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. © 2009 Springer-Verlag.
CITATION STYLE
Cheng, G., Vemuri, B. C., Carney, P. R., & Mareci, T. H. (2009). Non-rigid registration of high angular resolution diffusion images represented by Gaussian mixture fields. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5761 LNCS, pp. 190–197). https://doi.org/10.1007/978-3-642-04268-3_24
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