Search results for " image processing."

showing 10 items of 2265 documents

An adapted optical flow algorithm for robust quantification of cardiac wall motion from standard cine-MR examinations

2012

International audience; This paper presents a method for local myocardial motion estimation from a conventional steady-state free precession cine-MRI sequence using a modified phase-based optical flow (OF) technique. Initially, the technique was tested on synthetic images to evaluate its robustness with regards to Rician noise and to brightness variations. The method was then applied to cardiac images acquired on 11 healthy subjects. Myocardial velocity is measured in centimeter per second in each studied pixel and visualized as colored vectors superimposed on MRI images. The estimated phase-based OF results were compared with a reference OF method and gave similar results on synthetic imag…

MaleBrightnessPhysics::Medical Physics[INFO.INFO-IM] Computer Science [cs]/Medical Imaging02 engineering and technology030218 nuclear medicine & medical imagingmotion estimation0302 clinical medicineCine-MRI0202 electrical engineering electronic engineering information engineeringImage Processing Computer-AssistedComputer visionMESH : FemaleOptical filterMESH : AlgorithmsMathematicsMESH: Middle Aged[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingGeneral MedicineMESH: Magnetic Resonance Imaging CineMiddle AgedMESH : AdultMESH : Magnetic Resonance Imaging CineMESH: Image Processing Computer-AssistedComputer Science Applicationscardiovascular system020201 artificial intelligence & image processingFemaleAlgorithmsMESH : Image Processing Computer-AssistedBiotechnologyAdultMESH : MaleOptical flowMagnetic Resonance Imaging CineImage processingMESH: Algorithmsheartoptical flow03 medical and health sciencesMESH : HeartRobustness (computer science)Motion estimation[ SDV.MHEP ] Life Sciences [q-bio]/Human health and pathology[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumansMESH : Middle AgedElectrical and Electronic EngineeringCentimeterMESH: HumansPixelbusiness.industryMESH : HumansMESH: AdultMESH: MaleMESH: HeartArtificial intelligencebusinessMESH: Female[SDV.MHEP]Life Sciences [q-bio]/Human health and pathology
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Discrimination of retinal images containing bright lesions using sparse coded features and SVM

2015

Diabetic Retinopathy (DR) is a chronic progressive disease of the retinal microvasculature which is among the major causes of vision loss in the world. The diagnosis of DR is based on the detection of retinal lesions such as microaneurysms, exudates and drusen in retinal images acquired by a fundus camera. However, bright lesions such as exudates and drusen share similar appearances while being signs of different diseases. Therefore, discriminating between different types of lesions is of interest for improving screening performances. In this paper, we propose to use sparse coding techniques for retinal images classification. In particular, we are interested in discriminating between retina…

MaleDatabases Factualgenetic structuresFeature extractionHealth Informatics02 engineering and technologyDrusen[ INFO.INFO-CV ] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]Retina030218 nuclear medicine & medical imaging03 medical and health scienceschemistry.chemical_compound0302 clinical medicine0202 electrical engineering electronic engineering information engineeringmedicineImage Processing Computer-AssistedHumansComputer visionRetinaDiabetic RetinopathyContextual image classificationbusiness.industry[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]RetinalDiabetic retinopathymedicine.diseaseComputer Science ApplicationsSupport vector machinemedicine.anatomical_structurechemistry020201 artificial intelligence & image processingFemaleArtificial intelligenceNeural codingbusiness
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Transport of the major myelin proteolipid protein is directed by VAMP3 and VAMP7.

