Detail publikace

Automatic system for MR perfusion images processing

Originální název

Automatic system for MR perfusion images processing

Anglický název

Automatic system for MR perfusion images processing

Jazyk

en

Originální abstrakt

This article describes automated detection and segmentation of the tumor and tumor edema. Automated detection of the tumor tissue area is based on the human brain symmetry. Healthy brain has a strong sagittal symmetry. Assuming the tumor is not placed symmetrically in both hemispheres, is possible use this method for its detection. Tumor area is evaluated from image which is obtained by summing partial results from all T2 weighted images. Segmentation and precise etection of the tumor in the by previous step marked area is based on Chan Vese algorithm. Segmentation is provided in T1 and T2 weighted images in order to achieve highest precision on the tumor border. Resulting masks are transformed into perfusion image coordinates and applied to the various perfusion maps.

Anglický abstrakt

This article describes automated detection and segmentation of the tumor and tumor edema. Automated detection of the tumor tissue area is based on the human brain symmetry. Healthy brain has a strong sagittal symmetry. Assuming the tumor is not placed symmetrically in both hemispheres, is possible use this method for its detection. Tumor area is evaluated from image which is obtained by summing partial results from all T2 weighted images. Segmentation and precise etection of the tumor in the by previous step marked area is based on Chan Vese algorithm. Segmentation is provided in T1 and T2 weighted images in order to achieve highest precision on the tumor border. Resulting masks are transformed into perfusion image coordinates and applied to the various perfusion maps.

BibTex


@inproceedings{BUT102216,
  author="Martin {Čáp} and Karel {Bartušek} and Petr {Marcoň}",
  title="Automatic system for MR perfusion images processing",
  annote="This article describes automated detection and segmentation of the tumor and tumor edema. Automated detection of the tumor tissue area is based on the human brain symmetry. Healthy brain has a strong sagittal symmetry. Assuming the tumor is not placed symmetrically in both hemispheres, is possible use this method for its detection. Tumor area is evaluated from image which is obtained by summing partial results from all T2 weighted images. Segmentation and precise  etection of the tumor in the by previous step marked area is based on Chan Vese algorithm. Segmentation is provided in T1 and T2 weighted images in order to achieve highest precision on the tumor border. Resulting masks are transformed  into perfusion image coordinates and applied to the various perfusion maps.",
  booktitle="International Interdisciplinary PhD Workshop 2013, Proceedings",
  chapter="102216",
  howpublished="electronic, physical medium",
  year="2013",
  month="september",
  pages="297--301",
  type="conference paper"
}