Knowledge Commons of Institute of Automation,CAS
Robust Global Optimized Affine Registration Method for Microscopic Images of Biological Tissue | |
Lv YN(吕亚楠)1,3![]() ![]() ![]() ![]() | |
2020-05 | |
会议名称 | IEEE International Conference on Acoustics, Speech and Signal Processing |
会议日期 | 4-8 May 2020 |
会议地点 | Barcelona, Spain |
摘要 | Affine registration can fit the non-rigid deformation of slices effectively, and it is widely used in volume reconstruction of biological tissue. But most of the existing affine registration methods are registered in a given sequence, which results in the accumulation of errors. In this paper, a global optimized affine registration method is proposed, which can be used in volume reconstruction. To eliminate the cumulative error, the affine transformation of all images is estimated simultaneously based on an energy function. A constraint on affine transformation is added to restrict the shearing of images. Experiments show that our method provides a more reliable registration result compared with sequential affine registration. It can solve the problems caused by the accumulation of errors. The registration result fits the deformation of slices well and preserves the rigidity of images. |
关键词 | Volume reconstruction registration affine transformation |
学科门类 | 工学 |
DOI | 10.1109/ICASSP40776.2020.9054568 |
收录类别 | EI |
资助项目 | Strategic Priority Research Program of Chinese Academy of Science[XDB32030200] ; Special Program of Beijing Municipal Science & Technology Commission[Z181100000118002] ; National Science Foundation of China[61701497] ; National Science Foundation of China[61673381] ; National Science Foundation of China[61673381] ; National Science Foundation of China[61701497] ; Special Program of Beijing Municipal Science & Technology Commission[Z181100000118002] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32030200] |
语种 | 英语 |
七大方向——子方向分类 | 图像视频处理与分析 |
引用统计 | |
文献类型 | 会议论文 |
条目标识符 | http://ir.ia.ac.cn/handle/173211/44304 |
专题 | 脑图谱与类脑智能实验室_微观重建与智能分析 |
通讯作者 | Han H(韩华) |
作者单位 | 1.University of Chinese Academy of Sciences, Beijing 2.Institute of Automation, Chinese Academy of Sciences 3.The Center for Excellence in Brain Science and Intelligence Technology 4.National Laboratory of Pattern Recognition 5.School of Future Technology, University of Chinese Academy of Sciences |
通讯作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Lv YN,Chen X,Shu C,et al. Robust Global Optimized Affine Registration Method for Microscopic Images of Biological Tissue[C],2020. |
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文件名称/大小 | 文献类型 | 版本类型 | 开放类型 | 使用许可 | ||
final_lyn.pdf(579KB) | 会议论文 | 开放获取 | CC BY-NC-SA | 浏览 下载 |
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