Quantification of measurement error in DTI: theoretical predictions and validation.
The presence of Rician noise in magnetic resonance imaging (MRI) introduces systematic errors in diffusion tensor imaging (DTI) measurements. This paper evaluates gradient direction schemes and tensor estimation routines to determine how to achieve the maximum accuracy and precision of tensor derived measures for a fixed amount of scan time. We present Monte Carlo simulations that quantify the effect of noise on diffusion measurements and validate these simulation results against appropriate in-vivo images. The predicted values of the systematic and random error caused by imaging noise are essential both for interpreting the results of statistical analysis and for selecting optimal imaging protocols given scan time limitations.
Department of Computer Science, University of North Carolina, USA.
Casey
C
Goodlett
P Thomas
PT
Fletcher
Weili
W
Lin
Guido
G
Gerig
D000465:Algorithms; D016477:Artifacts; D001921:Brain / Q000033:anatomy & histology*; D003198:Computer Simulation; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods; D008959:Models, Neurological; D009413:Nerve Fibers, Myelinated / Q000648:ultrastructure*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity