Non-mechanical two-dimensional scanning biological microscope based on electrically tunable lenses for dynamic region of interest imaging

光学 材料科学 生物成像 显微镜 显微镜 光学显微镜 扫描电子显微镜 物理 荧光
作者
Yang Cheng,Mengyao Liu,Zhaohui Li,Jiale Wei,Qun Hao
出处
期刊:Optics Express [Optica Publishing Group]
卷期号:33 (16): 34984-34984
标识
DOI:10.1364/oe.563375
摘要

Two-dimensional scanning microscopy demonstrates unique advantages in biological cell observation owing to its ability to provide dynamic, region-specific imaging. However, existing mechanical and non-mechanical implementations face fundamental technical trade-offs between large-angle scanning, stable imaging performance, and low-cost integration, leading to persistent challenges in practical applications. This study presents a non-mechanical microscopy system based on fully integrated electrically tunable lenses (ETLs) that enables dynamic observation of biological specimens through coordinated two-dimensional scanning. The system uses a cage-structured optical configuration with four ETLs. Two ETLs provide directional beam steering through longitudinal shifts of 2.03 mm and lateral shifts of 1.99 mm, respectively, while the remaining two independently control beam divergence. This design provides a longitudinal scanning range of −125 µm to +165 µm and a lateral scanning range of −80 µm to +130 µm, allowing synchronized control of beam angle and divergence without mechanical movement. Theoretical analysis, optical simulations, and experimental verification demonstrate the system's adaptive focusing and region of interest (ROI) beam scanning capability. In experiments on herbaceous plant stems and Phyllostachys edulis bamboo stem cross-sections, the system localized target areas within 2 seconds by the field of view (FOV) deflection and reconstructed large-scale vascular bundle distributions and parenchyma cell networks using multi-FOV image stitching. This versatile and highly scalable system overcomes the limitations of conventional scanning, improves the efficiency of complex specimen analysis, and significantly expands biological microscopy applications by providing a novel method for multi-region specimen dynamic observation.
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