We present a new methodology based on directional data clustering to represent white matter fiber orientations in magnetic\r\nresonance analyses for high angular resolution diffusion imaging.Aprobabilistic methodology is proposed for estimating intravoxel\r\nprincipal fiber directions, based on clustering directional data arising from orientation distribution function (ODF) profiles. ODF\r\nreconstructions are used to estimate intravoxel fiber directions using mixtures of von Mises-Fisher distributions. The method\r\nfocuses on clustering data on the unit sphere, where complexity arises from representing ODF profiles as directional data. The\r\nproposed method is validated on synthetic simulations, as well as on a real data experiment. Based on experiments, we show that\r\nby clustering profile data using mixtures of vonMises-Fisher distributions it is possible to estimate multiple fiber configurations in\r\na more robust manner than currently used approaches, without recourse to regularization or sharpening procedures.The method\r\nholds promise to support robust tractographic methodologies and to build realistic models of white matter tracts in the human\r\nbrain.
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