Search results for " processing"

showing 10 items of 7549 documents

Fast PET Scan Tumor Segmentation Using Superpixels, Principal Component Analysis and K-Means Clustering

2018

Positron Emission Tomography scan images are extensively used in radiotherapy planning, clinical diagnosis, assessment of growth and treatment of a tumor. These all rely on fidelity and speed of detection and delineation algorithm. Despite intensive research, segmentation remained a challenging problem due to the diverse image content, resolution, shape, and noise. This paper presents a fast positron emission tomography tumor segmentation method in which superpixels are extracted first from the input image. Principal component analysis is then applied on the superpixels and also on their average. Distance vector of each superpixel from the average is computed in principal components coordin…

FOS: Computer and information sciencespositron emission tomographyprincipal component analysisComputer scienceComputer Vision and Pattern Recognition (cs.CV)k-meansCoordinate systemComputer Science - Computer Vision and Pattern RecognitionFOS: Physical sciences02 engineering and technologyBenchmarkQuantitative Biology - Quantitative MethodsBiochemistry Genetics and Molecular Biology (miscellaneous)030218 nuclear medicine & medical imagingsuperpixels03 medical and health sciences0302 clinical medicineStructural Biology0202 electrical engineering electronic engineering information engineeringmedicineSegmentationComputer visionTissues and Organs (q-bio.TO)Cluster analysisQuantitative Methods (q-bio.QM)Pixelmedicine.diagnostic_testbusiness.industrysegmentationk-means clusteringQuantitative Biology - Tissues and OrgansPattern recognitionPhysics - Medical PhysicsPositron emission tomographyFOS: Biological sciencesPhysics - Data Analysis Statistics and ProbabilityPrincipal component analysis020201 artificial intelligence & image processingMedical Physics (physics.med-ph)Artificial intelligenceNoise (video)businessData Analysis Statistics and Probability (physics.data-an)BiotechnologyMethods and Protocols
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Fast Estimation of Diffusion Tensors under Rician noise by the EM algorithm

2016

Diffusion tensor imaging (DTI) is widely used to characterize, in vivo, the white matter of the central nerve system (CNS). This biological tissue contains much anatomic, structural and orientational information of fibers in human brain. Spectral data from the displacement distribution of water molecules located in the brain tissue are collected by a magnetic resonance scanner and acquired in the Fourier domain. After the Fourier inversion, the noise distribution is Gaussian in both real and imaginary parts and, as a consequence, the recorded magnitude data are corrupted by Rician noise. Statistical estimation of diffusion leads a non-linear regression problem. In this paper, we present a f…

FOS: Computer and information sciencesreduced computationGaussianModels NeurologicalDatasets as Topicta3112Statistics - ComputationStatistics - ApplicationsTime030218 nuclear medicine & medical imagingMethodology (stat.ME)Diffusion03 medical and health sciencessymbols.namesake0302 clinical medicineScoring algorithmRician fadingPrior probabilityExpectation–maximization algorithmImage Processing Computer-AssistedMaximum a posteriori estimationHumansApplications (stat.AP)Computer SimulationComputation (stat.CO)Statistics - MethodologyMathematicsta112Likelihood FunctionsGeneral NeuroscienceBrainEstimatormaximum likelihood estimatorFisher scoringMagnetic Resonance ImagingWhite MatterRician likelihoodDiffusion Tensor ImagingFourier transformNonlinear Dynamicssymbolsmaximum a posteriori estimatorAlgorithmAlgorithms030217 neurology & neurosurgerydata augmentation
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Low-Power Audio Keyword Spotting using Tsetlin Machines

2021

The emergence of Artificial Intelligence (AI) driven Keyword Spotting (KWS) technologies has revolutionized human to machine interaction. Yet, the challenge of end-to-end energy efficiency, memory footprint and system complexity of current Neural Network (NN) powered AI-KWS pipelines has remained ever present. This paper evaluates KWS utilizing a learning automata powered machine learning algorithm called the Tsetlin Machine (TM). Through significant reduction in parameter requirements and choosing logic over arithmetic based processing, the TM offers new opportunities for low-power KWS while maintaining high learning efficacy. In this paper we explore a TM based keyword spotting (KWS) pipe…

