The purpose of the study was to demonstrate the accuracy and clinical utility of an automated method of image analysis of 4D (3D + time) magnetic resonance (MR) imaging of the human aorta. Serial MR images of the entire thoracic aorta were acquired on 32 healthy individuals. Graph theory based segmentation was applied to the images and cross sectional area (CSA) was determined for the entire length of thoracic aorta. Mean CSA was compared between the 3 years. CSA values at the level of sinuses of Valsalva and sino-tubular junction were used to calculate average diameters for comparison to Roman-Devereux norms. A robust automated segmentation method was developed that accurately reproduced CSA measurements for the entire length of thoracic aorta in serially acquired scans with a 1% error compared to expert tracing. Calculated aortic root diameters based on CSA correlated with Roman-Devereux norms. Mean CSA for the aortic root agreed well with previously published manually derived values. Automated analysis of 4D MR images of the thoracic aorta provides accurate and reproducible results for CSA in healthy human subjects. The ability to simultaneously analyze the entire length of thoracic aorta throughout the cardiac cycle opens the door to the calculation of novel indices of aortic biophysical properties. These novel indices may lead to earlier detection of patients at risk for adverse events.