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showing 10 items of 2426 documents

Simple computation of the approximated modulation transfer function (MTF) using spreadsheet-software: method and evaluation in five maxillofacial CBC…

2019

OBJECTIVES: To develop a simple way to compute the approximated modulation transfer function (MTF) manually using conventional spreadsheet software. METHODS: Basing on an edge-image a method was developed, facilitating computation of the edge spread and line spread function in open-source spreadsheet software (Gnumeric; http://projects.gnome.org/gnumeric/downloads.shtml). By means of the integrated fast Fourier transformation Fourier coefficients are obtained from the line spread function which can then be plotted vs spatial frequency to obtain MTF-plots. For the experimental evaluation an edge test object was exposed in five commercial CBCT devices for maxillofacial applications. RESULTS: …

Computer science030218 nuclear medicine & medical imaging03 medical and health sciencessymbols.namesake0302 clinical medicineTechnical ReportSimple (abstract algebra)Optical transfer functionRadiography DentalHumansRadiology Nuclear Medicine and imagingGeneral DentistryDigital signal processingSimple computationbusiness.industrySpreadsheet softwarePhantoms ImagingComputer Science::Software EngineeringReproducibility of Results030206 dentistryGeneral MedicineSpiral Cone-Beam Computed TomographyRadiographic Image EnhancementFourier transformOtorhinolaryngologysymbolsbusinessAlgorithmSoftware
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Hierarchical modeling for rare event detection and cell subset alignment across flow cytometry samples.

2013

Flow cytometry is the prototypical assay for multi-parameter single cell analysis, and is essential in vaccine and biomarker research for the enumeration of antigen-specific lymphocytes that are often found in extremely low frequencies (0.1% or less). Standard analysis of flow cytometry data relies on visual identification of cell subsets by experts, a process that is subjective and often difficult to reproduce. An alternative and more objective approach is the use of statistical models to identify cell subsets of interest in an automated fashion. Two specific challenges for automated analysis are to detect extremely low frequency event subsets without biasing the estimate by pre-processing…

Computer scienceAdaptive Immunitycomputer.software_genre0302 clinical medicineSingle-cell analysisEnumerationBiology (General)Immune ResponseEvent (probability theory)0303 health sciencesEcologymedicine.diagnostic_testT CellsStatisticsFlow Cytometry3. Good healthComputational Theory and MathematicsData modelModeling and SimulationMedicineData miningImmunotherapyResearch ArticleTumor ImmunologyQH301-705.5Immune CellsImmunologyContext (language use)BiostatisticsModels BiologicalFlow cytometry03 medical and health sciencesCellular and Molecular NeuroscienceGeneticsmedicineHumansSensitivity (control systems)Statistical MethodsImmunoassaysMolecular BiologyBiologyEcology Evolution Behavior and Systematics030304 developmental biologybusiness.industryImmunityReproducibility of ResultsPattern recognitionStatistical modelImmunologic SubspecialtiesLymphocyte SubsetsImmunologic TechniquesClinical ImmunologyArtificial intelligencebusinesscomputerMathematics030215 immunologyPLoS computational biology
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Parallelizing Epistasis Detection in GWAS on FPGA and GPU-Accelerated Computing Systems

2015

This is a post-peer-review, pre-copyedit version of an article published in IEEE - ACM Transactions on Computational Biology and Bioinformatics. The final authenticated version is available online at: http://dx.doi.org/10.1109/TCBB.2015.2389958 [Abstract] High-throughput genotyping technologies (such as SNP-arrays) allow the rapid collection of up to a few million genetic markers of an individual. Detecting epistasis (based on 2-SNP interactions) in Genome-Wide Association Studies is an important but time consuming operation since statistical computations have to be performed for each pair of measured markers. Computational methods to detect epistasis therefore suffer from prohibitively lon…

Computer scienceBioinformaticsDNA Mutational AnalysisGenome-wide association studyParallel computingPolymorphism Single NucleotideSensitivity and SpecificityComputational biologyComputer GraphicsGeneticsComputer architectureField-programmable gate arrayRandom access memoryApplied MathematicsChromosome MappingHigh-Throughput Nucleotide SequencingReproducibility of ResultsField programmable gate arraysEpistasis GeneticSignal Processing Computer-AssistedEquipment DesignRandom access memoryComputing systemsReconfigurable computingEquipment Failure AnalysisTask (computing)EpistasisHost (network)Graphics processing unitsGenome-Wide Association StudyBiotechnology
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The Brain Electrophysiological recording & STimulation (BEST) toolbox

