English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT

Released

Journal Article

Differentiable model-based adaptive optics with transmitted and reflected light

MPS-Authors
/persons/resource/persons250112

Vishniakou,  Ivan
Max Planck Research Group Neural Circuits, Center of Advanced European Studies and Research (caesar), Max Planck Society;

/persons/resource/persons188171

Seelig,  Johannes Dominik
Max Planck Research Group Neural Circuits, Center of Advanced European Studies and Research (caesar), Max Planck Society;

Fulltext (public)

oe-28-18-26436.pdf
(Publisher version), 7MB

Supplementary Material (public)
There is no public supplementary material available
Citation

Vishniakou, I., & Seelig, J. D. (2020). Differentiable model-based adaptive optics with transmitted and reflected light. Optics Express, 28(18), 26436-26446. doi:10.1364/OE.403487.


Cite as: http://hdl.handle.net/21.11116/0000-0006-EBE8-C
Abstract
Aberrations limit optical systems in many situations, for example when imaging in biological tissue. Machine learning offers novel ways to improve imaging under such conditions by learning inverse models of aberrations. Learning requires datasets that cover a wide range of possible aberrations, which however becomes limiting for more strongly scattering samples, and does not take advantage of prior information about the imaging process. Here, we show that combining model-based adaptive optics with the optimization techniques of machine learning frameworks can find aberration corrections with a small number of measurements. Corrections are determined in a transmission configuration through a single aberrating layer and in a reflection configuration through two different layers at the same time. Additionally, corrections are not limited by a predetermined model of aberrations (such as combinations of Zernike modes). Focusing in transmission can be achieved based only on reflected light, compatible with an epidetection imaging configuration.