Large-FOV 3D localization microscopy by spatially variant point spread function generation
Accurate characterization of the microscopic point spread function (PSF) is crucial for achieving high-performance localization microscopy (LM). Traditionally, LM assumes a spatially-invariant PSF to simplify the modeling of the imaging system. However, for large fields of view (FOV) imaging, it becomes important to account for the spatially variant nature of the PSF. In this work, we propose an accurate and fast principal component analysis (PCA)-based field-dependent 3D PSF generator (PPG3D) and localizer for LM. Through simulations and experimental 3D single molecule localization microscopy (SMLM), we demonstrate the effectiveness of PPG3D, enabling super-resolution imaging of mitochondria and microtubules with high fidelity over a large FOV. A comparison of PPG3D with three other shift-invariant and shift-variant PSF generators for 3D LM reveals a three-fold improvement in accuracy and an operation speed approximately one hundred times faster. Given its user-friendliness and conciseness, we believe that PPG3D holds great potential for widespread application in SMLM and other imaging modalities.