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| Author | Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate | ||||
| 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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| Address | Miraflores de la Sierra; Madrid; June 2017 | ||||
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| Area | Expedition | Conference | MEIONET | ||
Notes  |
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 | ||||
| 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 | |
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| 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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| ISSN | ISBN | 978-84-697-3767-5 | Medium | ||
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| Notes |
IAM; 600.096; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ SBG2017c | Serial | 2961 | ||
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| Author | Mireia Sole; Joan Blanco; Debora Gil; G. Fonseka; Richard Frodsham; Oliver Valero; Francesca Vidal; Zaida Sarrate | ||||
| Title | Análisis 3d de la territorialidad cromosómica en células espermatogénicas: explorando la infertilidad desde un nuevo prisma | Type | Journal | ||
| Year | 2017 | Publication | Revista Asociación para el Estudio de la Biología de la Reproducción | Abbreviated Journal | ASEBIR |
| Volume | 22 | Issue | 2 | Pages | 105 |
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IAM; 600.096; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ SBG2017d | Serial | 3042 | ||
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| Author | Debora Gil; Ruth Aris; Agnes Borras; Esmitt Ramirez; Rafael Sebastian; Mariano Vazquez | ||||
| 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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| Notes |
IAM; 600.096; 601.323; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ GAB2019a | Serial | 3133 | ||
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| Author | Debora Gil; Aura Hernandez-Sabate; Julien Enconniere; Saryani Asmayawati; Pau Folch; Juan Borrego-Carazo; Miquel Angel Piera | ||||
| 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 | |
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| 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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| Notes |
IAM; 600.139; 600.118; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ GHE2022 | Serial | 3721 | ||
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| Author | Jose Elias Yauri; Aura Hernandez-Sabate; Pau Folch; Debora Gil | ||||
| 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. |
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| Address | Virtual; October 20-22 2021 | ||||
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| 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 | Debora Gil; Antonio Esteban Lansaque; Agnes Borras; Carles Sanchez | ||||
| Title | Enhancing virtual bronchoscopy with intra-operative data using a multi-objective GAN | Type | Journal Article | ||
| Year | 2019 | Publication | International Journal of Computer Assisted Radiology and Surgery | Abbreviated Journal | IJCAR |
| Volume | 7 | Issue | 1 | Pages | |
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| Abstract | This manuscript has been withdrawn by bioRxiv due to upload of an incorrect version of the manuscript by the authors. Therefore, this manuscript should not be cited as reference for this project. | ||||
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IAM; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ GEB2019 | Serial | 3307 | ||
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| Author | Debora Gil; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell | ||||
| Title | Segmentation of Distal Airways using Structural Analysis | Type | Journal Article | ||
| Year | 2019 | Publication | PloS one | Abbreviated Journal | Plos |
| Volume | 14 | Issue | 12 | Pages | |
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| Abstract | Segmentation of airways in Computed Tomography (CT) scans is a must for accurate support of diagnosis and intervention of many pulmonary disorders. In particular, lung cancer diagnosis would benefit from segmentations reaching most distal airways. We present a method that combines descriptors of bronchi local appearance and graph global structural analysis to fine-tune thresholds on the descriptors adapted for each bronchial level. We have compared our method to the top performers of the EXACT09 challenge and to a commercial software for biopsy planning evaluated in an own-collected data-base of high resolution CT scans acquired under different breathing conditions. Results on EXACT09 data show that our method provides a high leakage reduction with minimum loss in airway detection. Results on our data-base show the reliability across varying breathing conditions and a competitive performance for biopsy planning compared to a commercial solution. | ||||
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IAM; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ GSB2019 | Serial | 3357 | ||
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| Author | Marta Ligero; Guillermo Torres; Carles Sanchez; Katerine Diaz; Raquel Perez; Debora Gil | ||||
| Title | Selection of Radiomics Features based on their Reproducibility | Type | Conference Article | ||
| Year | 2019 | Publication | 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society | Abbreviated Journal | |
| Volume | Issue | Pages | 403-408 | ||
