Learning flat optics for extended depth of field microscopy imaging
Abstract: Conventional microscopy systems have limited depth of field, which often necessitates depth scanning techniques hindered by light scattering. Various techniques have been developed to address this challenge, but they have limited extended depth of field (EDOF) capabilities. To overcome this challenge, this study proposes an end-to-end optimization framework for building a computational EDOF microscope that combines a 4f microscopy optical setup incorporating learned optics at the Fourier plane and a post-processing deblurring neural network. Utilizing the end-to-end differentiable model, we present a systematic design methodology for computational EDOF microscopy based on the specific visualization requirements of the sample under examination. In particular, we demonstrate that the metasurface optics provides key advantages for extreme EDOF imaging conditions, where the extended DOF range is well beyond what is demonstrated in state of the art, achieving superior EDOF performance.
- Location
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Deutsche Nationalbibliothek Frankfurt am Main
- Extent
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Online-Ressource
- Language
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Englisch
- Bibliographic citation
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Learning flat optics for extended depth of field microscopy imaging ; volume:12 ; number:18 ; year:2023 ; pages:3623-3632 ; extent:10
Nanophotonics ; 12, Heft 18 (2023), 3623-3632 (gesamt 10)
- Creator
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Atalay Appak, Ipek Anil
Sahin, Erdem
Guillemot, Christine
Caglayan, Humeyra
- DOI
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10.1515/nanoph-2023-0321
- URN
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urn:nbn:de:101:1-2023091114031466431009
- Rights
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Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
- Last update
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14.08.2025, 10:57 AM CEST
Data provider
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.
Associated
- Atalay Appak, Ipek Anil
- Sahin, Erdem
- Guillemot, Christine
- Caglayan, Humeyra
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