An improved fiber tracking method for crossing fibers

Ning Zheng, Wenyao Zhang*, Xiaofan Liu

*Corresponding author for this work

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

Abstract

Fiber tracking is a basic task in analyzing data obtained by diffusion tensor magnetic resonance imaging (DT-MRI). In order to get a better tracking result for crossing fibers with noise, an improved fiber tracking method is proposed in this paper. The method is based on the framework of Bayesian fiber tracking, but improves its ability to deal with crossing fibers, by introducing the high order tensor (HOT) model as well as a new fiber direction selection strategy. In this method, orientation distribution function is first obtained from HOT model, and then used as the likelihood probability to control fiber tracing. On this basis, the direction in candidates that has the smallest change relative to current two previous directions is selected as the next tracing direction. By this means, our method achieves better performance in processing crossing fibers.

Original languageEnglish
Title of host publicationImage and Graphics - 8th International Conference, ICIG 2015, Proceedings
EditorsYu-Jin Zhang
PublisherSpringer Verlag
Pages552-561
Number of pages10
ISBN (Print)9783319219776
DOIs
Publication statusPublished - 2015
Event8th International Conference on Image and Graphics, ICIG 2015 - Tianjin, China
Duration: 13 Aug 201516 Aug 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9217
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference8th International Conference on Image and Graphics, ICIG 2015
Country/TerritoryChina
CityTianjin
Period13/08/1516/08/15

Keywords

  • Crossing fibers
  • Diffusion tensor magnetic resonance imaging (DT-MRI)
  • Fiber tracking
  • High order tensor (HOT)

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