Biomedical Engineering, University of Texas at Austin, Austin, TX, USA.
ISS, Inc., 1602 Newton Drive, Champaign, IL, 61822, USA.
Nanoscale. 2023 Jun 1;15(21):9449-9456. doi: 10.1039/d3nr00305a.
As a super-resolution imaging method, stimulated emission depletion (STED) microscopy has unraveled fine intracellular structures and provided insights into nanoscale organizations in cells. Although image resolution can be further enhanced by continuously increasing the STED-beam power, the resulting photodamage and phototoxicity are major issues for real-world applications of STED microscopy. Here we demonstrate that, with 50% less STED-beam power, the STED image resolution can be improved up to 1.45-fold using the separation of photons by a lifetime tuning (SPLIT) scheme combined with a deep learning-based phasor analysis algorithm termed (fluorescence lifetime imaging based on a generative adversarial network). This work offers a new approach for STED imaging in situations where only a limited photon budget is available.
作为一种超分辨率成像方法，受激发射耗尽（STED）显微镜已经揭示了精细的细胞内结构，并提供了对细胞中纳米尺度组织的深入了解。尽管可以通过不断增加 STED 光束功率来进一步提高图像分辨率，但由此产生的光损伤和光毒性是 STED 显微镜实际应用中的主要问题。在这里，我们证明，通过使用通过寿命调谐（SPLIT）方案分离光子，并结合基于深度学习的相量分析算法（基于生成对抗网络的荧光寿命成像），可以在 STED 光束功率降低 50%的情况下，将 STED 图像分辨率提高高达 1.45 倍。这项工作为仅可用有限光子预算的 STED 成像提供了一种新方法。
