Deep Learning Assisted Zonal Adaptive Aberration Correction
Deep learning (DL) has been recently applied to adaptive optics (AO) to correct optical aberrations rapidly in biomedical imaging. Here we propose a DL assisted zonal adaptive correction method to perform corrections of high degrees of freedom while maintaining the fast speed. With a trained DL neur...
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Veröffentlicht in: | Frontiers in physics 2021-01, Vol.8 |
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Hauptverfasser: | , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | Deep learning (DL) has been recently applied to adaptive optics (AO) to correct optical aberrations rapidly in biomedical imaging. Here we propose a DL assisted zonal adaptive correction method to perform corrections of high degrees of freedom while maintaining the fast speed. With a trained DL neural network, the pattern on the correction device which is divided into multiple zone phase elements can be directly inferred from the aberration distorted point-spread function image in this method. The inference can be completed in 12.6 ms with the average mean square error 0.88 when 224 zones are used. The results show a good performance on aberrations of different complexities. Since no extra device is required, this method has potentials in deep tissue imaging and large volume imaging. |
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ISSN: | 2296-424X 2296-424X |
DOI: | 10.3389/fphy.2020.621966 |