A deep learning pipeline to automate high-resolution arterial segmentation with or without intravenous contrast - Chandrashekar, A; Handa, A; Shivakumar, N; Lapolla, P; Uberoi, R; Grau, V; Lee, R (Lippincott, Williams and Wilkins, 2020)
Background: Existing methods to reconstruct vascular structures from a computerized tomography (CT) angiogram rely on contrast injection to enhance the radio-density within the vessel lumen. However, pathological changes in the vasculature may be present that prevent accurate reconstruction. In aortic aneurysmal disease, a thrombus adherent to the aortic wall within the expanding aneurysmal sac is present in > 90% of cases. These deformations prevent the automatic extraction of vital clinical information by existing image reconstruction methods.