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Deterministic fibre tracking improved by diffusion tensor similarity

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journal contribution
posted on 2019-05-02, 10:25 authored by Lei Ye, Diwei Zhou, Eugenie Hunsicker, Baihua Li
Fibre tracking is a non-invasive technique based on Diffusion Tensor Imaging (DTI) that provides useful information about biological anatomy and connectivity. In this paper, we propose a new tractography algorithm, named TAS (Tracking by Angle and Similarity), which is able to overcome the shortfalls of existing algorithms by considering not only the main diffusion directions, but also the similarity of diffusion tensors. The algorithm achieved better tracking results in simulation experiments. Fibre tracking from a real brain dataset is presented.

History

School

  • Science

Department

  • Mathematical Sciences

Published in

MIUA 2019

Citation

YE, L. .... et al., 2019. Deterministic fibre tracking improved by diffusion tensor similarity. Presented at the 23rd Conference on Medical Image Understanding and Analysis (MIUA), 24-26 July 2019, Liverpool.

Publisher

Springer

Version

  • AM (Accepted Manuscript)

Publisher statement

This is a pre-copyedited version of a contribution published in Medical Image Understanding and Analysis. Yalin Zheng; Bryan Williams; Ke Chen (eds.) published by Springer. The definitive authenticated version is available online via http://dx.doi.org/10.1007/978-3-030-39343-4

Acceptance date

2019-04-15

Publication date

2020-03-14

Copyright date

2020

ISBN

9783030393434

ISSN

1865-0929

Book series

Communications in Computer and Information Science; 1065

Language

  • en

Editor(s)

Yalin Zheng; Bryan Williams; Ke Chen

Location

Liverpool

Event dates

24-26 July 2019

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    Loughborough Publications

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