The NanoZoomer artificial intelligence connectomics pipeline for tracer injection studies of the marmoset brain

Alexander Woodward, Rui Gong, Hiroshi Abe, Ken Nakae, Junichi Hata, Henrik Skibbe, Yoko Yamaguchi, Shin Ishii, Hideyuki Okano, Tetsuo Yamamori, Noritaka Ichinohe

研究成果: Article査読

2 被引用数 (Scopus)

抄録

We describe our connectomics pipeline for processing anterograde tracer injection data for the brain of the common marmoset (Callithrix jacchus). Brain sections were imaged using a batch slide scanner (NanoZoomer 2.0-HT) and we used artificial intelligence to precisely segment the tracer signal from the background in the fluorescence images. The shape of each brain was reconstructed by reference to a block-face and all data were mapped into a common 3D brain space with atlas and 2D cortical flat map. To overcome the effect of using a single template atlas to specify cortical boundaries, brains were cyto- and myelo-architectonically annotated to create individual 3D atlases. Registration between the individual and common brain cortical boundaries in the flat map space was done to absorb the variation of each brain and precisely map all tracer injection data into one cortical brain space. We describe the methodology of our pipeline and analyze the accuracy of our tracer segmentation and brain registration approaches. Results show our pipeline can successfully process and normalize tracer injection experiments into a common space, making it suitable for large-scale connectomics studies with a focus on the cerebral cortex.

本文言語English
ページ(範囲)1225-1243
ページ数19
ジャーナルBrain Structure and Function
225
4
DOI
出版ステータスPublished - 2020 5月 1
外部発表はい

ASJC Scopus subject areas

  • 解剖学
  • 神経科学(全般)
  • 組織学

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