Detail publikace

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.

Originální název

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

Anglický název

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

Jazyk

en

Originální abstrakt

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.

Anglický abstrakt

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.

Dokumenty

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",
  annote="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.",
  address="Springer",
  chapter="96701",
  institution="Springer",
  number="6",
  volume="25",
  year="2012",
  month="december",
  pages="1--12",
  publisher="Springer",
  type="journal article - other"
}