# Differentiable model-based adaptive optics for two-photon microscopy

arXiv: https://arxiv.org/abs/2104.14308 · HTML: https://mlsanity.com/paper/2104.14308/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 9 of its 42 references that are in the map.
- First posted on arXiv 29 Apr 2021.

## Builds on (most cited first, 9 of 9)

- [Automatic differentiation in machine learning: a survey](https://mlsanity.com/paper/1502.05767/) (2015)
- [Deep Learning Techniques for Inverse Problems in Imaging](https://mlsanity.com/paper/2005.06001/) (2020)
- [SPNets: Differentiable Fluid Dynamics for Deep Neural Networks](https://mlsanity.com/paper/1806.06094/) (2018)
- [Deep Phase Decoder: Self-calibrating phase microscopy with an untrained deep neural network](https://mlsanity.com/paper/2001.09803/) (2020)
- [Data-Driven Design for Fourier Ptychographic Microscopy](https://mlsanity.com/paper/1904.04175/) (2019)
- [Diffraction tomography with a deep image prior](https://mlsanity.com/paper/1912.05330/) (2019)
- [Automatic Differentiation of Rigid Body Dynamics for Optimal Control and Estimation](https://mlsanity.com/paper/1709.03799/) (2017)
- [Differentiable model-based adaptive optics with transmitted and reflected light](https://mlsanity.com/paper/2007.13400/) (2020)
- [Adaptive optics with reflected light and deep neural networks](https://mlsanity.com/paper/2004.04603/) (2020)

## Built on by (most cited first, 2 of 2)

- [Estimation of Optical Aberrations in 3D Microscopic Bioimages](https://mlsanity.com/paper/2209.07911/) (2022)
- [Differentiable optimization of the Debye-Wolf integral for light shaping and adaptive optics in two-photon microscopy](https://mlsanity.com/paper/2211.16930/) (2022)

## Abstract (arXiv)

Aberrations limit scanning fluorescence microscopy when imaging in scattering materials such as biological tissue. Model-based approaches for adaptive optics take advantage of a computational model of the optical setup. Such models can be combined with the optimization techniques of machine learning frameworks to find aberration corrections, as was demonstrated for focusing a laser beam through aberrations onto a camera [arXiv:2007.13400]. Here, we extend this approach to two-photon scanning microscopy. The developed sensorless technique finds corrections for aberrations in scattering samples and will be useful for a range of imaging application, for example in brain tissue.