Deep structural brain imaging via computational three-photon microscopy.

ABSTRACT:

Significance

High-resolution optical imaging at significant depths is challenging due to scattering, which impairs image quality in living matter with complex structures. We address the need for improved imaging techniques in deep tissues.

Aim

We aim to develop a computational deep three-photon microscopy (3PM) method that enhances image quality without compromising acquisition speed, increasing excitation power, or adding extra optical components.

Approach

We introduce a method called low-rank diffusion model (LRDM)-3PM, which utilizes customized aggregation-induced emission nanoprobes and self-supervised deep learning. This approach leverages superficial information from three-dimensional (3D) images to compensate for scattering and structured noise from the imaging

SUBMITTER: Chen L 

PROVIDER: S-EPMC11954598 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature