Search results for "MRI."

showing 10 items of 591 documents

Theory of Heterogeneous Circuits With Stochastic Memristive Devices

2022

We introduce an approach based on the Chapman-Kolmogorov equation to model heterogeneous stochastic circuits, namely, the circuits combining binary or multi-state stochastic memristive devices and continuum reactive components (capacitors and/or inductors). Such circuits are described in terms of occupation probabilities of memristive states that are functions of reactive variables. As an illustrative example, the series circuit of a binary memristor and capacitor is considered in detail. Some analytical solutions are found. Our work offers a novel analytical/numerical tool for modeling complex stochastic networks, which may find a broad range of applications.

Computer scienceContinuum (topology)Binary numberCapacitorsMemristorSwitching circuitsTopologyInductorSeries and parallel circuitslaw.inventionComputer Science::Hardware ArchitectureCapacitorRange (mathematics)Mathematical modelComputer Science::Emerging TechnologiesStochastic processesIntegrated circuit modelinglawHardware_INTEGRATEDCIRCUITSElectrical and Electronic EngineeringMemristorsSwitchesElectronic circuitIEEE Transactions on Circuits and Systems II: Express Briefs
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Deep Learning-Based Methods for Prostate Segmentation in Magnetic Resonance Imaging

2021

Magnetic Resonance Imaging-based prostate segmentation is an essential task for adaptive radiotherapy and for radiomics studies whose purpose is to identify associations between imaging features and patient outcomes. Because manual delineation is a time-consuming task, we present three deep-learning (DL) approaches, namely UNet, efficient neural network (ENet), and efficient residual factorized convNet (ERFNet), whose aim is to tackle the fully-automated, real-time, and 3D delineation process of the prostate gland on T2-weighted MRI. While UNet is used in many biomedical image delineation applications, ENet and ERFNet are mainly applied in self-driving cars to compensate for limited hardwar…

Computer scienceGraphics processing unit02 engineering and technologyResiduallcsh:TechnologyArticle030218 nuclear medicine & medical imaginglcsh:Chemistrydeep learning; segmentation; prostate; MRI; ENet; UNet; ERFNet; radiomicsSet (abstract data type)03 medical and health sciences0302 clinical medicineENetERFNet0202 electrical engineering electronic engineering information engineeringGeneral Materials ScienceSegmentationlcsh:QH301-705.5InstrumentationSettore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniFluid Flow and Transfer ProcessesprostateArtificial neural networklcsh:Tbusiness.industryProcess Chemistry and TechnologyDeep learningsegmentationGeneral EngineeringProcess (computing)deep learningUNetPattern recognitionlcsh:QC1-999Computer Science Applicationslcsh:Biology (General)lcsh:QD1-999lcsh:TA1-2040radiomics020201 artificial intelligence & image processingArtificial intelligenceCentral processing unitlcsh:Engineering (General). Civil engineering (General)businesslcsh:PhysicsMRIApplied Sciences
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Minimally Invasive Assessment of Mental Stress based on Wearable Wireless Physiological Sensors and Multivariate Biosignal Processing

2019

The development of connected health technologies for the continuous monitoring of the psychophysical state of individuals performing daily life activities requires the aggregation of non-intrusive sensors and the availability of methods and algorithms for extracting the relevant physiological information. The present study proposes an integrated approach for the objective assessment of mental stress which combines wirelessly connected low invasive biosensors with multivariate physiological time series analysis. In a group of 18 healthy subjects monitored in a relaxed resting state and during two experimental conditions inducing mental stress and sustained attention (respectively, mental ari…

Computer scienceWearable computerwearable deviceElectroencephalographySettore ING-INF/01 - Elettronica03 medical and health sciences0302 clinical medicinetime series analysimedicineTime domainBiosignalEEGstress assessmentTime series030304 developmental biology0303 health sciencesResting state fMRImedicine.diagnostic_testbusiness.industryContinuous monitoringPattern recognitionphysiological signalConnected healthSettore ING-INF/06 - Bioingegneria Elettronica E Informaticaphysiological signals EEG stress assessment time series analysis wearable devicesArtificial intelligencebusiness030217 neurology & neurosurgery
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Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project

