Evaluation of Fiber Tracking Results from UKF Tractography Methods

Na Wang, Wenyao Zhang, Wen Zhao

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

Abstract

Tractography is an important way to get insight into white matter of brain. Many techniques like the promising UKF tractography have been developed for this purpose. In this paper, four measure metrics including spatial metric, tangent metric, curve metric, and Hausdorff distance, are used to evaluate and compare the accuracy of UKF tractography with different tensor models. And a synthetic diffusion-weighted imaging dataset and a real brain dataset are used to test the tractography methods. Quantitative and qualitative test results indicate that UKF tractography based on two-tensor model needs to be further improved in accuracy though it has advantages in processing cross fibers. This is a helpful hint for future study of UKF tractography.

Original languageEnglish
Title of host publicationProceedings - 13th International Conference on Computational Intelligence and Security, CIS 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages603-606
Number of pages4
ISBN (Electronic)9781538648223
DOIs
Publication statusPublished - 2 Jul 2017
Event13th International Conference on Computational Intelligence and Security, CIS 2017 - Hong Kong, Hong Kong
Duration: 15 Dec 201718 Dec 2017

Publication series

NameProceedings - 13th International Conference on Computational Intelligence and Security, CIS 2017
Volume2018-January

Conference

Conference13th International Conference on Computational Intelligence and Security, CIS 2017
Country/TerritoryHong Kong
CityHong Kong
Period15/12/1718/12/17

Keywords

  • UKF
  • evaluation
  • fiber tracts
  • tractography

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