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| Abstract | Dimensionality reduction is key to alleviate machine learning artifacts in clinical applications with Small Sample Size (SSS) unbalanced datasets. Existing methods rely on either the probabilistic distribution of training data or the discriminant power of the reduced space, disregarding the impact of repeatability and uncertainty in features.In the present study is proposed the use of reproducibility of radiomics features to select features with high inter-class correlation coefficient (ICC). The reproducibility includes the variability introduced in the image acquisition, like medical scans acquisition parameters and convolution kernels, that affects intensity-based features and tumor annotations made by physicians, that influences morphological descriptors of the lesion.For the reproducibility of radiomics features three studies were conducted on cases collected at Vall Hebron Oncology Institute (VHIO) on responders to oncology treatment. The studies focused on the variability due to the convolution kernel, image acquisition parameters, and the inter-observer lesion identification. The features selected were those features with a ICC higher than 0.7 in the three studies.The selected features based on reproducibility were evaluated for lesion malignancy classification using a different database. Results show better performance compared to several state-of-the-art methods including Principal Component Analysis (PCA), Kernel Discriminant Analysis via QR decomposition (KDAQR), LASSO, and an own built Convolutional Neural Network. | ||||
| Address | Berlin; Alemanya; July 2019 | ||||
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| Area | Expedition | Conference | EMBC | ||
| Notes |
IAM; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ LTS2019 | Serial | 3358 | ||
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| Author | Debora Gil; Antoni Rosell | ||||
| Title | Advances in Artificial Intelligence – How Lung Cancer CT Screening Will Progress? | Type | Abstract | ||
| Year | 2019 | Publication | World Lung Cancer Conference | Abbreviated Journal | |
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| Abstract | Invited speaker | ||||
| Address | Barcelona; September 2019 | ||||
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| Area | Expedition | Conference | IASLC WCLC | ||
| Notes |
IAM; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ GiR2019 | Serial | 3361 | ||
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| Author | Antonio Esteban Lansaque | ||||
| Title | An Endoscopic Navigation System for Lung Cancer Biopsy | Type | Book Whole | ||
| Year | 2019 | Publication | PhD Thesis, Universitat Autonoma de Barcelona-CVC | Abbreviated Journal | |
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| Abstract | Lung cancer is one of the most diagnosed cancers among men and women. Actually,
lung cancer accounts for 13% of the total cases with a 5-year global survival rate in patients. Although Early detection increases survival rate from 38% to 67%, accurate diagnosis remains a challenge. Pathological confirmation requires extracting a sample of the lesion tissue for its biopsy. The preferred procedure for tissue biopsy is called bronchoscopy. A bronchoscopy is an endoscopic technique for the internal exploration of airways which facilitates the performance of minimal invasive interventions with low risk for the patient. Recent advances in bronchoscopic devices have increased their use for minimal invasive diagnostic and intervention procedures, like lung cancer biopsy sampling. Despite the improvement in bronchoscopic device quality, there is a lack of intelligent computational systems for supporting in-vivo clinical decision during examinations. Existing technologies fail to accurately reach the lesion due to several aspects at intervention off-line planning and poor intra-operative guidance at exploration time. Existing guiding systems radiate patients and clinical staff,might be expensive and achieve a suboptimlal 70% of yield boost. Diagnostic yield could be improved reducing radiation and costs by developing intra-operative support systems able to guide the bronchoscopist to the lesion during the intervention. The goal of this PhD thesis is to develop an image-based navigation systemfor intra-operative guidance of bronchoscopists to a target lesion across a path previously planned on a CT-scan. We propose a 3D navigation system which uses the anatomy of video bronchoscopy frames to locate the bronchoscope within the airways. Once the bronchoscope is located, our navigation system is able to indicate the bifurcation which needs to be followed to reach the lesion. In order to facilitate an off-line validation as realistic as possible, we also present a method for augmenting simulated virtual bronchoscopies with the appearance of intra-operative videos. Experiments performed on augmented and intra-operative videos, prove that our algorithm can be speeded up for an on-line implementation in the operating room. |
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| Address | October 2019 | ||||
| Corporate Author | Thesis | Ph.D. thesis | |||
| Publisher | Ediciones Graficas Rey | Place of Publication | Editor | Debora Gil;Carles Sanchez | |
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| ISSN | ISBN | 978-84-121011-0-2 | Medium | ||
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| Notes |
IAM; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ Est2019 | Serial | 3392 | ||
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| Author | Debora Gil; Antonio Esteban Lansaque; Agnes Borras; Esmitt Ramirez; Carles Sanchez | ||||
| 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 | |
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| 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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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 | ||||
| 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 |
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| 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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IAM; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ MHE2022 | Serial | 3468 | ||
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| Author | Debora Gil; Guillermo Torres | ||||
| 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 | |
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| Address | Virtual; June 2020 | ||||
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| Area | Expedition | Conference | CARS | ||
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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 | ||||
| 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. |
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| Address | Jan 2022 | ||||
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IAM; 600.139; 600.145 | Approved | no | ||
| Call Number | Admin @ si @ TBS2022 | Serial | 3699 | ||
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