Segmenting crossing fiber geometries using fluid mechanics tensor distribution function tractography

Nathan Hageman, Alex Leow, David Shattuck, Liang Zhan, Paul Thompson, Siwei Zhu, Arthur Toga

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

We introduce a fluid mechanics based tractography method that estimates the most likely connection path between points in a tensor distribution function (TDF) dataset. We simulated the flow of an artificial fluid whose properties are related to the underlying TDF dataset. The resulting fluid velocity was used as a metric of connection strength. We validated our algorithm using a digital phantom dataset based on a pattern with two intersecting tracts. When compared to a TDF streamline method and our single tensor fluid mechanics tractography algorithm, our method was able to segment intersecting tracts at a finer spatial resolution. Our method was successfully applied to human control data to segment a major fiber pathway, the corpus callosum, even in problematic regions with crossing fiber geometries.

Original languageEnglish
Title of host publicationProceedings - 2009 IEEE International Symposium on Biomedical Imaging
Subtitle of host publicationFrom Nano to Macro, ISBI 2009
Pages1390-1393
Number of pages4
DOIs
StatePublished - 2009
Externally publishedYes
Event2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009 - Boston, MA, United States
Duration: 28 Jun 20091 Jul 2009

Publication series

NameProceedings - 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009

Conference

Conference2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, ISBI 2009
Country/TerritoryUnited States
CityBoston, MA
Period28/06/091/07/09

Keywords

  • Biomedical image processing
  • Fluid flow
  • Image segmentation
  • Magnetic resonance imaging
  • Partial differential equations

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