模糊及强噪声条件下中心线的提取

提出一种“重心预取多尺度求精”的中心线提取算法，即利用重心估算大致的中心线，并在线上的关键点附近，特别是分叉处进行多尺度求精，从三维图象中提取树状分支物体的中心线，该算法综合了重心法估算的简单性和尺度空间分析法的准确性等特点，特别适合在边界模糊、强噪声条件下的应用。该算法已成功地应用在医学ＣＴ心脏三维图象的可视化中，文中同时说明了如何从中心线生成曲截面展开图，首次实现了分支血管的曲截面显示。

Medial Axis Extraction from Blurred and Noisy Images

In order to extract medial axes of tree like objects from three dimensional images. A medial axis extraction algorithm is presented, it estimates coarse medial axis using centroids and applies multi scale refinement to its main points, especially at bifurcations. The algorithm has both simplicity (as of centroid algorithms) and accuracy (as of scale space analysis methods) properties, and is suited in blurred and noisy conditions. The algorithm is successfully applied to the visualization of three dimensional images of human heart that are acquired from medical CT. The method of generating curved section from medial axis and spreading it to screen is also given. Curved sectional display of branched vessels is firstly realized.