Department of Biomedical Engineering, Swansea University, Swansea, UK.
Cell Rep Methods. 2021 Oct 25;1(6):100103. doi: 10.1016/j.crmeth.2021.100103.
Deep learning neural networks are a powerful tool in the analytical toolbox of modern microscopy, but they come with an exacting requirement for accurately annotated, ground truth cell images. Otesteanu et al. (2021) elegantly streamline this process, implementing network training by using patient-level rather than cell-level disease classification.
深度学习神经网络是现代显微镜分析工具包中的强大工具，但它们需要准确标注的、真实的细胞图像作为基础。Otesteanu 等人（2021）巧妙地简化了这个过程，通过使用患者级而不是细胞级的疾病分类来实现网络训练。
