Publication result detail

3D Brain Tissue Selection and Segmentation from MRI

UHER, V.; BURGET, R.; MAŠEK, J.; DUTTA, M.

Original Title

3D Brain Tissue Selection and Segmentation from MRI

English Title

3D Brain Tissue Selection and Segmentation from MRI

Type

Paper in proceedings (conference paper)

Original Abstract

Magnetic resonance imaging (MRI) is a visualizing method used in radiology that enables viewing internal structures of the body. Using several mathematical methods with data retrieved from MRI it is possible to quantify the brain compartment volume, which has many applications in cognitive, clinical and comparative neurosciences. This paper introduces a new fully automatic method, which can measure the volume of brain tissue using scans obtained from MRI devices. The method introduced in this paper was trained on data taken from 12 patients and the trained result was validated on other independent data obtained from 10 patients and compared to a human experts accuracy. The result achieves 99.407 % +/- 0.062 voxel error accuracy, which is comparable to results achieved by humans (99.540 % + 0.0775) but in a significantly shorter time and without the need of human involvement.

English abstract

Magnetic resonance imaging (MRI) is a visualizing method used in radiology that enables viewing internal structures of the body. Using several mathematical methods with data retrieved from MRI it is possible to quantify the brain compartment volume, which has many applications in cognitive, clinical and comparative neurosciences. This paper introduces a new fully automatic method, which can measure the volume of brain tissue using scans obtained from MRI devices. The method introduced in this paper was trained on data taken from 12 patients and the trained result was validated on other independent data obtained from 10 patients and compared to a human experts accuracy. The result achieves 99.407 % +/- 0.062 voxel error accuracy, which is comparable to results achieved by humans (99.540 % + 0.0775) but in a significantly shorter time and without the need of human involvement.

Keywords

Image processing, skull stripping, machine learning, brain selection, segmentation.

Key words in English

Image processing, skull stripping, machine learning, brain selection, segmentation.

Authors

UHER, V.; BURGET, R.; MAŠEK, J.; DUTTA, M.

RIV year

2014

Released

02.07.2013

ISBN

978-1-4799-0402-0

Book

36th International Conference on Telecommunications and Signal processing

Pages from

839

Pages to

842

Pages count

4

BibTex

@inproceedings{BUT100924,
  author="Václav {Uher} and Radim {Burget} and Jan {Mašek} and Malay Kishore {Dutta}",
  title="3D Brain Tissue Selection and Segmentation from MRI",
  booktitle="36th International Conference on Telecommunications and Signal processing",
  year="2013",
  pages="839--842",
  isbn="978-1-4799-0402-0"
}