2011

CNS myelination by oligodendrocytes requires directed transport of myelin membrane components and a timely and spatially controlled membrane expansion. In this study, we show the functional involvement of the R-solubleN-ethylmaleimide-sensitive factor attachment protein receptor (R-SNARE) proteins VAMP3/cellubrevin and VAMP7/TI-VAMP in myelin membrane trafficking. VAMP3 and VAMP7 colocalize with the major myelin proteolipid protein (PLP) in recycling endosomes and late endosomes/lysosomes, respectively. Interference with VAMP3 or VAMP7 function using small interfering RNA-mediated silencing and exogenous expression of dominant-negative proteins diminished transport of PLP to the oligodendro…

MaleProteolipid protein 1Vesicle-Associated Membrane Protein 3MESH: Myelin SheathMESH: R-SNARE Proteins[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/NeurobiologyR-SNARE ProteinsMiceMyelin0302 clinical medicineMESH: Microscopy ImmunoelectronMESH: Genetic VectorsImage Processing Computer-AssistedMESH: AnimalsMicroscopy ImmunoelectronMESH: Myelin Proteolipid ProteinCells CulturedMyelin SheathMESH: Vesicle-Associated Membrane Protein 3VAMP30303 health sciencesMESH: ExocytosisGeneral NeuroscienceMESH: Enzyme-Linked Immunosorbent AssayArticlesImmunohistochemistryMESH: Image Processing Computer-AssistedMyelin proteolipid proteinCell biologymedicine.anatomical_structureElectrophoresis Polyacrylamide GelFemaleRNA InterferenceMESH: Cells CulturedEndosomeGenetic VectorsMESH: RNA InterferenceBiological Transport ActiveEnzyme-Linked Immunosorbent AssayEndosomesBiologyTransfectionExocytosisExocytosis03 medical and health sciencesMESH: Mice Inbred C57BLmedicineAnimalsSecretionMyelin Proteolipid ProteinMESH: MiceSecretory pathway030304 developmental biologyMESH: TransfectionCell MembraneMESH: ImmunohistochemistryMESH: MaleMice Inbred C57BLnervous systemMESH: EndosomesMESH: Biological Transport ActiveLysosomesMESH: Female030217 neurology & neurosurgeryMESH: LysosomesMESH: Cell MembraneMESH: Electrophoresis Polyacrylamide Gel
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A happiness degree predictor using the conceptual data structure for deep learning architectures

2017

Abstract Background and Objective: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventional methodologies are based on linear relationships, such as the commonly used Multivariate Linear Regression (MLR), which may suffer from the lack of representative capacity to the varied psychological features. Using Deep Neural Networks (DNN), we define a Happiness Degree Predictor (H-DP) based on the answers to five psychometric standardized questionnaires. Methods: A Data-Structure driven architecture for DNNs (D-SDNN) is proposed …

MalePsychometricsmedia_common.quotation_subjectEmotionsHappiness050109 social psychologyHealth Informatics02 engineering and technologyModels PsychologicalMachine learningcomputer.software_genrePredictive Value of TestsSurveys and QuestionnairesBayesian multivariate linear regressionAdaptation Psychological0202 electrical engineering electronic engineering information engineeringCIENCIAS DE LA COMPUTACION E INTELIGENCIA ARTIFICIALHumans03.- Garantizar una vida saludable y promover el bienestar para todos y todas en todas las edades0501 psychology and cognitive sciencesDimension (data warehouse)HappinessHappiness-Degree Predictor (H-DP)media_commonMathematicsArtificial neural networkbusiness.industryPsychological researchDeep learning05 social sciencesSocial SupportDeep learningOutcome (probability)Computer Science ApplicationsData-structure driven deep neural network (D-SDNN)Cross-Sectional StudiesMultivariate AnalysisHappinessORGANIZACION DE EMPRESASFemale020201 artificial intelligence & image processingArtificial intelligencePositive psychologybusinessMATEMATICA APLICADAcomputerAlgorithmsMedical InformaticsStress PsychologicalSoftware
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Normal Reference Ranges for Echocardiography: Rationale, study design, and methodology (NORRE Study)

2013

International audience; BACKGROUND: Availability of normative reference values for cardiac chamber dimensions, volumes, mass, and function is a prerequisite for the accurate application of echocardiography for both clinical and research purposes. However, due to the lack of consistency in current echocardiographic 'reference values', their use for clinical decision-making remains questionable. AIMS: The aim of the 'Normal Reference Ranges for Echocardiography Study (NORRE Study)' is to obtain a set of 'normal values' for cardiac chamber geometry and function in a large cohort of healthy Caucasian individuals aged over a wide range of ages (25-75 years) using both conventional and advanced e…

