YONNET , Manuel

We present here a label-free development based on preexisting Quantitative Phase Imaging (QPI) that allows non-invasive live monitoring of both individual cells and cell populations. Growth, death, effect of toxic compounds are quantified under visible light with a standard inverted microscope. We show that considering the global biomass of a...

This interdisciplinary work focuses on the interest of a new proximal algorithm (ADRS) for supervised classification of live cell populations growing in a thermostated imaging station and acquired by a Quantitative Phase Imaging (QP I) camera. This type of camera produces interferograms that have to be processed in order to extract features...