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Author |
Esmitt Ramirez; Carles Sanchez; Debora Gil |
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Title |
Localizing Pulmonary Lesions Using Fuzzy Deep Learning |
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Conference Article |
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2019 |
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21st International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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290-294 |
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The usage of medical images is part of the clinical daily in several healthcare centers around the world. Particularly, Computer Tomography (CT) images are an important key in the early detection of suspicious lung lesions. The CT image exploration allows the detection of lung lesions before any invasive procedure (e.g. bronchoscopy, biopsy). The effective localization of lesions is performed using different image processing and computer vision techniques. Lately, the usage of deep learning models into medical imaging from detection to prediction shown that is a powerful tool for Computer-aided software. In this paper, we present an approach to localize pulmonary lung lesion using fuzzy deep learning. Our approach uses a simple convolutional neural network based using the LIDC-IDRI dataset. Each image is divided into patches associated a probability vector (fuzzy) according their belonging to anatomical structures on a CT. We showcase our approach as part of a full CAD system to exploration, planning, guiding and detection of pulmonary lesions. |
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Timisoara; Rumania; September 2019 |
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IAM; 600.145; 600.140; 601.337; 601.323 |
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Admin @ si @ RSG2019 |
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3531 |
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Author |
Carles Sanchez; Miguel Viñas; Coen Antens; Agnes Borras; Debora Gil |
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Title |
Back to Front Architecture for Diagnosis as a Service |
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2018 |
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20th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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343-346 |
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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. |
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Timisoara; Rumania; September 2018 |
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IAM; 600.145 |
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Admin @ si @ SVA2018 |
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3360 |
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Debora Gil; Aura Hernandez-Sabate; David Castells; Jordi Carrabina |
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CYBERH: Cyber-Physical Systems in Health for Personalized Assistance |
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2017 |
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International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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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. |
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Timisoara; Rumania; September 2017 |
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IAM; 600.085; 600.096; 600.075; 600.145 |
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Admin @ si @ GHC2017 |
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3045 |
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David Roche; Debora Gil; Jesus Giraldo |
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Title |
Detecting loss of diversity for an efficient termination of EAs |
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2013 |
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15th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing |
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561 - 566 |
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EA termination; EA population diversity; EA steady state |
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Termination of Evolutionary Algorithms (EA) at its steady state so that useless iterations are not performed is a main point for its efficient application to black-box problems. Many EA algorithms evolve while there is still diversity in their population and, thus, they could be terminated by analyzing the behavior some measures of EA population diversity. This paper presents a numeric approximation to steady states that can be used to detect the moment EA population has lost its diversity for EA termination. Our condition has been applied to 3 EA paradigms based on diversity and a selection of functions
covering the properties most relevant for EA convergence.
Experiments show that our condition works regardless of the search space dimension and function landscape. |
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Timisoara; Rumania; |
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978-1-4799-3035-7 |
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IAM; 600.044; 600.060; 605.203 |
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Admin @ si @ RGG2013c |
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2299 |
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Stepan Simsa; Michal Uricar; Milan Sulc; Yash Patel; Ahmed Hamdi; Matej Kocian; Matyas Skalicky; Jiri Matas; Antoine Doucet; Mickael Coustaty; Dimosthenis Karatzas |
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Title |
Overview of DocILE 2023: Document Information Localization and Extraction |
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Conference Article |
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2023 |
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International Conference of the Cross-Language Evaluation Forum for European Languages |
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14163 |
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276–293 |
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Information Extraction; Computer Vision; Natural Language Processing; Optical Character Recognition; Document Understanding |
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This paper provides an overview of the DocILE 2023 Competition, its tasks, participant submissions, the competition results and possible future research directions. This first edition of the competition focused on two Information Extraction tasks, Key Information Localization and Extraction (KILE) and Line Item Recognition (LIR). Both of these tasks require detection of pre-defined categories of information in business documents. The second task additionally requires correctly grouping the information into tuples, capturing the structure laid out in the document. The competition used the recently published DocILE dataset and benchmark that stays open to new submissions. The diversity of the participant solutions indicates the potential of the dataset as the submissions included pure Computer Vision, pure Natural Language Processing, as well as multi-modal solutions and utilized all of the parts of the dataset, including the annotated, synthetic and unlabeled subsets. |