MaleRadiology Nuclear Medicine and ImagingMESH: Echocardiography DopplerLeftSex Factor030204 cardiovascular system & hematologyDoppler echocardiographyDoppler imagingMESH: Stroke VolumeMESH: Ventricular Function LeftVentricular Function Left030218 nuclear medicine & medical imagingHeart VentricleCohort Studies0302 clinical medicine[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingNuclear Medicine and ImagingVentricular FunctionAge FactorProspective StudiesProspective cohort studyMESH: Cohort StudiesMESH: Aged2D and 3D echocardiographyMESH: Middle Agedmedicine.diagnostic_testAnthropometryAge FactorsDopplerGeneral MedicinePulsedReference Standardsreference valuesMiddle AgedCardiac mechanicEchocardiography Doppler3. Good healthEuropeMESH: Echocardiography Doppler PulsedCardiac mechanicsEchocardiographyMESH: Reference Standards[SDV.IB]Life Sciences [q-bio]/BioengineeringFemaleRadiologyCardiology and Cardiovascular Medicine[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingCohort study2D and 3D echocardiography; Cardiac mechanics; Chamber size and function; M-mode; reference values; Adult; Age Factors; Aged; Anthropometry; Cohort Studies; Echocardiography Doppler; Echocardiography Doppler Pulsed; Europe; Female; Heart Ventricles; Humans; Male; Middle Aged; Prospective Studies; Reference Standards; Sensitivity and Specificity; Sex Factors; Stroke Volume; Ventricular Function Left; Cardiology and Cardiovascular Medicine; Radiology Nuclear Medicine and ImagingHumanAdultmedicine.medical_specialtyHeart VentriclesM-modeChamber size and functionSensitivity and Specificity03 medical and health sciencesSex FactorsMESH: Sex FactorsMESH: Anthropometry[SDV.MHEP.CSC]Life Sciences [q-bio]/Human health and pathology/Cardiology and cardiovascular systemmedicineHumansMedical physicsAgedMESH: Age FactorsEchocardiography Doppler PulsedReproducibilityMESH: Humansbusiness.industryreference valueMESH: AdultStroke VolumeMESH: MaleMESH: Prospective StudiesMESH: Sensitivity and SpecificitySurgeryClinical trialProspective StudieSample size determinationReference StandardObservational studyMESH: EuropeMESH: Heart VentriclesCohort StudiebusinessMESH: Female
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Implicit learning of a repeated segment in continuous tracking: A reappraisal

2006

Several prior studies (e.g., Shea, Wulf, Whitacre, & Park, 2001; Wulf & Schmidt, 1997) have apparently demonstrated implicit learning of a repeated segment in continuous-tracking tasks. In two conceptual replications of these studies, we failed to reproduce the original findings. However, these findings were reproduced in a third experiment, in which we used the same repeated segment as that used in the Wulf et al. studies. Analyses of the velocity and the acceleration of the target suggests that this repeated segment could be easier to track than the random segments serving as control, accounting for the results of Wulf and collaborators. Overall these experiments suggest that lea…

MaleSerial reaction timeTime Factors[ INFO.INFO-TS ] Computer Science [cs]/Signal and Image ProcessingPhysiologySpeech recognition[SHS.PSY]Humanities and Social Sciences/Psychology050109 social psychologyExperimental and Cognitive Psychology[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingTracking (particle physics)050105 experimental psychologyRandom Allocation[ SHS.PSY ] Humanities and Social Sciences/PsychologyAcceleration[INFO.INFO-TS]Computer Science [cs]/Signal and Image ProcessingPhysiology (medical)Reaction TimeHumansLearningTraitement du signal et de l'imagePsychology0501 psychology and cognitive sciencesStudentsGeneral PsychologyAnalysis of VarianceCommunicationbusiness.industry05 social sciencesSignal and Image processingRetention PsychologyRecognition PsychologyGeneral MedicineImplicit learningNeuropsychology and Physiological PsychologyPsychologieFemalebusinessPsychology[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingPsychomotor PerformanceTraitement du signal et de l'image (Informatique)
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Evaluation of Deep Neural Networks for Semantic Segmentation of Prostate in T2W MRI

