Publication result detail

A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research

SCHWARZ, D.; PROVAZNÍK, I.

Original Title

A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research

English Title

A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research

Type

Peer-reviewed article not indexed in WoS or Scopus

Original Abstract

Image registration methods play a crucial role in computational neuroanatomy. This paper mainly contributes to the field of image registration with the use of nonlinear spatial transformations. Particularly, problems connected to matching magnetic resonance imaging (MRI) brain image data obtained from various subjects and with various imaging conditions are solved here. Registration is driven by local forces derived from multimodal point similarity measures which are estimated with the use of joint intensity histogram and tissue probability maps. A spatial deformation model imitating principles of continuum mechanics is used. Five similarity measures are tested in an experiment with image data obtained from the Simulated Brain Database and a quantitative evaluation of the algorithm is presented. Results of application of the method in automated spatial detection of anatomical abnormalities in first-episode schizophrenia are presented.

English abstract

Image registration methods play a crucial role in computational neuroanatomy. This paper mainly contributes to the field of image registration with the use of nonlinear spatial transformations. Particularly, problems connected to matching magnetic resonance imaging (MRI) brain image data obtained from various subjects and with various imaging conditions are solved here. Registration is driven by local forces derived from multimodal point similarity measures which are estimated with the use of joint intensity histogram and tissue probability maps. A spatial deformation model imitating principles of continuum mechanics is used. Five similarity measures are tested in an experiment with image data obtained from the Simulated Brain Database and a quantitative evaluation of the algorithm is presented. Results of application of the method in automated spatial detection of anatomical abnormalities in first-episode schizophrenia are presented.

Keywords

Computational neuroanatomy, deformable registration, first-episode schizophrenia, magnetic resonance imaging.

Key words in English

Computational neuroanatomy, deformable registration, first-episode schizophrenia, magnetic resonance imaging.

Authors

SCHWARZ, D.; PROVAZNÍK, I.

RIV year

2010

Released

01.04.2007

Publisher

IEEE

Location

USA

ISBN

0278-0062

Periodical

IEEE TRANSACTIONS ON MEDICAL IMAGING

Volume

26

Number

4

State

United States of America

Pages from

452

Pages to

461

Pages count

10

BibTex

@article{BUT45079,
  author="Daniel {Schwarz} and Valentýna {Provazník}",
  title="A Deformable Registration Method for Automated Morphometry of MRI Brain Images in Neuropsychiatric Research",
  journal="IEEE TRANSACTIONS ON MEDICAL IMAGING",
  year="2007",
  volume="26",
  number="4",
  pages="452--461",
  issn="0278-0062"
}