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Conference Paper/Proceeding/Abstract 404 views

Finding Complete 3D Vertex Correspondence for Statistical Shape Modeling / Robert Palmer; Gary Tam; Xianghua Xie

IEEE Engineering in Medicine and Biology Society

Swansea University Author: Xianghua, Xie

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 e...

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Published in: IEEE Engineering in Medicine and Biology Society
Published: IEEE 2015
URI: https://cronfa.swan.ac.uk/Record/cronfa22236
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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.
Keywords: Statistical shape model, shape analysis, registration, mesh processing
College: College of Science