2020

In this paper, we present an evaluation of four encoder&ndash

MaleSimilarity (geometry)Computer scienceSegNet02 engineering and technologylcsh:Chemical technologyBiochemistryArticleencoder–decoder030218 nuclear medicine & medical imagingAnalytical Chemistry03 medical and health sciencesProstate cancer0302 clinical medicineProstateImage Processing Computer-Assisted0202 electrical engineering electronic engineering information engineeringmedicineHumanslcsh:TP1-1185SegmentationElectrical and Electronic EngineeringInstrumentationmedicine.diagnostic_testPixelbusiness.industryProstateCNNsPattern recognitionMagnetic resonance imagingFCNmedicine.diseaseMagnetic Resonance ImagingU-NetAtomic and Molecular Physics and OpticsSemanticsIntensity normalizationmedicine.anatomical_structureDeepLabV3+Deep neural networks020201 artificial intelligence & image processingNeural Networks ComputerArtificial intelligencebusinessDNNSensors
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Common variation in PHACTR1 is associated with susceptibility to cervical artery dissection

2014

Item does not contain fulltext Cervical artery dissection (CeAD), a mural hematoma in a carotid or vertebral artery, is a major cause of ischemic stroke in young adults although relatively uncommon in the general population (incidence of 2.6/100,000 per year). Minor cervical traumas, infection, migraine and hypertension are putative risk factors, and inverse associations with obesity and hypercholesterolemia are described. No confirmed genetic susceptibility factors have been identified using candidate gene approaches. We performed genome-wide association studies (GWAS) in 1,393 CeAD cases and 14,416 controls. The rs9349379[G] allele (PHACTR1) was associated with lower CeAD risk (odds ratio…

Male[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/Imaging[SDV.NEU.NB]Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]/NeurobiologyMyocardial InfarctionGenome-wide association studyCarotid Artery Internal DissectionGastroenterologyepidemiology [Carotid Artery Internal Dissection]Brain Ischemia0302 clinical medicineMigraine DisorderOdds RatioFinlandVertebral Artery Dissection0303 health scienceseducation.field_of_studyepidemiology [Hypercholesterolemia]MESH: Middle AgedMESH: Polymorphism Single NucleotidePhactr-1 protein humanMESH: Brain IschemiaMESH: Follow-Up Studies3. Good healthMESH: Myocardial InfarctionHumanmedicine.medical_specialtyMigraine DisordersHypercholesterolemiaMESH: Vertebral Artery DissectionLower riskgenetics [Brain Ischemia]ArticleFollow-Up StudieMESH: Carotid Artery Internal Dissection03 medical and health sciencesGeneticSDG 3 - Good Health and Well-beinggenetics [Carotid Artery Internal Dissection]GeneticsGenetic predispositionepidemiology [Brain Ischemia]Humansepidemiology [Vertebral Artery Dissection]PolymorphismeducationAllelesMESH: Humansgenetics [Vertebral Artery Dissection]MESH: AdultOdds ratioMicrofilament Proteinmedicine.diseaseAdult; Brain Ischemia; Carotid Artery Internal Dissection; Female; Finland; Follow-Up Studies; Genetic Pleiotropy; Genetic Predisposition to Disease; Genome-Wide Association Study; Humans; Hypercholesterolemia; Hypertension; Male; Microfilament Proteins; Middle Aged; Migraine Disorders; Myocardial Infarction; Obesity; Odds Ratio; Risk Factors; Vertebral Artery Dissection; Alleles; Polymorphism Single NucleotideMESH: Genome-Wide Association StudyCarotid ArteryMESH: Female030217 neurology & neurosurgeryepidemiology [Finland]Cervical ArteryVertebral artery dissectionepidemiology [Hypertension]MESH: HypertensionRisk FactorsMESH: Risk FactorsMESH: ObesityStrokeAlleleGeneticsDissectionMESH: FinlandMicrofilament ProteinsMESH: Genetic Predisposition to DiseaseMESH: HypercholesterolemiaGenetic PleiotropySingle NucleotideMiddle AgedMESH: Migraine DisordersDisorders of movement Donders Center for Medical Neuroscience [Radboudumc 3]epidemiology [Myocardial Infarction][INFO.INFO-TI]Computer Science [cs]/Image Processing [eess.IV]HypertensionFemale[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingAdultPopulationMESH: Genetic Pleiotropyphysiology [Microfilament Proteins]BiologyPolymorphism Single NucleotideMESH: Microfilament ProteinsInternal medicineddc:570medicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingGenetic Predisposition to DiseaseObesity030304 developmental biologyepidemiology [Obesity]Risk FactorMESH: Alleles[INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV]InternalMESH: Odds RatioMESH: Maleepidemiology [Migraine Disorders]genetics [Microfilament Proteins]Follow-Up StudiesGenome-Wide Association Study
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Computer-Aided Detection for Prostate Cancer Detection based on Multi-Parametric Magnetic Resonance Imaging

