Detail publikace

Atlas-based Registration of MRI Brain Images with the Use of Point Similarity Measures

SCHWARZ, D.

Originální název

Atlas-based Registration of MRI Brain Images with the Use of Point Similarity Measures

Anglický název

Atlas-based Registration of MRI Brain Images with the Use of Point Similarity Measures

Jazyk

en

Originální abstrakt

High-dimensional deformable registration of MRI brain images is presented here. The deformation is driven by local forces estimated from point similarities based on joint histogram and with the use of prior information obtained from tissue probability maps available in selected commonly used brain atlases. Three point similarity measures are tested in an experiment with data obtained from standard Simulated Brain Database.

Anglický abstrakt

High-dimensional deformable registration of MRI brain images is presented here. The deformation is driven by local forces estimated from point similarities based on joint histogram and with the use of prior information obtained from tissue probability maps available in selected commonly used brain atlases. Three point similarity measures are tested in an experiment with data obtained from standard Simulated Brain Database.

Dokumenty

BibTex 


@inproceedings{BUT14557,
  author="Daniel {Schwarz}",
  title="Atlas-based Registration of MRI Brain Images with the Use of Point Similarity Measures",
  annote="High-dimensional deformable registration of MRI brain images is presented here. The deformation is driven by local forces estimated from point similarities based on joint histogram and with the use of prior information obtained from tissue probability maps available in selected commonly used brain atlases. Three point similarity measures are tested in an experiment with data obtained from standard Simulated Brain Database.",
  address="VUT Brno",
  booktitle="Proceedings of the International Interdisciplinary Students' Contest HONEYWELL EMI 2005",
  chapter="14557",
  institution="VUT Brno",
  year="2005",
  month="april",
  pages="632",
  publisher="VUT Brno",
  type="conference paper"
}