On-the-fly estimation of a microscopy point spread function.

Area of Science:

• Optical microscopy
• Image processing
• Computational imaging

Background:

• Accurate point-spread function (PSF) estimation is crucial for deconvolution and calibration in optical microscopy.
• Spherical aberrations significantly impact image quality and require precise characterization.

Purpose of the Study:

• To develop and validate a novel method for estimating the spherically aberrated PSF directly from observed samples in 3D wide-field fluorescence microscopy.
• To demonstrate the method's effectiveness using simulations and experimental data.

Main Methods:

• The proposed approach estimates the PSF by expressing it as a linear combination of 4 basis functions.
• PSF estimation is achieved by minimizing a novel criterion derived from microscope noise statistics, directly from acquired images.
• The method was tested using simulations and experiments with quantum dots.

Main Results:

• The study successfully demonstrated an effective PSF approximation model for spherically aberrated microscopes.
• The developed estimation method accurately determined the PSF directly from sample images.
• Validation was performed using both simulated data and real experimental results.

Conclusions:

• The proposed method provides a robust way to estimate microscope PSFs, enhancing deconvolution and calibration.
• The approach is flexible and can be extended to handle non-spherical aberrations and other microscopy techniques.
• Direct PSF estimation from samples offers a practical solution for improving imaging performance in various microscopy modalities.