MRC-Laboratory for Molecular Cell Biology, University College London, London, U.K.
Department of Cell and Developmental Biology, University College London, London, U.K.
Biochem Soc Trans. 2019 Aug 30;47(4):1029-1040. doi: 10.1042/BST20180391. Epub 2019 Jul 31.
Artificial Intelligence based on Deep Learning (DL) is opening new horizons in biomedical research and promises to revolutionize the microscopy field. It is now transitioning from the hands of experts in computer sciences to biomedical researchers. Here, we introduce recent developments in DL applied to microscopy, in a manner accessible to non-experts. We give an overview of its concepts, capabilities and limitations, presenting applications in image segmentation, classification and restoration. We discuss how DL shows an outstanding potential to push the limits of microscopy, enhancing resolution, signal and information content in acquired data. Its pitfalls are discussed, along with the future directions expected in this field.
基于深度学习（DL）的人工智能正在为生物医学研究开辟新的视野，并有望彻底改变显微镜领域。它现在正在从计算机科学专家手中转移到生物医学研究人员手中。在这里，我们以非专业人士易于理解的方式介绍了应用于显微镜的 DL 的最新发展。我们概述了它的概念、功能和局限性，并介绍了在图像分割、分类和恢复中的应用。我们讨论了 DL 如何显示出极大的潜力来推动显微镜的极限，提高获取数据的分辨率、信号和信息量。还讨论了它的缺陷，以及该领域未来的预期方向。
