Publication detail

Tracking of axonal bundles in diffusion MRI brain images

PISKOŘOVÁ, Z. LABOUNEK, R.

Original Title

Tracking of axonal bundles in diffusion MRI brain images

English Title

Tracking of axonal bundles in diffusion MRI brain images

Type

conference paper

Language

en

Original Abstract

The aim of this work is to design tracking algorithm which will be able to track brain axonal bundles in diffusion weighted MRI data. Estimation of anisotropic diffusion profile inside voxels was performed by diffusion tensor imaging model (DTI). Tracing is based on the 4th order Runge-Kutta method. Algorithm is implemented in the MATLAB computing environment and is tested on real data biological phantom.

English abstract

The aim of this work is to design tracking algorithm which will be able to track brain axonal bundles in diffusion weighted MRI data. Estimation of anisotropic diffusion profile inside voxels was performed by diffusion tensor imaging model (DTI). Tracing is based on the 4th order Runge-Kutta method. Algorithm is implemented in the MATLAB computing environment and is tested on real data biological phantom.

Keywords

Diffusion MRI, tractography, diffusion tensor imaging, DTI, Runge-Kutta method, deterministic tracking algorithm

RIV year

2015

Released

23.04.2015

Publisher

Brno University of Technology, Faculty of Electrical Engineering and Communication

Location

Brno

ISBN

978-80-214-5148-3

Book

Proceedings of the 21st Conference STUDENT EEICT 2015

Edition number

1

Pages from

137

Pages to

139

Pages count

3

URL

BibTex


@inproceedings{BUT118242,
  author="Zuzana {Piskořová} and René {Labounek}",
  title="Tracking of axonal bundles in diffusion MRI brain images",
  annote="The aim of this work is to design tracking algorithm which will be able to track brain axonal bundles in diffusion weighted MRI data. Estimation of anisotropic diffusion profile inside voxels was performed by diffusion tensor imaging model (DTI). Tracing is based on the 4th order Runge-Kutta method. Algorithm is implemented in the MATLAB computing environment and is tested on real data biological phantom.",
  address="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  booktitle="Proceedings of the 21st Conference STUDENT EEICT 2015",
  chapter="118242",
  howpublished="online",
  institution="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  year="2015",
  month="april",
  pages="137--139",
  publisher="Brno University of Technology, Faculty of Electrical Engineering and Communication",
  type="conference paper"
}