Segmentation of aortic flow in real time magnetic resonance images

Real-time spiral phase contrast magnetic resonance imaging (MRI) is capable of non-invasively measuring the stroke volume associated with each individual heartbeat. The quality of these measurements depends on how good the segmentation of the interface between aortic wall and lumen is. Such process is hampered by the low-resolution and low-contrast nature of real-time images. Image segmentation using traditional techniques has proven not robust. This paper presents a novel model-based approach, which is capable of very accurately segmenting aortic flow. Instead of attempting to achieve a millimetrically-accurate segmentation of the wall-lumen interface, the proposed algorithm focuses on separating the aortic flow from neighboring flows. This provides robustness, even when this interface is not visually distinguishable. The proposed segmentation takes real-time MRI one step further towards becoming the non-invasive gold standard for assessment of stroke volume variability.