Rapid wavefront shaping using an optical gradient acquisition

TL;DR

This paper introduces a fast wavefront shaping method that uses gradient descent and an analytical framework to quickly correct aberrations in deep tissue imaging, outperforming traditional sequential approaches.

Contribution

It presents a novel gradient-based wavefront shaping technique that infers the optimal modulation from measurements, enabling high-resolution corrections in complex tissues.

Findings

Rapid wavefront correction demonstrated in confocal microscopy.

Algorithm complexity independent of modulation parameters.

Effective aberration correction in thick tissue layers.

Abstract

Wavefront shaping systems aim to image deep into scattering tissue by reshaping incoming and outgoing light to correct aberrations caused by tissue inhomogeneity However, the desired modulation depends on the unknown tissue structure and therefore its estimation is a challenging time-consuming task. Most strategies rely on coordinate descent optimization, which sequentially varies each modulation parameter and assesses its impact on the resulting image. We propose a rapid wavefront shaping scheme that transitions from coordinate descent to gradient descent optimization, using the same measurement to update all modulation parameters simultaneously. To achieve this, we have developed an analytical framework that expresses the gradient of the wavefront shaping score with respect to all modulation parameters. Although this gradient depends on the unknown tissue structure, we demonstrate how it can be inferred from the optical system's measurements. Our new framework enables rapid inference of wavefront shaping modulations. Additionally, since the complexity of our algorithm does not scale with the number of modulation parameters, we can achieve very high-resolution modulations, leading to better corrections in thicker tissue layers. We showcase the effectiveness of our framework in correcting aberrations in a coherent confocal microscope.