Your browser doesn't support javascript.
loading
Fast fit-free analysis of fluorescence lifetime imaging via deep learning.
Smith, Jason T; Yao, Ruoyang; Sinsuebphon, Nattawut; Rudkouskaya, Alena; Un, Nathan; Mazurkiewicz, Joseph; Barroso, Margarida; Yan, Pingkun; Intes, Xavier.
Afiliação
  • Smith JT; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180; smithj28@rpi.edu intesx@rpi.edu.
  • Yao R; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180.
  • Sinsuebphon N; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180.
  • Rudkouskaya A; Department of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208.
  • Un N; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180.
  • Mazurkiewicz J; Department of Neuroscience and Experimental Therapeutics, Albany Medical College, Albany, NY 12208.
  • Barroso M; Department of Molecular and Cellular Physiology, Albany Medical College, Albany, NY 12208.
  • Yan P; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180.
  • Intes X; Department of Biomedical Engineering, Rensselaer Polytechnic Institute, Troy, NY 12180; smithj28@rpi.edu intesx@rpi.edu.
Proc Natl Acad Sci U S A ; 116(48): 24019-24030, 2019 11 26.
Article em En | MEDLINE | ID: mdl-31719196
Assuntos
Palavras-chave
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Imagem Óptica / Aprendizado Profundo Limite: Animals / Female / Humans Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2019 Tipo de documento: Article
Texto completo
Imprimir
XML
PubMed Links
Buscar no Google

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Processamento de Imagem Assistida por Computador / Imagem Óptica / Aprendizado Profundo Limite: Animals / Female / Humans Idioma: En Revista: Proc Natl Acad Sci U S A Ano de publicação: 2019 Tipo de documento: Article