Automatic cutting plane identification for computer-aided analysis of intracranial aneurysms

Clinical studies have established the importance of morphologic measurements of intracranial aneurysm size, neck width, aspect ratio and other shape indices for the assessment of the risk of rupture and selection of the best treatment option. Obtaining these morphologic measurements requires segmentation of vascular structures in an angiographic image, reconstruction of a 3D vascular surface mesh, and isolation of the aneurysm surface mesh from parent vessels. High variability of aneurysm shapes appearing at various anatomical locations renders isolation of the aneurysm a critical step, which, if performed poorly, may adversely impact the morphologic measurements and possibly corrupt important information used for clinical assessment of the aneurysm. Previous quantitative validation of isolation methods showed that manual cutting plane based isolation is more accurate than isolation by state-of-the-art automatic methods. In this paper, we propose and quantitatively validate a novel method for automated cutting plane identification and aneurysm isolation based solely on analysis of the vascular surface mesh.