2017

International audience; Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world. In the last decades, new imaging techniques based on magnetic resonance imaging (MRI) have been developed improving diagnosis. In practice, diagnosis is affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and diagnosis (CAD) systems are being designed to help radiologists in their clinical practice. We propose a CAD system taking advantage of all MRI modalities (i.e., T2-W-MRI, DCE-MRI, diffusion weighted (DW)-MRI, MRSI). The aim of this CAD system was to provide a probabilistic map of cancer…

Malemedicine.medical_specialtySource codemedia_common.quotation_subject[INFO.INFO-IM] Computer Science [cs]/Medical ImagingContrast MediaCAD[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processing030218 nuclear medicine & medical imaging03 medical and health sciencesProstate cancer0302 clinical medicine[STAT.ML]Statistics [stat]/Machine Learning [stat.ML]Prostatemedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumans[ STAT.ML ] Statistics [stat]/Machine Learning [stat.ML][SPI.SIGNAL] Engineering Sciences [physics]/Signal and Image processingmedia_commonMulti parametricModality (human–computer interaction)[ INFO.INFO-IM ] Computer Science [cs]/Medical Imagingmedicine.diagnostic_testbusiness.industryProstatic NeoplasmsCancerMagnetic resonance imagingmedicine.diseaseMagnetic Resonance Imaging[STAT.ML] Statistics [stat]/Machine Learning [stat.ML]3. Good healthmedicine.anatomical_structureRadiologybusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing030217 neurology & neurosurgery
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Computer-Aided Detection and diagnosis for prostate cancer based on mono and multi-parametric MRI: A review

2015

Prostate cancer is the second most diagnosed cancer of men all over the world. In the last few decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed to improve diagnosis. In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexity of the lesions. In this regard, computer-aided detection and computer-aided diagnosis systems have been designed to help radiologists in their clinical practice. Research on computer-aided systems specifically focused for prostate cancer is a young technology and has been part of a dynamic field of research for the last 10years. This survey aims to provide a comprehen…

Malemedicine.medical_specialtyTime FactorsHealth InformaticsCAD[ SPI.SIGNAL ] Engineering Sciences [physics]/Signal and Image processingProstate cancerImage Processing Computer-AssistedMedicineHumansMass ScreeningMedical physicsDiagnosis Computer-AssistedObserver VariationMulti parametricmedicine.diagnostic_testbusiness.industryCarcinomaProstatic NeoplasmsReproducibility of ResultsMagnetic resonance imagingmedicine.diseaseMagnetic Resonance ImagingComputer aided detection3. Good healthComputer Science ApplicationsClinical PracticeMultiple factorsComputer-aided diagnosisResearch DesignNeural Networks ComputerNeoplasm Gradingbusiness[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processingMedical InformaticsSoftware
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