Adaptive correction of depth-induced aberrations in multiphoton scanning microscopy using a deformable mirror

Area of Science:

• Microscopy and Imaging Science
• Optical Engineering
• Biomedical Optics

Background:

• Multiphoton microscopy enables deep tissue imaging but is limited by aberrations.
• Spherical aberration, particularly depth-induced, degrades image quality and resolution.
• Adaptive optics offer a potential solution for real-time aberration correction.

Purpose of the Study:

• To demonstrate adaptive aberration correction for depth-induced spherical aberration in multiphoton scanning microscopy.
• To utilize a micromachined deformable mirror controlled by a genetic learning algorithm for aberration correction.
• To enhance the axial scanning range and imaging depth of multiphoton microscopy.

Main Methods:

• Implemented a genetic learning algorithm for adaptive mirror control.
• Utilized two-photon fluorescence intensity as feedback for the algorithm.
• Employed a micromachined deformable mirror for aberration correction.
• Tested the system with a 40x/0.6 NA long working distance objective.

Main Results:

• Successfully corrected depth-induced spherical aberration.
• Achieved adaptive aberration correction using a genetic learning algorithm and fluorescence feedback.
• Significantly increased the axial scanning range from 150 mm to 600 mm.
• Demonstrated improved imaging performance at greater depths.

Conclusions:

• Adaptive aberration correction is effective for multiphoton microscopy.
• Genetic learning algorithms combined with deformable mirrors can enhance imaging depth.
• This technique offers a valuable tool for deep-tissue multiphoton imaging.