Memory-less scattering imaging with ultrafast convolutional optical neural networks

The optical memory effect in complex scattering media including turbid tissue and speckle layers has been a critical foundation for macroscopic and microscopic imaging methods. However, image reconstruction from strong scattering media without the optical memory effect has not been achieved. Here, w...

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Bibliographic Details
Published in:Science advances 2024-06, Vol.10 (24), p.eadn2205
Main Authors: Zhang, Yuchao, Zhang, Qiming, Yu, Haoyi, Zhang, Yinan, Luan, Haitao, Gu, Min
Format: Article
Language:English
Subjects:
Applied Physics
Optics
Physical and Materials Sciences
SciAdv r-articles
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Summary:The optical memory effect in complex scattering media including turbid tissue and speckle layers has been a critical foundation for macroscopic and microscopic imaging methods. However, image reconstruction from strong scattering media without the optical memory effect has not been achieved. Here, we demonstrate image reconstruction through scattering layers where no optical memory effect exists, by developing a multistage convolutional optical neural network (ONN) integrated with multiple parallel kernels operating at the speed of light. Training this Fourier optics-based, parallel, one-step convolutional ONN with the strong scattering process for direct feature extraction, we achieve memory-less image reconstruction with a field of view enlarged by a factor up to 271. This device is dynamically reconfigurable for ultrafast multitask image reconstruction with a computational power of 1.57 peta-operations per second (POPS). Our achievement establishes an ultrafast and high energy-efficient optical machine learning platform for graphic processing.
ISSN:2375-2548
2375-2548
DOI:10.1126/sciadv.adn2205