Search results for "ECoG"

showing 10 items of 3774 documents

Valutazione delle lesioni focali del tendine del sovraspinato con elastosonografia: confronto con ecografia B-mode e risonanza magnetica: esperienza …

2012

Obiettivo. Scopo dello studio era valutare l’elasticità del tendine del sovraspinato nella spalla sintomatica di pazienti con sospetto clinico di rottura unilaterale della cuffia dei rotatori, e comparare i reperti riscontrati con quelli dell’ecografia convenzionale (ultrasound, US) e della risonanza magnetica (RM). Metodi. Nel periodo compreso tra gennaio e dicembre 2009 sono state esaminate da un radiologo entrambe le spalle di 58 pazienti (età media: 46 anni; range 32-58 anni) sia con modulo elastosonografico in real-time che in B-mode tramite uno stesso ecografo (EUB - Hitachi 7500), usando una sonda lineare a elevata frequenza (13 MHz). L’elasticità delle fibre tendinee del sovraspinat…

risonanza magneticaecogragiaelastosonografialesionesovraspinato
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trattamento ecoguidato della rizo artrosi con steroidi e acido ialuronico .

2014

rizoartrosi infiltrazione ecoguidata
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Contributions à l’imagerie polarimétrique et à ses applications en vision pour la robotique

2019

Ce mémoire présente le bilan de l'ensemble de mes travaux de recherche effectués de septembre 2006 à juin 2019 au sein de l'équipe Creusotine du laboratoire Le2i devenue équipe Vibot ERL CNRS 6000 depuis janvier 2018. Les principales activités de recherche que j'ai menées au cours de ces 10 dernières années autour de l'imagerie polarimétrique, de la vision omnidirectionnelle et de leurs applications en vision pour la robotique seront particulièrement détaillées dans ce document. Elles seront présentées selon deux grandes parties : la première concernera plutôt l'aspect mise en œuvre et calibrage des caméras et la seconde se concentrera sur les applications potentielles en vision pour la rob…

robotics[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing[INFO.INFO-TI] Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing[INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Polarimetric imaging systemcomputer visionImagerie polarimétriquevision pour la robotique
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Contributions à l'analyse et à l'interprétation des images : Extraction et représentation de caractéristiques

2016

Ce mémoire, rédigé en vue de l'obtention de l'Habilitation à Diriger des Recherches (HDR), offre un aperçu des travaux de recherche et d’encadrement que j’ai pu mener depuis l'obtention de mon doctorat. Il montre la diversité des champs d’application et de recherche (en vision et en imagerie médicale) que j’ai pu couvrir , ainsi que mon implication dans l’encadrement doctoral.Mes activités de recherche se divisent en deux grandes parties. D'une part, l'analyse de scènes dynamiques, à savoir la détection de regions d'intérêt dans des séquences d'images, pour réduire la taile des données à traiter, et la détection et le suivi d'objets mobiles à l'aide de caméras de diverses natures (perspecti…

rétinopathie diabétique[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV][INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]imagerie OCTObject tracking[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Visual saliency detectionAttention visuellesuivi d'objetsDiabetic retinopathy screeningOCT retinal imaging
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Visual saliency by keypoints distribution analysis

2011

In this paper we introduce a new method for Visual Saliency detection. The goal of our method is to emphasize regions that show rare visual aspects in comparison with those showing frequent ones. We propose a bottom up approach that performs a new technique based on low level image features (texture) analysis. More precisely, we use SIFT Density Maps (SDM), to study the distribution of keypoints into the image with different scales of observation, and its relationship with real fixation points. The hypothesis is that the image regions that show a larger distance from the mode (most frequent value) of the keypoints distribution over all the image are the same that better capture our visual a…

saliency visual attentiontexture SIFTComputer sciencebusiness.industryFixation (visual)ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONVisual attentionScale-invariant feature transformPattern recognitionComputer visionTop-down and bottom-up designArtificial intelligencebusinessVisual saliency
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Automated Detection of Microaneurysms Using Scale-Adapted Blob Analysis and Semi-Supervised Learning

2014

International audience; Despite several attempts, automated detection of microaneurysm (MA) from digital fundus images still remains to be an open issue. This is due to the subtle nature of MAs against the surrounding tissues. In this paper, the microaneurysm detection problem is modeled as finding interest regions or blobs from an image and an automatic local-scale selection technique is presented. Several scale-adapted region descriptors are then introduced to characterize these blob regions. A semi-supervised based learning approach, which requires few manually annotated learning examples, is also proposed to train a classifier to detect true MAs. The developed system is built using only…

semi-supervised learningFundus OculiComputer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONMicroaneurysmsblobsHealth Informatics02 engineering and technologySemi-supervised learningFundus (eye)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]030218 nuclear medicine & medical imagingScale spaceAutomation03 medical and health scienceschemistry.chemical_compound0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineHumansLearningComputer visionBlob analysisMicroaneurysmbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]RetinalDiabetic retinopathymedicine.diseaseAneurysmComputer Science Applicationsdiabetic retinopathyfundus imagechemistryscale-space.scale-space020201 artificial intelligence & image processingArtificial intelligencebusinessClassifier (UML)SoftwareRetinopathy
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Some Investigations on Similarity Measures Based on Absent Words

