CA2 area detection from hippocampal microscope images using deep learning

Shohei Morinaga, Tomoe Ishikawa, Masato Yasui, Mototsugu Hamada, Tadahiro Kuroda

研究成果: Conference contribution

抄録

In this study, we created a semantic segmentation model to recognize the Cornu Ammonis 2 (CA2) area inside the horizontal hippocampal slice section in a microscopic transparent-light image, which was only recognizable by biomarkers such as immunohistochemistry. The U-Net was modified so that we could incorporate the way how experts recognized the CA2 area. We achieved 100% accuracy and 84% precision. We built a system on an edge computing device and provided a practical microscope solution to assist neuroscientists.

本文言語English
ホスト出版物のタイトル2021 IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2021 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ページ603-606
ページ数4
ISBN(電子版)9781665424615
DOI
出版ステータスPublished - 2021 8月 9
イベント2021 IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2021 - Virtual, East Lansing, United States
継続期間: 2021 8月 92021 8月 11

出版物シリーズ

名前Midwest Symposium on Circuits and Systems
2021-August
ISSN(印刷版)1548-3746

Conference

Conference2021 IEEE International Midwest Symposium on Circuits and Systems, MWSCAS 2021
国/地域United States
CityVirtual, East Lansing
Period21/8/921/8/11

ASJC Scopus subject areas

  • 電子材料、光学材料、および磁性材料
  • 電子工学および電気工学

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