Leibniz Institute of Photonic Technology, Albert-Einstein-Straße 9, Jena, Germany.
Institute of Physical Chemistry and Abbe Center of Photonics, Friedrich-Schiller-University, Jena, Germany.
PLoS One. 2019 Jan 9;14(1):e0209827. doi: 10.1371/journal.pone.0209827. eCollection 2019.
High optical resolution in microscopy usually goes along with costly hardware components, such as lenses, mechanical setups and cameras. Several studies proved that Single Molecular Localization Microscopy can be made affordable, relying on off-the-shelf optical components and industry grade CMOS cameras. Recent technological advantages have yielded consumer-grade camera devices with surprisingly good performance. The camera sensors of smartphones have benefited of this development. Combined with computing power smartphones provide a fantastic opportunity for "imaging on a budget". Here we show that a consumer cellphone is capable of optical super-resolution imaging by (direct) Stochastic Optical Reconstruction Microscopy (dSTORM), achieving optical resolution better than 80 nm. In addition to the use of standard reconstruction algorithms, we used a trained image-to-image generative adversarial network (GAN) to reconstruct video sequences under conditions where traditional algorithms provide sub-optimal localization performance directly on the smartphone. We believe that "cellSTORM" paves the way to make super-resolution microscopy not only affordable but available due to the ubiquity of cellphone cameras.
在显微镜中，高光学分辨率通常需要昂贵的硬件组件，例如透镜、机械装置和相机。有几项研究证明，依赖于现成的光学组件和工业级 CMOS 相机，可以使单分子定位显微镜变得经济实惠。最近的技术优势使得消费者级别的相机设备具有惊人的良好性能。智能手机的相机传感器从中受益。结合智能手机提供的计算能力，为“预算内成像”提供了绝佳机会。在这里，我们展示了一部消费级手机通过（直接）随机光学重建显微镜（dSTORM）实现光学超分辨率成像的能力，其实现的光学分辨率优于 80nm。除了使用标准的重建算法之外，我们还使用了经过训练的图像到图像生成对抗网络（GAN），在传统算法提供次优定位性能的情况下，直接在智能手机上重建视频序列。我们相信，“cellSTORM”为实现超分辨率显微镜铺平了道路，不仅使显微镜变得负担得起，而且由于手机摄像头无处不在，使得显微镜变得更加普及。
