Automatic segmentation method which divides a cerebral artery tree in time-of-flight MR-angiography into artery segments

Akihiro Takemura; Masayuki Suzuki; Hajime Harauchi; Yusuke Okumura; Tokuo Umeda

doi:10.1117/12.647100

15 March 2006 Automatic segmentation method which divides a cerebral artery tree in time-of-flight MR-angiography into artery segments

Akihiro Takemura, Masayuki Suzuki, Hajime Harauchi, Yusuke Okumura, Tokuo Umeda

Author Affiliations +

Proceedings Volume 6144, Medical Imaging 2006: Image Processing; 61443G (2006) https://doi.org/10.1117/12.647100
Event: Medical Imaging, 2006, San Diego, California, United States

Abstract

To achieve sufficient accuracy and robustness, 2D/3D registration methods between DSA and MRA of the cerebral artery require an automatic extraction method that can isolate wanted segments from the cerebral artery tree. Here, we described an automatic segmentation method that divides the cerebral artery tree in time-of-flight magnetic resonance angiography (TOF-MRA) into each artery. This method requires a 3D dataset of the cerebral artery tree obtained by TOF-MRA. The processes of this method are: 1) every branch in the cerebral artery tree is labeled with a unique index number, 2) the 3D center of the Circle of Willis is determined using 2D and 3D templates, and 3) the labeled branches are classified with reference to the 3D territory map of cerebral arteries centered on the Circle of Willis. This method classifies all branches into internal carotid arteries (ICA), basilar artery (BA), middle cerebral artery (MCA), a1 segment of anterior cerebral artery (ACA(A1)), other segments of the anterior cerebral artery (ACA), posterior communication artery (PcomA), and posterior cerebral artery (PCA). In the eleven cases examined, the numbers of correctly segmented pixels in each branch were counted and the percentages based on the total number of pixels of the artery were calculated. Manually classified arteries of each case were used as references. Mean percentages were: ACA, 87.6%; R-ACA(A1), 44.9%; L-ACA(A1), 30.4%; R-MC, 82.4%; L-MC, 79.0%; R-PcomA, 0.5%; L-PcomA, 0.0%; R-PCA, 77.2%; L-PCA, 80.0%; R-ICA, 78.6%; L-ICA, 93.05; BA, 77.1%; and total arteries, 78.9%.

Citation Download Citation

Akihiro Takemura, Masayuki Suzuki, Hajime Harauchi, Yusuke Okumura, and Tokuo Umeda "Automatic segmentation method which divides a cerebral artery tree in time-of-flight MR-angiography into artery segments", Proc. SPIE 6144, Medical Imaging 2006: Image Processing, 61443G (15 March 2006); https://doi.org/10.1117/12.647100

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