Nonlinear smoothing for reduction of systematic and random errors in diffusion tensor imaging

Autor:	G J, Parker, J A, Schnabel, M R, Symms, D J, Werring, G J, Barker
Rok vydání:	2000
Předmět:	Nonlinear Dynamics Anisotropy Brain Humans Artifacts Image Enhancement Magnetic Resonance Imaging Sensitivity and Specificity
Zdroj:	Journal of magnetic resonance imaging : JMRI. 11(6)
ISSN:	1053-1807
Popis:	Calculation and sorting of the eigenvectors of diffusion using diffusion tensor imaging has previously been shown to be sensitive to noise levels in the acquired data. This sensitivity manifests as random and systematic errors in the diffusion eigenvalues and derived parameters such as indices of anisotropy. An optimized application of nonlinear smoothing techniques to diffusion data prior to calculation of the diffusion tensor is shown to reduce both random and systematic errors, while causing little blurring of anatomical structures. Conversely, filtering applied to calculated images of fractional anisotropy is shown to fail in reducing systematic errors and in recovering anatomical detail. Using both real and simulated brain data sets, it is demonstrated that this approach has the potential to allow acquisition of data that would otherwise be too noisy to be of use.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=pmid________::f702509fd1594d77f614cd907cbb8eb9 https://pubmed.ncbi.nlm.nih.gov/10862071 Zobrazit plný text záznamu Plný text