title: Finding complete 3D vertex correspondence for statistical shape modeling.
abstract: A statistical shape model that accurately generalizes a family of 3D shapes requires establishing correspondences across the set of shapes. However in 3D anatomical meshes, finding a sufficient number of landmarks to accurately describe the shape can be a challenge, and often only a few points are easily identifiable due to the smooth nature of the object surface. Using a sparse set of landmarks, this paper finds a dense set of vertex correspondences across a set of 3D aortic root meshes. This is achieved by non-rigidly transforming a source mesh to a target mesh. Then, for every vertex on the target, a corresponding vertex on the deformed source is found, resulting in complete correspondence. A more accurate transformation results in better correspondence establishment, and our mesh registration experiments show an average Hausdorff distance of 3.65mm, and an average point-to-mesh distance of 0.41mm, i. e. within one voxel.
authors.forename: Robert Ieuan
authors.initials: RI
authors.lastname: Palmer
authors.lastname: Xianghua Xie
authors.forename: Gary
authors.initials: G
authors.lastname: Tam
mesh_terms: D000465:Algorithms; D006257:Head; D021621:Imaging, Three-Dimensional; D015233:Models, Statistical