连续组织切片图像的配准

Registration of serial tissue section images

目的 解决生物组织连续切片计算机三维重建中的图像配准问题。方法 采用自动图像配准的分割－计数法，通过 对图像做简单的阈值分割，将优化的准则函数定义为图像的联合直方图特定区域上的计数值，通过优化搜索，得到配准 参数。结果 将该方法用于小鼠胚胎的连续切片图像配准，大大加快了配准速度。结论 使用自动图像配准分割－计数法 能够实现连续组织切片图像的准确配准，并且具有计算简单，速度快的优点。

Objective This study aims to tackle the problem of image registration during computer-assisted three-dimensional (3D) reconstruction of serial tissue sections. Methods We proposed segmentation-counting algorithm for computerized image registration on the basis of joint histogram. This approach utilizes thresholding of the 2 images to be registered, and the criterion function is defined as the counting in a specific region of the joint histogram. The registration parameters can be obtained by optimizing the criterion function. Results In the trial application of this approach in image registration for the serial tissue sections of mouse embryos, a more efficient result was achieved. Conclusion The method can rapidly accomplish the image registration task for serial tissue sections with simpler calculation processes.