基于单分子定位显微镜的大视场大景深超分辨成像技术研究

单分子定位显微镜作为超分辨显微成像技术的一种，具有极高的三维分辨率和出色的单分子定量化能力，在生命科学研究中助力了一系列新发现和新应用。与此同时，日益增长的观测和数据分析需求也给单分子定位显微镜提出了新的问题与挑战。针对目前该技术成像通量不足和像差导致的定位伪影等问题，本文从更准确的点扩散函数建模、移变定位算法的开发和大视场成像的硬件设计等角度出发开展了一系列研究工作，有效提升了单分子定位显微镜的景深、视野和成像质量。本文的主要研究内容如下：

考虑到单分子定位显微镜依赖于对点扩散函数的精准建模，本文构建了基于矢量衍射理论的强聚焦物镜成像模型，并充分考虑了相机传感器的像素积分效应。在此基础上开发出一套可在不同光学采样率和噪声水平下评估单分子定位精度的工具，对领域内常用的点扩散函数工程进行了系统详细地分析，并总结出与视场大小相关的最优像素采样率。针对应用点扩散函数工程时存在理论设计波前与实际波前不匹配的问题，本文进一步开发基于可变形镜的点扩散函数优化框架DMO PSF（Deformable mirror optimized PSF）。该框架利用实验校准的可变形镜促动器响应函数为基设计波前，通过推导理论定位精度关于响应函数的偏微分解析式，将点扩散函数的设计转换为一个最优化问题。DMO PSF可根据实验需求灵活调节景深，并且避免了器件投影误差。基于该方法得到的点扩散函数工程的定位精度显著提高，其中6 μm景深的DMO PSF可实现无需轴向扫描的全细胞核成像。

本文搭建了一套大视场单分子定位显微系统。在照明光路方面，通过多模光纤耦合多个激光器输出以提高激发功率，并利用振动电机实现均匀的大视场照明。成像光路使用可变形镜和大尺寸透镜，并结合大面阵相机实现全画幅成像。此外，为了描述视场中位置相关的像差，本文建立了移变点扩散函数的理论模型，并开发相应的基于极大似然估计的快速标定方法，成功表征了大视场系统的多种像差分布。由于传统的单分子定位算法是基于线性移不变的假设，在大视场系统中不再有效。本文进一步提出场相关深度学习定位算法FD-DeepLoc（Field-dependent deep learning localization），该算法引入坐标卷积策略以克服卷积神经网络对空间位置不敏感的局限性。通过损失函数与训练策略设计，结合分而治之的分析方法，FD-DeepLoc实现了在大视场移变系统上的精确单分子定位，其在测试数据上的定位表现是领域内最先进算法的两倍。

为了验证所开发技术的有效性和优越性，本文选择多个具有代表性的生物样品进行实验成像。例如，在大视场中观测多个细胞核孔并定量分析其精细的双层环状结构；将线粒体的高通量成像与下游图像分析相结合，根据形态、网络连通性等参数总结出三种不同类型的细胞；观测大范围神经突组织并解析轴突上的周期性膜骨架结构。其中单次实验的成像通量最高可达约180×180×5 μm³，相比传统方法提高了100倍。

综上所述，本文对大视场大景深单分子定位显微镜的关键技术开展了一系列研究，通过模型、算法和硬件的创新，成功突破当前超分辨成像技术的通量限制，实现了在以超高分辨率解析亚细胞器结构的同时还能观察到细胞种群间的微小差异，为生物医学研究提供了新视角和新工具。

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