Detail publikačního výsledku

Registration of FA and T1-weighted MRI Data of Healthy Human Brain based on Template Matching and Normalized Cross-correlation

MALÍNSKÝ, M.; PETER, R.; HODNELAND, E.; LUNDERVOLD, A.; LUNDERVOLD, A.; JAN, J.

Original Title

Registration of FA and T1-weighted MRI Data of Healthy Human Brain based on Template Matching and Normalized Cross-correlation

English Title

Registration of FA and T1-weighted MRI Data of Healthy Human Brain based on Template Matching and Normalized Cross-correlation

Type

Peer-reviewed article not indexed in WoS or Scopus

Original Abstract

Image registration is an essential process in a large range of medical image applications helping medical experts to increase the structural information and describe mutual relations between images. In a human brain studies it is a crucial step to spatially align diffusion tensor images (DTI) and anatomy data to quantitatively compare neural and structure features obtained from the same subject at different time-points. In this paper we propose a registration workflow for a reliable alignment of diffusion weighted fractional anisotropy (FA) images and T1-weighted high-resolution anatomical images of more than hundred subjects. Use of Template matching algorithm yields the robust inner subject registration and speed up of the registration process which helps in better assess of structural and functional brain connectivity. This method has been compared with well-known B-spline multiresolution registration algorithm.

English abstract

Image registration is an essential process in a large range of medical image applications helping medical experts to increase the structural information and describe mutual relations between images. In a human brain studies it is a crucial step to spatially align diffusion tensor images (DTI) and anatomy data to quantitatively compare neural and structure features obtained from the same subject at different time-points. In this paper we propose a registration workflow for a reliable alignment of diffusion weighted fractional anisotropy (FA) images and T1-weighted high-resolution anatomical images of more than hundred subjects. Use of Template matching algorithm yields the robust inner subject registration and speed up of the registration process which helps in better assess of structural and functional brain connectivity. This method has been compared with well-known B-spline multiresolution registration algorithm.

Keywords

Brain, Neuroscience, Magnetic resonance, Multimodal image registration, Template matching, Diffusion tensor imaging

Key words in English

Brain, Neuroscience, Magnetic resonance, Multimodal image registration, Template matching, Diffusion tensor imaging

Authors

MALÍNSKÝ, M.; PETER, R.; HODNELAND, E.; LUNDERVOLD, A.; LUNDERVOLD, A.; JAN, J.

RIV year

2016

Released

10.12.2012

Publisher

Springer

Location

Německo

ISBN

0897-1889

Periodical

JOURNAL OF DIGITAL IMAGING

Volume

25

Number

6

State

United States of America

Pages from

1

Pages to

12

Pages count

12

Full text in the Digital Library

http://hdl.handle.net/

BibTex

@article{BUT96701,
  author="Miloš {Malínský} and Roman {Peter} and Erlend {Hodneland} and A.J. {Lundervold} and Arvid {Lundervold} and Jiří {Jan}",
  title="Registration of FA and T1-weighted MRI Data of Healthy Human Brain based on Template Matching and Normalized Cross-correlation",
  journal="JOURNAL OF DIGITAL IMAGING",
  year="2012",
  volume="25",
  number="6",
  pages="1--12",
  issn="0897-1889"
}