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Author Debora Gil; Antonio Esteban Lansaque; Agnes Borras; Esmitt Ramirez; Carles Sanchez edit   pdf
url  doi
openurl 
  Title Intraoperative Extraction of Airways Anatomy in VideoBronchoscopy Type Journal Article
  Year 2020 Publication IEEE Access Abbreviated Journal ACCESS  
  Volume 8 Issue Pages 159696 - 159704  
  Keywords  
  Abstract A main bottleneck in bronchoscopic biopsy sampling is to efficiently reach the lesion navigating across bronchial levels. Any guidance system should be able to localize the scope position during the intervention with minimal costs and alteration of clinical protocols. With the final goal of an affordable image-based guidance, this work presents a novel strategy to extract and codify the anatomical structure of bronchi, as well as, the scope navigation path from videobronchoscopy. Experiments using interventional data show that our method accurately identifies the bronchial structure. Meanwhile, experiments using simulated data verify that the extracted navigation path matches the 3D route.  
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  Area Expedition Conference  
  Notes (down) IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ GEB2020 Serial 3467  
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Author Saad Minhas; Aura Hernandez-Sabate; Shoaib Ehsan; Klaus McDonald Maier edit  doi
openurl 
  Title Effects of Non-Driving Related Tasks during Self-Driving mode Type Journal Article
  Year 2022 Publication IEEE Transactions on Intelligent Transportation Systems Abbreviated Journal TITS  
  Volume 23 Issue 2 Pages 1391-1399  
  Keywords  
  Abstract Perception reaction time and mental workload have proven to be crucial in manual driving. Moreover, in highly automated cars, where most of the research is focusing on Level 4 Autonomous driving, take-over performance is also a key factor when taking road safety into account. This study aims to investigate how the immersion in non-driving related tasks affects the take-over performance of drivers in given scenarios. The paper also highlights the use of virtual simulators to gather efficient data that can be crucial in easing the transition between manual and autonomous driving scenarios. The use of Computer Aided Simulations is of absolute importance in this day and age since the automotive industry is rapidly moving towards Autonomous technology. An experiment comprising of 40 subjects was performed to examine the reaction times of driver and the influence of other variables in the success of take-over performance in highly automated driving under different circumstances within a highway virtual environment. The results reflect the relationship between reaction times under different scenarios that the drivers might face under the circumstances stated above as well as the importance of variables such as velocity in the success on regaining car control after automated driving. The implications of the results acquired are important for understanding the criteria needed for designing Human Machine Interfaces specifically aimed towards automated driving conditions. Understanding the need to keep drivers in the loop during automation, whilst allowing drivers to safely engage in other non-driving related tasks is an important research area which can be aided by the proposed study.  
  Address Feb. 2022  
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  Notes (down) IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ MHE2022 Serial 3468  
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Author Debora Gil; Guillermo Torres edit   pdf
openurl 
  Title A multi-shape loss function with adaptive class balancing for the segmentation of lung structures Type Conference Article
  Year 2020 Publication 34th International Congress and Exhibition on Computer Assisted Radiology & Surgery Abbreviated Journal  
  Volume Issue Pages  
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  Abstract  
  Address Virtual; June 2020  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference CARS  
  Notes (down) IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ GiT2020 Serial 3472  
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Author Guillermo Torres; Sonia Baeza; Carles Sanchez; Ignasi Guasch; Antoni Rosell; Debora Gil edit  doi
openurl 
  Title An Intelligent Radiomic Approach for Lung Cancer Screening Type Journal Article
  Year 2022 Publication Applied Sciences Abbreviated Journal APPLSCI  
  Volume 12 Issue 3 Pages 1568  
  Keywords Lung cancer; Early diagnosis; Screening; Neural networks; Image embedding; Architecture optimization  
  Abstract The efficiency of lung cancer screening for reducing mortality is hindered by the high rate of false positives. Artificial intelligence applied to radiomics could help to early discard benign cases from the analysis of CT scans. The available amount of data and the fact that benign cases are a minority, constitutes a main challenge for the successful use of state of the art methods (like deep learning), which can be biased, over-fitted and lack of clinical reproducibility. We present an hybrid approach combining the potential of radiomic features to characterize nodules in CT scans and the generalization of the feed forward networks. In order to obtain maximal reproducibility with minimal training data, we propose an embedding of nodules based on the statistical significance of radiomic features for malignancy detection. This representation space of lesions is the input to a feed
forward network, which architecture and hyperparameters are optimized using own-defined metrics of the diagnostic power of the whole system. Results of the best model on an independent set of patients achieve 100% of sensitivity and 83% of specificity (AUC = 0.94) for malignancy detection.
 
  Address Jan 2022  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
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  Area Expedition Conference  
  Notes (down) IAM; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ TBS2022 Serial 3699  
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Author Debora Gil; Aura Hernandez-Sabate; Julien Enconniere; Saryani Asmayawati; Pau Folch; Juan Borrego-Carazo; Miquel Angel Piera edit  doi
openurl 
  Title E-Pilots: A System to Predict Hard Landing During the Approach Phase of Commercial Flights Type Journal Article
  Year 2022 Publication IEEE Access Abbreviated Journal ACCESS  
  Volume 10 Issue Pages 7489-7503  
  Keywords  
  Abstract More than half of all commercial aircraft operation accidents could have been prevented by executing a go-around. Making timely decision to execute a go-around manoeuvre can potentially reduce overall aviation industry accident rate. In this paper, we describe a cockpit-deployable machine learning system to support flight crew go-around decision-making based on the prediction of a hard landing event.
This work presents a hybrid approach for hard landing prediction that uses features modelling temporal dependencies of aircraft variables as inputs to a neural network. Based on a large dataset of 58177 commercial flights, the results show that our approach has 85% of average sensitivity with 74% of average specificity at the go-around point. It follows that our approach is a cockpit-deployable recommendation system that outperforms existing approaches.
 
