Self-supervised deep learning for highly efficient spatial immunophenotypingResearch in context

Self-supervised deep learning for highly efficient spatial immunophenotypingResearch in context

Summary: Background: Efficient biomarker discovery and clinical translation depend on the fast and accurate analytical output from crucial technologies such as multiplex imaging. However, reliable cell classification often requires extensive annotations. Label-efficient strategies are urgently need...

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Bibliographic Details
Main Authors: Hanyun Zhang, Khalid AbdulJabbar, Tami Grunewald, Ayse U. Akarca, Yeman Hagos, Faranak Sobhani, Catherine S.Y. Lecat, Dominic Patel, Lydia Lee, Manuel Rodriguez-Justo, Kwee Yong, Jonathan A. Ledermann, John Le Quesne, E. Shelley Hwang, Teresa Marafioti, Yinyin Yuan
Format: Article
Language:English
Published: Elsevier 2023-09-01
Series:EBioMedicine
Subjects:
Deep learning
Self-supervised learning
Cell classification
Multiplex imaging
Multiplex immunohistochemistry
Imaging mass cytometry
Online Access:http://www.sciencedirect.com/science/article/pii/S2352396423003353

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http://www.sciencedirect.com/science/article/pii/S2352396423003353

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