LBAI, UMR 1227, Univ Brest, Inserm, Brest, France.
CHU de Brest, Brest, France.
Front Immunol. 2023 Mar 2;14:1072118. doi: 10.3389/fimmu.2023.1072118. eCollection 2023.
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.
近年来,成像质谱细胞术技术的出现导致了越来越多的高维数据的产生,因此需要专门针对特定多参数研究的高性能生物信息学工具。处理获得的图像的第一步也是最重要的一步是能够对后续分析进行高效的细胞分割。在这种情况下,我们开发了 YOUPI(强大而智能的工具)软件。它将基于深度学习算法的高级分割技术与面向非生物信息学用户的友好图形用户界面相结合。在本文中,我们介绍了为 YOUPI 开发的分割算法。我们使用基于数学的分割方法设置了一个基准,以估计其在分割不同组织活检中的稳健性。