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  Area Expedition Conference  
  Notes (down) IAM; 600.139; 600.118; 600.145 Approved no  
  Call Number Admin @ si @ GHE2022 Serial 3721  
Permanent link to this record
 

 
Author 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  
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  Series Editor Series Title Abbreviated Series Title  
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  ISSN ISBN Medium  
  Area Expedition Conference CCIA  
  Notes (down) IAM; 600.139; 600.118; 600.145 Approved no  
  Call Number Admin @ si @ Serial 3723  
Permanent link to this record
 

 
Author Debora Gil; Ruth Aris; Agnes Borras; Esmitt Ramirez; Rafael Sebastian; Mariano Vazquez edit   pdf
doi  openurl
  Title Influence of fiber connectivity in simulations of cardiac biomechanics Type Journal Article
  Year 2019 Publication International Journal of Computer Assisted Radiology and Surgery Abbreviated Journal IJCAR  
  Volume 14 Issue 1 Pages 63–72  
  Keywords Cardiac electromechanical simulations; Diffusion tensor imaging; Fiber connectivity  
  Abstract PURPOSE:
Personalized computational simulations of the heart could open up new improved approaches to diagnosis and surgery assistance systems. While it is fully recognized that myocardial fiber orientation is central for the construction of realistic computational models of cardiac electromechanics, the role of its overall architecture and connectivity remains unclear. Morphological studies show that the distribution of cardiac muscular fibers at the basal ring connects epicardium and endocardium. However, computational models simplify their distribution and disregard the basal loop. This work explores the influence in computational simulations of fiber distribution at different short-axis cuts.

METHODS:
We have used a highly parallelized computational solver to test different fiber models of ventricular muscular connectivity. We have considered two rule-based mathematical models and an own-designed method preserving basal connectivity as observed in experimental data. Simulated cardiac functional scores (rotation, torsion and longitudinal shortening) were compared to experimental healthy ranges using generalized models (rotation) and Mahalanobis distances (shortening, torsion).

RESULTS:
The probability of rotation was significantly lower for ruled-based models [95% CI (0.13, 0.20)] in comparison with experimental data [95% CI (0.23, 0.31)]. The Mahalanobis distance for experimental data was in the edge of the region enclosing 99% of the healthy population.

CONCLUSIONS:
Cardiac electromechanical simulations of the heart with fibers extracted from experimental data produce functional scores closer to healthy ranges than rule-based models disregarding architecture connectivity.
 
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  Area Expedition Conference  
  Notes (down) IAM; 600.096; 601.323; 600.139; 600.145 Approved no  
  Call Number Admin @ si @ GAB2019a Serial 3133  
Permanent link to this record
 

 
Author Mireia Sole; Joan Blanco; Debora Gil; Oliver Valero; G. 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  
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  Abstract  
  Address Florencia; Italia; July 2017  
  Corporate Author Thesis  
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  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference ECA  
  Notes (down) IAM; 600.096; 600.145 Approved no  
  Call Number Admin @ si @ SBG2017a Serial 2936  
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Author Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate edit   pdf
openurl 
  Title Is there a pattern of Chromosome territoriality along mice spermatogenesis? Type Conference Article
  Year 2017 Publication 3rd Spanish MeioNet Meeting Abstract Book Abbreviated Journal  
  Volume Issue Pages 55-56  
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  Abstract  
  Address Miraflores de la Sierra; Madrid; June 2017  
  Corporate Author Thesis  
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  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title  
  Series Volume Series Issue Edition  
  ISSN ISBN Medium  
  Area Expedition Conference MEIONET  
  Notes (down) IAM; 600.096; 600.145 Approved no  
  Call Number Admin @ si @ Serial 2958  
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Author Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Francesca Vidal; Zaida Sarrate edit   pdf
isbn  openurl
  Title Noves perspectives en l estudi de la territorialitat cromosomica de cel·lules germinals masculines: estudis tridimensionals Type Journal
  Year 2017 Publication Biologia de la Reproduccio Abbreviated Journal JBR  
  Volume 15 Issue Pages 73-78  
  Keywords  
  Abstract In somatic cells, chromosomes occupy specific nuclear regions called chromosome territories which are involved in the
maintenance and regulation of the genome. Preliminary data in male germ cells also suggest the importance of chromosome
territoriality in cell functionality. Nevertheless, the specific characteristics of testicular tissue (presence of different
cell types with different morphological characteristics, in different stages of development and with different ploidy)
makes difficult to achieve conclusive results. In this study we have developed a methodology to approach the threedimensional
study of all chromosome territories in male germ cells from C57BL/6J mice (Mus musculus). The method
includes the following steps: i) Optimized cell fixation to obtain an optimal preservation of the three-dimensionality cell
morphology, ii) Chromosome identification by FISH (Chromoprobe Multiprobe® OctoChrome™ Murine System; Cytocell)
and confocal microscopy (TCS-SP5, Leica Microsystems), iii) Cell type identification by immunofluorescence
iv) Image analysis using Matlab scripts, v) Numerical data extraction related to chromosome features, chromosome
radial position and chromosome relative position. This methodology allows the unequivocally identification and the
analysis of the chromosome territories of all spermatogenic stages. Results will provide information about the features
that determine chromosomal position, preferred associations between chromosomes, and the relationship between chromosome
positioning and genome regulation.
 
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  Series Volume Series Issue Edition  
  ISSN ISBN 978-84-697-3767-5 Medium  
  Area Expedition Conference  
  Notes (down) IAM; 600.096; 600.145 Approved no  
  Call Number Admin @ si @ SBG2017c Serial 2961  
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