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Abstract #0065

Streamlet Tractography

Matthew George Liptrot1,2, Sune Darkner1, Aasa Feragen1, and Francois Lauze1

1Department of Computer Science, University of Copenhagen, Copenhagen, Denmark, 2Department of Applied Mathematics and Computer Science, Technical University of Denmark, Lyngby, Denmark

Streamlet tractography is a novel approach that aims to combine the benefits of both streamline and global tractography approaches. In contrast to requiring individual streamlines to successfully propagate from seed to target regions to register as a connection, here short streamlines - streamlets - are initially generated from each white-matter voxel, and then seed-to-target connectivity is assessed by evaluating connectivity between these streamlets. In this way, streamlet generation can adapt to the local environment, whilst seed-to-target connectivity is assessed at the global level. Furthermore, the proposed framework permits the inclusion of previous results and alternative data sources.

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