Segmentation, or the outlining of objects within images, is a critical step
in the measurement and analysis of cells within microscopy images. While
improvements continue to be made in tools that rely on classical methods for
segmentation, deep learning-based tools increasingly dominate advances in the
technology. Specialist models such as Cellpose continue to improve in accuracy
and user-friendliness, and segmentation challenges such as the Multi-Modality
Cell Segmentation Challenge continue to push innovation in accuracy across
widely-varying test data as well as efficiency and usability. Increased
attention on documentation, sharing, and evaluation standards are leading to
increased user-friendliness and acceleration towards the goal of a truly
universal method.

细分、测量和分析细胞图像的关键步骤在于对象分割。深度学习基于的工具在该领域中逐渐取得了主导地位，以 Cellpose 为代表的专业模型在准确性和用户友好性方面不断提升，多模态细胞分割挑战推动了准确性、效率和可用性方面的创新。文档、共享和评估标准的日益重视加快了朝着真正通用方法的目标迈进。