FOS: Computer and information sciencesspeech commandSound (cs.SD)Computer scienceSpeech recognition02 engineering and technologykeyword spottingMachine learningcomputer.software_genreComputer Science - SoundReduction (complexity)Audio and Speech Processing (eess.AS)020204 information systemsFOS: Electrical engineering electronic engineering information engineering0202 electrical engineering electronic engineering information engineeringElectrical and Electronic EngineeringArtificial neural networkLearning automatabusiness.industrylearning automatalcsh:Applications of electric power020206 networking & telecommunicationslcsh:TK4001-4102Pipeline (software)Power (physics)machine learningTsetlin MachineMFCCKeyword spottingelectrical_electronic_engineeringScalabilityMemory footprintpervasive AI020201 artificial intelligence & image processingMel-frequency cepstrumArtificial intelligencebusinesscomputerartificial neural networkEfficient energy useElectrical Engineering and Systems Science - Audio and Speech Processing
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Can visualization alleviate dichotomous thinking? Effects of visual representations on the cliff effect

2021

Common reporting styles for statistical results in scientific articles, such as $p$ p -values and confidence intervals (CI), have been reported to be prone to dichotomous interpretations, especially with respect to the null hypothesis significance testing framework. For example when the $p$ p -value is small enough or the CIs of the mean effects of a studied drug and a placebo are not overlapping, scientists tend to claim significant differences while often disregarding the magnitudes and absolute differences in the effect sizes. This type of reasoning has been shown to be potentially harmful to science. Techniques relying on the visual estimation of the strength of evidence have been recom…

FOS: Computer and information sciencesvisualisointiBayesian inferencetilastomenetelmätComputer Science - Human-Computer Interactiontulkinta02 engineering and technologyBayesian inferenceluottamustasotHuman-Computer Interaction (cs.HC)cliff effectData visualizationhypothesis testing0202 electrical engineering electronic engineering information engineeringStatistical inferencevisualizationconfidence intervalsStatistical hypothesis testingpäättelybusiness.industrybayesilainen menetelmäOther Statistics (stat.OT)Multilevel model020207 software engineeringtilastografiikkaComputer Graphics and Computer-Aided DesignConfidence intervalStatistics - Other StatisticsSignal ProcessingComputer Vision and Pattern RecognitionbusinessPsychologyNull hypothesisValue (mathematics)SoftwareCognitive psychologystatistical inference
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Laplacian versus Adjacency Matrix in Quantum Walk Search

2015

A quantum particle evolving by Schr\"odinger's equation contains, from the kinetic energy of the particle, a term in its Hamiltonian proportional to Laplace's operator. In discrete space, this is replaced by the discrete or graph Laplacian, which gives rise to a continuous-time quantum walk. Besides this natural definition, some quantum walk algorithms instead use the adjacency matrix to effect the walk. While this is equivalent to the Laplacian for regular graphs, it is different for non-regular graphs, and is thus an inequivalent quantum walk. We algorithmically explore this distinction by analyzing search on the complete bipartite graph with multiple marked vertices, using both the Lapla…

FOS: Physical sciences01 natural sciencesComplete bipartite graph010305 fluids & plasmasTheoretical Computer Sciencesymbols.namesake0103 physical sciencesQuantum walkAdjacency matrixElectrical and Electronic Engineering010306 general physicsMathematicsQuantum computerDiscrete mathematicsQuantum PhysicsDiscrete spaceStatistical and Nonlinear PhysicsMathematics::Spectral TheoryElectronic Optical and Magnetic MaterialsModeling and SimulationSignal ProcessingsymbolsLaplacian matrixQuantum Physics (quant-ph)Hamiltonian (quantum mechanics)Laplace operator
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The temporal analogue of diffractive couplers

2020

International audience; Based on the space-time duality of light, we numerically demonstrate that temporal dispersion grating couplers can generate from a single pulse an array of replicas of equal amplitude. The phase-only profile of the temporal grating is optimized by a genetic algorithm that takes into account the optoelectronic bandwidth limitations of the setup.

FOS: Physical sciencesDuality (optimization)Physics::Optics02 engineering and technologyGrating01 natural sciences010309 optics020210 optoelectronics & photonicsOptics0103 physical sciencesDispersion (optics)Genetic algorithm0202 electrical engineering electronic engineering information engineeringUltrafast processingPhysics[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics]business.industryBandwidth (signal processing)Single pulseGeneral MedicineQC350-467Optics. LightAmplitudePhase modulationSpace-time analogybusinessOptics (physics.optics)Physics - Optics
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Applications of sinusoidal phase modulation in temporal optics to highlight some properties of the Fourier transform

2019

International audience; Fourier analysis plays a major role in the analysis and understanding of many phenomena in physics and contemporary engineering. However, students, who have often discovered this notion through numerical tools, do not necessarily understand all the richness that can be derived from joint analysis in the temporal and spectral domains, particularly in the field of optics. As part of the second year of the Master's degree in Physics Lasers and Materials at the University of Burgundy, we have set up a set of experiments to highlight these concepts and to show, on a non-trivial example of periodic phase modulation, the precautions to be taken in the interpretation of the …

