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Automated digital image quantification of histological staining for the analysis of the trilineage differentiation potential of mesenchymal stem cells.

Benjamin EggerschwilerDaisy D CanepaHans-Christoph PapeElisa A CasanovaPaolo Cinelli
Published in: Stem cell research & therapy (2019)
Our approach represents a novel method that simplifies the laboratory procedures not only for the quantification of histological dyes and the degree of differentiation of MSCs, but also due to its color independence, it can be easily adapted for the quantification of a wide range of staining procedures in histology. The method is easily applicable since it is based on open source software and standard light microscopy.
Keyphrases
  • mesenchymal stem cells
  • umbilical cord
  • deep learning
  • high throughput
  • high resolution
  • machine learning
  • bone marrow
  • optical coherence tomography
  • high speed
  • risk assessment
  • human health