2021

Abstract Non-invasive brain stimulation (NIBS) experiments involve many recurring procedures that are not sufficiently standardized in the community. Given the diversity in experimental design and experience of the investigators, automated but yet flexible data collection and analysis tools are needed to increase objectivity, reliability, and reproducibility of NIBS experiments. The B rain E lectrophysiological recording and ST imulation (BEST) Toolbox is a MATLAB-based, open-source software with graphical user interface that allows users to design, run, and share freely configurable multi-protocol, multi-session NIBS studies, including transcranial magnetic, electric, and ultrasound stimul…

Computer scienceBiophysicsNeurosciences. Biological psychiatry. NeuropsychiatryElectroencephalographySoftwareEMGmedicineEEGEvoked potentialtESGraphical user interfacemedicine.diagnostic_testbusiness.industryGeneral NeurosciencefMRIBrainReproducibility of ResultsElectroencephalographyEvoked Potentials MotorTranscranial Magnetic StimulationAutomationTUSToolboxInterfacingBrain stimulationTMSNeurology (clinical)businessComputer hardwareRC321-571Brain Stimulation
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Power estimation for non-standardized multisite studies

2016

A concern for researchers planning multisite studies is that scanner and T1-weighted sequence-related biases on regional volumes could overshadow true effects, especially for studies with a heterogeneous set of scanners and sequences. Current approaches attempt to harmonize data by standardizing hardware, pulse sequences, and protocols, or by calibrating across sites using phantom-based corrections to ensure the same raw image intensities. We propose to avoid harmonization and phantom-based correction entirely. We hypothesized that the bias of estimated regional volumes is scaled between sites due to the contrast and gradient distortion differences between scanners and sequences. Given this…

Computer scienceCognitive Neurosciencecomputer.software_genreSensitivity and Specificity050105 experimental psychologyImaging phantomArticleSet (abstract data type)03 medical and health sciences0302 clinical medicineDistortionImage Interpretation Computer-AssistedCalibrationmedicine[INFO.INFO-IM]Computer Science [cs]/Medical ImagingHumans0501 psychology and cognitive sciencesSegmentationComputer Simulation10. No inequalityScalingModels Statisticalmedicine.diagnostic_test05 social sciencesContrast (statistics)BrainReproducibility of ResultsMagnetic resonance imagingEquipment DesignScale factorImage EnhancementMagnetic Resonance ImagingUnited StatesEquipment Failure AnalysisEuropeNeurologyOrdinary least squaresData miningFunction and Dysfunction of the Nervous SystemArtifactscomputer030217 neurology & neurosurgeryAlgorithms
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An advanced system for the simulation and planning of orthodontic treatment

2000

This paper presents a new system for three-dimensional (3-D) orthodontic treatment planning and movement of teeth. We describe a computer vision technique for the acquisition and processing of 3-D images of the profile of hydrocolloid dental imprints. Profile measurement is based on the triangulation method which detects deformation of the projection of a laser line on the dental imprints. The system is computer-controlled and designed to achieve depth and lateral resolutions of 0.1 and 0.2 mm, respectively, within a depth range of 40 mm. The 3-D image of the imprint is segmented in order to identify different teeth. Two operators are presented: one for the detection of molars and premolars…

Computer scienceComputer measurementOrthodonticsHealth InformaticsModels BiologicalPatient Care Planningstomatognathic systemHumansComputer SimulationRadiology Nuclear Medicine and imagingDiagnosis Computer-AssistedLaser lineProjection (set theory)Dental alveolusOrthodonticsMeasurement methodRadiological and Ultrasound TechnologyReproducibility of ResultsDental ModelsTriangulation (computer vision)Computer Graphics and Computer-Aided DesignModels DentalBiomechanical Phenomenastomatognathic diseasesTherapy Computer-AssistedAcquisition timeComputer Vision and Pattern RecognitionMedical Image Analysis
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Automatic skull stripping in MRI based on morphological filters and fuzzy c-means segmentation

2012

In this paper a new automatic skull stripping method for T1-weighted MR image of human brain is presented. Skull stripping is a process that allows to separate the brain from the rest of tissues. The proposed method is based on a 2D brain extraction making use of fuzzy c-means segmentation and morphological operators applied on transversal slices. The approach is extended to the 3D case, taking into account the result obtained from the preceding slice to solve the organ splitting problem. The proposed approach is compared with BET (Brain Extraction Tool) implemented in MRIcro software.

