ist2019_v8.pdf (4.37 MB)
Brain fibre tracking improved by diffusion tensor similarity using non-Euclidean distances
conference contribution
posted on 2019-12-13, 13:35 authored by Lei Ye, Eugenie Hunsicker, Baihua LiBaihua Li, Diwei ZhouDiwei ZhouFibre 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 fibre tracking 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 using
non-Euclidean distances. Quantitative comparison is carried out
through a collection of simulation experiments using statistics
of diffusion tensor anisotropy and volume, and tracking errors.
Fibre tracking in Corpus Callosum from a healthy human brain
dataset is presented.
History
School
- Science
Department
- Computer Science
- Mathematical Sciences
Published in
2019 IEEE International Conference on Imaging Systems and Techniques (IST)Publisher
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher statement
Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksAcceptance date
2019-10-31Publication date
2020-02-27Copyright date
2019ISBN
9781728138688Publisher version
Language
- en
Location
Abu Dhabi, United Arab EmiratesEvent dates
8-10th Dec 2019Depositor
Dr Diwei Zhou Deposit date: 11 December 2019Usage metrics
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