2008
Calculation of the confidence intervals for transformation parameters in the registration of medical images
Bansal R, Staib LH, Laine AF, Xu D, Liu J, Posecion LF, Peterson BS. Calculation of the confidence intervals for transformation parameters in the registration of medical images. Medical Image Analysis 2008, 13: 215-233. PMID: 19138877, PMCID: PMC2891652, DOI: 10.1016/j.media.2008.09.002.Peer-Reviewed Original ResearchMeSH KeywordsAlgorithmsArtificial IntelligenceConfidence IntervalsCorpus CallosumData Interpretation, StatisticalHumansImage EnhancementImage Interpretation, Computer-AssistedImaging, Three-DimensionalMagnetic Resonance ImagingPattern Recognition, AutomatedReproducibility of ResultsSensitivity and SpecificitySubtraction TechniqueConceptsSimilarity transformationMultivariate GaussianLeast squares estimationTransformation parametersMathematical frameworkRandom variablesPresence of noiseCovariance matrixLandmark pointsQuantifying errorsSimilarity parameterAmount of misregistrationInherent technological limitationsAmount of noiseGaussianCoordinatesInevitable errorsReal-world datasetsFunctional relationAmount of blurErrorParametersWorld datasetsNoiseConfidence intervals
2007
Voxel-wise comparisons of the morphology of diffusion tensors across groups of experimental subjects
Bansal R, Staib LH, Plessen KJ, Xu D, Royal J, Peterson BS. Voxel-wise comparisons of the morphology of diffusion tensors across groups of experimental subjects. Psychiatry Research 2007, 156: 225-245. PMID: 18006284, PMCID: PMC2215316, DOI: 10.1016/j.pscychresns.2006.12.015.Peer-Reviewed Original ResearchConceptsApproximate covariance matrixRespective true valuesScalar measureMathematical frameworkMultivariate GaussianCovariance matrixMean eigenvaluesTensor morphologyEigenvaluesDelta methodEigenvectorsOrthogonal vectorsDiffusion tensorTensor eigenvectorsScalar magnitudeNonlinear wayTensorTrue valueGaussianComplex 3D morphologyDT dataAnisotropyNeuroanatomical connectivityProbabilityDirection