An Iterative Zernike-Mode Sensorless Adaptive Optics Approach for Microscopy

Adaptive optics (AO) can compensate for system- and object-related aberrations and is essential for achieving high-resolution deep-tissue imaging — a promising framework across the various microscopy modalities used in bioimaging. Conventional AO is sensor-based and employs a combination of a wavefront sensor (typically a Shack–Hartmann sensor) to determine the wavefront profile and a spatial light modulator (SLM) for wavefront correction. Among SLM varieties, piston micromirror array (MMA)–based devices offer several distinct advantages: a high number of actuators (thousands to millions), quasi-continuous displacement operation (8-bit resolution with a maximum mirror deflection of 400 nm), a high frame rate (kHz-range), and spectral broadband, polarization-independent performance from deep ultraviolet to near-infrared wavelengths.

Since wavefront sensors are typically much slower than SLMs (Hz versus kHz) and provide less pixel resolution, we have developed an algorithm in which the SLM plays a dual-mode role, serving both as a rapid wavefront sensor and as a wavefront corrector within a sensorless AO microscopy framework. The kHz-level refresh rate of the piston-MMA is the key to this approach, as it allows hundreds of optimization iterations per second despite the absence of a dedicated wavefront sensor. To realize this sensorless AO approach, we extended a custom-built widefield microscope operating in reflectance mode by integrating a piston MMA-based SLM from Fraunhofer IPMS. We implement an iterative modal approach that optimizes the superposition of low-order Zernike modes by maximizing image sharpness as quantified by the Tenengrad gradient metric. This approach yields a direct and fast estimation of the aberrations and a corresponding wavefront correction by generating the appropriate MMA pattern on the SLM. Estimation and correction of both system- and object-induced aberrations across the field of view in sensorless AO widefield microscopy are now completed within a minute; after further optimization, we expect to perform them within seconds, enabling near real-time improvement of image quality. We demonstrate improved image resolution for green leaf, corneocyte, and cellulose probes. In this work, we outline that this single-device strategy reduces optical complexity and costs, and enables fast, high-precision AO microscopy correction applicable to various microscopy types, suitable for enhanced real-time bioimaging with minimal phototoxicity.