Computerized scheme for detection of arterial occlusion in brain MRA images

ABSTRACT 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. Detecti on 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 th e target image and the refere nce 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. Keywords: Computer-aided diagnosis, Magnetic resonance angiography, Arterial occlusion, Image registration