Reconstructing Surfaces from CT Cross-Sections Based on Shape Feature Point Matching
基于形状特征点匹配的CT断层图象表面重建

How to fast and accurately reconstruct complex surfaces of organs has become increasingly important while the interslice distance is much larger than the interpixel distance. First, this paper presents a shape-keeping and adaptive feature points sampling algorithm, which can reduce storage and computational requirments in the post-processing procedure. Second, an algorithm for reconstructing surfaces from CT cross-sections based on shape feature point matching is presented, which takes into account four properties of tomographic images, i. e. intensity,gradient magnitude, gradient direction, and position disparity of the feature points to improve the accduracy of the reconstructed surface. The experimental results show the effectiveness of the above algorithms.