Iterative co-linearity filtering and parameterization of fiber tracts in the entire cingulum

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Abstract

We present a method for the fully automated extraction of the cingulum using diffusion tensor imaging (DTI) data. We perform whole-brain tractography and initialize tract selection in the cingulum with a registered DTI atlas. Tracts are parameterized from which tract co-linearity is derived. The tract set, filtered on the basis of co-linearity with the cingulum shape, yields an improved segmentation of the cingulum and is subsequently optimized in an iterative fashion to further improve the tract selection. We evaluate the method using a large DTI database of 500 subjects from the general population and show robust extraction of tracts in the entire cingulate bundle in both hemispheres. We demonstrate the use of the extracted fiber-tracts to compare left and right cingulate bundles. Our asymmetry analysis shows a higher fractional anisotropy in the left anterior part of the cingulum compared to the right side, and the opposite effect in the posterior part. © 2009 Springer-Verlag.

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De Groot, M., Vernooij, M. W., Klein, S., Leemans, A., De Boer, R., Van Der Lugt, A., … Niessen, W. J. (2009). Iterative co-linearity filtering and parameterization of fiber tracts in the entire cingulum. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5761 LNCS, pp. 853–860). https://doi.org/10.1007/978-3-642-04268-3_105

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