastic lesions and graph structural analysis applied to deep-learning feature spaces can achieve competitive results.
 
  Address Quebec; Canada; September 2017  
  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 (up) CLIP  
  Notes IAM; 600.096; 600.075; 600.145 Approved no  
  Call Number Admin @ si @ GRM2017 Serial 2957  
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Author Debora Gil; Antonio Esteban Lansaque; Sebastian Stefaniga; Mihail Gaianu; Carles Sanchez edit  url
openurl 
  Title Data Augmentation from Sketch Type Conference Article
  Year 2019 Publication International Workshop on Uncertainty for Safe Utilization of Machine Learning in Medical Imaging Abbreviated Journal  
  Volume 11840 Issue Pages 155-162  
  Keywords Data augmentation; cycleGANs; Multi-objective optimization  
  Abstract State of the art machine learning methods need huge amounts of data with unambiguous annotations for their training. In the context of medical imaging this is, in general, a very difficult task due to limited access to clinical data, the time required for manual annotations and variability across experts. Simulated data could serve for data augmentation provided that its appearance was comparable to the actual appearance of intra-operative acquisitions. Generative Adversarial Networks (GANs) are a powerful tool for artistic style transfer, but lack a criteria for selecting epochs ensuring also preservation of intra-operative content.

We propose a multi-objective optimization strategy for a selection of cycleGAN epochs ensuring a mapping between virtual images and the intra-operative domain preserving anatomical content. Our approach has been applied to simulate intra-operative bronchoscopic videos and chest CT scans from virtual sketches generated using simple graphical primitives.
 
  Address Shenzhen; China; October 2019  
  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 (up) CLIP  
  Notes IAM; 600.145; 601.337 Approved no  
  Call Number Admin @ si @ GES2019 Serial 3359  
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Author Debora Gil; Jaume Garcia; Ruth Aris; Guillaume Houzeaux; Manuel Vazquez edit   pdf
openurl 
  Title A Riemmanian approach to cardiac fiber architecture modelling Type Conference Article
  Year 2009 Publication 1st International Conference on Mathematical & Computational Biomedical Engineering Abbreviated Journal  
  Volume Issue Pages 59-62  
  Keywords cardiac fiber architecture; diffusion tensor magnetic resonance imaging; differential (Rie- mannian) geometry.  
  Abstract There is general consensus that myocardial fiber architecture should be modelled in order to fully understand the electromechanical properties of the Left Ventricle (LV). Diffusion Tensor magnetic resonance Imaging (DTI) is the reference image modality for rapid measurement of fiber orientations by means of the tensor principal eigenvectors. In this work, we present a mathematical framework for across subject comparison of the local geometry of the LV anatomy including the fiber architecture from the statistical analysis of DTI studies. We use concepts of differential geometry for defining a parametric domain suitable for statistical analysis of a low number of samples. We use Riemannian metrics to define a consistent computation of DTI principal eigenvector modes of variation. Our framework has been applied to build an atlas of the LV fiber architecture from 7 DTI normal canine hearts.  
  Address  
  Corporate Author Thesis  
  Publisher Place of Publication Swansea (UK) Editor Nithiarasu, R.L.R.V.L.  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference (up) CMBE  
  Notes IAM Approved no  
  Call Number IAM @ iam @ FGA2009 Serial 1520  
Permanent link to this record
 

 
Author Patricia Marquez; Debora Gil; Aura Hernandez-Sabate edit   pdf
url  doi
openurl 
  Title Evaluation of the Capabilities of Confidence Measures for Assessing Optical Flow Quality Type Conference Article
  Year 2013 Publication ICCV Workshop on Computer Vision in Vehicle Technology: From Earth to Mars Abbreviated Journal  
  Volume Issue Pages 624-631  
  Keywords  
  Abstract Assessing Optical Flow (OF) quality is essential for its further use in reliable decision support systems. The absence of ground truth in such situations leads to the computation of OF Confidence Measures (CM) obtained from either input or output data. A fair comparison across the capabilities of the different CM for bounding OF error is required in order to choose the best OF-CM pair for discarding points where OF computation is not reliable. This paper presents a statistical probabilistic framework for assessing the quality of a given CM. Our quality measure is given in terms of the percentage of pixels whose OF error bound can not be determined by CM values. We also provide statistical tools for the computation of CM values that ensures a given accuracy of the flow field.  
  Address Sydney; Australia; December 2013  
  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 (up) CVTT:E2M  
  Notes IAM; ADAS; 600.044; 600.057; 601.145 Approved no  
  Call Number Admin @ si @ MGH2013b Serial 2351  
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Author Mireia Sole; J. Blanco; Debora Gil; Oliver Valero; Gothami Fonseka; M. Lawrie; Francesca Vidal; Zaida Sarrate edit   pdf
openurl 
  Title Chromosome Territories in Mice Spermatogenesis: A new three-dimensional methodology of study Type Conference Article
  Year 2017 Publication 11th European CytoGenesis Conference Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Florencia; Italia; July 2017  
  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 (up) ECA  
  Notes IAM; 600.096; 600.145 Approved no  
  Call Number Admin @ si @ SBG2017a Serial 2936  
Permanent link to this record
 

