Japanese Journal of Medical Physics (Igakubutsuri)
Online ISSN : 2186-9634
Print ISSN : 1345-5354
ISSN-L : 1345-5354
Automatic Anatomical Labeling Method of Cerebral Arteries in MR-Angiography Data Set
Akihiro TakemuraMasayuki SuzukiHajime HarauchiYusuke Okumura
Author information
JOURNAL FREE ACCESS

2006 Volume 26 Issue 4 Pages 187-198

Details
Abstract
To improve the accuracy and robustness of 2D/3D registration of digital subtraction angiography images and magnetic resonance angiography (MRA) data, we have developed an automatic method for anatomical labeling of the cerebral arteries in MRA data. The anatomical labeling method is a location-based method which segments an artery tree to branches and classifies the branches into labeled segments, i. e., internal carotid arteries (ICA), basilar artery (BA), middle cerebral arteries (MCA), Al segments of the anterior cerebral artery (ACA(A1)), other segments of the anterior cerebral artery (ACA), posterior communication arteries (PcomA) and posterior cerebral arteries (PCA), according to their location. Arteries were extracted from MRA data for this labeling method by the region-growing technique. Fifteen cases were examined to evaluate the method accuracy. The number of correctly segmented voxels in each artery segment was determined, and the correct labeling percentage was calculated based on the total number of voxels of the artery. Mean percentages were as follows: ACA,82.7%; Right (R-) ACA(A1),47.1%; Left (L-) ACA(A1),46.1%; R-MCA,80.4%; L-MCA,74.1%; R-PcomA,0.0%; L-PcomA,3.3%; R-PCA,60.3%; LPCA,66.9%; R-ICA,90.7%; L-ICA,90.7%; BA,89.9%; and total arteries,84.1%. The ACA, MCA, ICA and BA were consistently identified correctly.
Content from these authors
© The Japan Society of Medical Physics
Previous article Next article
feedback
Top