2021

ABSTRACTDiffusion-weighted magnetic resonance imaging (dMRI) measurements and models provide information about brain connectivity and are sensitive to the physical properties of tissue microstructure. Diffusional Kurtosis Imaging (DKI) quantifies the degree of non-Gaussian diffusion in biological tissue from dMRI. These estimates are of interest because they were shown to be more sensitive to microstructural alterations in health and diseases than measures based on the total anisotropy of diffusion which are highly confounded by tissue dispersion and fiber crossings. In this work, we implemented DKI in the Diffusion in Python (DIPY) project - a large collaborative open-source project which …

Computer scienceopen-source softwaremicrostructureNeurosciences. Biological psychiatry. NeuropsychiatryGrey matter030218 nuclear medicine & medical imagingWhite matterdiffusion MRI03 medical and health sciencesBehavioral Neuroscience0302 clinical medicinebiophysicsmedicineTechnology and CodeReference implementationDiffusion (business)DKIBiological Psychiatrycomputer.programming_languageGround truthmedicine.diagnostic_testMagnetic resonance imagingHuman NeuroscienceBiological tissueInvariant (physics)Python (programming language)Characterization (materials science)pythonDiffusion imagingPsychiatry and Mental healthmedicine.anatomical_structureNeuropsychology and Physiological PsychologyNeurologyDTIKurtosisAlgorithmcomputer030217 neurology & neurosurgeryRC321-571MRITractographyDiffusion MRIFrontiers in Human Neuroscience
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The representation of segmental information: an fMRI investigation of the consonant-vowel distinction

2004

Harvard University, Cambridge, MA, USAAvailable online 23 July 2004IntroductionRecent studies suggest that consonants and vowels are repre-sented separately in cognitive/neural space. Much of the evidencecomes from research on dysgraphia (for review, see Miceli & Cap-asso, submitted). In the first place, letter substitution errors preservethe consonant/vowel (CV) status of the target (e.g., cinema fi ciremaor cinoma, but not cintma). Second, there are reports of selectiveimpairment for consonants or vowels. Additional evidence comesfrom disorders of phonology, demonstrating the dissociability be-tween consonants and vowels (Caramazza, Chialant, Capasso, Mthe ISI was variable (mean 6.75 s). Th…

ConsonantLinguistics and Languagemedicine.medical_specialtyCognitive NeuroscienceExperimental and Cognitive PsychologyPhonologyconsonant vowel language fmriCognitive neuroscienceAudiologymedicine.diseasecomputer.software_genreLanguage and LinguisticsLinguisticsSpeech and HearingDysgraphiaVoxelCoronal planeVowelmedicineConsonant vowelPsychologycomputer
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Eine Kombination niedrig und hochauflösender dynamischer T1-gewichteter Sequenzen zur besseren Beurteilung der Morphologie Kontrastmittel aufnehmende…

2002

Purpose: Presentation of a new protocol for simultaneous acquisition of both low and high resolution T 1 -weighted images of breast lesions for dynamic contrast-enhanced MR mammography. Demonstration of possible diagnostic improvement with representative measurements in patients with suspected breast cancer by adding morphologic parameters from high resolution sequences to the analysis of the signal-time curve. Materials and Methods: Dynamic MR imaging was performed with a 1.5 T system (Magnetom SONATA, Siemens Medical Systems, Germany) and the manufacturer's double-breast coil. Coronal T 1 -weighted 3D FLASH sequences (spatial resolution 1.25 ×1.25 mm 2 ; slice thickness 1.7 mm) were acqui…

Contrast mediumNuclear magnetic resonanceMaterials sciencePulse (signal processing)Dynamic contrast-enhanced MRIResolution (electron density)Radiology Nuclear Medicine and imagingSensitivity (control systems)Image resolutionSignalImaging phantomBiomedical engineeringRöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren
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How is gravity integrated into motor planning : behavioural and fMRI approaches

2016

Gravity is immutable, ubiquitous and affects the dynamic of our daily movements. The gravitational attraction (9.81 m / s2) which varies less than 1% of the earth's surface, is an actress of the evolution of all living species. Thanks to an efficient sensorimotor system, the dynamical consequences of the effects of gravity on our movements are stored as internal representations. To circumvent the time delays of the afferent signals coming from the sensorimotor system (too long to plan quick movements), the Central Nervous System (CNS) acts in a proactive fashion by using suitable internal models developed during our past experiences. These models are mainly used during the motor planning to…

