Publication detail

Unsupervised Pathological Area Extraction Using 3D T2 and FLAIR MR Images

DVOŘÁK, P. BARTUŠEK, K. SMÉKAL, Z.

Original Title

Unsupervised Pathological Area Extraction Using 3D T2 and FLAIR MR Images

English Title

Unsupervised Pathological Area Extraction Using 3D T2 and FLAIR MR Images

Type

journal article in Web of Science

Language

en

Original Abstract

This work deals with fully automated extraction of brain tumor and edema in 3D MR volumes. The goal of this work is the extraction of the whole pathological area using such an algorithm that does not require a human intervention. For the good visibility of these kinds of tissues both T2-weighted and FLAIR images were used. The proposed method was tested on 80 MR volumes of publicly available BRATS database, which contains high and low grade gliomas, both real and simulated. The performance was evaluated by Dice coefficient, where the results were differentiated between high and low grade and real and simulated gliomas. The method reached promising results for all of the combination of images: real high grade (0.73), real low grade (0.81), simulated high grade (0.81), simulated low grade (0.81).

English abstract

This work deals with fully automated extraction of brain tumor and edema in 3D MR volumes. The goal of this work is the extraction of the whole pathological area using such an algorithm that does not require a human intervention. For the good visibility of these kinds of tissues both T2-weighted and FLAIR images were used. The proposed method was tested on 80 MR volumes of publicly available BRATS database, which contains high and low grade gliomas, both real and simulated. The performance was evaluated by Dice coefficient, where the results were differentiated between high and low grade and real and simulated gliomas. The method reached promising results for all of the combination of images: real high grade (0.73), real low grade (0.81), simulated high grade (0.81), simulated low grade (0.81).

Keywords

Brain tumor, Brain tumor segmentation, Extraction, Magnetic Resonance, MRI, Pathology, Segmentation, Symmetry analysis.

RIV year

2014

Released

20.11.2014

Publisher

Walter de Gruyter GmbH, Berlin, Germany

ISBN

1335-8871

Periodical

Measurement Science Review

Year of study

14

Number

6

State

SK

Pages from

357

Pages to

364

Pages count

8

Documents

BibTex


@article{BUT109899,
  author="Pavel {Dvořák} and Karel {Bartušek} and Zdeněk {Smékal}",
  title="Unsupervised Pathological Area Extraction Using 3D T2 and FLAIR MR Images",
  annote="This work deals with fully automated extraction of brain tumor and edema in 3D MR volumes. 
The goal of this work is the extraction of the whole pathological area using such an algorithm that does not require a human intervention. For the good visibility of these kinds of tissues both T2-weighted and FLAIR images were used.
The proposed method was tested on 80 MR volumes of publicly available BRATS database, which contains high and low grade gliomas, both real and simulated. The performance was evaluated by Dice coefficient, where the results were differentiated between high and low grade and real and simulated gliomas. The method reached promising results for all of the combination of images: real high grade (0.73), real low grade (0.81), simulated high grade (0.81), simulated low grade (0.81).",
  address="Walter de Gruyter GmbH, Berlin, Germany",
  chapter="109899",
  doi="10.2478/msr-2014-0049",
  howpublished="online",
  institution="Walter de Gruyter GmbH, Berlin, Germany",
  number="6",
  volume="14",
  year="2014",
  month="november",
  pages="357--364",
  publisher="Walter de Gruyter GmbH, Berlin, Germany",
  type="journal article in Web of Science"
}