Generation of a probabilistic arterial cerebrovascular atlas derived from 700 time-of-flight MRA datasets.
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Generation of a probabilistic arterial cerebrovascular atlas derived from 700 time-of-flight MRA datasets. / Forkert, Nils; Suniaga, Santiago; Fiehler, Jens; Wersching, Heike; Knecht, Stefan; Kemmling, Andre.
In: Stud Health Technol Inform, Vol. 180, 2012, p. 148-152.Research output: SCORING: Contribution to journal › SCORING: Journal article › Research › peer-review
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TY - JOUR
T1 - Generation of a probabilistic arterial cerebrovascular atlas derived from 700 time-of-flight MRA datasets.
AU - Forkert, Nils
AU - Suniaga, Santiago
AU - Fiehler, Jens
AU - Wersching, Heike
AU - Knecht, Stefan
AU - Kemmling, Andre
PY - 2012
Y1 - 2012
N2 - The cerebral vasculature is a complex vessel network with high variations among human subjects. Although the coarse structure and spatial relationships of the main cerebrovascular branches are well known, not much knowledge about inter-individual vessel variability of humans at a finer level is available. The aim of this work is to present a probabilistic atlas of cerebral arterial vascular structures derived from 700 Time-of-Flight (TOF) magnetic resonance angiography (MRA) datasets of healthy subjects. Therefore, the cerebrovascular system was automatically segmented in each TOF datasets. In a following step, each TOF dataset and corresponding segmentation was registered to the MNI brain atlas. The registered datasets were then used for generation of a probabilistic cerebrovascular atlas. The generated atlas was evaluated with respect to three possible applications. The results suggest that the atlas is especially helpful to obtain knowledge about the cerebrovascular anatomy and its variations in terms of vessel occurrence probability. Furthermore, it appears useful for initialization of automatic cerebrovascular segmentation methods while an application for detection of vessel pathologies seems only feasible for large malformations.
AB - The cerebral vasculature is a complex vessel network with high variations among human subjects. Although the coarse structure and spatial relationships of the main cerebrovascular branches are well known, not much knowledge about inter-individual vessel variability of humans at a finer level is available. The aim of this work is to present a probabilistic atlas of cerebral arterial vascular structures derived from 700 Time-of-Flight (TOF) magnetic resonance angiography (MRA) datasets of healthy subjects. Therefore, the cerebrovascular system was automatically segmented in each TOF datasets. In a following step, each TOF dataset and corresponding segmentation was registered to the MNI brain atlas. The registered datasets were then used for generation of a probabilistic cerebrovascular atlas. The generated atlas was evaluated with respect to three possible applications. The results suggest that the atlas is especially helpful to obtain knowledge about the cerebrovascular anatomy and its variations in terms of vessel occurrence probability. Furthermore, it appears useful for initialization of automatic cerebrovascular segmentation methods while an application for detection of vessel pathologies seems only feasible for large malformations.
KW - Humans
KW - Models, Neurological
KW - Models, Statistical
KW - Imaging, Three-Dimensional/methods
KW - Models, Anatomic
KW - Magnetic Resonance Angiography/methods
KW - Image Interpretation, Computer-Assisted/methods
KW - Cerebral Arteries/anatomy & histology
KW - Cerebral Veins/anatomy & histology
KW - Models, Cardiovascular
KW - Subtraction Technique
KW - Humans
KW - Models, Neurological
KW - Models, Statistical
KW - Imaging, Three-Dimensional/methods
KW - Models, Anatomic
KW - Magnetic Resonance Angiography/methods
KW - Image Interpretation, Computer-Assisted/methods
KW - Cerebral Arteries/anatomy & histology
KW - Cerebral Veins/anatomy & histology
KW - Models, Cardiovascular
KW - Subtraction Technique
M3 - SCORING: Journal article
VL - 180
SP - 148
EP - 152
ER -
