Simultaneous particle tracking, phase retrieval and point spread function reconstruction.

Area of Science:

• Biophysics
• Optical Microscopy
• Computational Biology

Background:

• 3D tracking of fluorescent biomolecules monitors cellular processes.
• Sample-induced wavefront distortions cause point spread function (PSF) aberrations, leading to significant localization errors in 3D particle tracking.
• Current aberration correction methods, like adaptive optics, require hardware adjustments.

Purpose of the Study:

• To develop a framework for simultaneous particle tracking, pupil function learning, and PSF reconstruction directly from imaging data.
• To overcome limitations of pre-calibrated PSFs and hardware-dependent aberration correction.

Main Methods:

• A Bayesian framework is employed with continuous 2D priors on pupil phase and amplitude.
• The method reconstructs the pupil phase and PSF directly from acquired 3D imaging data.
• Framework validated using synthetic and experimental data, including static and diffusing particles, and multiple particles with overlapping PSFs.

Main Results:

• Achieved simultaneous particle tracking, phase retrieval, and PSF reconstruction.
• Retrieved pupil phase with less than 10% error in realistic scenarios.
• Restored sub-diffraction limited localization precisions of 10-25 nm (lateral) and 20-50 nm (axial).

Conclusions:

• The proposed framework effectively corrects sample-induced aberrations without hardware adjustments.
• Enables accurate 3D particle tracking and localization, crucial for understanding cellular dynamics.
• Offers a robust and data-driven approach for improving super-resolution microscopy.