Search results for " Computer Science"

showing 10 items of 3983 documents

NCprocessing: a software to determine non-compacted and compacted masses from MRI

2015

International audience

[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMilieux_MISCELLANEOUS
researchProduct

Indications de l'IRM cardiaque.

1999

International audience

[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[INFO.INFO-IM] Computer Science [cs]/Medical ImagingComputingMilieux_MISCELLANEOUS
researchProduct

Improving the evaluation of cardiac function in rats at 7T by using non-local means filtering.

2012

International audience; Multi-element cardiac coil arrays are often required for signal reception to attain high-quality images of the rat heart. These coils are not yet widely available. We investigated the effect of the non-local means filter on lower quality cardiac cine-MR images, particularly on the accuracy and the variability of cardiac function parameters.

[ INFO.INFO-IM ] Computer Science [cs]/Medical Imaging[INFO.INFO-IM]Computer Science [cs]/Medical Imaging[INFO.INFO-IM] Computer Science [cs]/Medical Imagingcardiovascular system
researchProduct

A Supervised Learning Framework for Automatic Prostate Segmentation in Trans Rectal Ultrasound Images

2012

International audience; Heterogeneous intensity distribution inside the prostate gland, significant variations in prostate shape, size, inter dataset contrast variations, and imaging artifacts like shadow regions and speckle in Trans Rectal Ultrasound (TRUS) images challenge computer aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose a supervised learning schema based on random forest for automatic initialization and propagation of statistical shape and appearance model. Parametric representation of the statistical model of shape and appearance is derived from principal component analysis (PCA) of the probability distribution inside the prostate and PC…

[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industryComputer sciencePosterior probabilitySupervised learning[INFO.INFO-IM] Computer Science [cs]/Medical ImagingStatistical modelPattern recognition02 engineering and technology030218 nuclear medicine & medical imagingRandom forestActive appearance model03 medical and health sciences0302 clinical medicinePoint distribution model0202 electrical engineering electronic engineering information engineering[INFO.INFO-IM]Computer Science [cs]/Medical Imaging020201 artificial intelligence & image processingComputer visionSegmentationArtificial intelligencebusinessParametric statistics
researchProduct

Multiple Mean Models of Statistical Shape and Probability Priors for Automatic Prostate Segmentation

2011

International audience; Low contrast of the prostate gland, heterogeneous intensity distribution inside the prostate region, imaging artifacts like shadow regions, speckle and significant variations in prostate shape, size and in- ter dataset contrast in Trans Rectal Ultrasound (TRUS) images challenge computer aided automatic or semi-automatic segmentation of the prostate. In this paper, we propose a probabilistic framework for automatic initialization and propagation of multiple mean parametric models derived from principal component analysis of shape and posterior probability information of the prostate region to segment the prostate. Unlike traditional statistical models of shape and int…

[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industryPosterior probability[INFO.INFO-IM] Computer Science [cs]/Medical ImagingProbabilistic logicInitializationStatistical modelPattern recognition02 engineering and technology030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicinePrior probabilityParametric modelPrincipal component analysis[INFO.INFO-IM]Computer Science [cs]/Medical Imaging0202 electrical engineering electronic engineering information engineering020201 artificial intelligence & image processingSegmentationArtificial intelligencebusinessMathematics
researchProduct

CLEARMiner: a new algorithm for mining association patterns on heterogeneous time series from climate data

2010

International audience; Recently, improvements in sensor technology contributed to increasing in spatial data acquisition. The use of remote sensing in many countries and states, where agricultural business is a large part of their gross income, can provide a valuable source to improve their economy. The combination of climate and remote sensing data can reveal useful information, which can help researchers to monitor and estimate the production of agricultural crops. Data mining techniques are the main tools to analyze and extract relationships and patterns. In this context, this paper presents a new algorithm for mining association patterns in Geo-referenced databases of climate and satel…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Association rule learning[INFO.INFO-WB] Computer Science [cs]/WebComputer scienceAssociation (object-oriented programming)[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer scienceContext (language use)computer.software_genreNOAA-AVHRR imagesImage-based Information Systemsassociation rules[SCCO.COMP] Cognitive science/Computer science[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]Spatial analysisAgricultural crops[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]Series (mathematics)[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM][ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Remote sensing (archaeology)[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Data mining[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]Vegetation IndexAlgorithmcomputer
researchProduct

User profile matching in social networks

2010

International audience; Inter-social networks operations and functionalities are required in several scenarios (data integration, data enrichment, information retrieval, etc.). To achieve this, matching user profiles is required. Current methods are so restrictive and do not consider all the related problems. Particularly, they assume that two profiles describe the same physical person only if the values of their Inverse Functional Property or IFP (e.g. the email address, homepage, etc.) are the same. However, the observed trend in social networks is not fully compatible with this assumption since users tend to create more than one social network account (for personal use, for work, etc.) w…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Matching (statistics)Computer science[SCCO.COMP]Cognitive science/Computer science02 engineering and technologySimilarity measurecomputer.software_genreElectronic mail[SCCO.COMP] Cognitive science/Computer science020204 information systemsFOAF0202 electrical engineering electronic engineering information engineeringPattern matchingUser profileSocial networkbusiness.industrycomputer.file_formatProfile MatchingSocial Networks[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]020201 artificial intelligence & image processingData mining[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]businesscomputerData integration
researchProduct

Management and interaction with multimodal information content

2010

[Chbeir, Richard] Univ Bourgogne, CNRS, LE2I, Dept Comp Sci, F-21000 Dijon, France. [Coninx, Karin] Univ Hasselt, Expertise Ctr Digital Media EDM, BE-3590 Diepenbeek, Belgium. [Ferri, Fernando; Grifoni, Patrizia] CNR, Inst Res Populat & Social Policies, Rome, Italy.

