Research on Stitching and Alignment of Mouse Carcass EM Images

图像拼接 图像配准 计算机视觉 人工智能 计算机科学 图像融合 匹配(统计) 图像(数学) 特征检测(计算机视觉) 特征(语言学) 分割 图像分割 模式识别(心理学) 图像处理 数学 统计 哲学 语言学
作者
Jing Zhu,Hongyu Ge,Ao Cheng,Ruobing Zhang,Lirong Wang
标识
DOI:10.1109/trustcom50675.2020.00198
摘要

Many researches have been carried out to explore the ultrastructure of organisms at home and abroad, and different algorithms have been used to reconstruct the images of different samples at the nanoscale. Image “matching” and “fusion” are two significant research fields that directly affect the performance of image Mosaic. As image stitching the first and the last step, if there is no correct image matching and fusion algorithm, it is almost impossible to successful image stitching. Image registration is to map one image to another by looking for a space transformation for two images in a set of image data, so that the points corresponding to the same position in the space in the two images correspond one to one, so as to achieve the purpose of information fusion. In this paper, the feature-based image stitching algorithm was used to transform the analysis of the whole image into the analysis of some features of the image, which greatly reduced the calculation amount. Meanwhile, the feature points were further optimized and selected to reduce the mismatching rate, and the electron microscope images of autistic mice were mosaically splicing. In the registration part, this paper adopts the elastic registration method and makes fine adjustments on this basis to obtain more accurate registration results, which will be helpful for the subsequent segmentation of each organizational structure.

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