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Using DeepContact with Amira graphical user interface.
Liu, Liqing; Wu, Hongjun; Yang, Shuxin; Yi, Ke; Hu, Junjie; Xiao, Li; Xu, Tao.
Afiliação
  • Liu L; Center for Biological Imaging, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China. Electronic address: liuliqing@ibp.ac.cn.
  • Wu H; School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.
  • Yang S; Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China; School of Computer and Control Engineering, University of Chinese Academy of Sciences, Beijing, China.
  • Yi K; School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China.
  • Hu J; National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China. Electronic address: huj@ibp.ac.cn.
  • Xiao L; Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China; School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China; School of Computer and Control Engineering, University of Chine
  • Xu T; National Laboratory of Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences, Beijing, China; College of Life Science, University of Chinese Academy of Sciences, Beijing, China; School of Biomedical Engineering, Guangzhou Medical University, Guangzhou, Guangdong, China. Electronic
STAR Protoc ; 4(4): 102558, 2023 Dec 15.
Article em En | MEDLINE | ID: mdl-37717213
ABSTRACT
DeepContact is a deep learning software for high-throughput quantification of membrane contact site (MCS) in 2D electron microscopy images. This protocol will guide users through incorporating available DeepContact models in Amira's artificial intelligence module, thereby allowing invoking of DeepContact functions in organelle segmentation and quantifying of MCS with a user-friendly graphical user interface of Amira software. For complete details on the use and execution of this protocol, please refer to Liu et al. (2022).1.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Inteligência Artificial Idioma: En Revista: STAR Protoc Ano de publicação: 2023 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Algoritmos / Inteligência Artificial Idioma: En Revista: STAR Protoc Ano de publicação: 2023 Tipo de documento: Article