Human attention-inspired volume reconstruction method on serial section electron microscopy images

doi:10.1002/cyto.a.24332

	Human attention-inspired volume reconstruction method on serial section electron microscopy images
	Zhou, Fangxu1,2 ; Shen, Lijun1 ; Chen, Bohao1 ; Chen, Xi1 ; Hua, Han1,2,3
发表期刊	CYTOMETRY PART A
ISSN	1552-4922
	2021-03-18
页码	11
通讯作者	Chen, Xi(xi.chen@ia.ac.cn) ; Hua, Han(hua.han@ia.ac.cn)
摘要	The alignment of a 2D microscopic image stack to create a 3D image volume is an indispensable aspect of serial section electron microscopy (EM) technology, which could restore the original 3D integrity of biological tissues destroyed by chemical fixation and physical dissection. However, due to the similar texture intrasection and complex variations intersections of neural images, previous registration methods usually failed to yield reliable correspondences. And this also led to misalignment and impeded restoring the z-axis anatomical continuity of the neuron volume. In this article, inspired by human behaviors in finding correspondences, which use the topological relationship of image contents, we developed a spatial attention-based registration method for serial EM images to improve registration accuracy. Our approach combined the U-Net framework with spatial transformer networks (STN) to regress corresponding transformation maps in an unsupervised training fashion. The spatial attention (SA) module was incorporated into the U-Net architecture to increase the distinctiveness of image features by modeling its topological relationship. Experiments are conducted on both simulated and real data sets (MAS and RegCremi). Quantitative and qualitative comparisons demonstrate that our approach results in state of art accuracy (using the evaluation index of NCC, SSIM, Dice, Landmark error) and providing smooth and reliable transformation with less texture blur and unclear boundary than existing techniques. Our method is able to restore image stacks for visualization and quantitative analysis of EM image sequences.
关键词	3D volume reconstruction electron microscopy image image registration
DOI	10.1002/cyto.a.24332
收录类别	SCI
语种	英语
资助项目	Bureau of International Cooperation, Chinese Academy of Sciences[153D31KYSB20170059] ; National Natural Science Foundation of China[61673381] ; National Natural Science Foundation of China[61701497] ; Special Program of Beijing Municipal Science and Technology Commission[Z181100000118002] ; Strategic Priority Research Program of Chinese Academy of Science[XDB32030200]
项目资助者	Bureau of International Cooperation, Chinese Academy of Sciences ; National Natural Science Foundation of China ; Special Program of Beijing Municipal Science and Technology Commission ; Strategic Priority Research Program of Chinese Academy of Science
WOS研究方向	Biochemistry & Molecular Biology ; Cell Biology
WOS类目	Biochemical Research Methods ; Cell Biology
WOS记录号	WOS:000630082200001
出版者	WILEY
七大方向——子方向分类	脑网络分析
引用统计
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44077
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	Chen, Xi; Hua, Han
作者单位	1.Chinese Acad Sci, Natl Lab Pattern Recognit, Inst Automat, Beijing, Peoples R China 2.Univ Chinese Acad Sci, Sch Future Technol, Beijing, Peoples R China 3.CAS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai, Peoples R China
第一作者单位	模式识别国家重点实验室
通讯作者单位	模式识别国家重点实验室
推荐引用方式 GB/T 7714	Zhou, Fangxu,Shen, Lijun,Chen, Bohao,et al. Human attention-inspired volume reconstruction method on serial section electron microscopy images[J]. CYTOMETRY PART A,2021:11.
APA	Zhou, Fangxu,Shen, Lijun,Chen, Bohao,Chen, Xi,&Hua, Han.(2021).Human attention-inspired volume reconstruction method on serial section electron microscopy images.CYTOMETRY PART A,11.
MLA	Zhou, Fangxu,et al."Human attention-inspired volume reconstruction method on serial section electron microscopy images".CYTOMETRY PART A (2021):11.