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Automated Cell Lineage Reconstruction using Label-Free 4D Microscopy.
Waliman, Matthew; Johnson, Ryan L; Natesan, Gunalan; Tan, Shiqin; Santella, Anthony; Hong, Ray L; Shah, Pavak K.
Afiliação
  • Waliman M; Department of Electrical and Computer Engineering, University of California, Los Angeles, California, United States of America.
  • Johnson RL; Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United State of America.
  • Natesan G; Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United State of America.
  • Tan S; Department of Computational and Systems Biology, University of California, Los Angeles, California, United States of America.
  • Santella A; Molecular Cytology Core, Memorial Sloan Kettering Cancer Center, New York, New York, United States of America.
  • Hong RL; Department of Biology, California State University, Northridge, California, United States of America.
  • Shah PK; Department of Molecular, Cell and Developmental Biology, University of California, Los Angeles, California, United State of America.
bioRxiv ; 2024 Jan 22.
Article em En | MEDLINE | ID: mdl-38328064
ABSTRACT
Here we describe embGAN, a deep learning pipeline that addresses the challenge of automated cell detection and tracking in label-free 3D time lapse imaging. embGAN requires no manual data annotation for training, learns robust detections that exhibits a high degree of scale invariance and generalizes well to images acquired in multiple labs on multiple instruments.

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2024 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Idioma: En Revista: BioRxiv Ano de publicação: 2024 Tipo de documento: Article