Differentiable model-based adaptive optics for microscopy

Abstract

We demonstrate the usefulness of differentiable optimization approaches, as implemented in machine learning frameworks, for adaptive optics in microscopy. We show that aberrations can be corrected in an epidetection configuration only using reflected light. The method is also extended to two-photon scanning fluorescence microscopy.