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  • Diffusion Tensor Imaging (DTI) and fiber tractography are established methods to reconstruct major white matter tracts in the human brain in-vivo. Particularly in the context of neurosurgical procedures, reliable information about the course of fiber bundles is important to minimize postoperative deficits while maximizing the tumor resection volume. Since routinely used deterministic streamline tractography approaches often underestimate the spatial extent of white matter tracts, a novel approach to improve fiber segmentation is presented here, considering clinical time constraints. Therefore, fiber tracking visualization is enhanced with statistical information from multiple tracking applications to determine uncertainty in reconstruction based on clinical DTI data. After initial deterministic fiber tracking and centerline calculation, new seed regions are generated along the result's midline. Tracking is applied to all new seed regions afterwards, varying in number and applied offset. The number of fibers passing each voxel is computed to model different levels of fiber bundle membership.
  • Diffusion Tensor Imaging (DTI) and fiber tractography are established methods to reconstruct major white matter tracts in the human brain in-vivo. Particularly in the context of neurosurgical procedures, reliable information about the course of fiber bundles is important to minimize postoperative deficits while maximizing the tumor resection volume. Since routinely used deterministic streamline tractography approaches often underestimate the spatial extent of white matter tracts, a novel approach to improve fiber segmentation is presented here, considering clinical time constraints. Therefore, fiber tracking visualization is enhanced with statistical information from multiple tracking applications to determine uncertainty in reconstruction based on clinical DTI data. After initial deterministic fiber tracking and centerline calculation, new seed regions are generated along the result's midline. Tracking is applied to all new seed regions afterwards, varying in number and applied offset. The number of fibers passing each voxel is computed to model different levels of fiber bundle membership. (en)
Title
  • Reconstruction of White Matter Tracts via Repeated Deterministic Streamline Tracking - Initial Experience
  • Reconstruction of White Matter Tracts via Repeated Deterministic Streamline Tracking - Initial Experience (en)
skos:prefLabel
  • Reconstruction of White Matter Tracts via Repeated Deterministic Streamline Tracking - Initial Experience
  • Reconstruction of White Matter Tracts via Repeated Deterministic Streamline Tracking - Initial Experience (en)
skos:notation
  • RIV/00159816:_____/13:00060613!RIV14-MSM-00159816
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
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  • P(ED1.100/02/0123)
http://linked.open...iv/cisloPeriodika
  • 5
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
  • Bauer, Miriam Helen Anna
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  • 101779
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  • RIV/00159816:_____/13:00060613
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  • framework; tractography; human brain; glioma removal; wild bootstrap; thalamic nuclei; dti segmentation; glioblastoma-multiforme; diffusion tensor mri; neuronal fiber pathways (en)
http://linked.open.../riv/klicoveSlovo
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  • US - Spojené státy americké
http://linked.open...ontrolniKodProRIV
  • [21D336AB7DB6]
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  • PLoS ONE
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  • 8
http://linked.open...iv/tvurceVysledku
  • Klein, Jan
  • Bauer, Miriam Helen Anna
  • Kuhnt, Daniela
  • Nimsky, Christopher
  • Barbieri, Sebastiano
  • Becker, Andreas
  • Freisleben, Bernd
  • Hahn, Horst K.
http://linked.open...ain/vavai/riv/wos
  • 000321390200042
issn
  • 1932-6203
number of pages
http://bibframe.org/vocab/doi
  • 10.1371/journal.pone.0063082
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