13 March 2009 Computer-aided method for automated selection of optimal imaging plane for measurement of total cerebral blood flow by MRI
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Abstract
A computer-aided method for finding an optimal imaging plane for simultaneous measurement of the arterial blood inflow through the 4 vessels leading blood to the brain by phase contrast magnetic resonance imaging is presented. The method performance is compared with manual selection by two observers. The skeletons of the 4 vessels for which centerlines are generated are first extracted. Then, a global direction of the relatively less curved internal carotid arteries is calculated to determine the main flow direction. This is then used as a reference direction to identify segments of the vertebral arteries that strongly deviates from the main flow direction. These segments are then used to identify anatomical landmarks for improved consistency of the imaging plane selection. An optimal imaging plane is then identified by finding a plane with the smallest error value, which is defined as the sum of the angles between the plane's normal and the vessel centerline's direction at the location of the intersections. Error values obtained using the automated and the manual methods were then compared using 9 magnetic resonance angiography (MRA) data sets. The automated method considerably outperformed the manual selection. The mean error value with the automated method was significantly lower than the manual method, 0.09±0.07 vs. 0.53±0.45, respectively (p<.0001, Student's t-test). Reproducibility of repeated measurements was analyzed using Bland and Altman's test, the mean 95% limits of agreements for the automated and manual method were 0.01~0.02 and 0.43~0.55 respectively.
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Pang-yu Teng, Ahmet Murat Bagci, Noam Alperin, "Computer-aided method for automated selection of optimal imaging plane for measurement of total cerebral blood flow by MRI", Proc. SPIE 7261, Medical Imaging 2009: Visualization, Image-Guided Procedures, and Modeling, 72613C (13 March 2009); doi: 10.1117/12.813819; https://doi.org/10.1117/12.813819
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