Department of Physics, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea.
KAIST Institute for Health Science and Technology, KAIST, Daejeon, Republic of Korea.
Nat Methods. 2023 Nov;20(11):1645-1660. doi: 10.1038/s41592-023-02041-4. Epub 2023 Oct 23.
Quantitative phase imaging, integrated with artificial intelligence, allows for the rapid and label-free investigation of the physiology and pathology of biological systems. This review presents the principles of various two-dimensional and three-dimensional label-free phase imaging techniques that exploit refractive index as an intrinsic optical imaging contrast. In particular, we discuss artificial intelligence-based analysis methodologies for biomedical studies including image enhancement, segmentation of cellular or subcellular structures, classification of types of biological samples and image translation to furnish subcellular and histochemical information from label-free phase images. We also discuss the advantages and challenges of artificial intelligence-enabled quantitative phase imaging analyses, summarize recent notable applications in the life sciences, and cover the potential of this field for basic and industrial research in the life sciences.
定量相位成像与人工智能相结合,可以快速、无标记地研究生物系统的生理学和病理学。本文综述了利用折射率作为固有光学成像对比度的各种二维和三维无标记相位成像技术的原理。特别是,我们讨论了基于人工智能的生物医学研究分析方法,包括图像增强、细胞或亚细胞结构的分割、生物样本类型的分类以及图像转换,以提供无标记相位图像的亚细胞和组织化学信息。我们还讨论了人工智能赋能的定量相位成像分析的优点和挑战,总结了生命科学中最近的显著应用,并介绍了该领域在生命科学基础和工业研究中的潜力。