Point-cloud method for image-based biomechanical stress analysis

Abstract

This paper introduces a point-cloud method for the stress analysis in biological systems. The method takes a point-cloud as the geometric input. Each point represents a small material volume that is assumed to undergo a uniform deformation during motion. The strain at each point is computed from the relative displacements of a set of neighboring points. Delaunay tessellation is utilized to provide the neighboring relation and the point volume. An efficient method is developed to extract point-cloud model from medical images. An aorta inflation problem and a skull impact problem are presented to demonstrate the utility of the method. © 2011 John Wiley & Sons, Ltd.