Computer scienceComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISIONSensitivity and SpecificityFuzzy logicPattern Recognition AutomatedFuzzy LogicImage Interpretation Computer-AssistedmedicineHumansSegmentationComputer visionSettore ING-INF/05 - Sistemi Di Elaborazione Delle Informazionimedicine.diagnostic_testSkull Stripping Fuzzy C-means Morphological Filters.business.industrySkullProcess (computing)BrainReproducibility of ResultsMagnetic resonance imagingImage segmentationImage EnhancementMagnetic Resonance ImagingSubtraction TechniquePattern recognition (psychology)Skull strippingArtificial intelligenceMr imagesbusinessAlgorithms2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Are nonlinear model-free conditional entropy approaches for the assessment of cardiac control complexity superior to the linear model-based one?

2016

Objective : We test the hypothesis that the linear model-based (MB) approach for the estimation of conditional entropy (CE) can be utilized to assess the complexity of the cardiac control in healthy individuals. Methods : An MB estimate of CE was tested in an experimental protocol (i.e., the graded head-up tilt) known to produce a gradual decrease of cardiac control complexity as a result of the progressive vagal withdrawal and concomitant sympathetic activation. The MB approach was compared with traditionally exploited nonlinear model-free (MF) techniques such as corrected approximate entropy, sample entropy, corrected CE, two k -nearest-neighbor CE procedures and permutation CE. Electroca…

Computer scienceEntropyBiomedical EngineeringSensitivity and Specificity01 natural sciencesApproximate entropy03 medical and health sciencesEntropy (classical thermodynamics)0302 clinical medicineHeart RateHeart Rate Determination0103 physical sciencesStatisticsHumansEntropy (information theory)Autonomic nervous systemComputer SimulationEntropy (energy dispersal)010306 general physicsEntropy (arrow of time)Heart rate variabilityFeedback PhysiologicalConditional entropyEntropy (statistical thermodynamics)Head-up tiltModels CardiovascularLinear modelCardiovascular regulationReproducibility of ResultsHeartStatistical modelMutual informationSample entropyMutual informationNonlinear DynamicsConcomitantSettore ING-INF/06 - Bioingegneria Elettronica E InformaticaLinear ModelsAlgorithmRandom variableAlgorithms030217 neurology & neurosurgeryEntropy (order and disorder)
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Characterization of entropy measures against data loss: Application to EEG records

2012

This study is aimed at characterizing three signal entropy measures, Approximate Entropy (ApEn), Sample Entropy (SampEn) and Multiscale Entropy (MSE) over real EEG signals when a number of samples are randomly lost due to, for example, wireless data transmission. The experimental EEG database comprises two main signal groups: control EEGs and epileptic EEGs. Results show that both SampEn and ApEn enable a clear distinction between control and epileptic signals, but SampEn shows a more robust performance over a wide range of sample loss ratios. MSE exhibits a poor behavior for ratios over a 40% of sample loss. The EEG non-stationary and random trends are kept even when a great number of samp…

Computer scienceEntropyInformation Storage and RetrievalData lossElectroencephalographySensitivity and SpecificityApproximate entropyMultiscale entropyEntropy (classical thermodynamics)SeizuresStatisticsmedicineHumansEntropy (information theory)Entropy (energy dispersal)Entropy (arrow of time)medicine.diagnostic_testbusiness.industryEntropy (statistical thermodynamics)Reproducibility of ResultsElectroencephalographyPattern recognitionSample entropyArtificial intelligenceArtifactsbusinessAlgorithmsEntropy (order and disorder)2011 Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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Semi-automated evaluation tool for retinal vasculopathy.

2009

The ocular fundus is the only area of human body where vascular system is visible using relatively simple instrumentation. Furthermore, there is medical suggestive evidence of a direct relationship between certain measures of vascular characteristics in the ocular fundus (arteriolar and venular calibers and focal arteriolar narrowing) and cardiovascular diseases. In order to establish such relationship on sound statistical basis a method must be provided to measure the needed values in an easy, yet precise and repeatable way. This paper presents a system to assist physicians in signaling and storing the data associated to signs of vascular deterioration and vascular calibers in non-mydriati…

Computer scienceHealth InformaticsFundus (eye)Sensitivity and SpecificityPattern Recognition AutomatedUser-Computer InterfaceRetinal DiseasesArtificial IntelligenceImage Interpretation Computer-AssistedmedicinePhotographyHumansComputer visionInstrumentation (computer programming)Vascular DiseasesRetinoscopymedicine.diagnostic_testbusiness.industryPhotographyReproducibility of ResultsRetinal Vesselseye diseasesComputer Science ApplicationsRetinal vasculopathyArtificial intelligencebusinessAlgorithmsSoftwareRetinoscopyComputer methods and programs in biomedicine
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