Ma Bin, Lin Zhuang, Winkelbach Simon, Lindenmaier Werner, Dittmar Kurt E J
Gene Regulation and Differentiation, Helmholtz Centre for Infection Research, Braunschweig, Inhoffenstrasse 7, D-38124 Braunschweig, Germany.
Micron. 2008 Jun;39(4):387-96. doi: 10.1016/j.micron.2007.03.005. Epub 2007 Mar 19.
The first step towards the three-dimensional (3D) reconstruction of histological structures from serial sectioned tissue blocks is the proper alignment of microscope image sequences. We have accomplished an automatic rigid registration program, named Image-Reg, to align serial sections from mouse lymph node and Peyer's patch. Our approach is based on the calculation of the pixel-correlation of objects in adjacent images. The registration process is mainly divided into two steps. Once the foreground images have been segmented from the original images, the first step (primary alignment) is performed on the binary images of segmented objects; this process includes rotation by using the moments and translation through the X, Y axes by using the centroid. In the second step, the matching error of two binary images is calculated and the registration results are refined through multi-scale iterations. In order to test the registration performance, Image-Reg has been applied to an image and its transformed (rotated) version and subsequently to an image sequence of three serial sections of mouse lymph node. In addition, to compare our algorithm with other registration methods, three other approaches, viz. manual registration with Reconstruct, semi-automatic landmark registration with Image-Pro Plus and the automatic phase-correlation method with Image-Pro Plus, have also been applied to these three sections. The performance of our program has been also tested on other two-image data sets. These include: (a) two light microscopic images acquired by the automatic microscope (stitched with other software); (b) two images fluorescent images acquired by confocal microscopy (tiled with other software). Our proposed approach provides a fast and accurate linear alignment of serial image sequences for the 3D reconstruction of tissues and organs.
从连续切片组织块进行组织结构三维（3D）重建的第一步是显微镜图像序列的正确对齐。我们已经完成了一个名为Image-Reg的自动刚性配准程序，用于对齐来自小鼠淋巴结和派尔集合淋巴结的连续切片。我们的方法基于相邻图像中对象的像素相关性计算。配准过程主要分为两步。一旦从原始图像中分割出前景图像，第一步（初步对齐）就在分割对象的二值图像上进行；这个过程包括使用矩进行旋转以及使用质心在X、Y轴上进行平移。在第二步中，计算两个二值图像的匹配误差，并通过多尺度迭代对配准结果进行优化。为了测试配准性能，Image-Reg已应用于一幅图像及其变换（旋转）版本，随后应用于小鼠淋巴结三个连续切片的图像序列。此外，为了将我们的算法与其他配准方法进行比较，还将其他三种方法，即使用Reconstruct进行手动配准、使用Image-Pro Plus进行半自动地标配准以及使用Image-Pro Plus进行自动相位相关方法，应用于这三个切片。我们程序的性能也在其他两组图像数据集上进行了测试。这些包括：（a）由自动显微镜获取的两幅光学显微镜图像（用其他软件拼接）；（b）由共聚焦显微镜获取的两幅荧光图像（用其他软件平铺）。我们提出的方法为组织和器官的3D重建提供了快速准确的连续图像序列线性对齐。
