
High-power homogeneous illumination for super-resolution localization microscopy with large field-of-view
Author(s) -
Zeyu Zhao,
Bo Xin,
Luchang Li,
Zhen-Li Huang
Publication year - 2017
Publication title -
optics express
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.394
H-Index - 271
ISSN - 1094-4087
DOI - 10.1364/oe.25.013382
Subject(s) - optics , field of view , pixel , image resolution , physics , homogeneity (statistics) , computer science , machine learning
As a wide-field imaging technique, super-resolution localization microscopy (SRLM) is theoretically capable of increasing field-of-view (FOV) without sacrificing either imaging speed or spatial resolution. There are two key factors for realizing large FOV SRLM: one is high-power illumination over the whole FOV with sufficient illumination homogeneity and the other is large FOV signal detection by a camera that has large number of pixels and sufficient detection sensitivity. However nowadays, even though the state-of-art scientific complementary metal-oxide semiconductor (sCMOS) cameras provide single molecule fluorescence signal detection ability over an FOV of more than 200 μm × 200 μm, large FOV SRLM still has not been achieved due to the lack of high-power homogeneous illumination. In this paper, we report large FOV SRLM with a high-power homogeneous illumination system. We demonstrate experimentally that our illumination system, which is based on a newly designed multimode fiber combiner, is capable of providing sufficient illumination intensity (~4.7 kW/cm 2 @ 640 nm) and excellent illumination homogeneity. Compared with the reported approaches, our illumination system is advantageous in laser power scaling and square-shape illumination without beam clipping. As a result, our system makes full use of the sensor of a representative Hamamatsu Flash 4.0 V2 sCMOS camera (2048 × 2048 active pixels) and achieves a FOV as large as 221 μm × 221 μm with homogeneous spatial resolution. The flexible solution for realizing large FOV SRLM reported in this paper pushes a significant step toward the development of SRLM.