 
Author David Roche; Debora Gil; Jesus Giraldo edit   pdf
openurl 
  Title Using statistical inference for designing termination conditions ensuring convergence of Evolutionary Algorithms Type Conference Article
  Year 2011 Publication 11th European Conference on Artificial Life Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract A main challenge in Evolutionary Algorithms (EAs) is determining a termination condition ensuring stabilization close to the optimum in real-world applications. Although for known test functions distribution-based quantities are good candidates (as far as suitable parameters are used), in real-world problems an open question still remains unsolved. How can we estimate an upper-bound for the termination condition value ensuring a given accuracy for the (unknown) EA solution?
We claim that the termination problem would be fully solved if we defined a quantity (depending only on the EA output) behaving like the solution accuracy. The open question would be, then, satisfactorily answered if we had a model relating both quantities, since accuracy could be predicted from the alternative quantity. We present a statistical inference framework addressing two topics: checking the correlation between the two quantities and defining a regression model for predicting (at a given confidence level) accuracy values from the EA output.
 
  Address Paris, France  
  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 (up) ECAL  
  Notes IAM; Approved no  
  Call Number IAM @ iam @ RGG2011b Serial 1678  
Permanent link to this record
 

 
Author Carles Sanchez; Debora Gil; R. Tazi; Jorge Bernal; Y. Ruiz; L. Planas; F. Javier Sanchez; Antoni Rosell edit  openurl
  Title Quasi-real time digital assessment of Central Airway Obstruction Type Conference Article
  Year 2015 Publication 3rd European congress for bronchology and interventional pulmonology ECBIP2015 Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract  
  Address Barcelona; Spain; April 2015  
  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 (up) ECBIP  
  Notes IAM; MV; 600.075 Approved no  
  Call Number SGT2015 Serial 2612  
Permanent link to this record
 

 
Author Saad Minhas; Aura Hernandez-Sabate; Shoaib Ehsan; Katerine Diaz; Ales Leonardis; Antonio Lopez; Klaus McDonald Maier edit   pdf
openurl 
  Title LEE: A photorealistic Virtual Environment for Assessing Driver-Vehicle Interactions in Self-Driving Mode Type Conference Article
  Year 2016 Publication 14th European Conference on Computer Vision Workshops Abbreviated Journal  
  Volume 9915 Issue Pages 894-900  
  Keywords Simulation environment; Automated Driving; Driver-Vehicle interaction  
  Abstract Photorealistic virtual environments are crucial for developing and testing automated driving systems in a safe way during trials. As commercially available simulators are expensive and bulky, this paper presents a low-cost, extendable, and easy-to-use (LEE) virtual environment with the aim to highlight its utility for level 3 driving automation. In particular, an experiment is performed using the presented simulator to explore the influence of different variables regarding control transfer of the car after the system was driving autonomously in a highway scenario. The results show that the speed of the car at the time when the system needs to transfer the control to the human driver is critical.  
  Address Amsterdam; The Netherlands; October 2016  
  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 (up) ECCV-W  
  Notes ADAS;IAM; 600.085; 600.076 Approved no  
  Call Number MHE2016 Serial 2865  
Permanent link to this record
 

 
Author Patricia Marquez;Debora Gil;Aura Hernandez-Sabate edit   pdf
doi  isbn
openurl 
  Title A Complete Confidence Framework for Optical Flow Type Conference Article
  Year 2012 Publication 12th European Conference on Computer Vision – Workshops and Demonstrations Abbreviated Journal  
  Volume 7584 Issue 2 Pages 124-133  
  Keywords Optical flow, confidence measures, sparsification plots, error prediction plots  
  Abstract Medial representations are powerful tools for describing and parameterizing the volumetric shape of anatomical structures. Existing methods show excellent results when applied to 2D objects, but their quality drops across dimensions. This paper contributes to the computation of medial manifolds in two aspects. First, we provide a standard scheme for the computation of medial manifolds that avoid degenerated medial axis segments; second, we introduce an energy based method which performs independently of the dimension. We evaluate quantitatively the performance of our method with respect to existing approaches, by applying them to synthetic shapes of known medial geometry. Finally, we show results on shape representation of multiple abdominal organs, exploring the use of medial manifolds for the representation of multi-organ relations.  
  Address  
  Corporate Author Thesis  
  Publisher Springer-Verlag Place of Publication Florence, Italy, October 7-13, 2012 Editor Andrea Fusiello, Vittorio Murino ,Rita Cucchiara  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-3-642-33867-0 Medium  
  Area Expedition Conference (up) ECCVW  
  Notes IAM;ADAS; Approved no  
  Call Number IAM @ iam @ MGH2012b Serial 1991  
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