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  Differentiable Model-based Adaptive Optics for Microscopy

Vishniakou, I., & Seelig, J. D. (2021). Differentiable Model-based Adaptive Optics for Microscopy. In OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), OSA Technical Digest. Optica Publishing Group. doi:10.1364/COSI.2021.CM1A.3.

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Genre: Conference Paper

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 Creators:
Vishniakou, Ivan1, Author           
Seelig, Johannes D.1, Author                 
Affiliations:
1Max Planck Research Group Neural Circuits, Center of Advanced European Studies and Research (caesar), Max Planck Society, ou_2237639              

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 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.

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Language(s): eng - English
 Dates: 2021
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: No review
 Identifiers: DOI: 10.1364/COSI.2021.CM1A.3
 Degree: -

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Title: Computational Optical Sensing and Imaging 2021 / OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP)
Place of Event: Washington, DC, United States
Start-/End Date: 2021-07-19 - 2021-07-23

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Title: OSA Imaging and Applied Optics Congress 2021 (3D, COSI, DH, ISA, pcAOP), OSA Technical Digest
Source Genre: Proceedings
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Publ. Info: Optica Publishing Group
Pages: - Volume / Issue: - Sequence Number: CM1A.3 Start / End Page: - Identifier: ISBN: 978-1-943580-89-7