Detail publikace

Automatic Detection of Brain Tumors in MR Images

Originální název

Automatic Detection of Brain Tumors in MR Images

Anglický název

Automatic Detection of Brain Tumors in MR Images

Jazyk

en

Originální abstrakt

This paper deals with automatic brain tumor detection in magnetic resonance images. The goal is to determine whether the MR image of a brain contains a tumor. The proposed method works with T2-weighted magnetic resonance images, where the head is vertically aligned. The detection is based on checking the left-right symmetry of the brain, which is the assumption for healthy brain. The algorithm was tested by fivefold cross-validation technique on 72 images of brain containing tumors and 131 images of healthy brain. The proposed method reaches the true positive rate of 91.16% and the true negative rate of 94.68%.

Anglický abstrakt

This paper deals with automatic brain tumor detection in magnetic resonance images. The goal is to determine whether the MR image of a brain contains a tumor. The proposed method works with T2-weighted magnetic resonance images, where the head is vertically aligned. The detection is based on checking the left-right symmetry of the brain, which is the assumption for healthy brain. The algorithm was tested by fivefold cross-validation technique on 72 images of brain containing tumors and 131 images of healthy brain. The proposed method reaches the true positive rate of 91.16% and the true negative rate of 94.68%.

BibTex


@inproceedings{BUT100457,
  author="Pavel {Dvořák} and Walter G. {Kropatsch} and Karel {Bartušek}",
  title="Automatic Detection of Brain Tumors in MR Images",
  annote="This paper deals with automatic brain tumor detection in magnetic resonance images. The goal is to determine whether the MR image of a brain contains a tumor. The proposed method works with T2-weighted magnetic resonance images, where the head is vertically aligned. The detection is based on checking the left-right symmetry of the brain, which is the assumption for healthy brain. The algorithm was tested by fivefold cross-validation technique on 72 images of brain containing tumors and 131 images of healthy brain. The proposed method reaches the true positive rate of 91.16% and the true negative rate of 94.68%.",
  booktitle="2013 36th International Conference on Telecommunications and Signal Processing (id 21150)",
  chapter="100457",
  howpublished="electronic, physical medium",
  year="2013",
  month="july",
  pages="577--580",
  type="conference paper"
}