A METHOD OF 3D OBJECT RECONSTRUCTION FROM A SERIES OF CROSS-SECTIONAL IMAGES

Abstract

This paper addresses a method for constructing surface representation of 3D structures from a sequence of cross-sectional images. Firstly, we propose cell-boundary representation, which is a generalization of PVP method proposed by Yun and Park [18], and develop an efficient surface construction algorithm from a cell-boundary. Cell-boundary consists of a set of boundary cells with their 1-voxel configurations, and can compactly describe binary volumetric data. Secondly, to produce external surface from the cell-boundary representation, we define 19 modeling primitives (MP) including volumetric, planar and linear groups. Surface polygons are created from those modeling primitives using a simple table look-up operation. Since a cell-boundary can be obtained using only topological information of neighboring voxels, there is no ambiguity in determining modeling primitives which may arise in PVP method. Since our algorithm has data locality and is very simple to implement, it is very appropriate for parallel processing.