Adaptive Optics Microscopy with Wavefront Sensing Based on Neighbor Correlation

Complex structures in living cells and tissues induce wavefront errors when light waves pass through them, and images observed with optical microscopes are undesirably blurred. This problem is especially serious for living plant cells because images are strikingly degraded even within a single cell. Adaptive optics (AO) is expected to be a solution to this problem by correcting such wavefront errors, thus enabling high-resolution imaging. In particular, scene-based AO involves wavefront sensing based on the image correlation between subapertures in a Shack-Hartmann wavefront sensor and thus does not require an intense point light source. However, the complex 3D structures of living cells often cause low correlation between subimages, leading to loss of accuracy in wavefront sensing. This paper proposes a novel method for scene-based sensing using only image correlations between adjacent subapertures. The method can minimize changes between subimages to be correlated and thus prevent inaccuracy in phase estimation. Using an artificial test target mimicking the optical properties of a layer of living plant cells, an imaging performance with a Strehl ratio of approximately 0.5 was confirmed. Upon observation of chloroplast autofluorescence inside living leaf cells of the moss Physcomitrium patens, recovered resolution images were successfully obtained even with complex biological structures. Under bright-field illumination, the proposed method outperformed the conventional method, demonstrating the future potential of this method for label- and damage-free AO microscopy. Several points for improvement in terms of the effect of AO correction are discussed.

Automated summary

This study proposes a novel scene-based wavefront sensing method that corrects wavefront errors caused by complex cell structures using only image correlations between subapertures. The imaging performance of the method was confirmed using an artificial test target and high-resolution images were successfully obtained even with complex biological structures. The results demonstrate the potential of this method for label- and damage-free adaptive optics microscopy.