Deep learning-enabled computational microscopy and diffractive imaging

Aydogan Ozcan

doi:10.1117/12.3008166

20 September 2023 Deep learning-enabled computational microscopy and diffractive imaging

Aydogan Ozcan

Proceedings Volume 12608, Biomedical Imaging and Sensing Conference; 126081N (2023) https://doi.org/10.1117/12.3008166
Event: Optics and Photonics International Congress, 2023, Yokohama, Japan

Abstract

In this talk, I will discuss diffractive optical networks designed by deep learning to all-optically implement various complex functions as the input light diffracts through spatially-engineered surfaces. These diffractive processors designed by deep learning have various applications, e.g., all-optical image analysis, feature detection, object classification, computational imaging and seeing through diffusers, also enabling task-specific camera designs and new optical components for spatial, spectral and temporal beam shaping and spatially-controlled wavelength division multiplexing. These deep learning-designed diffractive systems can broadly impact (1) all-optical statistical inference engines, (2) computational camera and microscope designs and (3) inverse design of optical systems that are task-specific. In this talk, I will give examples of each group, enabling transformative capabilities for various applications of interest, e.g., autonomous systems, defense/security, telecommunications as well as biomedical imaging and sensing.

Citation Download Citation

Aydogan Ozcan "Deep learning-enabled computational microscopy and diffractive imaging", Proc. SPIE 12608, Biomedical Imaging and Sensing Conference, 126081N (20 September 2023); https://doi.org/10.1117/12.3008166

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