Practical sensorless aberration estimation for 3D microscopy with deep learning
Debayan Saha,
Uwe Schmidt,
Qinrong Zhang
et al.
Abstract:Estimation of optical aberrations from volumetric intensity images is a key step in sensorless adaptive optics for 3D microscopy. Recent approaches based on deep learning promise accurate results at fast processing speeds. However, collecting ground truth microscopy data for training the network is typically very difficult or even impossible thereby limiting this approach in practice. Here, we demonstrate that neural networks trained only on simulated data yield accurate predictions for real experimental image… Show more
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