Adaptive aberration correction for specimen induced spherical aberration

TLDR: A genetic learning algorithm is applied in conjunction with third harmonic generation to determine the appropriate shape of the deformable mirror to correct for aberrations in longitudinal depth scanning in a confocal microscope.

Abstract: Summary form only given. In normal operation with a dry or oil immersion microscope objective there is an index mismatch with a water-based biological sample. This index mismatch causes a depth dependant spherical aberration that severely limits the range that a sample can be imaged along the optical axis. We have previously demonstrated the use of a membrane deformable mirror to correct for off-axis aberrations in a confocal microscopy system. In this study we apply a genetic learning algorithm in conjunction with third harmonic generation to determine the appropriate shape of the deformable mirror to correct for aberrations in longitudinal depth scanning in a confocal microscope.