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An automated pipeline for mitochondrial segmentation on ATUM-SEM stacks
Li, Weifu1,2; Deng, Hao2,3; Rao, Qiang2; Xie, Qiwei2; Chen, Xi2; Han, Hua2,4,5
AbstractIt is possible now to look more closely into mitochondrial physical structures due to the rapid development of electron microscope (EM). Mitochondrial physical structures play important roles in both cellular physiology and neuronal functions. Unfortunately, the segmentation of mitochondria from EM images has proven to be a difficult and challenging task, due to the presence of various subcellular structures, as well as image distortions in the sophisticated background. Although the current state-of-the-art algorithms have achieved some promising results, they have demonstrated poor performances on these mitochondria which are in close proximity to vesicles or various membranes. In order to overcome these limitations, this study proposes explicitly modelling the mitochondrial double membrane structures, and acquiring the image edges by way of ridge detection rather than by image gradient. In addition, this study also utilizes group-similarity in context to further optimize the local misleading segmentation. Then, the experimental results determined from the images acquired by automated tape-collecting ultramicrotome scanning electron microscopy (ATUM-SEM) demonstrate the effectiveness of this study's proposed algorithm.
KeywordAtum-sem Membrane Enhancement Mitochondria Group-similarity
WOS HeadingsScience & Technology ; Life Sciences & Biomedicine ; Technology
Indexed BySCI
Funding OrganizationSpecial Program of Beijing Municipal Science & Technology Commission(Z161100000216146) ; Strategic Priority Research Program of the CAS(XDB02060001) ; National Science Foundation of China(61673381 ; Institute of Automation, CAS(Y3J2031DZ1) ; 61201050 ; 61306070)
WOS Research AreaBiochemistry & Molecular Biology ; Computer Science ; Mathematical & Computational Biology
WOS SubjectBiochemical Research Methods ; Computer Science, Interdisciplinary Applications ; Mathematical & Computational Biology
WOS IDWOS:000404061500009
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Cited Times:7[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Affiliation1.Hubei Univ, Fac Math & Stat, Wuhan 430062, Peoples R China
2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Macau Univ Sci & Technol, Fac Informat Technol, Hefei 999078, Macau, Peoples R China
4.Univ Chinese Acad Sci, Future Technol Coll, Beijing 100190, Peoples R China
5.CBS Ctr Excellence Brain Sci & Intelligence Techn, Shanghai 200031, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Li, Weifu,Deng, Hao,Rao, Qiang,et al. An automated pipeline for mitochondrial segmentation on ATUM-SEM stacks[J]. JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY,2017,15(3):1750015.
APA Li, Weifu,Deng, Hao,Rao, Qiang,Xie, Qiwei,Chen, Xi,&Han, Hua.(2017).An automated pipeline for mitochondrial segmentation on ATUM-SEM stacks.JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY,15(3),1750015.
MLA Li, Weifu,et al."An automated pipeline for mitochondrial segmentation on ATUM-SEM stacks".JOURNAL OF BIOINFORMATICS AND COMPUTATIONAL BIOLOGY 15.3(2017):1750015.
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