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基于双折射超构光学的高分辨率超构立体显微镜

High resolution meta-stereomicroscope based on birefringent meta-optics

Liheng Yan, Haowen Liang, Emiliano R. Martins, Yikun Liu, Tao Li, Thomas F. Krauss, Juntao Li, Xue-Hua Wang

arXiv 2608.03300首次发表:更新:

AI 中文总结

本文提出一种基于双折射超构光学的全超构立体显微镜,通过消除视场不匹配问题实现高横向(435 nm)与深度(1026 nm)分辨率成像,可应用于生物医学与工业检测领域。

AI 中文摘要

同时实现高横向分辨率与高深度分辨率是立体显微镜领域长期追求的目标。尽管超构光学(meta-optics)已通过突破传统光学架构的物理限制革新了透镜设计,但现有超构透镜(metalens)辅助的立体显微镜仍存在超构光学组件与传统光学组件间的视场(FOV)不匹配问题,进而限制其成像性能。本文展示,通过全超构光学架构可从根本上消除该不匹配问题。该集成系统可灵活控制数值孔径与放大率,具备比超构透镜辅助立体显微镜更大的景深(DOF)与视场。实验中,我们研制出集成超构立体显微镜,其横向分辨率达435 nm,优于此前报道的立体显微镜性能。借助立体神经网络,该系统可直接重建高分辨率三维表面形貌,深度分辨率达1026 nm,证明其可同时实现高横向与深度分辨率成像。该集成架构可在透射与反射模式下运行,适用于生物医学成像与工业检测,凸显其在生物医学与工业场景实时观测中的广泛适用性。

英文摘要

Achieving both high lateral and high depth resolution is a longstanding goal in stereomicroscopy. Although meta-optics have revolutionized lens design by alleviating the physical constraints of conventional optical architectures, existing metalens-assisted stereomicroscopes still suffer from field of view (FOV) mismatch between meta-optical and conventional optical components in stereomicroscopes, thereby limiting their imaging performance. Here, we show that this mismatch can be fundamentally eliminated through a fully meta-optical architecture. The integrated system enables flexible control of numerical aperture and magnification with larger depth of field (DOF) and FOV than those of the metalens-assisted stereomicroscopes. Experimentally, we achieve an integrated meta-stereomicroscope with a lateral resolution of 435 nm, surpassing the performance of previously reported stereomicroscopes. Empowered by a stereo neural network, the system enables straightforward reconstruction of high-resolution three-dimensional surface morphology with a depth resolution of 1026 nm, demonstrating the capability to simultaneously achieve high lateral and depth resolution imaging. This integrated architecture operates in both transmission and reflection modes for biomedical imaging and industrial inspection, highlighting its broad applicability for real-time observation across biomedical and industrial scenarios.

Comments14 pages, 5 figures

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