Streamlet Tractography
Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
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Streamlet Tractography. / Liptrot, Matthew George; Darkner, Sune; Feragen, Aasa; Lauze, Francois Bernard.
2017. Abstract from 25th ISMRM Annual Meeting, Honolulu, United States.Research output: Contribution to conference › Conference abstract for conference › Research › peer-review
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TY - ABST
T1 - Streamlet Tractography
AU - Liptrot, Matthew George
AU - Darkner, Sune
AU - Feragen, Aasa
AU - Lauze, Francois Bernard
N1 - Conference code: 25
PY - 2017/4
Y1 - 2017/4
N2 - 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.
AB - 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.
UR - https://www.ismrm.org/17/program_files/O71.htm
M3 - Conference abstract for conference
Y2 - 22 April 2017 through 27 April 2017
ER -
ID: 183736281