Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI.

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Version: Final published version
License: CC BY 4.0
Serval ID
serval:BIB_219A4428FEC4
Type
Article: article from journal or magazin.
Collection
Publications
Institution
Title
Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI.
Journal
PloS one
Author(s)
Choi U.S., Kawaguchi H., Matsuoka Y., Kober T., Kida I.
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Publication state
Published
Issued date
2019
Peer-reviewed
Oui
Volume
14
Number
2
Pages
e0210803
Language
english
Notes
Publication types: Journal Article
Publication Status: epublish
Abstract
We proposed a method for segmentation of brain tissues-gray matter, white matter, and cerebrospinal fluid-using multi-contrast images, including a T1 map and a uniform T1-weighted image, from a magnetization-prepared 2 rapid acquisition gradient echoes (MP2RAGE) sequence at 7 Tesla. The proposed method was evaluated with respect to the processing time and the similarity of the segmented masks of brain tissues with those obtained using FSL, FreeSurfer, and SPM12. The processing time of the proposed method (28 ± 0 s) was significantly shorter than those of FSL and SPM12 (444 ± 4 s and 159 ± 2 s for FSL and SPM12, respectively). In the similarity assessment, the tissue mask of the brain obtained by the proposed method showed higher consistency with those obtained using FSL than with those obtained using SPM12. The proposed method misclassified the subcortical structures and large vessels since it is based on the intensities of multi-contrast images obtained using MP2RAGE, which uses a similar segmentation approach as FSL but is not based on a template image or a parcellated brain atlas, which are used for FreeSurfer and SPM12, respectively. However, the proposed method showed good segmentation in the cerebellum and white matter in the medial part of the brain in comparison with the other methods. Thus, because the proposed method using different contrast images of MP2RAGE sequence showed the shortest processing time and similar segmentation ability as the other methods, it may be useful for both neuroimaging research and clinical diagnosis.
Pubmed
Web of science
Open Access
Yes
Create date
25/03/2019 18:42
Last modification date
20/08/2019 13:58
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