Aortic Vessel Tree Segmentation for Cardiovascular Diseases Treatment: Status Quo

Abstract

The aortic vessel tree, composed of the aorta and its branches, is crucial for blood supply to the body. Aortic diseases, such as aneurysms and dissections, can lead to life-threatening ruptures, often requiring open surgery. Therefore, patients commonly undergo treatment under constant monitoring, which requires regular inspections of the vessels through medical imaging techniques. Overlapping and comparing aortic vessel tree geometries from consecutive images allows for tracking changes in both the aorta and its branches. Manual reconstruction of the vessel tree is time-consuming and impractical in clinical settings. In contrast, automatic or semi-automatic segmentation algorithms can perform this task much faster, making them suitable for routine clinical use. This paper systematically reviews methods for the automatic and semi-automatic segmentation of the aortic vessel tree, concluding with a discussion on their clinical applicability, the current research landscape, and ongoing challenges.