Detail publikace

Automated Segmentation of Brain Tumor Edema in FLAIR MRI Using Symmetry and Thresholding

Originální název

Automated Segmentation of Brain Tumor Edema in FLAIR MRI Using Symmetry and Thresholding

Anglický název

Automated Segmentation of Brain Tumor Edema in FLAIR MRI Using Symmetry and Thresholding

Jazyk

en

Originální abstrakt

Nowadays, the brain tumor detection and segmentation in MR images is a developing issue. There are many research teams producing different and interesting methods andalgorithms for this particular task of medical image processing. Many of them are semi-automatic, but the aim of current research, and of this work, is to find a fully automatic method. This paper focuses on the automatic edema segmentation in FLAIR images. his type of contrast images was selected because of the visibility and manifestation of edema in this image type. Since in axial plane of healthy brain, the approximate left-right symmetry exists, it is used as the prior knowledge for searching the approximate edema location. It is assumed that the edema is not located symmetrically in both hemispheres, which is met in most cases. For the detection, the multi-resolution approach is used. Since the edemas manifest as a hyperintense area in FLAIR images, it is extracted using thresholding. For the automatic determination of the threshold, the Otsu's algorithm is used. This work does not deal with the tumor presence detection. One of our previous work focuses on this topic. The main reason for the edema segmentation is for the tumor classification. This will be carried out by applying the resulting mask of the proposed method to perfusion MR images. Since perfusion images are of very low contrast, the pathological area, it means the tumor and a potential edema around it, has to be detected and segmented in another type of MR images.

Anglický abstrakt

Nowadays, the brain tumor detection and segmentation in MR images is a developing issue. There are many research teams producing different and interesting methods andalgorithms for this particular task of medical image processing. Many of them are semi-automatic, but the aim of current research, and of this work, is to find a fully automatic method. This paper focuses on the automatic edema segmentation in FLAIR images. his type of contrast images was selected because of the visibility and manifestation of edema in this image type. Since in axial plane of healthy brain, the approximate left-right symmetry exists, it is used as the prior knowledge for searching the approximate edema location. It is assumed that the edema is not located symmetrically in both hemispheres, which is met in most cases. For the detection, the multi-resolution approach is used. Since the edemas manifest as a hyperintense area in FLAIR images, it is extracted using thresholding. For the automatic determination of the threshold, the Otsu's algorithm is used. This work does not deal with the tumor presence detection. One of our previous work focuses on this topic. The main reason for the edema segmentation is for the tumor classification. This will be carried out by applying the resulting mask of the proposed method to perfusion MR images. Since perfusion images are of very low contrast, the pathological area, it means the tumor and a potential edema around it, has to be detected and segmented in another type of MR images.

BibTex


@inproceedings{BUT100878,
  author="Pavel {Dvořák} and Karel {Bartušek} and Walter G. {Kropatsch}",
  title="Automated Segmentation of Brain Tumor Edema in FLAIR MRI Using Symmetry and Thresholding",
  annote="Nowadays, the brain tumor detection and segmentation in MR images is a developing issue. There are many research teams producing different and interesting methods andalgorithms for this particular task of medical image processing. Many of them are semi-automatic, but the aim of current research, and of this work, is to find a fully automatic method. This paper focuses on the automatic edema segmentation in FLAIR images.  his type of contrast images was selected because of the visibility and manifestation of edema in this image type. Since in axial plane of healthy brain, the approximate left-right symmetry exists, it is used as the prior knowledge for searching the approximate edema location. It is assumed that the edema is not located symmetrically in both hemispheres, which is met in most cases. For the detection, the multi-resolution approach is used. Since the edemas manifest as a hyperintense area in FLAIR images, it is extracted using thresholding. For the automatic determination of the threshold, the Otsu's algorithm is used. This work does not deal with the tumor presence detection. One of our previous work focuses on this topic. The main reason for the edema segmentation is for the tumor classification. This will be carried out by applying the resulting mask of the proposed method to perfusion MR images. Since perfusion images are of very low contrast, the pathological area, it means the tumor and a potential edema around it, has to be detected and segmented in another type of MR images.",
  booktitle="PIERS 2013 Stockholm Proceedings",
  chapter="100878",
  howpublished="online",
  year="2013",
  month="august",
  pages="936--939",
  type="conference paper"
}