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2021, Volume 22, Issue 10

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Frontiers of Information Technology & Electronic Engineering >> 2021, Volume 22, Issue 10 doi: 10.1631/FITEE.2000422

Deep learning based wavefront sensor for complex wavefront detection in adaptive optical microscopes

Affiliation(s): Department of Neurology of the First Affiliated Hospital, State Key Laboratory of Modern Optical Instrumentation, Zhejiang University School of Medicine, Hangzhou 310009, China; College of Optical Science and Engineering, Zhejiang University, Hangzhou 310027, China; Research Units for Emotion and Emotion Disorders, Chinese Academy of Medical Sciences, MOE Frontier Science Center for Brain Research and Brain-Machine Integration, School of Brain Science and Brain Medicine, Zhejiang University, Hangzhou 310058, China; less

Received: 2020-08-21 Accepted: 2021-10-08 Available online: 2021-10-08
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Abstract

The Shack-Hartmann wavefront sensor (SHWS) is an essential tool for wavefront sensing in adaptive optical microscopes. However, the distorted spots induced by the complex wavefront challenge its detection performance. Here, we propose a based method which combines point spread function image based Zernike coefficient estimation and wavefront stitching. Rather than using the centroid displacements of each micro-lens, this method first estimates the of local wavefront distribution over each micro-lens and then stitches the local wavefronts for reconstruction. The proposed method can offer low root mean square wavefront errors and high accuracy for complex , and has potential to be applied in adaptive optical microscopes.

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