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Registration, Atlas Estimation and Variability Analysis of White Matter Fiber Bundles Modeled as Currents
S. Durrleman, P. Fillard, X. Pennec, A. Trouvé, N. Ayache. In NeuroImage, Note: DOI: 10.1016/j.neuroimage.2010.11.056, pp. (in press). 2010.
This paper proposes a generic framework for the registration, the template estimation and the variability analysis of white matter fi ber bundles extracted from di ffusion images. This framework is based on the metric on currents for the comparison of fi ber bundles. This metric measures anatomical diff erences between fi ber bundles, seen as global homologous structures across subjects. It avoids the need to establish correspondences between points or between individual bers of diff erent bundles. It can measure di fferences both in terms of the geometry of the bundles (like its boundaries) and in terms of the density of fibers within the bundle. It is robust to fi ber interruptions and reconnections. In addition, a recently introduced sparse approximation algorithm allows us to give an interpretable representation of the fi ber bundles and their variations in the framework of currents.
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