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
2004
Correcting Nonuniformities in MRI Intensities Using Entropy Minimization Based on an Elastic Model
Bansal R, Staib L, Peterson B. Correcting Nonuniformities in MRI Intensities Using Entropy Minimization Based on an Elastic Model. Lecture Notes In Computer Science 2004, 3216: 78-86. DOI: 10.1007/978-3-540-30135-6_10.Peer-Reviewed Original ResearchPartial differential equationsConstraints of interestEntropy minimizationBody forceBias fieldDifferential equationsObserved imagesMathematical formulationOverall entropyElastic deformationEntropyElastic modelHomogeneous regionsMinimizationFieldConstraintsFormulationEquationsNonuniformityMultiplicative bias fieldAlgorithmOriginal imageDeformationForce