Certain tissue components, in particular neurons in the brain, are fluorescent meaning that we can use illumination at a certain wavelength to excite them, and they emit light at a new wavelength. This new color allows biologists to distinguish them from the rest of the tissue. However, when fluorescent components are located deep inside the tissue the emitted light scatters on its way to the camera and one can only see very aberrated images. Fluorescent signals are usually very weak and the aberrated images also suffer from a very low SNR. As a result, methods that attempt to computationally analyze the aberrated images and restore them are usually inapplicable at such low SNR. A promising alternative attempts to apply aberration correction inside the optical path, by placing a deformable mirror or a spatial light modulator, that reshapes the light waves and directs the photons emerging from a single point inside the tissue into a single sensor pixel. Despite the large potential to revolutionize tissue imaging, before our work wavefront shaping was only applied to various synthetic targets and not on real biological signals. This has to do with 4 major challenges. First one needs to be able to find the desired shape of the modulation correction using noninvasive feedback from the sample. Second, modulation estimation needs to work with weak sources under a very low SNR. Third, previous modulation estimation approaches involved very slow computation, but modulation estimation needs to happen fast enough to support the fast dynamics of a living tissue. Finally, since the scattering happens in a 3D volume, the desired correction varies spatially very fast, and each modulation supports the correction of an extremely small tissue window.
The line of research from our group in the last years addresses all these hard challenges.
First the work of Aizik, nature communications 2024 proposed a wavefront shaping system that can correct aberrations using the weak fluorescent signal emitted from neurons deep inside brain tissue. After years of wavefront shaping research by a large research community, this is really the first time that wavefront shaping was successfully applied on biological data. The paper received a lot of interest from the research community, as evident by the fact that it won the best paper award, and by the fact that serious researchers are interested in applying the technique in their lab.
Another recent important paper from our lab (Monin 25) develops a fast algorithm for estimating the desired correction using the ideas of optical computing.
Finally, the work of Alterman CVPR 2025 studies fundamental theory beyond a 3D wavefront-shaping correction and attempts to understand how to extend them to correct wide field of view images.
