Towards automatization of organoid analysis: A deep learning approach to localize and quantify organoid images

The interest in the use of organoids in the biomedical field has increased exponentially in the past years. Organoids, or three-dimensional “mini-organs”, have the ability to proliferate and self-organize in-vitro, while displaying varying morphologies. When in culture, these structures can overlap with each other making the quantification and morphological characterization a challenging task. Quick and reliable analysis of organoid images could help in precisely modeling disease phenotypes as well as provide information on organ development. Therefore, automatization of the quantification and measurements is an important step towards an easier, faster, and less biased workflow.