Search results for "Statistical noise"

showing 5 items of 5 documents

Fast and robust phase-shift estimation in two-dimensional structured illumination microscopy.

2019

A method of determining unknown phase-shifts between elementary images in two-dimensional Structured Illumination Microscopy (2D-SIM) is presented. The proposed method is based on the comparison of the peak intensity of spectral components. These components correspond to the inherent structured illumination spectral content and the residual compo- nent that appears from wrongly estimated phase-shifts. The estimation of the phase-shifts is carried out by finding the absolute maximum of a function defined as the normalized peak intensity difference in the Fourier domain. This task is performed by an optimization method providing a fast estimation of the phase-shift. The algorithm stability an…

DiffractionStatistical NoisePhotonStructured illumination microscopy02 engineering and technologySignal-To-Noise RatioResidual01 natural sciencesPhase DeterminationMathematical and Statistical TechniquesFluorescence MicroscopyImage Processing Computer-AssistedFourier Anàlisi deMathematicsMicroscopyMultidisciplinaryFourier AnalysisPhysicsApplied MathematicsSimulation and ModelingStatisticsQRLight Microscopy021001 nanoscience & nanotechnologyGaussian NoiseMicroscòpiaFourier analysisPhysical SciencessymbolsCrystallographic TechniquesMedicine0210 nano-technologyAlgorithmDiffractionElementary ParticlesAlgorithmsResearch ArticleImaging TechniquesComputationScienceResearch and Analysis Methods010309 opticssymbols.namesakeRobustness (computer science)0103 physical sciencesParticle PhysicsPhotonsMicroscopy FluorescenceGaussian noiseWavesMathematicsImatges Processament Tècniques digitalsPLoS ONE
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TheINTEGRALspectrometer SPI: performance of point-source data analysis

2005

The performance of the SPI point-source data analysis system is assessed using a combination of simulations and of observations gathered during the first year of INTEGRAL operations. External error estimates are derived by comparing source positions and fluxes obtained from independent analyses. When the source detection significance provided by the SPIROS imaging reconstruction program increases from ∼10 to ∼100, the errors decrease as the inverse of the detection significance, with values from ∼10 to ∼1 arcmin in positions, and from ∼10 to ∼1 per cent in relative flux. These errors are dominated by Poisson counting noise. Our error estimates are consistent with those provided by the SPIRO…

Statistical noisePoint sourceInstrumentationdata analysis -gamma raysPoisson distribution01 natural sciencesNoise (electronics)[PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO]symbols.namesakeSignal-to-noise ratioOptics0103 physical sciencesSpurious relationship010303 astronomy & astrophysicsinstrumentationPhysics[SDU.ASTR]Sciences of the Universe [physics]/Astrophysics [astro-ph]010308 nuclear & particles physicsbusiness.industryAstronomy and AstrophysicsComputational physicsobservationsSpace and Planetary SciencesymbolsDeconvolutionbusinessmiscellaneous -methodsMonthly Notices of the Royal Astronomical Society
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Accounting for operating environments in measuring water utilities’ managerial efficiency

2009

In this paper adjusted input-specific scores of technical efficiency are computed for a sample of Spanish water utilities. Performance is adjusted by netting out efficiency scores from the effect of operating environments and statistical noise. The results show that computation of adjusted efficiency scores at the input level manifestly improves the assessment of utilities’ performance in our sample of water utilities. In addition, several environmental variables capable of affecting input-specific technical management are discovered, ownership or demand seasonality among them. Finally, distributions of conventional and adjusted scores of technical performance are found to be statistically …

Technical performanceStatistical noiseManagement of Technology and InnovationStrategy and ManagementEconomicsEconometricsSample (statistics)Technical managementNettingThe Service Industries Journal
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Comparison of basis functions for 3D PET reconstruction using a Monte Carlo system matrix.

2012

In emission tomography, iterative statistical methods are accepted as the reconstruction algorithms that achieve the best image quality. The accuracy of these methods relies partly on the quality of the system response matrix (SRM) that characterizes the scanner. The more physical phenomena included in the SRM, the higher the SRM quality, and therefore higher image quality is obtained from the reconstruction process. High-resolution small animal scanners contain as many as 103?104 small crystal pairs, while the field of view (FOV) is divided into hundreds of thousands of small voxels. These two characteristics have a significant impact on the number of elements to be calculated in the SRM. …

Time FactorsRadiological and Ultrasound TechnologyRotationStatistical noisebusiness.industryImage qualityPhantoms ImagingMonte Carlo methodBasis functioncomputer.software_genreNoiseImaging Three-DimensionalVoxelPositron-Emission TomographyRadiology Nuclear Medicine and imagingComputer visionArtificial intelligencebusinesscomputerAlgorithmImage resolutionMonte Carlo MethodSmoothingMathematicsPhysics in medicine and biology
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High Performance 3D PET Reconstruction Using Spherical Basis Functions on a Polar Grid

2011

Statistical iterative methods are a widely used method of image reconstruction in emission tomography. Traditionally, the image space is modelled as a combination of cubic voxels as a matter of simplicity. After reconstruction, images are routinely filtered to reduce statistical noise at the cost of spatial resolution degradation. An alternative to produce lower noise during reconstruction is to model the image space with spherical basis functions. These basis functions overlap in space producing a significantly large number of non-zero elements in the system response matrix (SRM) to store, which additionally leads to long reconstruction times. These two problems are partly overcome by expl…

lcsh:Medical physics. Medical radiology. Nuclear medicinelcsh:Medical technologyArticle SubjectComputer scienceStatistical noiseIterative methodImage qualitylcsh:R895-920ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONBasis functionReconstruction algorithmSpherical basisIterative reconstructioncomputer.software_genrelcsh:R855-855.5Radiology Nuclear Medicine and imagingData miningcomputerAlgorithmImage resolutionResearch ArticleComputingMethodologies_COMPUTERGRAPHICSInternational Journal of Biomedical Imaging
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