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Author Debora Gil; Aura Hernandez-Sabate; David Castells; Jordi Carrabina edit   pdf
openurl 
  Title CYBERH: Cyber-Physical Systems in Health for Personalized Assistance Type Conference Article
  Year 2017 Publication International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages  
  Keywords  
  Abstract Assistance systems for e-Health applications have some specific requirements that demand of new methods for data gathering, analysis and modeling able to deal with SmallData:
1) systems should dynamically collect data from, both, the environment and the user to issue personalized recommendations; 2) data analysis should be able to tackle a limited number of samples prone to include non-informative data and possibly evolving in time due to changes in patient condition; 3) algorithms should run in real time with possibly limited computational resources and fluctuant internet access.
Electronic medical devices (and CyberPhysical devices in general) can enhance the process of data gathering and analysis in several ways: (i) acquiring simultaneously multiple sensors data instead of single magnitudes (ii) filtering data; (iii) providing real-time implementations condition by isolating tasks in individual processors of multiprocessors Systems-on-chip (MPSoC) platforms and (iv) combining information through sensor fusion
techniques.
Our approach focus on both aspects of the complementary role of CyberPhysical devices and analysis of SmallData in the process of personalized models building for e-Health applications. In particular, we will address the design of Cyber-Physical Systems in Health for Personalized Assistance (CyberHealth) in two specific application cases: 1) A Smart Assisted Driving System (SADs) for dynamical assessment of the driving capabilities of Mild Cognitive Impaired (MCI) people; 2) An Intelligent Operating Room (iOR) for improving the yield of bronchoscopic interventions for in-vivo lung cancer diagnosis.
 
  Address Timisoara; Rumania; September 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 (up) Expedition Conference SYNASC  
  Notes IAM; 600.085; 600.096; 600.075; 600.145 Approved no  
  Call Number Admin @ si @ GHC2017 Serial 3045  
Permanent link to this record
 