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Operations research[INFO.INFO-WB] Computer Science [cs]/WebComputer Networks and CommunicationsComputer science[ INFO.INFO-WB ] Computer Science [cs]/WebLibrary science[SCCO.COMP]Cognitive science/Computer science02 engineering and technologyDigital media[SCCO.COMP] Cognitive science/Computer science0202 electrical engineering electronic engineering information engineeringMedia Technology[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB]ComputingMilieux_MISCELLANEOUS[ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]business.industry05 social sciences[INFO.INFO-WB]Computer Science [cs]/Web[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]020207 software engineering[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB]Hardware and Architecture[ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]0509 other social sciences050904 information & library sciencesbusinessSoftware
researchProduct

Toward Approximate GML Retrieval Based on Structural and Semantic Characteristics

2010

International audience; GML is emerging as the new standard for representing geographic information in GISs on the Web, allowing the encoding of structurally and semantically rich geographic data in self describing XML-based geographic entities. In this study, we address the problem of approximate querying and ranked results for GML data and provide a method for GML query evaluation. Our method consists of two main contributions. First, we propose a tree model for representing GML queries and data collections. Then, we introduce a GML retrieval method based on the concept of tree edit distance as an efficient means for comparing semi-structured data. Our approach allows the evaluation of bo…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR]Tree edit distanceSimilarity (geometry)[INFO.INFO-WB] Computer Science [cs]/WebComputer sciencecomputer.internet_protocol[ INFO.INFO-WB ] Computer Science [cs]/Web[SCCO.COMP]Cognitive science/Computer science02 engineering and technologycomputer.software_genre[SCCO.COMP] Cognitive science/Computer science020204 information systemsEncoding (memory)0202 electrical engineering electronic engineering information engineering[INFO.INFO-DB] Computer Science [cs]/Databases [cs.DB][ INFO.INFO-MM ] Computer Science [cs]/Multimedia [cs.MM][INFO.INFO-MM] Computer Science [cs]/Multimedia [cs.MM]Information retrieval[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]GML SearchStructural & Semantic Similarity[INFO.INFO-WB]Computer Science [cs]/WebProcess (computing)[INFO.INFO-MM]Computer Science [cs]/Multimedia [cs.MM]GISConstraint (information theory)[ INFO.INFO-DB ] Computer Science [cs]/Databases [cs.DB][ SCCO.COMP ] Cognitive science/Computer science[INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]Ranked retrieval020201 artificial intelligence & image processingData mining[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR]computerXMLDecision tree model
researchProduct

Towards A Twitter Observatory: A Multi-Paradigm Framework For Collecting, Storing And Analysing Tweets

2016

International audience; In this article we show how a multi-paradigm framework can fulfil the requirements of tweets analysis and reduce the waiting time for researchers that use computational resources and storage systems to support large-scale data analysis. The originality of our approach is to combine concerns about data harvesting, data storage, data analysis and data visualisation into a framework that supports inductive reasoning in multidisciplinary scientific research. Our main contribution is a polyglot storage system with a generic data model to support logical data independence and a set of tools that can provide a suitable solution for mixing different types of algorithms in or…

[ INFO.INFO-IR ] Computer Science [cs]/Information Retrieval [cs.IR][ INFO ] Computer Science [cs]Computer scienceknowledge discovery02 engineering and technology[INFO] Computer Science [cs][INFO.INFO-SI]Computer Science [cs]/Social and Information Networks [cs.SI]Data modelingmassive datasetsopen source softwareData visualization[ INFO.INFO-IT ] Computer Science [cs]/Information Theory [cs.IT]polyglot storage020204 information systems0202 electrical engineering electronic engineering information engineering[INFO]Computer Science [cs]Twitter analysis . SystemsComputingMilieux_MISCELLANEOUS[INFO.INFO-DB]Computer Science [cs]/Databases [cs.DB]business.industryPolyglotInductive reasoningData science[SPI.TRON] Engineering Sciences [physics]/ElectronicsData independence[ SPI.TRON ] Engineering Sciences [physics]/Electronics[SPI.TRON]Engineering Sciences [physics]/ElectronicsData model[INFO.INFO-IT]Computer Science [cs]/Information Theory [cs.IT][INFO.INFO-IR]Computer Science [cs]/Information Retrieval [cs.IR]020201 artificial intelligence & image processing[INFO.INFO-IR] Computer Science [cs]/Information Retrieval [cs.IR][INFO.INFO-IT] Computer Science [cs]/Information Theory [cs.IT]Data architecturebusinessSoftware architecture
researchProduct