Contrôle moteurPlanification motriceMotor controlFMRIGravityGravitéInformations sensoriellesSensorimotor information[SDV.NEU] Life Sciences [q-bio]/Neurons and Cognition [q-bio.NC]Internal modelsMotor planningModèle interneIRMf
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Graph cut-based method for segmenting the left ventricle from MRI or echocardiographic images

2017

International audience; In this paper, we present a fast and interactive graph cut method for 3D segmentation of the endocardial wall of the left ventricle (LV) adapted to work on two of the most widely used modalities: magnetic resonance imaging (MRI) and echocardiography. Our method accounts for the fundamentally different nature of both modalities: 3D echocardiographic images have a low contrast, a poor signal-to-noise ratio and frequent signal drop, while MR images are more detailed but also cluttered and contain highly anisotropic voxels. The main characteristic of our method is to work in a 3D Bezier coordinate system instead of the original Euclidean space. This comes with several ad…

Convex hullHeart VentriclesEnergy MinimizationCoordinate systemEchocardiography Three-DimensionalHealth InformaticsBézier curve02 engineering and technology[SDV.IB.MN]Life Sciences [q-bio]/Bioengineering/Nuclear medicinecomputer.software_genreAutomated Segmentation030218 nuclear medicine & medical imaging[ SDV.IB.MN ] Life Sciences [q-bio]/Bioengineering/Nuclear medicine03 medical and health sciences0302 clinical medicineVoxelCut0202 electrical engineering electronic engineering information engineering[INFO.INFO-IM]Computer Science [cs]/Medical ImagingMagnetic-Resonance ImagesHumansRadiology Nuclear Medicine and imagingComputer vision[ SDV.IB ] Life Sciences [q-bio]/BioengineeringCardiac MriImage gradientMathematicsWhole MyocardiumLeft ventricular 3-D segmentationRadiological and Ultrasound Technology[ INFO.INFO-IM ] Computer Science [cs]/Medical ImagingEuclidean spacebusiness.industryComputer Graphics and Computer-Aided DesignMagnetic Resonance ImagingEchocardiographyConstrained Level-SetGraph (abstract data type)020201 artificial intelligence & image processing[SDV.IB]Life Sciences [q-bio]/BioengineeringComputer Vision and Pattern RecognitionArtificial intelligencebusiness2d-EchocardiographycomputerAlgorithmsGraph cutMRI
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Segmentation Integrating Watershed and Shape Priors Applied to Cardiac Delayed Enhancement MR Images

2017

International audience; Background: In recent years, there has been a rapid rise in the use of shape priors applied to segmentation process of medical images. Previous approaches on left ventricle segmentation from Delayed-Enhancement Magnetic Resonance Imaging (DE-MRI) have focused on the extraction of myocardium or just diseased region in short axis orientation. However these studies did not take into account the segmentation of non-diseased myocardium from DE-MRI. The segmentation of non-diseased myocardium from DE-MRI, has some useful applications. For instance it can simplify the PET-MR registration process.Methods: This paper presents a novel semi-automatic segmentation method of non-…

DE-MRIComputer science[SDV.IB.IMA]Life Sciences [q-bio]/Bioengineering/ImagingBiomedical EngineeringBiophysicsScale-space segmentation030204 cardiovascular system & hematology030218 nuclear medicine & medical imaging03 medical and health sciences0302 clinical medicineSegmentationSørensen–Dice coefficientInformationMagnetic-Resonance ImagesSegmentationComputer vision[ SDV.IB ] Life Sciences [q-bio]/BioengineeringCardiac imaging[ SDV.IB.IMA ] Life Sciences [q-bio]/Bioengineering/ImagingOrientation (computer vision)business.industryImage segmentationGold standard (test)Computer aided diagnosisComputer-aided diagnosisGraph Cuts[SDV.IB]Life Sciences [q-bio]/BioengineeringArtificial intelligencebusinessShape priorsCardiac imaging
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Advanced techniques in Magnetic Resonance Imaging: characterization of non-gaussian water diffusion using DIFFUSION KURTOSIS IMAGING (DKI)

2014

DKI DTI MRISettore FIS/01 - Fisica SperimentaleSettore MED/37 - NeuroradiologiaSettore MED/36 - Diagnostica Per Immagini E RadioterapiaSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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