Improved segmentation of deep brain grey matter structures using magnetization transfer (MT) parameter maps
Helms, Gunther LU
; Draganski, Bogdan
; Frackowiak, Richard
; Ashburner, John
and Weiskopf, Nikolaus
(2009)
In NeuroImage
47(1).
p.194-198
- Abstract
- Basal ganglia and brain stem nuclei are involved in the pathophysiology of various neurological and neuropsychiatric disorders. Currently available structural T1-weighted (T1w) magnetic resonance images do not provide sufficient contrast for reliable automated segmentation of various subcortical grey matter structures. We use a novel, semi-quantitative magnetization transfer (MT) imaging protocol that overcomes limitations in T1w images, which are mainly due to their sensitivity to the high iron content in subcortical grey
matter. We demonstrate improved automated segmentation of putamen, pallidum, pulvinar and substantia nigra using MT images. A comparison with segmentation of high-quality T1w images was performed in 49
... (More) - Basal ganglia and brain stem nuclei are involved in the pathophysiology of various neurological and neuropsychiatric disorders. Currently available structural T1-weighted (T1w) magnetic resonance images do not provide sufficient contrast for reliable automated segmentation of various subcortical grey matter structures. We use a novel, semi-quantitative magnetization transfer (MT) imaging protocol that overcomes limitations in T1w images, which are mainly due to their sensitivity to the high iron content in subcortical grey
matter. We demonstrate improved automated segmentation of putamen, pallidum, pulvinar and substantia nigra using MT images. A comparison with segmentation of high-quality T1w images was performed in 49
healthy subjects. Our results show that MT maps are highly suitable for automated segmentation, and so for multi-subject morphometric studies with a focus on subcortical structures. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/8773612
- author
- Helms, Gunther
LU
; Draganski, Bogdan
; Frackowiak, Richard
; Ashburner, John
and Weiskopf, Nikolaus
- organization
- publishing date
- 2009
- type
- Contribution to journal
- publication status
- published
- subject
- in
- NeuroImage
- volume
- 47
- issue
- 1
- pages
- 194 - 198
- publisher
- Elsevier
- external identifiers
-
- scopus:67349261098
- pmid:19344771
- ISSN
- 1095-9572
- DOI
- 10.1016/j.neuroimage.2009.03.053
- language
- English
- LU publication?
- yes
- additional info
- 1
- id
- 107f1f99-fb90-4674-a773-72b6d65050db (old id 8773612)
- alternative location
- http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2694257/
- date added to LUP
- 2016-04-01 12:30:35
- date last changed
- 2022-03-13 18:49:24
@article{107f1f99-fb90-4674-a773-72b6d65050db,
abstract = {{Basal ganglia and brain stem nuclei are involved in the pathophysiology of various neurological and neuropsychiatric disorders. Currently available structural T1-weighted (T1w) magnetic resonance images do not provide sufficient contrast for reliable automated segmentation of various subcortical grey matter structures. We use a novel, semi-quantitative magnetization transfer (MT) imaging protocol that overcomes limitations in T1w images, which are mainly due to their sensitivity to the high iron content in subcortical grey<br/><br>
matter. We demonstrate improved automated segmentation of putamen, pallidum, pulvinar and substantia nigra using MT images. A comparison with segmentation of high-quality T1w images was performed in 49<br/><br>
healthy subjects. Our results show that MT maps are highly suitable for automated segmentation, and so for multi-subject morphometric studies with a focus on subcortical structures.}},
author = {{Helms, Gunther and Draganski, Bogdan and Frackowiak, Richard and Ashburner, John and Weiskopf, Nikolaus}},
issn = {{1095-9572}},
language = {{eng}},
number = {{1}},
pages = {{194--198}},
publisher = {{Elsevier}},
series = {{NeuroImage}},
title = {{Improved segmentation of deep brain grey matter structures using magnetization transfer (MT) parameter maps}},
url = {{http://dx.doi.org/10.1016/j.neuroimage.2009.03.053}},
doi = {{10.1016/j.neuroimage.2009.03.053}},
volume = {{47}},
year = {{2009}},
}