 
Author Esmitt Ramirez; Carles Sanchez; Agnes Borras; Marta Diez-Ferrer; Antoni Rosell; Debora Gil edit   pdf
url  openurl
  Title Image-Based Bronchial Anatomy Codification for Biopsy Guiding in Video Bronchoscopy Type Conference Article
  Year 2018 Publication OR 2.0 Context-Aware Operating Theaters, Computer Assisted Robotic Endoscopy, Clinical Image-Based Procedures, and Skin Image Analysis Abbreviated Journal  
  Volume 11041 Issue Pages  
  Keywords Biopsy guiding; Bronchoscopy; Lung biopsy; Intervention guiding; Airway codification  
  Abstract Bronchoscopy examinations allow biopsy of pulmonary nodules with minimum risk for the patient. Even for experienced bronchoscopists, it is difficult to guide the bronchoscope to most distal lesions and obtain an accurate diagnosis. This paper presents an image-based codification of the bronchial anatomy for bronchoscopy biopsy guiding. The 3D anatomy of each patient is codified as a binary tree with nodes representing bronchial levels and edges labeled using their position on images projecting the 3D anatomy from a set of branching points. The paths from the root to leaves provide a codification of navigation routes with spatially consistent labels according to the anatomy observes in video bronchoscopy explorations. We evaluate our labeling approach as a guiding system in terms of the number of bronchial levels correctly codified, also in the number of labels-based instructions correctly supplied, using generalized mixed models and computer-generated data. Results obtained for three independent observers prove the consistency and reproducibility of our guiding system. We trust that our codification based on viewer’s projection might be used as a foundation for the navigation process in Virtual Bronchoscopy systems.  
  Address Granada; September 2018  
  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 (up) Expedition Conference MICCAIW  
  Notes IAM; 600.096; 600.075; 601.323; 600.145 Approved no  
  Call Number Admin @ si @ RSB2018b Serial 3137  
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Author Marta Ligero; Guillermo Torres; Carles Sanchez; Katerine Diaz; Raquel Perez; Debora Gil edit  url
doi  openurl
  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  
  Keywords  
  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  
  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 (up) Expedition Conference EMBC  
  Notes IAM; no menciona Approved no  
  Call Number Admin @ si @ LTS2019 Serial 3358  
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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 (up) Expedition Conference CLIP  
  Notes IAM; 600.145; 601.337 Approved no  
  Call Number Admin @ si @ GES2019 Serial 3359  
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Author Carles Sanchez; Miguel Viñas; Coen Antens; Agnes Borras; Debora Gil edit  url
doi  openurl
  Title Back to Front Architecture for Diagnosis as a Service Type Conference Article
  Year 2018 Publication 20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing Abbreviated Journal  
  Volume Issue Pages 343-346  
  Keywords  
  Abstract Software as a Service (SaaS) is a cloud computing model in which a provider hosts applications in a server that customers use via internet. Since SaaS does not require to install applications on customers' own computers, it allows the use by multiple users of highly specialized software without extra expenses for hardware acquisition or licensing. A SaaS tailored for clinical needs not only would alleviate licensing costs, but also would facilitate easy access to new methods for diagnosis assistance. This paper presents a SaaS client-server architecture for Diagnosis as a Service (DaaS). The server is based on docker technology in order to allow execution of softwares implemented in different languages with the highest portability and scalability. The client is a content management system allowing the design of websites with multimedia content and interactive visualization of results allowing user editing. We explain a usage case that uses our DaaS as crowdsourcing platform in a multicentric pilot study carried out to evaluate the clinical benefits of a software for assessment of central airway obstruction.  
  Address Timisoara; Rumania; September 2018  
  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 (up) Expedition Conference SYNASC  
  Notes IAM; no menciona Approved no  
  Call Number Admin @ si @ SVA2018 Serial 3360  
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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 (up) 800 Expedition Conference CLIP  
  Notes MV; IAM; 600.047; 600.044; 600.060 Approved no  
  Call Number Admin @ si @ SBG2013 Serial 2302  
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Author Carles Sanchez; Debora Gil; Antoni Rosell; Albert Andaluz; F. Javier Sanchez edit   pdf
isbn  openurl
  Title Segmentation of Tracheal Rings in Videobronchoscopy combining Geometry and Appearance Type Conference Article
  Year 2013 Publication Proceedings of the International Conference on Computer Vision Theory and Applications Abbreviated Journal  
  Volume 1 Issue Pages 153--161  
  Keywords Video-bronchoscopy, tracheal ring segmentation, trachea geometric and appearance model  
  Abstract Videobronchoscopy is a medical imaging technique that allows interactive navigation inside the respiratory pathways and minimal invasive interventions. Tracheal procedures are ordinary interventions that require measurement of the percentage of obstructed pathway for injury (stenosis) assessment. Visual assessment of stenosis in videobronchoscopic sequences requires high expertise of trachea anatomy and is prone to human error. Accurate detection of tracheal rings is the basis for automated estimation of the size of stenosed trachea. Processing of videobronchoscopic images acquired at the operating room is a challenging task due to the wide range of artifacts and acquisition conditions. We present a model of the geometric-appearance of tracheal rings for its detection in videobronchoscopic videos. Experiments on sequences acquired at the operating room, show a performance close to inter-observer variability  
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher SciTePress Place of Publication Portugal Editor Sebastiano Battiato and José Braz  
  Language Summary Language Original Title  
  Series Editor Series Title Abbreviated Series Title LNCS  
  Series Volume Series Issue Edition  
  ISSN ISBN 978-989-8565-47-1 Medium  
  Area (up) 800 Expedition Conference VISAPP  
  Notes IAM;MV; 600.044; 600.047; 600.060; 605.203 Approved no  
  Call Number IAM @ iam @ SGR2013 Serial 2123  
Permanent link to this record
 

 
Author Joan M. Nuñez; Debora Gil; Fernando Vilariño edit  doi
openurl 
  Title Finger joint characterization from X-ray images for rheymatoid arthritis assessment Type Conference Article
  Year 2013 Publication 6th International Conference on Biomedical Electronics and Devices Abbreviated Journal  
  Volume Issue Pages 288-292  
  Keywords Rheumatoid Arthritis; X-Ray; Hand Joint; Sclerosis; Sharp Van der Heijde  
  Abstract In this study we propose amodular systemfor automatic rheumatoid arthritis assessment which provides a joint space width measure. A hand joint model is proposed based on the accurate analysis of a X-ray finger joint image sample set. This model shows that the sclerosis and the lower bone are the main necessary features in order to perform a proper finger joint characterization. We propose sclerosis and lower bone detection methods as well as the experimental setup necessary for its performance assessment. Our characterization is used to propose and compute a joint space width score which is shown to be related to the different degrees of arthritis. This assertion is verified by comparing our proposed score with Sharp Van der Heijde score, confirming that the lower our score is the more advanced is the patient affection.  
  Address Barcelona; February 2013  
  Corporate Author Thesis  
  Publisher SciTePress 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 (up) 800 Expedition Conference BIODEVICES  
  Notes IAM;MV; 600.057; 600.054 Approved no  
  Call Number IAM @ iam @ NGV2013 Serial 2196  
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