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Thessaloniki; Greece; September 2023 |
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DAG |
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Admin @ si @ SUS2023a |
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3924 |
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Konstantia Georgouli; Katerine Diaz; Jesus Martinez del Rincon; Anastasios Koidis |
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Building generic, easily-updatable chemometric models with harmonisation and augmentation features: The case of FTIR vegetable oils classification |
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2017 |
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3rd Ιnternational Conference Metrology Promoting Standardization and Harmonization in Food and Nutrition |
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Thessaloniki; Greece; October 2017 |
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IMEKOFOODS |
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ADAS; 600.118 |
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Admin @ si @ GDM2017 |
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3081 |
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Author |
Fernando Vilariño |
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Public Libraries Exploring how technology transforms the cultural experience of people |
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2019 |
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Workshop on Social Impact of AI. Open Living Lab Days Conference. |
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Thessaloniki; Grecia; September 2019 |
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MV; DAG; 600.140; 600.121;SIAI |
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Admin @ si @ Vil2019b |
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3458 |
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Author |
Angel Sappa |
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Title |
Automatic Extraction of Planar Projections from Panoramic Range Images |
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2004 |
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IEEE Int. Symp. on 3D Data Processing, Visualization and Transmission |
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454 |
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Angel Sappa |
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Surface Model Generation from Range Images of Industrial Environments |
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2004 |
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IEEE Int. Symp. on 3D Data Processing, Visualization and Transmission |
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Angel Sappa; Niki Aifanti; Sotiris Malassiotis; Michael G. Strintzis |
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Unsupervised Motion Classification by means of Efficient Feature Selection and Tracking |
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2004 |
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IEEE Int. Symp. on 3D Data Processing, Visualization and Transmission |
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ADAS @ adas @ SAM2004a |
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Oriol Pujol; David Rotger; Petia Radeva; O. Rodriguez; J. Mauri |
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Near Real Time Plaque Segmentation of IVUS |
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2003 |
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Proceedings of Computers in Cardiology |
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MILAB;HuPBA |
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Petia Radeva; Jordi Vitria |
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Region-Based Approach for Discriminant Snakes |
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2001 |
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Proceedings of ICIP |
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Hanne Kause; Patricia Marquez; Andrea Fuster; Aura Hernandez-Sabate; Luc Florack; Debora Gil; Hans van Assen |
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Quality Assessment of Optical Flow in Tagging MRI |
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2015 |
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5th Dutch Bio-Medical Engineering Conference BME2015 |
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The Netherlands; January 2015 |
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IAM; ADAS; 600.076; 600.075 |
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Admin @ si @ KMF2015 |
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2616 |
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David Rotger; Petia Radeva; Cristina Cañero; Juan J. Villanueva; J. Mauri; E Fernandez-Nofrerias; A. Tovar; V. Valle |
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Corresponding IVUS and Angiogram Image Data |
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2001 |
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Proceedings of Computers in Cardiology Rottherdam, (in press). |
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The Netherlands |
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BCNPCL @ bcnpcl @ RRC2001 |
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159 |
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Eduard Vazquez; Ramon Baldrich |
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Colour Image Segmentation in Presence of Shadows |
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2008 |
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4th European Conference on Colour in Graphics, Imaging and Vision Proceedings |
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383–387 |
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Terrassa (Spain) |
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Publisher |
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Place of Publication |
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Editor |
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Language |
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Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
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ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
CGIV08 |
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Notes |
CAT;CIC |
Approved |
no |
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Call Number |
CAT @ cat @ VaB2008 |
Serial |
966 |
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