In Frontiers in immunology ; h5-index 100.0
The recent emergence of imaging mass cytometry technology has led to the generation of an increasing amount of high-dimensional data and, with it, the need for suitable performant bioinformatics tools dedicated to specific multiparametric studies. The first and most important step in treating the acquired images is the ability to perform highly efficient cell segmentation for subsequent analyses. In this context, we developed YOUPI (Your Powerful and Intelligent tool) software. It combines advanced segmentation techniques based on deep learning algorithms with a friendly graphical user interface for non-bioinformatics users. In this article, we present the segmentation algorithm developed for YOUPI. We have set a benchmark with mathematics-based segmentation approaches to estimate its robustness in segmenting different tissue biopsies.
Scuiller Yvonne, Hemon Patrice, Le Rochais Marion, Pers Jacques-Olivier, Jamin Christophe, Foulquier Nathan
2023
U-NET, cell segmentation, images, imaging mass cytometry, new algorithm
