2009
Using Perturbation theory to reduce noise in diffusion tensor fields
Bansal R, Staib LH, Xu D, Laine AF, Liu J, Peterson BS. Using Perturbation theory to reduce noise in diffusion tensor fields. Medical Image Analysis 2009, 13: 580-597. PMID: 19540791, PMCID: PMC2782748, DOI: 10.1016/j.media.2009.05.001.Peer-Reviewed Original ResearchConceptsTensor fieldsDiffusion tensor fieldsPerturbation theoryMarkov random fieldPrior termDifferent spatial directionsRandom fieldsSymmetric tensorsRiemannian distanceSpatial directionsWhite matter fiber bundlesSmoothed fieldsLikelihood termEigenvaluesOriginal fieldEigenvectorsTensorReal-world datasetsDTI datasetsHomogeneous regionsTheoryLow signalNoiseNoise ratioFine structure
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