FOS: Physical sciencesGeneral Physics and Astronomy01 natural sciencesSession (web analytics)Interpretation (model theory)symbols.namesakeOpticsPhysics Education (physics.ed-ph)0103 physical sciencesoptical spectrum010306 general physicsSet (psychology)Telecommunications equipmentsignal processingPhysics[PHYS.PHYS.PHYS-OPTICS]Physics [physics]/Physics [physics]/Optics [physics.optics]business.industry05 social sciencesPhysics - Physics Education050301 educationSinusoidal phase modulationField (geography)Fourier transformFourier analysissymbolsFourier transformbusiness0503 educationPhase modulationPhysics - OpticsOptics (physics.optics)
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Spin Pumping and Torque Statistics in the Quantum Noise Limit

2016

We analyze the statistics of charge and energy currents and spin torque in a metallic nanomagnet coupled to a large magnetic metal via a tunnel contact. We derive a Keldysh action for the tunnel barrier, describing the stochastic currents in the presence of a magnetization precessing with the rate $\Omega$. In contrast to some earlier approaches, we include the geometric phases that affect the counting statistics. We illustrate the use of the action by deriving spintronic fluctuation relations, the quantum limit of pumped current noise, and consider the fluctuations in two specific cases: the situation with a stable precession of magnetization driven by spin transfer torque, and the torque-…

FOS: Physical sciencesGeneral Physics and Astronomy02 engineering and technologyMagnetization01 natural sciencesspin pumpingQuantum mechanicsMesoscale and Nanoscale Physics (cond-mat.mes-hall)0103 physical sciencesStatistics010306 general physicsMagnetic anisotropySpin-½PhysicsSpin pumpingStochastic systemsCondensed Matter - Mesoscale and Nanoscale Physicsta114SpintronicsCondensed matter physicsQuantum limitQuantum noiseSpin-transfer torqueCharge (physics)Condensed Matter::Mesoscopic Systems and Quantum Hall Effect021001 nanoscience & nanotechnologyNanomagnetTorquequantum noise limit0210 nano-technologytorque statisticsEnergy (signal processing)Physical Review Letters
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Nonlocality threshold for entanglement under general dephasing evolutions: A case study

2015

Determining relationships between different types of quantum correlations in open composite quantum systems is important since it enables the exploitation of a type by knowing the amount of another type. We here review, by giving a formal demonstration, a closed formula of the Bell function, witnessing nonlocality, as a function of the concurrence, quantifying entanglement, valid for a system of two noninteracting qubits initially prepared in extended Werner-like states undergoing any local pure-dephasing evolution. This formula allows for finding nonlocality thresholds for the concurrence depending only on the purity of the initial state. We then utilize these thresholds in a paradigmatic …

FOS: Physical sciencesQuantum entanglementSquashed entanglement01 natural sciencesSettore FIS/03 - Fisica Della Materia010305 fluids & plasmasTheoretical Computer ScienceQuantum entanglementQuantum nonlocalityQuantum mechanics0103 physical sciencesElectrical and Electronic Engineering010306 general physicsQuantum computerPhysicsBell stateQuantum PhysicsBell nonlocalityStatistical and Nonlinear PhysicsConcurrenceQuantum PhysicsElectronic Optical and Magnetic MaterialsOpen quantum systemModeling and SimulationQubitSignal ProcessingPure-dephasingW stateQuantum Physics (quant-ph)
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Unique continuation of the normal operator of the x-ray transform and applications in geophysics

2020

We show that the normal operator of the X-ray transform in $\mathbb{R}^d$, $d\geq 2$, has a unique continuation property in the class of compactly supported distributions. This immediately implies uniqueness for the X-ray tomography problem with partial data and generalizes some earlier results to higher dimensions. Our proof also gives a unique continuation property for certain Riesz potentials in the space of rapidly decreasing distributions. We present applications to local and global seismology. These include linearized travel time tomography with half-local data and global tomography based on shear wave splitting in a weakly anisotropic elastic medium.

FOS: Physical sciencesx-ray transformSpace (mathematics)01 natural sciencesTheoretical Computer SciencePhysics - GeophysicsContinuationtomografiaClassical Analysis and ODEs (math.CA)FOS: MathematicsNormal operatorUniqueness0101 mathematicsAnisotropyMathematical PhysicsMathematicsX-ray transformgeophysicsApplied Mathematics010102 general mathematicsMathematical analysisgeofysiikkaShear wave splittingInverse problemFunctional Analysis (math.FA)Geophysics (physics.geo-ph)Computer Science ApplicationsMathematics - Functional Analysis010101 applied mathematicsMathematics - Classical Analysis and ODEsSignal ProcessingInverse Problems
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