2019

In this paper we investigate similarity measures based on minimal absent words, introduced by Chairungsee and Crochemore in [1]. They make use of a length-weighted index on a sample set corresponding to the symmetric difference M(x)ΔM(y) of the minimal absent words M(x) and M(y) of two sequences x and y, respectively. We first propose a variant of this measure by choosing as a sample set a proper subset (x, y) of M(x)ΔM(y), which appears to be more appropriate for distinguishing x and y. From the algebraic point of view, we prove that (x, y) is the base of the ideal generated by M(x)ΔM(y). We then remark that such measures are able to recognize whether the sequences x and y share a common s…

sequence comparisonAlgebra and Number TheorySettore INF/01 - Informaticabusiness.industryComputer sciencePattern recognitionsimilarity measuresMinimal absent wordsTheoretical Computer ScienceComputational Theory and MathematicsSimilarity (network science)Artificial intelligencebusinessInformation SystemsFundamenta Informaticae
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METODOLOGIE E TECNICHE PER L’ANALISI DI DATI COMPLESSI IN AMBIENTE ECOGRAFICO PRENATALE

sezione sagittale medianaecografia prenataleSettore INF/01 - InformaticaTranslucenza Nucale; NT; sezione sagittale mediana; ecografia prenatale;nuchal translucency;NTTranslucenza Nucalenuchal translucency
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A Shape-based Statistical Method to Retrieve 2D TRUS-MR Slice Correspondence for Prostate Biopsy

2012

International audience; This paper presents a method based on shape-context and statistical measures to match interventional 2D Trans Rectal Ultrasound (TRUS) slice during prostate biopsy to a 2D Magnetic Resonance (MR) slice of a pre-acquired prostate volume. Accurate biopsy tissue sampling requires translation of the MR slice information on the TRUS guided biopsy slice. However, this translation or fusion requires the knowledge of the spatial position of the TRUS slice and this is only possible with the use of an electro-magnetic (EM) tracker attached to the TRUS probe. Since, the use of EM tracker is not common in clinical practice and 3D TRUS is not used during biopsy, we propose to per…

shape-contextProstate biopsyComputer science[INFO.INFO-IM] Computer Science [cs]/Medical Imaging030230 surgeryTranslation (geometry)[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]urologic and male genital diseasesRectal ultrasound030218 nuclear medicine & medical imagingProstate biopsy03 medical and health sciences0302 clinical medicine[INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]ProstateBiopsymedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingComputer visionnormalized mutual information.normalized mutual informationmedicine.diagnostic_test[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Magnetic resonance imagingTissue samplingmedicine.anatomical_structure2D TRUS/3D MR correspondenceArtificial intelligenceUltrasonographybusiness
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Deep-learning based reconstruction of the shower maximum X max using the water-Cherenkov detectors of the Pierre Auger Observatory

2021

The atmospheric depth of the air shower maximum $X_{\mathrm{max}}$ is an observable commonly used for the determination of the nuclear mass composition of ultra-high energy cosmic rays. Direct measurements of $X_{\mathrm{max}}$ are performed using observations of the longitudinal shower development with fluorescence telescopes. At the same time, several methods have been proposed for an indirect estimation of $X_{\mathrm{max}}$ from the characteristics of the shower particles registered with surface detector arrays. In this paper, we present a deep neural network (DNN) for the estimation of $X_{\mathrm{max}}$. The reconstruction relies on the signals induced by shower particles in the groun…

showers: energylongitudinal [showers]interaction: modelPhysics::Instrumentation and DetectorsAstronomyCalibration and fitting methods; Cluster finding; Data analysis; Large detector systems for particle and astroparticle physics; Particle identification methods; Pattern recognition01 natural sciencesHigh Energy Physics - ExperimentAugerHigh Energy Physics - Experiment (hep-ex)Particle identification methodscluster findingsurface [detector]ObservatoryLarge detector systemsInstrumentationMathematical PhysicsHigh Energy Astrophysical Phenomena (astro-ph.HE)astro-ph.HEPhysicsPattern recognition cluster finding calibration and fitting methodsPhysicsSettore FIS/01 - Fisica Sperimentalemodel [interaction]DetectorAstrophysics::Instrumentation and Methods for AstrophysicsData analysicalibration and fitting methodsenergy [showers]AugerobservatoryPattern recognition cluster finding calibration and fitting methodastroparticle physicsAstrophysics - Instrumentation and Methods for AstrophysicsAstrophysics - High Energy Astrophysical Phenomenaatmosphere [showers]airneural networkAstrophysics::High Energy Astrophysical PhenomenaUHE [cosmic radiation]Data analysisFOS: Physical sciences610Cosmic raydetector: fluorescencePattern recognition0103 physical sciencesddc:530High Energy Physicsddc:610[PHYS.PHYS.PHYS-INS-DET]Physics [physics]/Physics [physics]/Instrumentation and Detectors [physics.ins-det]cosmic radiation: UHEstructureparticle physicsnetwork: performance010306 general physicsInstrumentation and Methods for Astrophysics (astro-ph.IM)Ciencias ExactasCherenkov radiationfluorescence [detector]Pierre Auger ObservatoryCalibration and fitting methodsmass spectrum [nucleus]showers: atmospheredetector: surfacehep-ex010308 nuclear & particles physicsLarge detector systems for particle and astroparticle physicsCluster findingFísicaresolutioncalibrationComputational physicsperformance [network]Cherenkov counterAir showerLarge detector systems for particle and astroparticle physicExperimental High Energy PhysicsHigh Energy Physics::Experimentnucleus: mass spectrumshowers: longitudinalRAIOS CÓSMICOSEnergy (signal processing)astro-ph.IM
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