Non-rigid registration of high angular resolution diffusion images represented by Gaussian mixture fields.
In this paper, we present a novel algorithm for non-rigidly registering two high angular resolution diffusion weighted MRIs (HARDI), each represented by a Gaussian mixture field (GMF). We model the non-rigid warp by a thin-plate spline and formulate the registration problem as the minimization of the L2 distance between the two given GMFs. The key mathematical contributions of this work are, (i) a closed form expression for the derivatives of this objective function with respect to the parameters of the registration and (ii) a novel and simpler re-orientation scheme based on an extension to the "Preservation of Principle Directions" technique. We present results of our algorithm's performance on several synthetic and real HARDI data sets.
Cheng
Guang
G
CISE, University of Florida, USA. gcheng@cise.ufl.edu
Vemuri
Baba C
BC
Carney
Paul R
PR
Mareci
Thomas H
TH
D000465:Algorithms; D001185:Artificial Intelligence; D003627:Data Interpretation, Statistical; D038524:Diffusion Magnetic Resonance Imaging / Q000379:methods*; D006801:Humans; D007089:Image Enhancement / Q000379:methods*; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D016011:Normal Distribution; D010363:Pattern Recognition, Automated / Q000379:methods*; D019047:Phantoms, Imaging; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique