Versatile adaptive optics microscopy through embedded neural network control

Martin J. Booth; Qi Hu; Biwei Zhang; Yuyao Xiao

doi:10.1117/12.3003870

13 March 2024 Versatile adaptive optics microscopy through embedded neural network control

Martin J. Booth, Qi Hu, Biwei Zhang, Yuyao Xiao

Proceedings Volume PC12851, Adaptive Optics and Wavefront Control for Biological Systems X; PC128510A (2024) https://doi.org/10.1117/12.3003870
Event: SPIE BiOS, 2024, San Francisco, California, United States

Abstract

Wavefront-sensorless adaptive optics (AO) is commonly used to enable aberration estimation and correction using the information in images. We have introduced a machine learning (ML) approach that embeds physical understanding of the imaging process into a sensorless AO method. This enabled correction of aberrations with as few as two sample exposures across different microscope modalities. We extend the capabilities of such systems to more challenging imaging applications, including larger and more complex aberrations, lower signal levels, and specimen variations. We present a concept that permits estimation of multiple aberrations modes from a single image.

Conference Presentation

Citation Download Citation

Martin J. Booth, Qi Hu, Biwei Zhang, and Yuyao Xiao "Versatile adaptive optics microscopy through embedded neural network control", Proc. SPIE PC12851, Adaptive Optics and Wavefront Control for Biological Systems X, PC128510A (13 March 2024); https://doi.org/10.1117/12.3003870

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