Magnetic resonance angiography (MRA) is routinely employed in the diagnosis of cerebrovascular disease. Unruptured
aneurysms and arterial occlusions can be detected in examinations using MRA. This paper describes a computerized
detection method of arterial occlusion in MRA studies. Our database consists of 100 MRA studies, including 85 normal
cases and 15 abnormal cases with arterial occlusion. Detection of abnormality is based on comparison with a reference
(normal) MRA study with all the vessel known. Vessel regions in a 3D target MRA study is first segmented by using
thresholding and region growing techniques. Image registration is then performed so as to maximize the overlapping of
the vessel regions in the target image and the reference image. The segmented vessel regions are then classified into
eight arteries based on comparison of the target image and the reference image. Relative lengths of the eight arteries are
used as eight features in classifying the normal and arterial occlusion cases. Classifier based on the distance of a case
from the center of distribution of normal cases is employed for distinguishing between normal cases and abnormal cases.
The sensitivity and specificity for the detection of abnormal cases with arterial occlusion is 80.0% (12/15) and 95.3%
(81/85), respectively. The potential of our proposed method in detecting arterial occlusion is demonstrated.
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