中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Robust Global Optimized Affine Registration Method for Microscopic Images of Biological Tissue

文献类型:会议论文

作者Lv YN(吕亚楠)2,4; Chen X(陈曦)2; Shu C(舒畅)2,4; Han H(韩华)1,2,3,5
出版日期2020-05
会议日期4-8 May 2020
会议地点Barcelona, Spain
关键词Volume reconstruction registration affine transformation
DOI10.1109/ICASSP40776.2020.9054568
英文摘要

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.

语种英语
资助项目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]
源URL[http://ir.ia.ac.cn/handle/173211/44304]  
专题类脑智能研究中心_微观重建与智能分析
通讯作者Han H(韩华)
作者单位1.Institute of Automation, Chinese Academy of Sciences
2.The Center for Excellence in Brain Science and Intelligence Technology
3.National Laboratory of Pattern Recognition
4.University of Chinese Academy of Sciences, Beijing
5.School of Future Technology, University of Chinese Academy of Sciences
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]. 见:. Barcelona, Spain. 4-8 May 2020.

入库方式: OAI收割

来源:自动化研究所

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