Parametric mapping of cellular morphology in plant tissue sections by gray level granulometry.

David LeglandFabienne GuillonMarie-Françoise Devaux

Published in: Plant methods (2020)

We propose a methodology for the quantification of cellular morphology and of its variations within images of tissue sections. The results should help understanding how the cellular morphology is related to genotypic and / or environmental variations, and clarify the relationships between cellular morphology and chemical composition of cell walls.

Keyphrases

deep learning
stem cells
machine learning
optical coherence tomography
convolutional neural network
mesenchymal stem cells
cell wall