Long-term, real-time and label-free live cell image processing and analysis based on a combined algorithm of CellPose and watershed segmentation.

ABSTRACT: Developing a rapid and quantitative method to accurately evaluate the physiological abilities of living cells is critical for tumor control. Many experiments have been conducted in the field of biology in an attempt to measure the proliferation and movement abilities of cells, but existing methods cannot provide real-time and objective data for label-free cells. The quantitative imaging technique, including an automatic segmentation algorithm for individual label-free cells, has been a breakthrough in this regard. In this study, we develop a combined automatic image processing algorithm of CellPose and watershed segmentation for the long-term and real-time imaging of label-free cells. This method shows strong reliability in cell identification regardless of cell densities, allowing us to o

SUBMITTER: Jiang J 

PROVIDER: S-EPMC10520323 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature