在图像预处理基础上，考虑到生物体在序列切片图像上的重心位置具有连续性的事实，提出3种新的逐步求精的自动配准方法。该方法首先采用力矩主轴法对两幅图像进行粗略配准，然后对已有的配准结果作微小干扰，当图像互信息最大时获得最终精确配准结果。针对生物组织连续切片数量巨大的特点，构建有序体数据结构，在此基础上采用Shear Warp算法重建生物体内部结构。改进后的算法能够提高对体数据的遍历效率，减少对无效数据的访问，加速绘制过程。实验结果表明，新算法效果良好，便捷快速，值得推广应用于生物组织连续切片的科学计算可视化。

A novel method is proposed for two step slices registration and fast Shear Warp reconstruction of serial tissue section images. After image pre processing, an automatic stepwise accuracy method was used for slices registration. Based on the elementary result of the principal axes transformation method, the final optimal result was achieved when maximized the mutual information reflected the matching suitability at a given position. Considering the large amount of serial tissue section images, an improved Shear Warp algorithm based on sorted volumetric data structure was applied to reduce the access time of non contribution data cells and consequently speed up the reconstruction process. Experimental results demonstrate that the method is effective and efficient, which is suitable for visualization of serial tissue section images.