Deep Learning Assisted Zonal Adaptive Aberration Correction

Frontiers in Physics

Jiazhu Zhu¹  Biwei Zhang¹  Ke Si³  Wei Gong³ 

[1] College of Optical Science and Engineering, Zhejiang University, Hangzhou, China;Department of Neurology of the Second Affiliated Hospital, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University School of Medicine, Hangzhou, China;NHC and CAMS Key Laboratory of Medical Neurobiology, MOE Frontier Science Center for Brain Research and Brain–Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou, China;

关键词: deep learning;    microscopy;    biomedical imaging;    aberration correction;    deep tissue focusing;   

DOI  :  10.3389/fphy.2020.621966

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown