Automated 4D Segmentation of Aortic Magnetic Resonance Images

Automated and accurate segmentation of the aorta in 4D (3D+time) cardiovascular magnetic resonance (MR) image data is important for early detection of congenital aortic disease leading to aortic aneurysms and dissections. An automated 4D segmentation method is reported in this study. Our automated segmentation method combines level-set and optimal surface segmentation algorithms so that the final aortic surfaces in n cardiac phases are determined in a single optimization process. 4D MR image data sets acquired from 21 normal and connective tissue disorder subjects were used to evaluate the performance of our method. The automated 4D segmentation results produced accurate aortic surfaces in 16 cardiac phases, covering the aorta from the left-ventricular outflow tract to the diaphragm, yielding subvoxel accuracy with signed surface positioning errors of -0.07±1.16 voxel (-0.10±2.05 mm).