Bias of least squares approaches for diffusion tensor estimation from array coils in DT-MRI.
Least Squares (LS) and its weighted version are standard techniques to estimate the Diffusion Tensor (DT) from Diffusion Weighted Images (DWI). They require to linearize the problem by computing the logarithm of the DWI. For the single-coil Rician noise model it has been shown that this model does not introduce a significant bias, but for multiple array coils and parallel imaging, the noise cannot longer be modeled as Rician. As a result the validity of LS approaches is not assured. An analytical study of noise statistics for a multiple coil system is carried out, together with the Weighted LS formulation and noise analysis for this model. Results show that the bias in the computation of the components of the DT may be comparable to their variance in many cases, stressing the importance of unbiased filtering previous to DT estimation.
Tristán-Vega
Antonio
A
Laboratory of Image Processing, Universidad de Valladolid, Spain. atriveg@lpi.tel.uva.es
Westin
Carl-Fredrik
CF
Aja-Fernández
Santiago
S
D000465:Algorithms; D016477:Artifacts; D038524:Diffusion Magnetic Resonance Imaging / Q000295:instrumentation* / Q000379:methods*; D007089:Image Enhancement / Q000295:instrumentation / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016018:Least-Squares Analysis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity