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Optical errors, including spherical aberrations, hinder high-resolution imaging of biological samples due to biochemical components and physical properties. We developed the Deep-C microscope system to achieve aberration-free images, employing a motorized correction collar and contrast-based calculations. However, current contrast-maximization techniques, such as the Brenner gradient method, inadequately assess specific frequency bands. The Peak-C method addresses this issue, but its arbitrary neighbor selection and susceptibility to the noise limit its effectiveness. In this paper, we emphasize the importance of a broad spatial frequency range for accurate spherical aberration correction and propose Peak-F. This spatial frequency-based system utilizes a fast Fourier transform as a bandpass filter. This approach overcomes Peak-C's limitations and comprehensively covers the low-frequency domain of image spatial frequencies., (© The Author(s) 2023. Published by Oxford University Press on behalf of The Japanese Society of Microscopy.)

The high-resolution in vivo imaging of mouse brain for quantitative analysis of fine structures, such as dendritic spines, requires objectives with high numerical apertures (NAs) and long working distances (WDs). However, this imaging approach is often hampered by spherical aberration (SA) that results from the mismatch of refractive indices in the optical path and becomes more severe with increasing depth of target from the brain surface. Whereas a revolving objective correction collar has been designed to compensate SA, its adjustment requires manual operation and is inevitably accompanied by considerable focal shift, making it difficult to acquire the best image of a given fluorescent object. To solve the problems, we have created an objective-attached device and formulated a fast iterative algorithm for the realization of an automatic SA compensation system. The device coordinates the collar rotation and the Z-position of an objective, enabling correction collar adjustment while stably focusing on a target. The algorithm provides the best adjustment on the basis of the calculated contrast of acquired images. Together, they enable the system to compensate SA at a given depth. As proof of concept, we applied the SA compensation system to in vivo two-photon imaging with a 25 × water-immersion objective (NA, 1.05; WD, 2 mm). It effectively reduced SA regardless of location, allowing quantitative and reproducible analysis of fine structures of YFP-labeled neurons in the mouse cerebral cortical layers. Interestingly, although the cortical structure was optically heterogeneous along the z-axis, the refractive index of each layer could be assessed on the basis of the compensation degree. It was also possible to make fully corrected three-dimensional reconstructions of YFP-labeled neurons in live brain samples. Our SA compensation system, called Deep-C, is expected to bring out the best in all correction-collar-equipped objectives for imaging deep regions of heterogeneous tissues., (Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.)