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A three-sided pyramid prism is used as a wavefront sensor in non-modulating mode with an artificial neural network (NN) as a control unit in an adaptive optical setup. The NN is composed of a convolution network for feature extraction from the pyramid signal and a three-layer feed-forward back-propagation net. The network is trained with over 15,000 examples of signal–wavefront pairs. Presenting wavefronts of 6 mm pupil diameter and a RMS error of under 200 nm to the adaptive optical system with the trained network, it can correct the aberrations within three loops to a wavefront with

A compact adaptive optics system was developed and integrated into the system for multiphoton laser scanning ophthalmoscopy. Defocus, astigmatism, trefoil, and coma are compensated via a combination of telescope and rotating pairs of phase plates. The spherical aberration as well as all dynamic aberrations are corrected by an active micro-electromechanical (MEMS) mirror. Wavefront measurement is conducted by fast SHS and pyramid sensor devices. The MEMS-mirror based adaptive optics system was validated in a study on 60 eyes of 30 subjects.The adaptive-optical multiphoton ophthalmoscope is aimed at detecting the early onset of retinal diseases such as e.g. age-related macula degeneration.

We present a method of using pairs of rotating Zernike phase plates as a precompensation unit to correct the higher-order aberrations (typically coma and trefoil) in the human eye. The rotational properties of the Zernike polynomials allow compensation of variable higher-order aberrations of the human eye with a small number of specially designed Zernike phase plates.