ARMBIS: accurate and robust matching of brain image sequences from multiple modal imaging techniques | Zendy

Qi Shen | Zendy; Goayu Xiao | Zendy; Yingwei Zheng | Zendy; Jie Wang | Zendy; Yue Liu | Zendy; Xutao Zhu | Zendy; Fan Jia | Zendy; P. P. Su | Zendy; Binbin Nie | Zendy; Fuqiang Xu | Zendy; Bin Zhang | Zendy

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ARMBIS: accurate and robust matching of brain image sequences from multiple modal imaging techniques

Author(s) -

Qi Shen,

Goayu Xiao,

Yingwei Zheng,

Jie Wang,

Yue Liu,

Xutao Zhu,

Fan Jia,

P. P. Su,

Binbin Nie,

Fuqiang Xu,

Bin Zhang

Publication year - 2019

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btz404

Subject(s) - modal , computer science , matching (statistics) , artificial intelligence , pattern recognition (psychology) , image (mathematics) , neuroimaging , computer vision , mathematics , neuroscience , statistics , biology , chemistry , polymer chemistry

Study of brain images of rodent animals is the most straightforward way to understand brain functions and neural basis of physiological functions. An important step in brain image analysis is to precisely assign signal labels to specified brain regions through matching brain images to standardized brain reference atlases. However, no significant effort has been made to match different types of brain images to atlas images due to influence of artifact operation during slice preparation, relatively low resolution of images and large structural variations in individual brains.

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